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Sample records for activity neural activity

  1. Associative memory model with spontaneous neural activity

    NASA Astrophysics Data System (ADS)

    Kurikawa, Tomoki; Kaneko, Kunihiko

    2012-05-01

    We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

  2. Global rhythmic activities in hippocampal neural fields and neural coding.

    PubMed

    Ventriglia, Francesco

    2006-01-01

    Global oscillations of the neural field represent some of the most interesting expressions of the hippocampal activity, being related also to learning and memory. To study oscillatory activities of the CA3 field in theta range, a model of this sub-field of Hippocampus has been formulated. The model describes the firing activity of CA3 neuronal populations within the frame of a kinetic theory of neural systems and it has been used for computer simulations. The results show that the propagation of activities induced in the neural field by hippocampal afferents occurs only in narrow time windows confined by inhibitory barrages, whose time-course follows the theta rhythm. Moreover, during each period of a theta wave, the entire CA3 field bears a firing activity with peculiar space-time patterns, a sort of specific imprint, which can induce effects with similar patterns on brain regions driven by the hippocampal formation. The simulation has also demonstrated the ability of medial septum to influence the global activity of the CA3 pyramidal population through the control of the population of inhibitory interneurons. At last, the possible involvement of global population oscillations in neural coding has been discussed.

  3. Neural activation during response competition

    NASA Technical Reports Server (NTRS)

    Hazeltine, E.; Poldrack, R.; Gabrieli, J. D.

    2000-01-01

    The flanker task, introduced by Eriksen and Eriksen [Eriksen, B. A., & Eriksen, C. W. (1974). Effects of noise letters upon the identification of a target letter in a nonsearch task. Perception & Psychophysics, 16, 143--149], provides a means to selectively manipulate the presence or absence of response competition while keeping other task demands constant. We measured brain activity using functional magnetic resonance imaging (fMRI) during performance of the flanker task. In accordance with previous behavioral studies, trials in which the flanking stimuli indicated a different response than the central stimulus were performed significantly more slowly than trials in which all the stimuli indicated the same response. This reaction time effect was accompanied by increases in activity in four regions: the right ventrolateral prefrontal cortex, the supplementary motor area, the left superior parietal lobe, and the left anterior parietal cortex. The increases were not due to changes in stimulus complexity or the need to overcome previously learned associations between stimuli and responses. Correspondences between this study and other experiments manipulating response interference suggest that the frontal foci may be related to response inhibition processes whereas the posterior foci may be related to the activation of representations of the inappropriate responses.

  4. Modeling neural activity with cumulative damage distributions.

    PubMed

    Leiva, Víctor; Tejo, Mauricio; Guiraud, Pierre; Schmachtenberg, Oliver; Orio, Patricio; Marmolejo-Ramos, Fernando

    2015-10-01

    Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum-Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum-Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data.

  5. Persistent neural activity in head direction cells

    NASA Technical Reports Server (NTRS)

    Taube, Jeffrey S.; Bassett, Joshua P.; Oman, C. M. (Principal Investigator)

    2003-01-01

    Many neurons throughout the rat limbic system discharge in relation to the animal's directional heading with respect to its environment. These so-called head direction (HD) cells exhibit characteristics of persistent neural activity. This article summarizes where HD cells are found, their major properties, and some of the important experiments that have been conducted to elucidate how this signal is generated. The number of HD and angular head velocity cells was estimated for several brain areas involved in the generation of the HD signal, including the postsubiculum, anterior dorsal thalamus, lateral mammillary nuclei and dorsal tegmental nucleus. The HD cell signal has many features in common with what is known about how neural integration is accomplished in the oculomotor system. The nature of the HD cell signal makes it an attractive candidate for using neural network models to elucidate the signal's underlying mechanisms. The conditions that any network model must satisfy in order to accurately represent how the nervous system generates this signal are highlighted and areas where key information is missing are discussed.

  6. Deep Neural Networks with Multistate Activation Functions

    PubMed Central

    Cai, Chenghao; Xu, Yanyan; Ke, Dengfeng; Su, Kaile

    2015-01-01

    We propose multistate activation functions (MSAFs) for deep neural networks (DNNs). These MSAFs are new kinds of activation functions which are capable of representing more than two states, including the N-order MSAFs and the symmetrical MSAF. DNNs with these MSAFs can be trained via conventional Stochastic Gradient Descent (SGD) as well as mean-normalised SGD. We also discuss how these MSAFs perform when used to resolve classification problems. Experimental results on the TIMIT corpus reveal that, on speech recognition tasks, DNNs with MSAFs perform better than the conventional DNNs, getting a relative improvement of 5.60% on phoneme error rates. Further experiments also reveal that mean-normalised SGD facilitates the training processes of DNNs with MSAFs, especially when being with large training sets. The models can also be directly trained without pretraining when the training set is sufficiently large, which results in a considerable relative improvement of 5.82% on word error rates. PMID:26448739

  7. Active voltammetric microsensors with neural signal processing.

    SciTech Connect

    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 detect, recognize, and

  8. Understanding the brain by controlling neural activity

    PubMed Central

    Krug, Kristine; Salzman, C. Daniel; Waddell, Scott

    2015-01-01

    Causal methods to interrogate brain function have been employed since the advent of modern neuroscience in the nineteenth century. Initially, randomly placed electrodes and stimulation of parts of the living brain were used to localize specific functions to these areas. Recent technical developments have rejuvenated this approach by providing more precise tools to dissect the neural circuits underlying behaviour, perception and cognition. Carefully controlled behavioural experiments have been combined with electrical devices, targeted genetically encoded tools and neurochemical approaches to manipulate information processing in the brain. The ability to control brain activity in these ways not only deepens our understanding of brain function but also provides new avenues for clinical intervention, particularly in conditions where brain processing has gone awry. PMID:26240417

  9. Quantitative modeling of multiscale neural activity

    NASA Astrophysics Data System (ADS)

    Robinson, Peter A.; Rennie, Christopher J.

    2007-01-01

    The electrical activity of the brain has been observed for over a century and is widely used to probe brain function and disorders, chiefly through the electroencephalogram (EEG) recorded by electrodes on the scalp. However, the connections between physiology and EEGs have been chiefly qualitative until recently, and most uses of the EEG have been based on phenomenological correlations. A quantitative mean-field model of brain electrical activity is described that spans the range of physiological and anatomical scales from microscopic synapses to the whole brain. Its parameters measure quantities such as synaptic strengths, signal delays, cellular time constants, and neural ranges, and are all constrained by independent physiological measurements. Application of standard techniques from wave physics allows successful predictions to be made of a wide range of EEG phenomena, including time series and spectra, evoked responses to stimuli, dependence on arousal state, seizure dynamics, and relationships to functional magnetic resonance imaging (fMRI). Fitting to experimental data also enables physiological parameters to be infered, giving a new noninvasive window into brain function, especially when referenced to a standardized database of subjects. Modifications of the core model to treat mm-scale patchy interconnections in the visual cortex are also described, and it is shown that resulting waves obey the Schroedinger equation. This opens the possibility of classical cortical analogs of quantum phenomena.

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

    ERIC Educational Resources Information Center

    Kreiner, David S.

    2012-01-01

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

  11. Multiple faces elicit augmented neural activity

    PubMed Central

    Puce, Aina; McNeely, Marie E.; Berrebi, Michael E.; Thompson, James C.; Hardee, Jillian; Brefczynski-Lewis, Julie

    2013-01-01

    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. PMID:23785327

  12. Graphene microelectrode arrays for neural activity detection.

    PubMed

    Du, Xiaowei; Wu, Lei; Cheng, Ji; Huang, Shanluo; Cai, Qi; Jin, Qinghui; Zhao, Jianlong

    2015-09-01

    We demonstrate a method to fabricate graphene microelectrode arrays (MEAs) using a simple and inexpensive method to solve the problem of opaque electrode positions in traditional MEAs, while keeping good biocompatibility. To study the interface differences between graphene-electrolyte and gold-electrolyte, graphene and gold electrodes with a large area were fabricated. According to the simulation results of electrochemical impedances, the gold-electrolyte interface can be described as a classical double-layer structure, while the graphene-electrolyte interface can be explained by a modified double-layer theory. Furthermore, using graphene MEAs, we detected the neural activities of neurons dissociated from Wistar rats (embryonic day 18). The signal-to-noise ratio of the detected signal was 10.31 ± 1.2, which is comparable to those of MEAs made with other materials. The long-term stability of the MEAs is demonstrated by comparing differences in Bode diagrams taken before and after cell culturing.

  13. Models of neural networks with fuzzy activation functions

    NASA Astrophysics Data System (ADS)

    Nguyen, A. T.; Korikov, A. M.

    2017-02-01

    This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.

  14. Neurometabolic coupling between neural activity, glucose, and lactate in activated visual cortex.

    PubMed

    Li, Baowang; Freeman, Ralph D

    2015-11-01

    Neural activity is closely coupled with energy metabolism but details of the association remain to be identified. One basic area involves the relationships between neural activity and the main supportive substrates of glucose and lactate. This is of fundamental significance for the interpretation of non-invasive neural imaging. Here, we use microelectrodes with high spatial and temporal resolution to determine simultaneous co-localized changes in glucose, lactate, and neural activity during visual activation of the cerebral cortex in the cat. Tissue glucose and lactate concentration levels are measured with electrochemical microelectrodes while neural spiking activity and local field potentials are sampled by a microelectrode. These measurements are performed simultaneously while neurons are activated by visual stimuli of different contrast levels, orientations, and sizes. We find immediate decreases in tissue glucose concentration and simultaneous increases in lactate during neural activation. Both glucose and lactate signals return to their baseline levels instantly as neurons cease firing. No sustained changes or initial dips in glucose or lactate signals are elicited by visual stimulation. However, co-localized measurements of cerebral blood flow and neural activity demonstrate a clear delay in the cerebral blood flow signal such that it does not correlate temporally with the neural response. These results provide direct real-time evidence regarding the coupling between co-localized energy metabolism and neural activity during physiological stimulation. They are also relevant to a current question regarding the role of lactate in energy metabolism in the brain during neural activation. Dynamic changes in energy metabolites can be measured directly with high spatial and temporal resolution by use of enzyme-based microelectrodes. Here, to examine neuro-metabolic coupling during brain activation, we use combined microelectrodes to simultaneously measure

  15. Mesoscopic Patterns of Neural Activity Support Songbird Cortical Sequences

    PubMed Central

    Guitchounts, Grigori; Velho, Tarciso; Lois, Carlos; Gardner, Timothy J.

    2015-01-01

    Time-locked sequences of neural activity can be found throughout the vertebrate forebrain in various species and behavioral contexts. From “time cells” in the hippocampus of rodents to cortical activity controlling movement, temporal sequence generation is integral to many forms of learned behavior. However, the mechanisms underlying sequence generation are not well known. Here, we describe a spatial and temporal organization of the songbird premotor cortical microcircuit that supports sparse sequences of neural activity. Multi-channel electrophysiology and calcium imaging reveal that neural activity in premotor cortex is correlated with a length scale of 100 µm. Within this length scale, basal-ganglia–projecting excitatory neurons, on average, fire at a specific phase of a local 30 Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song. PMID:26039895

  16. Mesoscopic patterns of neural activity support songbird cortical sequences.

    PubMed

    Markowitz, Jeffrey E; Liberti, William A; Guitchounts, Grigori; Velho, Tarciso; Lois, Carlos; Gardner, Timothy J

    2015-06-01

    Time-locked sequences of neural activity can be found throughout the vertebrate forebrain in various species and behavioral contexts. From "time cells" in the hippocampus of rodents to cortical activity controlling movement, temporal sequence generation is integral to many forms of learned behavior. However, the mechanisms underlying sequence generation are not well known. Here, we describe a spatial and temporal organization of the songbird premotor cortical microcircuit that supports sparse sequences of neural activity. Multi-channel electrophysiology and calcium imaging reveal that neural activity in premotor cortex is correlated with a length scale of 100 µm. Within this length scale, basal-ganglia-projecting excitatory neurons, on average, fire at a specific phase of a local 30 Hz network rhythm. These results show that premotor cortical activity is inhomogeneous in time and space, and that a mesoscopic dynamical pattern underlies the generation of the neural sequences controlling song.

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

    NASA Astrophysics Data System (ADS)

    Sher, A.; Chichilnisky, E. J.; Dabrowski, W.; Grillo, A. A.; Grivich, M.; Gunning, D.; Hottowy, P.; Kachiguine, S.; Litke, A. M.; Mathieson, K.; Petrusca, D.

    2007-09-01

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

  18. OCT detection of neural activity in American cockroach nervous system

    NASA Astrophysics Data System (ADS)

    Gorczyńska, Iwona; Wyszkowska, Joanna; Bukowska, Danuta; Ruminski, Daniel; Karnowski, Karol; Stankiewicz, Maria; Wojtkowski, Maciej

    2013-03-01

    We show results of a project which focuses on detection of activity in neural tissue with Optical Coherence Tomography (OCT) methods. Experiments were performed in neural cords dissected from the American cockroach (Periplaneta americana L.). Functional OCT imaging was performed with ultrahigh resolution spectral / Fourier domain OCT system (axial resolution 2.5 μm). Electrical stimulation (voltage pulses) was applied to the sensory cercal nerve of the neural cord. Optical detection of functional activation of the sample was performed in the connective between the terminal abdominal ganglion and the fifth abdominal ganglion. Functional OCT data were collected over time with the OCT beam illuminating selected single point in the connectives (i.e. OCT M-scans were acquired). Phase changes of the OCT signal were analyzed to visualize occurrence of activation in the neural cord. Electrophysiology recordings (microelectrode method) were also performed as a reference method to demonstrate electrical response of the sample to stimulation.

  19. Neural network with formed dynamics of activity

    SciTech Connect

    Dunin-Barkovskii, V.L.; Osovets, N.B.

    1995-03-01

    The problem of developing a neural network with a given pattern of the state sequence is considered. A neural network structure and an algorithm, of forming its bond matrix which lead to an approximate but robust solution of the problem are proposed and discussed. Limiting characteristics of the serviceability of the proposed structure are studied. Various methods of visualizing dynamic processes in a neural network are compared. Possible applications of the results obtained for interpretation of neurophysiological data and in neuroinformatics systems are discussed.

  20. Neural activity, memory, and dementias: serotonergic markers.

    PubMed

    Meneses, Alfredo

    2017-04-01

    Dysfunctional memory seems to be a key component of diverse dementias and other neuropsychiatric disorders; unfortunately, no effective treatment exists for this, probably because of the absence of neural biomarkers accompanying it. Diverse neurotransmission systems have been implicated in memory, including serotonin or 5-hydroxytryptamine (5-HT). There are multiple serotonergic pharmacological tools, well-characterized downstream signaling in mammals' species and neural markers providing new insights into memory functions and dysfunctions. Serotonin in mammal species has multiple neural markers, including receptors (5-HT1-7), serotonin transporter, and volume transmission, which are present in brain areas involved in memory. Memory, amnesia, and forgetting modify serotonergic markers; this influence is bidirectional. Evidence shows insights and therapeutic targets and diverse approaches support the translatability of using neural markers and cerebral functions and dysfunctions, including memory formation and amnesia. For instance, 5-HT2A/2B/2C, 5-HT4, and 5-HT6 receptors are involved in tau protein hyperphosphorylation in Alzheimer's disease. In addition, at least, 5-HT1A, 5-HT4, 5-HT6, and 5-HT7 receptors as well as serotonin transporter seem to be useful neural markers and therapeutic targets. Hence, available evidence supports the notion that several mechanisms cooperate to achieve synaptic plasticity or memory, including changes in the number of neurotransmitter receptors and transporters. Considering that memory is a key component of dementias, hence reversing or reducing memory deficits might positively affect them?

  1. Technologies for imaging neural activity in large volumes

    PubMed Central

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

    2017-01-01

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

  2. The effect of the neural activity on topological properties of growing neural networks.

    PubMed

    Gafarov, F M; Gafarova, V R

    2016-09-01

    The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

  3. Optical imaging of neural and hemodynamic brain activity

    NASA Astrophysics Data System (ADS)

    Schei, Jennifer Lynn

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

  4. Optogenetic feedback control of neural activity

    PubMed Central

    Newman, Jonathan P; Fong, Ming-fai; Millard, Daniel C; Whitmire, Clarissa J; Stanley, Garrett B; Potter, Steve M

    2015-01-01

    Optogenetic techniques enable precise excitation and inhibition of firing in specified neuronal populations and artifact-free recording of firing activity. Several studies have suggested that optical stimulation provides the precision and dynamic range requisite for closed-loop neuronal control, but no approach yet permits feedback control of neuronal firing. Here we present the ‘optoclamp’, a feedback control technology that provides continuous, real-time adjustments of bidirectional optical stimulation in order to lock spiking activity at specified targets over timescales ranging from seconds to days. We demonstrate how this system can be used to decouple neuronal firing levels from ongoing changes in network excitability due to multi-hour periods of glutamatergic or GABAergic neurotransmission blockade in vitro as well as impinging vibrissal sensory drive in vivo. This technology enables continuous, precise optical control of firing in neuronal populations in order to disentangle causally related variables of circuit activation in a physiologically and ethologically relevant manner. DOI: http://dx.doi.org/10.7554/eLife.07192.001 PMID:26140329

  5. Internal models for interpreting neural population activity during sensorimotor control.

    PubMed

    Golub, Matthew D; Yu, Byron M; Chase, Steven M

    2015-12-08

    To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects' internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output.

  6. Mechanisms underlying spontaneous patterned activity in developing neural circuits

    PubMed Central

    Blankenship, Aaron G.; Feller, Marla B.

    2010-01-01

    Patterned, spontaneous activity occurs in many developing neural circuits, including the retina, the cochlea, the spinal cord, the cerebellum and the hippocampus, where it provides signals that are important for the development of neurons and their connections. Despite differences in adult architecture and output across these various circuits, the patterns of spontaneous network activity and the mechanisms that generate it are remarkably similar and can include a depolarizing action of GABA, transient synaptic connections, extrasynaptic transmission, gap junction coupling and the presence of pacemaker-like neurons. Interestingly, spontaneous activity is robust; if one element of a circuit is disrupted another will generate similar activity. This research suggests that developing neural circuits exhibit transient and tunable features that maintain a source of correlated activity during critical stages of development. PMID:19953103

  7. Controlling neural activity in Caenorhabditis elegans to evoke chemotactic behavior

    NASA Astrophysics Data System (ADS)

    Kocabas, Askin; Shen, Ching-Han; Guo, Zengcai V.; Ramanathan, Sharad

    2013-03-01

    Animals locate and track chemoattractive gradients in the environment to find food. With its simple nervous system, Caenorhabditis elegans is a good model system in which to understand how the dynamics of neural activity control this search behavior. To understand how the activity in its interneurons coordinate different motor programs to lead the animal to food, here we used optogenetics and new optical tools to manipulate neural activity directly in freely moving animals to evoke chemotactic behavior. By deducing the classes of activity patterns triggered during chemotaxis and exciting individual neurons with these patterns, we identified interneurons that control the essential locomotory programs for this behavior. Notably, we discovered that controlling the dynamics of activity in just one interneuron pair was sufficient to force the animal to locate, turn towards and track virtual light gradients.

  8. Nonoxidative Glucose Consumption during Focal Physiologic Neural Activity

    NASA Astrophysics Data System (ADS)

    Fox, Peter T.; Raichle, Marcus E.; Mintun, Mark A.; Dence, Carmen

    1988-07-01

    Brain glucose uptake, oxygen metabolism, and blood flow in humans were measured with positron emission tomography, and a resting-state molar ratio of oxygen to glucose consumption of 4.1:1 was obtained. Physiological neural activity, however, increased glucose uptake and blood flow much more (51 and 50 percent, respectively) than oxygen consumption (5 percent) and produced a molar ratio for the increases of 0.4:1. Transient increases in neural activity cause a tissue uptake of glucose in excess of that consumed by oxidative metabolism, acutely consume much less energy than previously believed, and regulate local blood flow for purposes other than oxidative metabolism.

  9. Typology of nonlinear activity waves in a layered neural continuum.

    PubMed

    Koch, Paul; Leisman, Gerry

    2006-04-01

    Neural tissue, a medium containing electro-chemical energy, can amplify small increments in cellular activity. The growing disturbance, measured as the fraction of active cells, manifests as propagating waves. In a layered geometry with a time delay in synaptic signals between the layers, the delay is instrumental in determining the amplified wavelengths. The growth of the waves is limited by the finite number of neural cells in a given region of the continuum. As wave growth saturates, the resulting activity patterns in space and time show a variety of forms, ranging from regular monochromatic waves to highly irregular mixtures of different spatial frequencies. The type of wave configuration is determined by a number of parameters, including alertness and synaptic conditioning as well as delay. For all cases studied, using numerical solution of the nonlinear Wilson-Cowan (1973) equations, there is an interval in delay in which the wave mixing occurs. As delay increases through this interval, during a series of consecutive waves propagating through a continuum region, the activity within that region changes from a single-frequency to a multiple-frequency pattern and back again. The diverse spatio-temporal patterns give a more concrete form to several metaphors advanced over the years to attempt an explanation of cognitive phenomena: Activity waves embody the "holographic memory" (Pribram, 1991); wave mixing provides a plausible cause of the competition called "neural Darwinism" (Edelman, 1988); finally the consecutive generation of growing neural waves can explain the discontinuousness of "psychological time" (Stroud, 1955).

  10. Predicting Reading and Mathematics from Neural Activity for Feedback Learning

    ERIC Educational Resources Information Center

    Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A.

    2017-01-01

    Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task…

  11. Analysing human neural stem cell ontogeny by consecutive isolation of Notch active neural progenitors.

    PubMed

    Edri, Reuven; Yaffe, Yakey; Ziller, Michael J; Mutukula, Naresh; Volkman, Rotem; David, Eyal; Jacob-Hirsch, Jasmine; Malcov, Hagar; Levy, Carmit; Rechavi, Gideon; Gat-Viks, Irit; Meissner, Alexander; Elkabetz, Yechiel

    2015-03-23

    Decoding heterogeneity of pluripotent stem cell (PSC)-derived neural progeny is fundamental for revealing the origin of diverse progenitors, for defining their lineages, and for identifying fate determinants driving transition through distinct potencies. Here we have prospectively isolated consecutively appearing PSC-derived primary progenitors based on their Notch activation state. We first isolate early neuroepithelial cells and show their broad Notch-dependent developmental and proliferative potential. Neuroepithelial cells further yield successive Notch-dependent functional primary progenitors, from early and midneurogenic radial glia and their derived basal progenitors, to gliogenic radial glia and adult-like neural progenitors, together recapitulating hallmarks of neural stem cell (NSC) ontogeny. Gene expression profiling reveals dynamic stage-specific transcriptional patterns that may link development of distinct progenitor identities through Notch activation. Our observations provide a platform for characterization and manipulation of distinct progenitor cell types amenable for developing streamlined neural lineage specification paradigms for modelling development in health and disease.

  12. Dynamic neural activity during stress signals resilient coping

    PubMed Central

    Sinha, Rajita; Lacadie, Cheryl M.; Constable, R. Todd; Seo, Dongju

    2016-01-01

    Active coping underlies a healthy stress response, but neural processes supporting such resilient coping are not well-known. Using a brief, sustained exposure paradigm contrasting highly stressful, threatening, and violent stimuli versus nonaversive neutral visual stimuli in a functional magnetic resonance imaging (fMRI) study, we show significant subjective, physiologic, and endocrine increases and temporally related dynamically distinct patterns of neural activation in brain circuits underlying the stress response. First, stress-specific sustained increases in the amygdala, striatum, hypothalamus, midbrain, right insula, and right dorsolateral prefrontal cortex (DLPFC) regions supported the stress processing and reactivity circuit. Second, dynamic neural activation during stress versus neutral runs, showing early increases followed by later reduced activation in the ventrolateral prefrontal cortex (VLPFC), dorsal anterior cingulate cortex (dACC), left DLPFC, hippocampus, and left insula, suggested a stress adaptation response network. Finally, dynamic stress-specific mobilization of the ventromedial prefrontal cortex (VmPFC), marked by initial hypoactivity followed by increased VmPFC activation, pointed to the VmPFC as a key locus of the emotional and behavioral control network. Consistent with this finding, greater neural flexibility signals in the VmPFC during stress correlated with active coping ratings whereas lower dynamic activity in the VmPFC also predicted a higher level of maladaptive coping behaviors in real life, including binge alcohol intake, emotional eating, and frequency of arguments and fights. These findings demonstrate acute functional neuroplasticity during stress, with distinct and separable brain networks that underlie critical components of the stress response, and a specific role for VmPFC neuroflexibility in stress-resilient coping. PMID:27432990

  13. Decoding Ventromedial Hypothalamic Neural Activity during Male Mouse Aggression

    PubMed Central

    Dollar, Piotr; Perona, Pietro

    2014-01-01

    The ventromedial hypothalamus, ventrolateral area (VMHvl) was identified recently as a critical locus for inter-male aggression. Optogenetic stimulation of VMHvl in male mice evokes attack toward conspecifics and inactivation of the region inhibits natural aggression, yet very little is known about its underlying neural activity. To understand its role in promoting aggression, we recorded and analyzed neural activity in the VMHvl in response to a wide range of social and nonsocial stimuli. Although response profiles of VMHvl neurons are complex and heterogeneous, we identified a subpopulation of neurons that respond maximally during investigation and attack of male conspecific mice and during investigation of a source of male mouse urine. These “male responsive” neurons in the VMHvl are tuned to both the inter-male distance and the animal's velocity during attack. Additionally, VMHvl activity predicts several parameters of future aggressive action, including the latency and duration of the next attack. Linear regression analysis further demonstrates that aggression-specific parameters, such as distance, movement velocity, and attack latency, can model ongoing VMHvl activity fluctuation during inter-male encounters. These results represent the first effort to understand the hypothalamic neural activity during social behaviors using quantitative tools and suggest an important role for the VMHvl in encoding movement, sensory, and motivation-related signals. PMID:24760856

  14. Systematic fluctuation expansion for neural network activity equations.

    PubMed

    Buice, Michael A; Cowan, Jack D; Chow, Carson C

    2010-02-01

    Population rate or activity equations are the foundation of a common approach to modeling for neural networks. These equations provide mean field dynamics for the firing rate or activity of neurons within a network given some connectivity. The shortcoming of these equations is that they take into account only the average firing rate, while leaving out higher-order statistics like correlations between firing. A stochastic theory of neural networks that includes statistics at all orders was recently formulated. We describe how this theory yields a systematic extension to population rate equations by introducing equations for correlations and appropriate coupling terms. Each level of the approximation yields closed equations; they depend only on the mean and specific correlations of interest, without an ad hoc criterion for doing so. We show in an example of an all-to-all connected network how our system of generalized activity equations captures phenomena missed by the mean field rate equations alone.

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

    NASA Astrophysics Data System (ADS)

    Mora, Thierry

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

  16. Neural activation during successful and unsuccessful verbal learning in schizophrenia.

    PubMed

    Heinze, Sibylle; Sartory, Gudrun; Müller, Bernhard W; de Greiff, Armin; Forsting, Michael; Jüptner, Markus

    2006-04-01

    Successful and unsuccessful intention to learn words was assessed by means of event-related functional MRI. Eighteen patients with schizophrenia and 15 healthy control participants were scanned while being given two word lists to read and another seven to learn with immediate recall. Neural activation patterns were segregated according to whether words were subsequently recalled or forgotten and these conditions were contrasted with each other and reading. Compared to controls, patients with schizophrenia showed deficits with regard to neural recruitment of right hippocampus and of cerebellar structures during successful verbal learning. Furthermore, a reversal of activated structures was evident in the two groups: Controls showed activation of right frontal and left middle temporal structures during the unsuccessful intention to learn. During successful learning, there was additional activation of right superior parietal lobule. In contrast, patients showed activation of right superior parietal lobule during unsuccessful and successful intention to learn. There were additional frontal and left middle temporal lobe activations during successful learning. We conclude that increased parietal activity may reflect a mechanism which compensates for the lack of hippocampal and cerebellar contributions to verbal learning in schizophrenia.

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

    PubMed

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

    2015-07-01

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

  18. Neural activity predicts attitude change in cognitive dissonance.

    PubMed

    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.

  19. Monitoring activity in neural circuits with genetically encoded indicators

    PubMed Central

    Broussard, Gerard J.; Liang, Ruqiang; Tian, Lin

    2014-01-01

    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 (GCaMPs), sensors probing synaptic activity, and genetically encoded voltage indicators. Using the family of the 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. PMID:25538558

  20. Neural circuit activity in freely behaving zebrafish (Danio rerio).

    PubMed

    Issa, Fadi A; O'Brien, Georgeann; Kettunen, Petronella; Sagasti, Alvaro; Glanzman, David L; Papazian, Diane M

    2011-03-15

    Examining neuronal network activity in freely behaving animals is advantageous for probing the function of the vertebrate central nervous system. Here, we describe a simple, robust technique for monitoring the activity of neural circuits in unfettered, freely behaving zebrafish (Danio rerio). Zebrafish respond to unexpected tactile stimuli with short- or long-latency escape behaviors, which are mediated by distinct neural circuits. Using dipole electrodes immersed in the aquarium, we measured electric field potentials generated in muscle during short- and long-latency escapes. We found that activation of the underlying neural circuits produced unique field potential signatures that are easily recognized and can be repeatedly monitored. In conjunction with behavioral analysis, we used this technique to track changes in the pattern of circuit activation during the first week of development in animals whose trigeminal sensory neurons were unilaterally ablated. One day post-ablation, the frequency of short- and long-latency responses was significantly lower on the ablated side than on the intact side. Three days post-ablation, a significant fraction of escapes evoked by stimuli on the ablated side was improperly executed, with the animal turning towards rather than away from the stimulus. However, the overall response rate remained low. Seven days post-ablation, the frequency of escapes increased dramatically and the percentage of improperly executed escapes declined. Our results demonstrate that trigeminal ablation results in rapid reconfiguration of the escape circuitry, with reinnervation by new sensory neurons and adaptive changes in behavior. This technique is valuable for probing the activity, development, plasticity and regeneration of neural circuits under natural conditions.

  1. Application of neural networks to seismic active control

    SciTech Connect

    Tang, Yu

    1995-07-01

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

  2. Structural damage detection using active members and neural networks

    NASA Astrophysics Data System (ADS)

    Manning, R. A.

    1994-06-01

    The detection of damage in structures is a topic which has considerable interest in many fields. In the past many methods for detecting damage in structures has relied on finite element model refinement methods. This note presents a structural damage methodology in which only active member transfer function data are used in conjunction with an artificial neural network to detect damage in structures. Specifically, the method relies on training a neural network using active member transfer function pole/zero information to classify damaged structure measurements and to predict the degree of damage in the structure. The method differs from many of the past damage detection algorithms in that no attempt is made to update a finite element model or to match measured data with new finite element analyses of the structure in a damaged state.

  3. Internal models for interpreting neural population activity during sensorimotor control

    PubMed Central

    Golub, Matthew D; Yu, Byron M; Chase, Steven M

    2015-01-01

    To successfully guide limb movements, the brain takes in sensory information about the limb, internally tracks the state of the limb, and produces appropriate motor commands. It is widely believed that this process uses an internal model, which describes our prior beliefs about how the limb responds to motor commands. Here, we leveraged a brain-machine interface (BMI) paradigm in rhesus monkeys and novel statistical analyses of neural population activity to gain insight into moment-by-moment internal model computations. We discovered that a mismatch between subjects’ internal models and the actual BMI explains roughly 65% of movement errors, as well as long-standing deficiencies in BMI speed control. We then used the internal models to characterize how the neural population activity changes during BMI learning. More broadly, this work provides an approach for interpreting neural population activity in the context of how prior beliefs guide the transformation of sensory input to motor output. DOI: http://dx.doi.org/10.7554/eLife.10015.001 PMID:26646183

  4. Neural activity triggers neuronal oxidative metabolism followed by astrocytic glycolysis.

    PubMed

    Kasischke, Karl A; Vishwasrao, Harshad D; Fisher, Patricia J; Zipfel, Warren R; Webb, Watt W

    2004-07-02

    We have found that two-photon fluorescence imaging of nicotinamide adenine dinucleotide (NADH) provides the sensitivity and spatial three-dimensional resolution to resolve metabolic signatures in processes of astrocytes and neurons deep in highly scattering brain tissue slices. This functional imaging reveals spatiotemporal partitioning of glycolytic and oxidative metabolism between astrocytes and neurons during focal neural activity that establishes a unifying hypothesis for neurometabolic coupling in which early oxidative metabolism in neurons is eventually sustained by late activation of the astrocyte-neuron lactate shuttle. Our model integrates existing views of brain energy metabolism and is in accord with known macroscopic physiological changes in vivo.

  5. Multivariate neural network operators with sigmoidal activation functions.

    PubMed

    Costarelli, Danilo; Spigler, Renato

    2013-12-01

    In this paper, we study pointwise and uniform convergence, as well as order of approximation, of a family of linear positive multivariate neural network (NN) operators with sigmoidal activation functions. The order of approximation is studied for functions belonging to suitable Lipschitz classes and using a moment-type approach. The special cases of NN operators, activated by logistic, hyperbolic tangent, and ramp sigmoidal functions are considered. Multivariate NNs approximation finds applications, typically, in neurocomputing processes. Our approach to NN operators allows us to extend previous convergence results and, in some cases, to improve the order of approximation. The case of multivariate quasi-interpolation operators constructed with sigmoidal functions is also considered.

  6. Neural activity associated with enhanced facial attractiveness by cosmetics use.

    PubMed

    Ueno, Aya; Ito, Ayahito; Kawasaki, Iori; Kawachi, Yousuke; Yoshida, Kazuki; Murakami, Yui; Sakai, Shinya; Iijima, Toshio; Matsue, Yoshihiko; Fujii, Toshikatsu

    2014-04-30

    Previous psychological studies have shown that make-up enhances facial attractiveness. Although neuroimaging evidence indicates that the orbitofrontal cortex (OFC) shows greater activity for faces of attractive people than for those of unattractive people, there is no direct evidence that the OFC also shows greater activity for the face of an individual wearing make-up than for the same face without make-up. Using functional magnetic resonance imaging (fMRI), we investigated neural activity while subjects viewed 144 photographs of the same faces with and without make-up (48 with make-up, 48 without make-up, and 48 scrambled photographs) and assigned these faces an attractiveness rating. The behavioral data showed that the faces with make-up were rated as more attractive than those without make-up. The imaging data revealed that the left OFC and the right hippocampus showed greater activity for faces with make-up than for those without make-up. Furthermore, the activities of the right anterior cingulate cortex, left hippocampus, and left OFC increased with increasing facial attractiveness resulting from cosmetics use. These results provide direct evidence of the neural underpinnings of cosmetically enhanced facial attractiveness.

  7. Supervised learning for neural manifold using spatiotemporal brain activity

    NASA Astrophysics Data System (ADS)

    Kuo, Po-Chih; Chen, Yong-Sheng; Chen, Li-Fen

    2015-12-01

    Objective. Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli. Approach. We propose a supervised locally linear embedding method to construct the embedded manifold from brain activity, taking into account similarities between corresponding stimuli. In our experiments, photographic portraits were used as visual stimuli and brain activity was calculated from magnetoencephalographic data using a source localization method. Main results. The results of 10 × 10-fold cross-validation revealed a strong correlation between manifolds of brain activity and the orientation of faces in the presented images, suggesting that high-level information related to image content can be revealed in the brain responses represented in the manifold. Significance. Our experiments demonstrate that the proposed method is applicable to investigation into the inherent patterns of brain activity.

  8. Light-Activated Ion Channels for Remote Control of Neural Activity

    PubMed Central

    Chambers, James J.; Kramer, Richard H.

    2009-01-01

    Light-activated ion channels provide a new opportunity to precisely and remotely control neuronal activity for experimental applications in neurobiology. In the past few years, several strategies have arisen that allow light to control ion channels and therefore neuronal function. Light-based triggers for ion channel control include caged compounds, which release active neurotransmitters when photolyzed with light, and natural photoreceptive proteins, which can be expressed exogenously in neurons. More recently, a third type of light trigger has been introduced: a photoisomerizable tethered ligand that directly controls ion channel activity in a light-dependent manner. Beyond the experimental applications for light-gated ion channels, there may be clinical applications in which these light-sensitive ion channels could prove advantageous over traditional methods. Electrodes for neural stimulation to control disease symptoms are invasive and often difficult to reposition between cells in tissue. Stimulation by chemical agents is difficult to constrain to individual cells and has limited temporal accuracy in tissue due to diffusional limitations. In contrast, ion channels that can be directly activated with light allow control with unparalleled spatial and temporal precision. The goal of this chapter is to describe light-regulated ion channels and how they have been tailored to control different aspects of neural activity, and how to use these channels to manipulate and better understand development, function, and plasticity of neurons and neural circuits. PMID:19195553

  9. Functional Embedding Predicts the Variability of Neural Activity

    PubMed Central

    Mišić, Bratislav; Vakorin, Vasily A.; Paus, Tomáš; McIntosh, Anthony R.

    2011-01-01

    Neural activity is irregular and unpredictable, yet little is known about why this is the case and how this property relates to the functional architecture of the brain. Here we show that the variability of a region’s activity systematically varies according to its topological role in functional networks. We recorded the resting-state electroencephalogram (EEG) and constructed undirected graphs of functional networks. We measured the centrality of each node in terms of the number of connections it makes (degree), the ease with which the node can be reached from other nodes in the network (efficiency) and the tendency of the node to occupy a position on the shortest paths between other pairs of nodes in the network (betweenness). As a proxy for variability, we estimated the information content of neural activity using multiscale entropy analysis. We found that the rate at which information was generated was largely predicted by centrality. Namely, nodes with greater degree, betweenness, and efficiency were more likely to have high information content, while peripheral nodes had relatively low information content. These results suggest that the variability of regional activity reflects functional embedding. PMID:22164135

  10. Motor Neuron Activation in Peripheral Nerves Using Infrared Neural Stimulation

    PubMed Central

    Peterson, EJ; Tyler, DJ

    2014-01-01

    Objective Localized activation of peripheral axons may improve selectivity of peripheral nerve interfaces. Infrared neural stimulation (INS) employs localized delivery to activate neural tissue. This study investigated INS to determine whether localized delivery limited functionality in larger mammalian nerves. Approach The rabbit sciatic nerve was stimulated extraneurally with 1875 nm-wavelength infrared light, electrical stimulation, or a combination of both. Infrared-sensitive regions (ISR) of the nerve surface and electromyogram (EMG) recruitment of the Medial Gastrocnemius, Lateral Gastrocnemius, Soleus, and Tibialis Anterior were the primary output measures. Stimulation applied included infrared-only, electrical-only, and combined infrared and electrical. Main results 81% of nerves tested were sensitive to INS, with 1.7± 0.5 ISR detected per nerve. INS was selective to a single muscle within 81% of identified ISR. Activation energy threshold did not change significantly with stimulus power, but motor activation decreased significantly when radiant power was decreased. Maximum INS levels typically recruited up to 2–9% of any muscle. Combined infrared and electrical stimulation differed significantly from electrical recruitment in 7% of cases. Significance The observed selectivity of INS indicates it may be useful in augmenting rehabilitation, but significant challenges remain in increasing sensitivity and response magnitude to improve the functionality of INS. PMID:24310923

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  12. Predicting reading and mathematics from neural activity for feedback learning.

    PubMed

    Peters, Sabine; Van der Meulen, Mara; Zanolie, Kiki; Crone, Eveline A

    2017-01-01

    Although many studies use feedback learning paradigms to study the process of learning in laboratory settings, little is known about their relevance for real-world learning settings such as school. In a large developmental sample (N = 228, 8-25 years), we investigated whether performance and neural activity during a feedback learning task predicted reading and mathematics performance 2 years later. The results indicated that feedback learning performance predicted both reading and mathematics performance. Activity during feedback learning in left superior dorsolateral prefrontal cortex (DLPFC) predicted reading performance, whereas activity in presupplementary motor area/anterior cingulate cortex (pre-SMA/ACC) predicted mathematical performance. Moreover, left superior DLPFC and pre-SMA/ACC activity predicted unique variance in reading and mathematics ability over behavioral testing of feedback learning performance alone. These results provide valuable insights into the relationship between laboratory-based learning tasks and learning in school settings, and the value of neural assessments for prediction of school performance over behavioral testing alone. (PsycINFO Database Record

  13. Social power and approach-related neural activity.

    PubMed

    Boksem, Maarten A S; Smolders, Ruud; De Cremer, David

    2012-06-01

    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.

  14. Multiview fusion for activity recognition using deep neural networks

    NASA Astrophysics Data System (ADS)

    Kavi, Rahul; Kulathumani, Vinod; Rohit, Fnu; Kecojevic, Vlad

    2016-07-01

    Convolutional neural networks (ConvNets) coupled with long short term memory (LSTM) networks have been recently shown to be effective for video classification as they combine the automatic feature extraction capabilities of a neural network with additional memory in the temporal domain. This paper shows how multiview fusion can be applied to such a ConvNet LSTM architecture. Two different fusion techniques are presented. The system is first evaluated in the context of a driver activity recognition system using data collected in a multicamera driving simulator. These results show significant improvement in accuracy with multiview fusion and also show that deep learning performs better than a traditional approach using spatiotemporal features even without requiring any background subtraction. The system is also validated on another publicly available multiview action recognition dataset that has 12 action classes and 8 camera views.

  15. Efficient Universal Computing Architectures for Decoding Neural Activity

    PubMed Central

    Rapoport, Benjamin I.; Turicchia, Lorenzo; Wattanapanitch, Woradorn; Davidson, Thomas J.; Sarpeshkar, Rahul

    2012-01-01

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

  16. Can Neural Activity Propagate by Endogenous Electrical Field?

    PubMed Central

    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

  17. Sparse Neural Network Models of Antimicrobial Peptide-Activity Relationships.

    PubMed

    Müller, Alex T; Kaymaz, Aral C; Gabernet, Gisela; Posselt, Gernot; Wessler, Silja; Hiss, Jan A; Schneider, Gisbert

    2016-12-01

    We present an adaptive neural network model for chemical data classification. The method uses an evolutionary algorithm for optimizing the network structure by seeking sparsely connected architectures. The number of hidden layers, the number of neurons in each layer and their connectivity are free variables of the system. We used the method for predicting antimicrobial peptide activity from the amino acid sequence. Visualization of the evolved sparse network structures suggested a high charge density and a low aggregation potential in solution as beneficial for antimicrobial activity. However, different training data sets and peptide representations resulted in greatly varying network structures. Overall, the sparse network models turned out to be less accurate than fully-connected networks. In a prospective application, we synthesized and tested 10 de novo generated peptides that were predicted to either possess antimicrobial activity, or to be inactive. Two of the predicted antibacterial peptides showed cosiderable bacteriostatic effects against both Staphylococcus aureus and Escherichia coli. None of the predicted inactive peptides possessed antibacterial properties. Molecular dynamics simulations of selected peptide structures in water and TFE suggest a pronounced peptide helicity in a hydrophobic environment. The results of this study underscore the applicability of neural networks for guiding the computer-assisted design of new peptides with desired properties.

  18. Multifractal detrended fluctuation analysis of optogenetic modulation of neural activity

    NASA Astrophysics Data System (ADS)

    Kumar, S.; Gu, L.; Ghosh, N.; Mohanty, S. K.

    2013-02-01

    Here, we introduce a computational procedure to examine whether optogenetically activated neuronal firing recordings could be characterized as multifractal series. Optogenetics is emerging as a valuable experimental tool and a promising approach for studying a variety of neurological disorders in animal models. The spiking patterns from cortical region of the brain of optogenetically-stimulated transgenic mice were analyzed using a sophisticated fluctuation analysis method known as multifractal detrended fluctuation analysis (MFDFA). We observed that the optogenetically-stimulated neural firings are consistent with a multifractal process. Further, we used MFDFA to monitor the effect of chemically induced pain (formalin injection) and optogenetic treatment used to relieve the pain. In this case, dramatic changes in parameters characterizing a multifractal series were observed. Both the generalized Hurst exponent and width of singularity spectrum effectively differentiates the neural activities during control and pain induction phases. The quantitative nature of the analysis equips us with better measures to quantify pain. Further, it provided a measure for effectiveness of the optogenetic stimulation in inhibiting pain. MFDFA-analysis of spiking data from other deep regions of the brain also turned out to be multifractal in nature, with subtle differences in the parameters during pain-induction by formalin injection and inhibition by optogenetic stimulation. Characterization of neuronal firing patterns using MFDFA will lead to better understanding of neuronal response to optogenetic activation and overall circuitry involved in the process.

  19. Reporting neural activity with genetically encoded calcium indicators

    PubMed Central

    Hires, S. Andrew; Tian, Lin; Looger, Loren L.

    2009-01-01

    Genetically encoded calcium indicators (GECIs), based on recombinant fluorescent proteins, have been engineered to observe calcium transients in living cells and organisms. Through observation of calcium, these indicators also report neural activity. We review progress in GECI construction and application, particularly toward in vivo monitoring of sparse action potentials (APs). We summarize the extrinsic and intrinsic factors that influence GECI performance. A simple model of GECI response to AP firing demonstrates the relative significance of these factors. We recommend a standardized protocol for evaluating GECIs in a physiologically relevant context. A potential method of simultaneous optical control and recording of neuronal circuits is presented. PMID:18941901

  20. Reading stories activates neural representations of visual and motor experiences.

    PubMed

    Speer, Nicole K; Reynolds, Jeremy R; Swallow, Khena M; Zacks, Jeffrey M

    2009-08-01

    To understand and remember stories, readers integrate their knowledge of the world with information in the text. Here we present functional neuroimaging evidence that neural systems track changes in the situation described by a story. Different brain regions track different aspects of a story, such as a character's physical location or current goals. Some of these regions mirror those involved when people perform, imagine, or observe similar real-world activities. These results support the view that readers understand a story by simulating the events in the story world and updating their simulation when features of that world change.

  1. Reading Stories Activates Neural Representations of Visual and Motor Experiences

    PubMed Central

    Speer, Nicole K.; Reynolds, Jeremy R.; Swallow, Khena M.; Zacks, Jeffrey M.

    2010-01-01

    To understand and remember stories, readers integrate their knowledge of the world with information in the text. Here we present functional neuroimaging evidence that neural systems track changes in the situation described by a story. Different brain regions track different aspects of a story, such as a character’s physical location or current goals. Some of these regions mirror those involved when people perform, imagine, or observe similar real-world activities. These results support the view that readers understand a story by simulating the events in the story world and updating their simulation when features of that world change. PMID:19572969

  2. Inference of other's internal neural models from active observation.

    PubMed

    Kim, Kyung-Joong; Cho, Sung-Bae

    2015-02-01

    Recently, there have been several attempts to replicate theory of mind, which explains how humans infer the mental states of other people using multiple sensory input, with artificial systems. One example of this is a robot that observes the behavior of other artificial systems and infers their internal models, mapping sensory inputs to the actuator's control signals. In this paper, we present the internal model as an artificial neural network, similar to biological systems. During inference, an observer can use an active incremental learning algorithm to guess an actor's internal neural model. This could significantly reduce the effort needed to guess other people's internal models. We apply an algorithm to the actor-observer robot scenarios with/without prior knowledge of the internal models. To validate our approach, we use a physics-based simulator with virtual robots. A series of experiments reveal that the observer robot can construct an "other's self-model", validating the possibility that a neural-based approach can be used as a platform for learning cognitive functions.

  3. Serotonin activates overall feeding by activating two separate neural pathways in Caenorhabditis elegans.

    PubMed

    Song, Bo-mi; Avery, Leon

    2012-02-08

    Food intake in the nematode Caenorhabditis elegans requires two distinct feeding motions, pharyngeal pumping and isthmus peristalsis. Bacteria, the natural food of C. elegans, activate both feeding motions (Croll, 1978; Horvitz et al., 1982; Chiang et al., 2006). The mechanisms by which bacteria activate the feeding motions are largely unknown. To understand the process, we studied how serotonin, an endogenous pharyngeal pumping activator whose action is triggered by bacteria, activates feeding motions. Here, we show that serotonin, like bacteria, activates overall feeding by activating isthmus peristalsis as well as pharyngeal pumping. During active feeding, the frequencies and the timing of onset of the two motions were distinct, but each isthmus peristalsis was coupled to the preceding pump. We found that serotonin activates the two feeding motions mainly by activating two separate neural pathways in response to bacteria. For activating pumping, the SER-7 serotonin receptor in the MC motor neurons in the feeding organ activated cholinergic transmission from MC to the pharyngeal muscles by activating the Gsα signaling pathway. For activating isthmus peristalsis, SER-7 in the M4 (and possibly M2) motor neuron in the feeding organ activated the G(12)α signaling pathway in a cell-autonomous manner, which presumably activates neurotransmission from M4 to the pharyngeal muscles. Based on our results and previous calcium imaging of pharyngeal muscles (Shimozono et al., 2004), we propose a model that explains how the two feeding motions are separately regulated yet coupled. The feeding organ may have evolved this way to support efficient feeding.

  4. Interpreting collective neural activity underlying spatial navigation in virtual reality

    NASA Astrophysics Data System (ADS)

    Meshulam, Leenoy; Gauthier, Jeff; Tank, David; Bialek, William

    2015-03-01

    Traditionally, cognitive- demanding processes like spatial navigation were studied by recording the activity of single neurons. However, recent technological progress allows imaging the simultaneous activity of large neuronal populations in awake behaving animals. This progress in experimental work calls for a similar adjustments of the modeling frameworks. To achieve a description of the ``real thermodynamics'' of the neural system, we construct maximum entropy models for optical imaging data taken in vivo, from the hippocampus of mice navigating in a virtual reality environment. This provides a natural extension of statistical mechanics applicable to brain activity, by focusing on the interactions between cells rather than on single cell's activity. We aim to determine how the topology of the energy landscape predicted by the model corresponds to the location of the animal in the environment. Since large subpopulations of the neurons in this area are spatially modulated, we expect the landscape to exhibit a large ``valley'' structure of local minima, corresponding to the animal's position along the environment. Such a finding is especially of interest because the location information emerges solely from the activity patterns that are accessible to the brain.

  5. Fast Delayed Rectifier Potassium Current Required for Circadian Neural Activity

    PubMed Central

    JN, Itri; S, Michel; MJ, Vansteensel; JH, Meijer; CS, Colwell

    2005-01-01

    In mammals, the precise circadian timing of many biological processes depends on the generation of oscillations in neural activity of pacemaker cells in the suprachiasmatic nucleus (SCN). The ionic mechanisms underlying these rhythms are largely unknown. Using the mouse brain slice preparation, we demonstrate that the magnitude of fast delayed rectifier potassium currents exhibits a diurnal rhythm that peaks during the day. Importantly, this rhythm continues in constant darkness, providing the first demonstration of the circadian regulation of an intrinsic voltage–gated current in mammalian cells. Blocking this current prevented the daily rhythm in firing rate in SCN neurons. Kv3.1b and Kv3.2 potassium channels were found to be widely distributed within the SCN with higher expression during the day. We conclude that the fast delayed rectifier is necessary for the circadian modulation of electrical activity in SCN neurons, and represents an important part of the ionic basis for the generation of rhythmic output. PMID:15852012

  6. Neural activity in the hippocampus during conflict resolution.

    PubMed

    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.

  7. Neural activity during free association to conflict–related sentences

    PubMed Central

    Kehyayan, Aram; Best, Katrin; Schmeing, Jo-Birger; Axmacher, Nikolai; Kessler, Henrik

    2013-01-01

    Psychodynamic conflicts form an important construct to understand the genesis and maintenance of mental disorders. Conflict-related themes should therefore provoke strong reactions on the behavioral, physiological, and neural level. We confronted N = 18 healthy subjects with a vast array of sentences describing typical psychodynamic conflict themes in the fMRI scanner and let them associate spontaneously in reaction. The overt associations were then analyzed according to psychoanalytic theory and the system of operationalized psychodynamic diagnosis and used as a genuinely psychodynamic indicator, whether each potentially conflict-related sentence actually touched a conflict theme of the individual. Behavioral, physiological, and neural reactions were compared between those subjects with an “apparent conflict” and those with “absent conflicts.” The first group reported stronger agreement with the conflict-related sentences, more negative valence in reaction, had higher levels of skin conductance reactivity and exhibited stronger activation in the anterior cingulate cortex, amongst other functions involved in emotion processing and conflict-monitoring. In conjunction, we interpret this activity as a possible correlate of subjects’ inherent reactions and regulatory processes evoked by conflict themes. This study makes a point for the fruitfulness of the neuropsychoanalytic endeavor by using free association, the classical technique most commonly used in psychoanalysis, to investigate aspects of conflict processing in neuroimaging. PMID:24298244

  8. Sociocultural patterning of neural activity during self-reflection

    PubMed Central

    Ma, Yina; Bang, Dan; Wang, Chenbo; Allen, Micah; Frith, Chris; Roepstorff, Andreas; Han, Shihui

    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 magnetic resonance imaging, we monitored neural responses from adults in East Asian (Chinese) and Western (Danish) cultural contexts during judgments of social, mental and physical attributes of themselves and public figures to assess cultural influences on self-referential processing of personal attributes in different dimensions. We found 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-reflection by changing the weight of the mPFC and TPJ in the social brain network. PMID:22956678

  9. Social decisions affect neural activity to perceived dynamic gaze

    PubMed Central

    Latinus, Marianne; Love, Scott A.; Rossi, Alejandra; Parada, Francisco J.; Huang, Lisa; Conty, Laurence; George, Nathalie; James, Karin

    2015-01-01

    Gaze direction, a cue of both social and spatial attention, is known to modulate early neural responses to faces e.g. N170. However, findings in the literature have been inconsistent, likely reflecting differences in stimulus characteristics and task requirements. Here, we investigated the effect of task on neural responses to dynamic gaze changes: away and toward transitions (resulting or not in eye contact). Subjects performed, in random order, social (away/toward them) and non-social (left/right) judgment tasks on these stimuli. Overall, in the non-social task, results showed a larger N170 to gaze aversion than gaze motion toward the observer. In the social task, however, this difference was no longer present in the right hemisphere, likely reflecting an enhanced N170 to gaze motion toward the observer. Our behavioral and event-related potential data indicate that performing social judgments enhances saliency of gaze motion toward the observer, even those that did not result in gaze contact. These data and that of previous studies suggest two modes of processing visual information: a ‘default mode’ that may focus on spatial information; a ‘socially aware mode’ that might be activated when subjects are required to make social judgments. The exact mechanism that allows switching from one mode to the other remains to be clarified. PMID:25925272

  10. Social decisions affect neural activity to perceived dynamic gaze.

    PubMed

    Latinus, Marianne; Love, Scott A; Rossi, Alejandra; Parada, Francisco J; Huang, Lisa; Conty, Laurence; George, Nathalie; James, Karin; Puce, Aina

    2015-11-01

    Gaze direction, a cue of both social and spatial attention, is known to modulate early neural responses to faces e.g. N170. However, findings in the literature have been inconsistent, likely reflecting differences in stimulus characteristics and task requirements. Here, we investigated the effect of task on neural responses to dynamic gaze changes: away and toward transitions (resulting or not in eye contact). Subjects performed, in random order, social (away/toward them) and non-social (left/right) judgment tasks on these stimuli. Overall, in the non-social task, results showed a larger N170 to gaze aversion than gaze motion toward the observer. In the social task, however, this difference was no longer present in the right hemisphere, likely reflecting an enhanced N170 to gaze motion toward the observer. Our behavioral and event-related potential data indicate that performing social judgments enhances saliency of gaze motion toward the observer, even those that did not result in gaze contact. These data and that of previous studies suggest two modes of processing visual information: a 'default mode' that may focus on spatial information; a 'socially aware mode' that might be activated when subjects are required to make social judgments. The exact mechanism that allows switching from one mode to the other remains to be clarified.

  11. Activity.

    ERIC Educational Resources Information Center

    Clearing: Nature and Learning in the Pacific Northwest, 1984

    1984-01-01

    Presents three activities: (1) investigating succession in a schoolground; (2) investigating oak galls; and (3) making sun prints (photographs made without camera or darkroom). Each activity includes a list of materials needed and procedures used. (JN)

  12. Natural lecithin promotes neural network complexity and activity

    PubMed Central

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

    2016-01-01

    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. PMID:27228907

  13. Neural activity reveals perceptual grouping in working memory.

    PubMed

    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.

  14. Cerebral Oxygen Delivery and Consumption During Evoked Neural Activity

    PubMed Central

    Vazquez, Alberto L.; Masamoto, Kazuto; Fukuda, Mitsuhiro; Kim, Seong-Gi

    2010-01-01

    Increases in neural activity evoke increases in the delivery and consumption of oxygen. Beyond observations of cerebral tissue and blood oxygen, the role and properties of cerebral oxygen delivery and consumption during changes in brain function are not well understood. This work overviews the current knowledge of functional oxygen delivery and consumption and introduces recent and preliminary findings to explore the mechanisms by which oxygen is delivered to tissue as well as the temporal dynamics of oxygen metabolism. Vascular oxygen tension measurements have shown that a relatively large amount of oxygen exits pial arterioles prior to capillaries. Additionally, increases in cerebral blood flow (CBF) induced by evoked neural activation are accompanied by arterial vasodilation and also by increases in arteriolar oxygenation. This increase contributes not only to the down-stream delivery of oxygen to tissue, but also to delivery of additional oxygen to extra-vascular spaces surrounding the arterioles. On the other hand, the changes in tissue oxygen tension due to functional increases in oxygen consumption have been investigated using a method to suppress the evoked CBF response. The functional decreases in tissue oxygen tension induced by increases in oxygen consumption are slow to evoked changes in CBF under control conditions. Preliminary findings obtained using flavoprotein autofluorescence imaging suggest cellular oxidative metabolism changes at a faster rate than the average changes in tissue oxygen. These issues are important in the determination of the dynamic changes in tissue oxygen metabolism from hemoglobin-based imaging techniques such as blood oxygenation-level dependent functional magnetic resonance imaging (fMRI). PMID:20616881

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

    NASA Astrophysics Data System (ADS)

    Mochizuki-Oda, Noriko; Kataoka, Yosky; Yamada, Hisao; Awazu, Kunio

    2004-08-01

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

  16. Multisynaptic activity in a pyramidal neuron model and neural code.

    PubMed

    Ventriglia, Francesco; Di Maio, Vito

    2006-01-01

    The highly irregular firing of mammalian cortical pyramidal neurons is one of the most striking observation of the brain activity. This result affects greatly the discussion on the neural code, i.e. how the brain codes information transmitted along the different cortical stages. In fact it seems to be in favor of one of the two main hypotheses about this issue, named the rate code. But the supporters of the contrasting hypothesis, the temporal code, consider this evidence inconclusive. We discuss here a leaky integrate-and-fire model of a hippocampal pyramidal neuron intended to be biologically sound to investigate the genesis of the irregular pyramidal firing and to give useful information about the coding problem. To this aim, the complete set of excitatory and inhibitory synapses impinging on such a neuron has been taken into account. The firing activity of the neuron model has been studied by computer simulation both in basic conditions and allowing brief periods of over-stimulation in specific regions of its synaptic constellation. Our results show neuronal firing conditions similar to those observed in experimental investigations on pyramidal cortical neurons. In particular, the variation coefficient (CV) computed from the inter-spike intervals (ISIs) in our simulations for basic conditions is close to the unity as that computed from experimental data. Our simulation shows also different behaviors in firing sequences for different frequencies of stimulation.

  17. Generalized activity equations for spiking neural network dynamics

    PubMed Central

    Buice, Michael A.; Chow, Carson C.

    2013-01-01

    Much progress has been made in uncovering the computational capabilities of spiking neural networks. However, spiking neurons will always be more expensive to simulate compared to rate neurons because of the inherent disparity in time scales—the spike duration time is much shorter than the inter-spike time, which is much shorter than any learning time scale. In numerical analysis, this is a classic stiff problem. Spiking neurons are also much more difficult to study analytically. One possible approach to making spiking networks more tractable is to augment mean field activity models with some information about spiking correlations. For example, such a generalized activity model could carry information about spiking rates and correlations between spikes self-consistently. Here, we will show how this can be accomplished by constructing a complete formal probabilistic description of the network and then expanding around a small parameter such as the inverse of the number of neurons in the network. The mean field theory of the system gives a rate-like description. The first order terms in the perturbation expansion keep track of covariances. PMID:24298252

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

    NASA Astrophysics Data System (ADS)

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

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

  19. A novel approach to image neural activity directly by MRI

    NASA Astrophysics Data System (ADS)

    Singh, Manbir; Sungkarat, Witaya

    2005-04-01

    Though an approach to image the electrical activity of neurons directly by detecting phase shifts in MRI was first reported in 1991, results to-date remain equivocal due to the low signal-to-noise ratio. The objective of this work was to develop a stimulus-presentation and data acquisition strategy specially geared to detect phase-dispersion effects of neuronal currents within 10-100 ms following stimulation. The key feature is to set the repeated MR data acquisition time TR and the stimulus presentation interval (TI) slightly different from each other so that the time at which images are acquired shifts gradually from one acquisition to the next with respect to stimulus onset. For example, at TR=275ms and 4 Hz stimulus presentation (TI=250ms), initial synchronization of the stimulus onset and MR acquisition would result in the first image being acquired at a latency of 0+/- (temporal width of data acquisition window), second image at a latency of 25ms, third image at a latency of 50ms and so on up to a latency of 250ms, at which time the stimulus and data acquisition times would become re-synchronized to once again acquire an image at latency=0. Human data were acquired on a 1.5T GE EXCITE scanner from two 8mm thick contiguous slices bracketing the calcarine fissure during a checkerboard flashing at 4 Hz. Preliminary results show activity in the visual cortex at latencies consistent with EEG studies, suggesting the potential of this methodology to image neural activity directly.

  20. Neural activity associated with distinguishing concurrent auditory objects

    NASA Astrophysics Data System (ADS)

    Alain, Claude; Schuler, Benjamin M.; McDonald, Kelly L.

    2002-02-01

    The neural processes underlying concurrent sound segregation were examined by using event-related brain potentials. Participants were presented with complex sounds comprised of multiple harmonics, one of which could be mistuned so that it was no longer an integer multiple of the fundamental. In separate blocks of trials, short-, middle-, and long-duration sounds were presented and participants indicated whether they heard one sound (i.e., buzz) or two sounds (i.e., buzz plus another sound with a pure-tone quality). The auditory stimuli were also presented while participants watched a silent movie in order to evaluate the extent to which the mistuned harmonic could be automatically detected. The perception of the mistuned harmonic as a separate sound was associated with a biphasic negative-positive potential that peaked at about 150 and 350 ms after sound onset, respectively. Long duration sounds also elicited a sustained potential that was greater in amplitude when the mistuned harmonic was perceptually segregated from the complex sound. The early negative wave, referred to as the object-related negativity (ORN), was present during both active and passive listening, whereas the positive wave and the mistuning-related changes in sustained potentials were present only when participants attended to the stimuli. These results are consistent with a two-stage model of auditory scene analysis in which the acoustic wave is automatically decomposed into perceptual groups that can be identified by higher executive functions. The ORN and the positive waves were little affected by sound duration, indicating that concurrent sound segregation depends on transient neural responses elicited by the discrepancy between the mistuned harmonic and the harmonic frequency expected based on the fundamental frequency of the incoming stimulus.

  1. Tools for resolving functional activity and connectivity within intact neural circuits.

    PubMed

    Jennings, Joshua H; Stuber, Garret D

    2014-01-06

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

  2. Integration of active devices on smart polymers for neural interfaces

    NASA Astrophysics Data System (ADS)

    Avendano-Bolivar, Adrian Emmanuel

    The increasing ability to ever more precisely identify and measure neural interactions and other phenomena in the central and peripheral nervous systems is revolutionizing our understanding of the human body and brain. To facilitate further understanding, more sophisticated neural devices, perhaps using microelectronics processing, must be fabricated. Materials often used in these neural interfaces, while compatible with these fabrication processes, are not optimized for long-term use in the body and are often orders of magnitude stiffer than the tissue with which they interact. Using the smart polymer substrates described in this work, suitability for processing as well as chronic implantation is demonstrated. We explore how to integrate reliable circuitry onto these flexible, biocompatible substrates that can withstand the aggressive environment of the body. To increase the capabilities of these devices beyond individual channel sensing and stimulation, active electronics must also be included onto our systems. In order to add this functionality to these substrates and explore the limits of these devices, we developed a process to fabricate single organic thin film transistors with mobilities up to 0.4 cm2/Vs and threshold voltages close to 0V. A process for fabricating organic light emitting diodes on flexible substrates is also addressed. We have set a foundation and demonstrated initial feasibility for integrating multiple transistors onto thin-film flexible devices to create new applications, such as matrix addressable functionalized electrodes and organic light emitting diodes. A brief description on how to integrate waveguides for their use in optogenetics is addressed. We have built understanding about device constraints on mechanical, electrical and in vivo reliability and how various conditions affect the electronics' lifetime. We use a bi-layer gate dielectric using an inorganic material such as HfO 2 combined with organic Parylene-c. A study of

  3. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

    PubMed Central

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

    2016-01-01

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

  4. Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

    PubMed

    Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

    2016-12-27

    Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

  5. Neural crest specification and migration independently require NSD3-related lysine methyltransferase activity

    PubMed Central

    Jacques-Fricke, Bridget T.; Gammill, Laura S.

    2014-01-01

    Neural crest precursors express genes that cause them to become migratory, multipotent cells, distinguishing them from adjacent stationary neural progenitors in the neurepithelium. Histone methylation spatiotemporally regulates neural crest gene expression; however, the protein methyltransferases active in neural crest precursors are unknown. Moreover, the regulation of methylation during the dynamic process of neural crest migration is unclear. Here we show that the lysine methyltransferase NSD3 is abundantly and specifically expressed in premigratory and migratory neural crest cells. NSD3 expression commences before up-regulation of neural crest genes, and NSD3 is necessary for expression of the neural plate border gene Msx1, as well as the key neural crest transcription factors Sox10, Snail2, Sox9, and FoxD3, but not gene expression generally. Nevertheless, only Sox10 histone H3 lysine 36 dimethylation requires NSD3, revealing unexpected complexity in NSD3-dependent neural crest gene regulation. In addition, by temporally limiting expression of a dominant negative to migratory stages, we identify a novel, direct requirement for NSD3-related methyltransferase activity in neural crest migration. These results identify NSD3 as the first protein methyltransferase essential for neural crest gene expression during specification and show that NSD3-related methyltransferase activity independently regulates migration. PMID:25318671

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

    ERIC Educational Resources Information Center

    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…

  7. Activities.

    ERIC Educational Resources Information Center

    Bippert, Judy

    1993-01-01

    Presents activities designed to give students an opportunity to solve concrete problems involving spatial relationships and logical thinking utilizing hands-on manipulatives. Provides teacher instructions and four reproducible worksheets. (MDH)

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Trait motivation moderates neural activation associated with goal pursuit.

    PubMed

    Spielberg, Jeffrey M; Miller, Gregory A; Warren, Stacie L; Engels, Anna S; Crocker, Laura D; Sutton, Bradley P; Heller, Wendy

    2012-06-01

    Research has indicated that regions of left and right dorsolateral prefrontal cortex (DLPFC) are involved in integrating the motivational and executive function processes related to, respectively, approach and avoidance goals. Given that sensitivity to pleasant and unpleasant stimuli is an important feature of conceptualizations of approach and avoidance motivation, it is possible that these regions of DLPFC are preferentially activated by valenced stimuli. The present study tested this hypothesis by using a task in which goal pursuit was threatened by distraction from valenced stimuli while functional magnetic resonance imaging data were collected. The analyses examined whether the impact of trait approach and avoidance motivation on the neural processes associated with executive function differed depending on the valence or arousal level of the distractor stimuli. The present findings support the hypothesis that the regions of DLPFC under investigation are involved in integrating motivational and executive function processes, and they also indicate the involvement of a number of other brain areas in maintaining goal pursuit. However, DLPFC did not display differential sensitivity to valence.

  10. Brain temperature fluctuation: a reflection of functional neural activation.

    PubMed

    Kiyatkin, Eugene A; Brown, P Leon; Wise, Roy A

    2002-07-01

    Although it is known that relatively large increases in local brain temperature can occur during behaviour and in response to various novel, stressful and emotionally arousing environmental stimuli, the source of this heat is not clearly established. To clarify this issue, we monitored the temperature in three brain structures (dorsal and ventral striatum, cerebellum) and in arterial blood at the level of the abdominal aorta in freely moving rats exposed to several environmental challenges ranging from traditional stressors to simple sensory stimuli (cage change, tail pinch, exposure to another male rat, a female rat, a mouse or an unexpected sound). We found that brain temperature was consistently higher than arterial blood temperature, and that brain temperature increased prior to, and to a greater extent than, the increase in blood temperature evoked by each test challenge. Thus, the local metabolic consequences of widely correlated neural activity appear to be the primary source of increases in brain temperature and a driving force behind the associated changes in body temperature.

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

    PubMed

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

    2015-06-01

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

  12. Specific domains of FoxD4/5 activate and repress neural transcription factor genes to control the progression of immature neural ectoderm to differentiating neural plate.

    PubMed

    Neilson, Karen M; Klein, Steven L; Mhaske, Pallavi; Mood, Kathy; Daar, Ira O; Moody, Sally A

    2012-05-15

    FoxD4/5, a forkhead transcription factor, plays a critical role in establishing and maintaining the embryonic neural ectoderm. It both up-regulates genes that maintain a proliferative, immature neural ectoderm and down-regulates genes that promote the transition to a differentiating neural plate. We constructed deletion and mutant versions of FoxD4/5 to determine which domains are functionally responsible for these opposite activities, which regulate the critical developmental transition of neural precursors to neural progenitors to differentiating neural plate cells. Our results show that up-regulation of genes that maintain immature neural precursors (gem, zic2) requires the Acidic blob (AB) region in the N-terminal portion of the protein, indicating that the AB is the transactivating domain. Additionally, down-regulation of those genes that promote the transition to neural progenitors (sox) and those that lead to neural differentiation (zic, irx) involves: 1) an interaction with the Groucho co-repressor at the Eh-1 motif in the C-terminus; and 2) sequence downstream of this motif. Finally, the ability of FoxD4/5 to induce the ectopic expression of neural precursor genes in the ventral ectoderm also involves both the AB region and the Eh-1 motif; FoxD4/5 accomplishes ectopic neural induction by both activating neural precursor genes and repressing BMP signaling and epidermal genes. This study identifies the specific, conserved domains of the FoxD4/5 protein that allow this single transcription factor to regulate a network of genes that controls the transition of a proliferative neural ectodermal population to a committed neural plate population poised to begin differentiation.

  13. Studying modulation on simultaneously activated SSVEP neural networks by a cognitive task.

    PubMed

    Wu, Zhenghua

    2014-01-01

    Since the discovery of steady-state visually evoked potential (SSVEP), it has been used in many fields. Numerous studies suggest that there exist three SSVEP neural networks in different frequency bands. An obvious phenomenon has been observed, that the amplitude and phase of SSVEP can be modulated by a cognitive task. Previous works have studied this modulation on separately activated SSVEP neural networks by a cognitive task. If two or more SSVEP neural networks are activated simultaneously in the process of a cognitive task, is the modulation on different SSVEP neural networks the same? In this study, two different SSVEP neural networks were activated simultaneously by two different frequency flickers, with a working memory task irrelevant to the flickers being conducted at the same time. The modulated SSVEP waves were compared with each other and to those only under one flicker in previous studies. The comparison results show that the cognitive task can modulate different SSVEP neural networks with a similar style.

  14. Activities.

    ERIC Educational Resources Information Center

    Kincaid, Charlene; And Others

    1993-01-01

    Presents an activity in which students collect and organize data from a real-world simulation of the scientific concept of half life. Students collect data using a marble sifter, analyze the data using a graphing calculator, and determine an appropriate mathematical model. Includes reproducible worksheets. (MDH)

  15. Convergence of nicotine-induced and auditory-evoked neural activity activates ERK in auditory cortex.

    PubMed

    Kawai, Hideki D; La, Maggie; Kang, Ho-An; Hashimoto, Yusuke; Liang, Kevin; Lazar, Ronit; Metherate, Raju

    2013-08-01

    Enhancement of sound-evoked responses in auditory cortex (ACx) following administration of systemic nicotine is known to depend on activation of extracellular-signaling regulated kinase (ERK), but the nature of this enhancement is not clear. Here, we show that systemic nicotine increases the density of cells immunolabeled for phosphorylated (activated) ERK (P-ERK) in mouse primary ACx (A1). Cortical injection of dihydro-β-erythroidine reduced nicotine-induced P-ERK immunolabel, suggesting a role for nicotinic acetylcholine receptors located in A1 and containing α4 and β2 subunits. P-ERK expressing cells were distributed mainly in layers 2/3 and more sparsely in lower layers, with many cells exhibiting immunolabel within pyramidal-shaped somata and proximal apical dendrites. About one-third of P-ERK positive cells also expressed calbindin. In the thalamus, P-ERK immunopositive cells were found in the nonlemniscal medial geniculate (MG) and adjacent nuclei, but were absent in the lemniscal MG. Pairing broad spectrum acoustic stimulation (white noise) with systemic nicotine increased P-ERK immunopositive cell density in ACx as well as the total amount of P-ERK protein, particularly the phosphorylated form of ERK2. However, narrow spectrum (tone) stimulation paired with nicotine increased P-ERK immunolabel preferentially at a site within A1 where the paired frequency was characteristic frequency (CF), relative to a second site with a spectrally distant CF (two octaves above or below the paired frequency). Together, these results suggest that ERK is activated optimally where nicotinic signaling and sound-evoked neural activity converge.

  16. Dampened neural activity and abolition of epileptic-like activity in cortical slices by active ingredients of spices

    PubMed Central

    Pezzoli, Maurizio; Elhamdani, Abdeladim; Camacho, Susana; Meystre, Julie; González, Stephanie Michlig; le Coutre, Johannes; Markram, Henry

    2014-01-01

    Active ingredients of spices (AIS) modulate neural response in the peripheral nervous system, mainly through interaction with TRP channel/receptors. The present study explores how different AIS modulate neural response in layer 5 pyramidal neurons of S1 neocortex. The AIS tested are agonists of TRPV1/3, TRPM8 or TRPA1. Our results demonstrate that capsaicin, eugenol, menthol, icilin and cinnamaldehyde, but not AITC dampen the generation of APs in a voltage- and time-dependent manner. This effect was further tested for the TRPM8 ligands in the presence of a TRPM8 blocker (BCTC) and on TRPM8 KO mice. The observable effect was still present. Finally, the influence of the selected AIS was tested on in vitro gabazine-induced seizures. Results coincide with the above observations: except for cinnamaldehyde, the same AIS were able to reduce the number, duration of the AP bursts and increase the concentration of gabazine needed to elicit them. In conclusion, our data suggests that some of these AIS can modulate glutamatergic neurons in the brain through a TRP-independent pathway, regardless of whether the neurons are stimulated intracellularly or by hyperactive microcircuitry. PMID:25359561

  17. Dampened neural activity and abolition of epileptic-like activity in cortical slices by active ingredients of spices.

    PubMed

    Pezzoli, Maurizio; Elhamdani, Abdeladim; Camacho, Susana; Meystre, Julie; González, Stephanie Michlig; le Coutre, Johannes; Markram, Henry

    2014-10-31

    Active ingredients of spices (AIS) modulate neural response in the peripheral nervous system, mainly through interaction with TRP channel/receptors. The present study explores how different AIS modulate neural response in layer 5 pyramidal neurons of S1 neocortex. The AIS tested are agonists of TRPV1/3, TRPM8 or TRPA1. Our results demonstrate that capsaicin, eugenol, menthol, icilin and cinnamaldehyde, but not AITC dampen the generation of APs in a voltage- and time-dependent manner. This effect was further tested for the TRPM8 ligands in the presence of a TRPM8 blocker (BCTC) and on TRPM8 KO mice. The observable effect was still present. Finally, the influence of the selected AIS was tested on in vitro gabazine-induced seizures. Results coincide with the above observations: except for cinnamaldehyde, the same AIS were able to reduce the number, duration of the AP bursts and increase the concentration of gabazine needed to elicit them. In conclusion, our data suggests that some of these AIS can modulate glutamatergic neurons in the brain through a TRP-independent pathway, regardless of whether the neurons are stimulated intracellularly or by hyperactive microcircuitry.

  18. Absolute exponential stability of recurrent neural networks with Lipschitz-continuous activation functions and time delays.

    PubMed

    Cao, Jinde; Wang, Jun

    2004-04-01

    This paper investigates the absolute exponential stability of a general class of delayed neural networks, which require the activation functions to be partially Lipschitz continuous and monotone nondecreasing only, but not necessarily differentiable or bounded. Three new sufficient conditions are derived to ascertain whether or not the equilibrium points of the delayed neural networks with additively diagonally stable interconnection matrices are absolutely exponentially stable by using delay Halanay-type inequality and Lyapunov function. The stability criteria are also suitable for delayed optimization neural networks and delayed cellular neural networks whose activation functions are often nondifferentiable or unbounded. The results herein answer a question: if a neural network without any delay is absolutely exponentially stable, then under what additional conditions, the neural networks with delay is also absolutely exponentially stable.

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

    PubMed Central

    Yuan, Peng

    2016-01-01

    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. SIGNIFICANCE STATEMENT 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. PMID:26758850

  20. Neural activity underlying tinnitus generation: results from PET and fMRI.

    PubMed

    Lanting, C P; de Kleine, E; van Dijk, P

    2009-09-01

    Tinnitus is the percept of sound that is not related to an acoustic source outside the body. For many forms of tinnitus, mechanisms in the central nervous system are believed to play an important role in the pathology. Specifically, three mechanisms have been proposed to underlie tinnitus: (1) changes in the level of spontaneous neural activity in the central auditory system, (2) changes in the temporal pattern of neural activity, and (3) reorganization of tonotopic maps. The neuroimaging methods fMRI and PET measure signals that presumably reflect the firing rates of multiple neurons and are assumed to be sensitive to changes in the level of neural activity. There are two basic paradigms that have been applied in functional neuroimaging of tinnitus. Firstly, sound-evoked responses as well as steady state neural activity have been measured to compare tinnitus patients to healthy controls. Secondly, paradigms that involve modulation of tinnitus by a controlled stimulus allow for a within-subject comparison that identifies neural activity that may be correlated to the tinnitus percept. Even though there are many differences across studies, the general trend emerging from the neuroimaging studies, is that tinnitus in humans may correspond to enhanced neural activity across several centers of the central auditory system. Also, neural activity in non-auditory areas including the frontal areas, the limbic system and the cerebellum seems associated with the perception of tinnitus. These results indicate that in addition to the auditory system, non-auditory systems may represent a neural correlate of tinnitus. Although the currently published neuroimaging studies typically show a correspondence between tinnitus and enhanced neural activity, it will be important to perform future studies on subject groups that are closely matched for characteristics such as age, gender and hearing loss in order to rule out the contribution of these factors to the abnormalities specifically

  1. Neural Activity in the Ventral Pallidum Encodes Variation in the Incentive Value of a Reward Cue

    PubMed Central

    Meyer, Paul J.; Ferguson, Lindsay M.; Robinson, Terry E.; Aldridge, J. Wayne

    2016-01-01

    There is considerable individual variation in the extent to which reward cues are attributed with incentive salience. For example, a food-predictive conditioned stimulus (CS; an illuminated lever) becomes attractive, eliciting approach toward it only in some rats (“sign trackers,” STs), whereas others (“goal trackers,” GTs) approach the food cup during the CS period. The purpose of this study was to determine how individual differences in Pavlovian approach responses are represented in neural firing patterns in the major output structure of the mesolimbic system, the ventral pallidum (VP). Single-unit in vivo electrophysiology was used to record neural activity in the caudal VP during the performance of ST and GT conditioned responses. All rats showed neural responses to both cue onset and reward delivery but, during the CS period, STs showed greater neural activity than GTs both in terms of the percentage of responsive neurons and the magnitude of the change in neural activity. Furthermore, neural activity was positively correlated with the degree of attraction to the cue. Given that the CS had equal predictive value in STs and GTs, we conclude that neural activity in the VP largely reflects the degree to which the CS was attributed with incentive salience. SIGNIFICANCE STATEMENT Cues associated with reward can acquire motivational properties (i.e., incentive salience) that cause them to have a powerful influence on desire and motivated behavior. There are individual differences in sensitivity to reward-paired cues, with some individuals attaching greater motivational value to cues than others. Here, we investigated the neural activity associated with these individual differences in incentive salience. We found that cue-evoked neural firing in the ventral pallidum (VP) reflected the strength of incentive motivation, with the greatest neural responses occurring in individuals that demonstrated the strongest attraction to the cue. This suggests that the VP

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

    PubMed Central

    Emadi, Nazli; Rajimehr, Reza; Esteky, Hossein

    2014-01-01

    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. PMID:25404900

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

    PubMed Central

    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

  4. Spontaneous neural activity during human slow wave sleep.

    PubMed

    Dang-Vu, Thien Thanh; Schabus, Manuel; Desseilles, Martin; Albouy, Geneviève; Boly, Mélanie; Darsaud, Annabelle; Gais, Steffen; Rauchs, Géraldine; Sterpenich, Virginie; Vandewalle, Gilles; Carrier, Julie; Moonen, Gustave; Balteau, Evelyne; Degueldre, Christian; Luxen, André; Phillips, Christophe; Maquet, Pierre

    2008-09-30

    Slow wave sleep (SWS) is associated with spontaneous brain oscillations that are thought to participate in sleep homeostasis and to support the processing of information related to the experiences of the previous awake period. At the cellular level, during SWS, a slow oscillation (<1 Hz) synchronizes firing patterns in large neuronal populations and is reflected on electroencephalography (EEG) recordings as large-amplitude, low-frequency waves. By using simultaneous EEG and event-related functional magnetic resonance imaging (fMRI), we characterized the transient changes in brain activity consistently associated with slow waves (>140 microV) and delta waves (75-140 microV) during SWS in 14 non-sleep-deprived normal human volunteers. Significant increases in activity were associated with these waves in several cortical areas, including the inferior frontal, medial prefrontal, precuneus, and posterior cingulate areas. Compared with baseline activity, slow waves are associated with significant activity in the parahippocampal gyrus, cerebellum, and brainstem, whereas delta waves are related to frontal responses. No decrease in activity was observed. This study demonstrates that SWS is not a state of brain quiescence, but rather is an active state during which brain activity is consistently synchronized to the slow oscillation in specific cerebral regions. The partial overlap between the response pattern related to SWS waves and the waking default mode network is consistent with the fascinating hypothesis that brain responses synchronized by the slow oscillation restore microwake-like activity patterns that facilitate neuronal interactions.

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

    NASA Astrophysics Data System (ADS)

    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

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

    PubMed

    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.

  7. A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

    PubMed Central

    Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

    2014-01-01

    Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

  8. Frequency domain active vibration control of a flexible plate based on neural networks

    NASA Astrophysics Data System (ADS)

    Liu, Jinxin; Chen, Xuefeng; He, Zhengjia

    2013-06-01

    A neural-network (NN)-based active control system was proposed to reduce the low frequency noise radiation of the simply supported flexible plate. Feedback control system was built, in which neural network controller (NNC) and neural network identifier (NNI) were applied. Multi-frequency control in frequency domain was achieved by simulation through the NN-based control systems. A pre-testing experiment of the control system on a real simply supported plate was conducted. The NN-based control algorithm was shown to perform effectively. These works lay a solid foundation for the active vibration control of mechanical structures.

  9. The optimization of force inputs for active structural acoustic control using a neural network

    NASA Technical Reports Server (NTRS)

    Cabell, R. H.; Lester, H. C.; Silcox, R. J.

    1992-01-01

    This paper investigates the use of a neural network to determine which force actuators, of a multi-actuator array, are best activated in order to achieve structural-acoustic control. The concept is demonstrated using a cylinder/cavity model on which the control forces, produced by piezoelectric actuators, are applied with the objective of reducing the interior noise. A two-layer neural network is employed and the back propagation solution is compared with the results calculated by a conventional, least-squares optimization analysis. The ability of the neural network to accurately and efficiently control actuator activation for interior noise reduction is demonstrated.

  10. Light-induced Notch activity controls neurogenic and gliogenic potential of neural progenitors.

    PubMed

    Kim, Kyung-Tai; Song, Mi-Ryoung

    2016-10-28

    Oscillations in Notch signaling are essential for reserving neural progenitors for cellular diversity in developing brains. Thus, steady and prolonged overactivation of Notch signaling is not suitable for generating neurons. To acquire greater temporal control of Notch activity and mimic endogenous oscillating signals, here we adopted a light-inducible transgene system to induce active form of Notch NICD in neural progenitors. Alternating Notch activity saved more progenitors that are prone to produce neurons creating larger number of mixed clones with neurons and progenitors in vitro, compared to groups with no light or continuous light stimulus. Furthermore, more upper layer neurons and astrocytes arose upon intermittent Notch activity, indicating that dynamic Notch activity maintains neural progeny and fine-tune neuron-glia diversity.

  11. In vivo blockade of neural activity alters dendritic development of neonatal CA1 pyramidal cells.

    PubMed

    Groc, Laurent; Petanjek, Zdravko; Gustafsson, Bengt; Ben-Ari, Yehezkel; Hanse, Eric; Khazipov, Roustem

    2002-11-01

    During development, neural activity has been proposed to promote neuronal growth. During the first postnatal week, the hippocampus is characterized by an oscillating neural network activity and a rapid neuronal growth. In the present study we tested in vivo, by injecting tetanus toxin into the hippocampus of P1 rats, whether this neural activity indeed promotes growth of pyramidal cells. We have previously shown that tetanus toxin injection leads to a strong reduction in the frequency of spontaneous GABA and glutamatergic synaptic currents, and to a complete blockade of the early neural network activity during the first postnatal week. Morphology of neurobiotin-filled CA1 pyramidal cells was analyzed at the end of the first postnatal week (P6-10). In activity-reduced neurons, the total length of basal dendritic tree was three times less than control. The number, but not the length, of basal dendritic branches was affected. The growth impairment was restricted to the basal dendrites. The apical dendrite, the axons, or the soma grew normally during activity deprivation. Thus, the in vivo neural activity in the neonate hippocampus seems to promote neuronal growth by initiating novel branches.

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

    PubMed

    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.

  13. Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

    PubMed Central

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

    2011-01-01

    Objective 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. Design 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. Results 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 ( Rself−report2=.15,Rself−report+neuralactivity2=.35,Rchange2=.20). Conclusion: 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. PMID:21261410

  14. Real-time Neural Network predictions of geomagnetic activity indices

    NASA Astrophysics Data System (ADS)

    Bala, R.; Reiff, P. H.

    2009-12-01

    The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction

  15. Spatiotemporal Imaging of Glutamate-Induced Biophotonic Activities and Transmission in Neural Circuits

    PubMed Central

    Tang, Rendong; Dai, Jiapei

    2014-01-01

    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 Ca2+. 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 neural

  16. Activity-Regulated Genes as Mediators of Neural Circuit Plasticity

    PubMed Central

    Leslie, Jennifer H.; Nedivi, Elly

    2011-01-01

    Modifications of neuronal circuits allow the brain to adapt and change with experience. This plasticity manifests during development and throughout life, and can be remarkably long lasting. Many electrophysiological and molecular mechanisms are common to the seemingly diverse types of activity-dependent functional adaptation that take place during developmental critical periods, learning and memory, and alterations to sensory map representations in the adult. Experience-dependent plasticity is triggered when neuronal excitation activates cellular signaling pathways from the synapse to the nucleus that initiate new programs of gene expression. The protein products of activity-regulated genes then work via a diverse array of cellular mechanisms to modify neuronal functional properties. They fine-tune brain circuits by strengthening or weakening synaptic connections or by altering synapse numbers. Their effects are further modulated by posttranscriptional regulatory mechanisms, often also dependent on activity, that control activity-regulated gene transcript and protein function. Thus, the cellular response to neuronal activity integrates multiple tightly coordinated mechanisms to precisely orchestrate long-lasting, functional and structural changes in brain circuits. PMID:21601615

  17. Fractal patterns of neural activity exist within the suprachiasmatic nucleus and require extrinsic network interactions.

    PubMed

    Hu, Kun; Meijer, Johanna H; Shea, Steven A; vanderLeest, Henk Tjebbe; Pittman-Polletta, Benjamin; Houben, Thijs; van Oosterhout, Floor; Deboer, Tom; Scheer, Frank A J L

    2012-01-01

    The mammalian central circadian pacemaker (the suprachiasmatic nucleus, SCN) contains thousands of neurons that are coupled through a complex network of interactions. In addition to the established role of the SCN in generating rhythms of ~24 hours in many physiological functions, the SCN was recently shown to be necessary for normal self-similar/fractal organization of motor activity and heart rate over a wide range of time scales--from minutes to 24 hours. To test whether the neural network within the SCN is sufficient to generate such fractal patterns, we studied multi-unit neural activity of in vivo and in vitro SCNs in rodents. In vivo SCN-neural activity exhibited fractal patterns that are virtually identical in mice and rats and are similar to those in motor activity at time scales from minutes up to 10 hours. In addition, these patterns remained unchanged when the main afferent signal to the SCN, namely light, was removed. However, the fractal patterns of SCN-neural activity are not autonomous within the SCN as these patterns completely broke down in the isolated in vitro SCN despite persistence of circadian rhythmicity. Thus, SCN-neural activity is fractal in the intact organism and these fractal patterns require network interactions between the SCN and extra-SCN nodes. Such a fractal control network could underlie the fractal regulation observed in many physiological functions that involve the SCN, including motor control and heart rate regulation.

  18. Dynamical Behaviors of Multiple Equilibria in Competitive Neural Networks With Discontinuous Nonmonotonic Piecewise Linear Activation Functions.

    PubMed

    Nie, Xiaobing; Zheng, Wei Xing

    2016-03-01

    This paper addresses the problem of coexistence and dynamical behaviors of multiple equilibria for competitive neural networks. First, a general class of discontinuous nonmonotonic piecewise linear activation functions is introduced for competitive neural networks. Then based on the fixed point theorem and theory of strict diagonal dominance matrix, it is shown that under some conditions, such n -neuron competitive neural networks can have 5(n) equilibria, among which 3(n) equilibria are locally stable and the others are unstable. More importantly, it is revealed that the neural networks with the discontinuous activation functions introduced in this paper can have both more total equilibria and locally stable equilibria than the ones with other activation functions, such as the continuous Mexican-hat-type activation function and discontinuous two-level activation function. Furthermore, the 3(n) locally stable equilibria given in this paper are located in not only saturated regions, but also unsaturated regions, which is different from the existing results on multistability of neural networks with multiple level activation functions. A simulation example is provided to illustrate and validate the theoretical findings.

  19. Early neural activation during facial affect processing in adolescents with Autism Spectrum Disorder☆

    PubMed Central

    Leung, Rachel C.; Pang, Elizabeth W.; Cassel, Daniel; Brian, Jessica A.; Smith, Mary Lou; Taylor, Margot J.

    2014-01-01

    Impaired social interaction is one of the hallmarks of Autism Spectrum Disorder (ASD). Emotional faces are arguably the most critical visual social stimuli and the ability to perceive, recognize, and interpret emotions is central to social interaction and communication, and subsequently healthy social development. However, our understanding of the neural and cognitive mechanisms underlying emotional face processing in adolescents with ASD is limited. We recruited 48 adolescents, 24 with high functioning ASD and 24 typically developing controls. Participants completed an implicit emotional face processing task in the MEG. We examined spatiotemporal differences in neural activation between the groups during implicit angry and happy face processing. While there were no differences in response latencies between groups across emotions, adolescents with ASD had lower accuracy on the implicit emotional face processing task when the trials included angry faces. MEG data showed atypical neural activity in adolescents with ASD during angry and happy face processing, which included atypical activity in the insula, anterior and posterior cingulate and temporal and orbitofrontal regions. Our findings demonstrate differences in neural activity during happy and angry face processing between adolescents with and without ASD. These differences in activation in social cognitive regions may index the difficulties in face processing and in comprehension of social reward and punishment in the ASD group. Thus, our results suggest that atypical neural activation contributes to impaired affect processing, and thus social cognition, in adolescents with ASD. PMID:25610782

  20. Early neural activation during facial affect processing in adolescents with Autism Spectrum Disorder.

    PubMed

    Leung, Rachel C; Pang, Elizabeth W; Cassel, Daniel; Brian, Jessica A; Smith, Mary Lou; Taylor, Margot J

    2015-01-01

    Impaired social interaction is one of the hallmarks of Autism Spectrum Disorder (ASD). Emotional faces are arguably the most critical visual social stimuli and the ability to perceive, recognize, and interpret emotions is central to social interaction and communication, and subsequently healthy social development. However, our understanding of the neural and cognitive mechanisms underlying emotional face processing in adolescents with ASD is limited. We recruited 48 adolescents, 24 with high functioning ASD and 24 typically developing controls. Participants completed an implicit emotional face processing task in the MEG. We examined spatiotemporal differences in neural activation between the groups during implicit angry and happy face processing. While there were no differences in response latencies between groups across emotions, adolescents with ASD had lower accuracy on the implicit emotional face processing task when the trials included angry faces. MEG data showed atypical neural activity in adolescents with ASD during angry and happy face processing, which included atypical activity in the insula, anterior and posterior cingulate and temporal and orbitofrontal regions. Our findings demonstrate differences in neural activity during happy and angry face processing between adolescents with and without ASD. These differences in activation in social cognitive regions may index the difficulties in face processing and in comprehension of social reward and punishment in the ASD group. Thus, our results suggest that atypical neural activation contributes to impaired affect processing, and thus social cognition, in adolescents with ASD.

  1. Neural Activation Underlying Cognitive Control in the Context of Neutral and Affectively Charged Pictures in Children

    ERIC Educational Resources Information Center

    Lamm, Connie; White, Lauren K.; McDermott, Jennifer Martin; Fox, Nathan A.

    2012-01-01

    The neural correlates of cognitive control for typically developing 9-year-old children were examined using dense-array ERPs and estimates of cortical activation (LORETA) during a go/no-go task with two conditions: a neutral picture condition and an affectively charged picture condition. Activation was estimated for the entire cortex after which…

  2. Linking neural activity and molecular oscillations in the SCN

    PubMed Central

    Colwell, Christopher S.

    2015-01-01

    Neurons in the suprachiasmatic nucleus (SCN) function as part of a central timing circuit that drives daily changes in our behaviour and underlying physiology. A hallmark feature of SCN neuronal populations is that they are mostly electrically silent during the night, start to fire action potentials near dawn and then continue to generate action potentials with a slow and steady pace all day long. Sets of currents are responsible for this daily rhythm, with the strongest evidence for persistent Na+ currents, L-type Ca2+ currents, hyperpolarization-activated currents (IH), large-conductance Ca2+ activated K+ (BK) currents and fast delayed rectifier (FDR) K+ currents. These rhythms in electrical activity are crucial for the function of the circadian timing system, including the expression of clock genes, and decline with ageing and disease. This article reviews our current understanding of the ionic and molecular mechanisms that drive the rhythmic firing patterns in the SCN. PMID:21886186

  3. Self-regulated homoclinic chaos in neural networks activity

    NASA Astrophysics Data System (ADS)

    Volman, Vladislav; Baruchi, Itay; Ben-Jacob, Eshel

    2004-12-01

    We compare the recorded activity of cultured neuronal networks with hybridized model simulations, in which the model neurons are driven by the recorded activity of special neurons. The latter, named `spiker' neurons, that exhibit fast firing with homoclinic chaos like characteristics, are expected to play an important role in the networks' self regulation. The cultured networks are grown from dissociated mixtures of cortical neurons and glia cells. Despite the artificial manner of their construction, the spontaneous activity of these networks exhibits rich dynamical behavior, marked by the formation of temporal sequences of synchronized bursting events (SBEs), and additional features which seemingly reflect the action of underlying regulating mechanism, rather than arbitrary causes and effects. Our model neurons are composed of soma described by the two Morris-Lecar dynamical variables (voltage and fraction of open potassium channels), with dynamical synapses described by the Tsodyks-Markram three variables dynamics. To study the recorded and simulated activities we evaluated the inter-neuron correlation matrices, and analyzed them utilizing the functional holography approach: the correlations are re-normalized by the correlation distances — Euclidean distances between the matrix columns. Then, we project the N-dimensional (for N channels) space spanned by the matrix of re-normalized correlations, or correlation affinities, onto a corresponding 3-D causal manifold (3-D Cartesian space constructed by the 3 leading principal vectors of the N-dimensional space. The neurons are located by their principal eigenvalues and linked by their original (not-normalized) correlations. This reveals hidden causal motifs: the neuron locations and their links form simple structures. Similar causal motifs are exhibited by the model simulations when feeded by the recorded activity of the spiker neurons. We illustrate that the homoclinic chaotic behavior of the spiker neurons can be

  4. Neural conversion of ES cells by an inductive activity on human amniotic membrane matrix

    PubMed Central

    Ueno, Morio; Matsumura, Michiru; Watanabe, Kiichi; Nakamura, Takahiro; Osakada, Fumitaka; Takahashi, Masayo; Kawasaki, Hiroshi; Kinoshita, Shigeru; Sasai, Yoshiki

    2006-01-01

    Here we report a human-derived material with potent inductive activity that selectively converts ES cells into neural tissues. Both mouse and human ES cells efficiently differentiate into neural precursors when cultured on the matrix components of the human amniotic membrane in serum-free medium [amniotic membrane matrix-based ES cell differentiation (AMED)]. AMED-induced neural tissues have regional characteristics (brainstem) similar to those induced by coculture with mouse PA6 stromal cells [a common method called stromal cell-derived inducing activity (SDIA) culture]. Like the SDIA culture, the AMED system is applicable to the in vitro generation of various CNS tissues, including dopaminergic neurons, motor neurons, and retinal pigment epithelium. In contrast to the SDIA method, which uses animal cells, the AMED culture uses a noncellular inductive material derived from an easily available human tissue; therefore, AMED should provide a more suitable and versatile system for generating a variety of neural tissues for clinical applications. PMID:16766664

  5. Distance modulation of neural activity in the visual cortex.

    PubMed

    Dobbins, A C; Jeo, R M; Fiser, J; Allman, J M

    1998-07-24

    Humans use distance information to scale the size of objects. Earlier studies demonstrated changes in neural response as a function of gaze direction and gaze distance in the dorsal visual cortical pathway to parietal cortex. These findings have been interpreted as evidence of the parietal pathway's role in spatial representation. Here, distance-dependent changes in neural response were also found to be common in neurons in the ventral pathway leading to inferotemporal cortex of monkeys. This result implies that the information necessary for object and spatial scaling is common to all visual cortical areas.

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

    NASA Astrophysics Data System (ADS)

    Oniga, Stefan; József, Sütő

    2015-12-01

    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.

  7. Fast fMRI can detect oscillatory neural activity in humans

    PubMed Central

    Lewis, Laura D.; Setsompop, Kawin; Rosen, Bruce R.; Polimeni, Jonathan R.

    2016-01-01

    Oscillatory neural dynamics play an important role in the coordination of large-scale brain networks. High-level cognitive processes depend on dynamics evolving over hundreds of milliseconds, so measuring neural activity in this frequency range is important for cognitive neuroscience. However, current noninvasive neuroimaging methods are not able to precisely localize oscillatory neural activity above 0.2 Hz. Electroencephalography and magnetoencephalography have limited spatial resolution, whereas fMRI has limited temporal resolution because it measures vascular responses rather than directly recording neural activity. We hypothesized that the recent development of fast fMRI techniques, combined with the extra sensitivity afforded by ultra-high-field systems, could enable precise localization of neural oscillations. We tested whether fMRI can detect neural oscillations using human visual cortex as a model system. We detected small oscillatory fMRI signals in response to stimuli oscillating at up to 0.75 Hz within single scan sessions, and these responses were an order of magnitude larger than predicted by canonical linear models. Simultaneous EEG–fMRI and simulations based on a biophysical model of the hemodynamic response to neuronal activity suggested that the blood oxygen level-dependent response becomes faster for rapidly varying stimuli, enabling the detection of higher frequencies than expected. Accounting for phase delays across voxels further improved detection, demonstrating that identifying vascular delays will be of increasing importance with higher-frequency activity. These results challenge the assumption that the hemodynamic response is slow, and demonstrate that fMRI has the potential to map neural oscillations directly throughout the brain. PMID:27729529

  8. Neural Activity during Encoding Predicts False Memories Created by Misinformation

    ERIC Educational Resources Information Center

    Okado, Yoko; Stark, Craig E. L.

    2005-01-01

    False memories are often demonstrated using the misinformation paradigm, in which a person's recollection of a witnessed event is altered after exposure to misinformation about the event. The neural basis of this phenomenon, however, remains unknown. The authors used fMRI to investigate encoding processes during the viewing of an event and…

  9. Increased Neural Activation during Picture Encoding and Retrieval in 60-Year-Olds Compared to 20-Year-Olds

    ERIC Educational Resources Information Center

    Burgmans, S.; van Boxtel, M. P. J.; Vuurman, E. F. P. M.; Evers, E. A. T.; Jolles, J.

    2010-01-01

    Brain aging has been associated with both reduced and increased neural activity during task execution. The purpose of the present study was to investigate whether increased neural activation during memory encoding and retrieval is already present at the age of 60 as well as to obtain more insight into the mechanism behind increased activity.…

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

    PubMed

    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.

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

    PubMed Central

    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

  12. New exponential synchronization criteria for time-varying delayed neural networks with discontinuous activations.

    PubMed

    Cai, Zuowei; Huang, Lihong; Zhang, Lingling

    2015-05-01

    This paper investigates the problem of exponential synchronization of time-varying delayed neural networks with discontinuous neuron activations. Under the extended Filippov differential inclusion framework, by designing discontinuous state-feedback controller and using some analytic techniques, new testable algebraic criteria are obtained to realize two different kinds of global exponential synchronization of the drive-response system. Moreover, we give the estimated rate of exponential synchronization which depends on the delays and system parameters. The obtained results extend some previous works on synchronization of delayed neural networks not only with continuous activations but also with discontinuous activations. Finally, numerical examples are provided to show the correctness of our analysis via computer simulations. Our method and theoretical results have a leading significance in the design of synchronized neural network circuits involving discontinuous factors and time-varying delays.

  13. Linking perception to neural activity as measured by visual evoked potentials.

    PubMed

    Norcia, Anthony M

    2013-11-01

    Linking propositions have played an important role in refining our understanding of the relationship between neural activity and perception. Over the last 40 years, visual evoked potentials (VEPs) have been used in many different ways to address questions of the relationship between neural activity and perception. This review organizes and discusses this research within the linking proposition framework developed by Davida Teller, and her colleagues. A series of examples from the VEP literature illustrates each of the five classes of linking propositions originally proposed by Davida Teller. The related concept of the bridge locus-the site at which neural activity can be said to first be proscriptive of perception-is discussed and a suggestion is made that the concept be expanded to include an evolution over time and cortical area.

  14. Control of a Shunt Active Power Filter with Neural Networks—Theory and Practical Results

    NASA Astrophysics Data System (ADS)

    Villalva, Marcelo G.; Filho, Ernesto Ruppert

    This paper presents theoretical studies and practical results obtained with a four-wire shunt active power filter fully controlled with neural networks. The paper is focused on a current compensation method based on adaptive linear elements (adalines), which are powerful and easy-to-use neural networks. The reader will find here an introduction about these networks, an explanatory section about the achievement of Fourier series with adalines, and the full description of an adaline-based selective current compensator. The paper also brings a quick discussion about the use of a feedforward neural network in the current controller of the active filter, as well as simulation and experimental results obtained with the prototype of an active power filter.

  15. Compact VLSI neural computer integrated with active pixel sensor for real-time ATR applications

    NASA Astrophysics Data System (ADS)

    Fang, Wai-Chi; Udomkesmalee, Gabriel; Alkalai, Leon

    1997-04-01

    A compact VLSI neural computer integrated with an active pixel sensor has been under development to mimic what is inherent in biological vision systems. This electronic eye- brain computer is targeted for real-time machine vision applications which require both high-bandwidth communication and high-performance computing for data sensing, synergy of multiple types of sensory information, feature extraction, target detection, target recognition, and control functions. The neural computer is based on a composite structure which combines Annealing Cellular Neural Network (ACNN) and Hierarchical Self-Organization Neural Network (HSONN). The ACNN architecture is a programmable and scalable multi- dimensional array of annealing neurons which are locally connected with their local neurons. Meanwhile, the HSONN adopts a hierarchical structure with nonlinear basis functions. The ACNN+HSONN neural computer is effectively designed to perform programmable functions for machine vision processing in all levels with its embedded host processor. It provides a two order-of-magnitude increase in computation power over the state-of-the-art microcomputer and DSP microelectronics. A compact current-mode VLSI design feasibility of the ACNN+HSONN neural computer is demonstrated by a 3D 16X8X9-cube neural processor chip design in a 2-micrometers CMOS technology. Integration of this neural computer as one slice of a 4'X4' multichip module into the 3D MCM based avionics architecture for NASA's New Millennium Program is also described.

  16. Improved training of neural networks for the nonlinear active control of sound and vibration.

    PubMed

    Bouchard, M; Paillard, B; Le Dinh, C T

    1999-01-01

    Active control of sound and vibration has been the subject of a lot of research in recent years, and examples of applications are now numerous. However, few practical implementations of nonlinear active controllers have been realized. Nonlinear active controllers may be required in cases where the actuators used in active control systems exhibit nonlinear characteristics, or in cases when the structure to be controlled exhibits a nonlinear behavior. A multilayer perceptron neural-network based control structure was previously introduced as a nonlinear active controller, with a training algorithm based on an extended backpropagation scheme. This paper introduces new heuristical training algorithms for the same neural-network control structure. The objective is to develop new algorithms with faster convergence speed (by using nonlinear recursive-least-squares algorithms) and/or lower computational loads (by using an alternative approach to compute the instantaneous gradient of the cost function). Experimental results of active sound control using a nonlinear actuator with linear and nonlinear controllers are presented. The results show that some of the new algorithms can greatly improve the learning rate of the neural-network control structure, and that for the considered experimental setup a neural-network controller can outperform linear controllers.

  17. Solar geomagnetic activity prediction using the fractal analysis and neural network

    NASA Astrophysics Data System (ADS)

    Ouadfeul, Sid-Ali; Aliouane, Leila

    2010-05-01

    The main goal of this work is to predict the Solar geomagnetic field activity using the neural network combined with the fractal analysis, first a multilayer perceptron neural network model is proposed to predict the future Solar geomagnetic field, the input of this machine is the geographic Coordinates and the time .The output is the three geomagnetic field components and the total field intensity recorded by the Orsted Satellite Mission. Holder Exponents of the measured geomagnetic field components and the total field intensity are calculated using the continuous wavelet transform. The Set of Holder exponents is used to train a Kohonen's Self-Organizing Map (SOM) neural machine which will become a classifier of the solar magnetic activity nature. The SOM neural network machine is used to predict the future solar magnetic storms, in this step the input is the calculated set of the Holder exponents of the predicted geomagnetic field components and the total field intensity. Obtained results show that the proposed technique is a powerful tool and can enhance the solar magnetic field activity prediction. Keywords: Solar geomagnetic activity, neural network, prediction, Orsted, Holder Exponents, Solar magnetic storms.

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

    PubMed

    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.

  19. Neural Activity Propagation in an Unfolded Hippocampal Preparation with a Penetrating Micro-electrode Array

    PubMed Central

    Gonzales-Reyes, Luis E.; Durand, Dominique M.

    2015-01-01

    This protocol describes a method for preparing a new in vitro flat hippocampus preparation combined with a micro-machined array to map neural activity in the hippocampus. The transverse hippocampal slice preparation is the most common tissue preparation to study hippocampus electrophysiology. A longitudinal hippocampal slice was also developed in order to investigate longitudinal connections in the hippocampus. The intact mouse hippocampus can also be maintained in vitro because its thickness allows adequate oxygen diffusion. However, these three preparations do not provide direct access to neural propagation since some of the tissue is either missing or folded. The unfolded intact hippocampus provides both transverse and longitudinal connections in a flat configuration for direct access to the tissue to analyze the full extent of signal propagation in the hippocampus in vitro. In order to effectively monitor the neural activity from the cell layer, a custom made penetrating micro-electrode array (PMEA) was fabricated and applied to the unfolded hippocampus. The PMEA with 64 electrodes of 200 µm in height could record neural activity deep inside the mouse hippocampus. The unique combination of an unfolded hippocampal preparation and the PMEA provides a new in-vitro tool to study the speed and direction of propagation of neural activity in the two-dimensional CA1-CA3 regions of the hippocampus with a high signal to noise ratio. PMID:25868081

  20. Epigenetic activation of Sox2 gene in the developing vertebrate neural plate.

    PubMed

    Bouzas, Santiago O; Marini, Melisa S; Torres Zelada, Eliana; Buzzi, Ailín L; Morales Vicente, David A; Strobl-Mazzulla, Pablo H

    2016-06-15

    One of the earliest manifestations of neural induction is onset of expression of the neural marker Sox2, mediated by the activation of the enhancers N1 and N2. By using loss and gain of function, we find that Sox2 expression requires the activity of JmjD2A and the Msk1 kinase, which can respectively demethylate the repressive H3K9me3 mark and phosphorylate the activating H3S10 (H3S10ph) mark. Bimolecular fluorescence complementation reveals that the adaptor protein 14-3-3, known to bind to H3S10ph, interacts with JMJD2A and may be involved in its recruitment to regulatory regions of the Sox2 gene. Chromatin immunoprecipitation reveals dynamic binding of JMJD2A to the Sox2 promoter and N-1 enhancer at the time of neural plate induction. Finally, we show a clear temporal antagonism on the occupancy of H3K9me3 and H3S10ph modifications at the promoter of the Sox2 locus before and after the neural plate induction. Taken together, our results propose a series of epigenetic events necessary for the early activation of the Sox2 gene in neural progenitor cells.

  1. Explorative data analysis for changes in neural activity

    NASA Astrophysics Data System (ADS)

    Blythe, Duncan A. J.; Meinecke, Frank C.; von Bünau, Paul; Müller, Klaus-Robert

    2013-04-01

    Neural recordings are non-stationary time series, i.e. their properties typically change over time. Identifying specific changes, e.g., those induced by a learning task, can shed light on the underlying neural processes. However, such changes of interest are often masked by strong unrelated changes, which can be of physiological origin or due to measurement artifacts. We propose a novel algorithm for disentangling such different causes of non-stationarity and in this manner enable better neurophysiological interpretation for a wider set of experimental paradigms. A key ingredient is the repeated application of Stationary Subspace Analysis (SSA) using different temporal scales. The usefulness of our explorative approach is demonstrated in simulations, theory and EEG experiments with 80 brain-computer interfacing subjects.

  2. Active Control of Complex Systems via Dynamic (Recurrent) Neural Networks

    DTIC Science & Technology

    1992-05-30

    course, to on-going changes brought about by learning processes. As research in neurodynamics proceeded, the concept of reverberatory information flows...Microstructure of Cognition . Vol. 1: Foundations, M.I.T. Press, Cambridge, Massachusetts, pp. 354-361, 1986. 100 I Schwarz, G., "Estimating the dimension of a...Continually Running Fully Recurrent Neural Networks, ICS Report 8805, Institute of Cognitive Science, University of California at San Diego, 1988. 10 II

  3. Neural activity in the parietal eye of a lizard.

    PubMed

    MILLER, W H; WOLBARSHT, M L

    1962-01-26

    Electrical signs of activity in response to illumination of the parietal eye of the American chameleon, Anolis carolinensis, have been investigated. The responses were of two types. Under conditions of direct-coupled amplification, with glass pipette electrodes recording extracellularly from the retinal surface, the response consisted of an increase in negativity maintained throughout prolonged illumination. With capacitance-coupled amplification and metal electrodes, brisk mass discharges of nerve impulses were detected at the onset and cessation of illumination. During illumination a less vigorous maintained discharge was observed.

  4. Brain Hyperglycemia Induced by Heroin: Association with Metabolic Neural Activation.

    PubMed

    Solis, Ernesto; Bola, R Aaron; Fasulo, Bradley J; Kiyatkin, Eugene A

    2017-02-15

    Glucose enters the brain extracellular space from arterial blood, and its proper delivery is essential for metabolic activity of brain cells. By using enzyme-based biosensors coupled with high-speed amperometry in freely moving rats, we previously showed that glucose levels in the nucleus accumbens (NAc) display high variability, increasing rapidly following exposure to various arousing stimuli. In this study, the same technology was used to assess NAc glucose fluctuations induced by intravenous heroin. Heroin passively injected at a low dose optimal for maintaining self-administration behavior (100 μg/kg) induces a rapid but moderate glucose rise (∼150-200 μM or ∼15-25% over resting baseline). When the heroin dose was doubled and tripled, the increase became progressively larger in magnitude and longer in duration. Heroin-induced glucose increases also occurred in other brain structures (medial thalamus, lateral striatum, hippocampus), suggesting that brain hyperglycemia is a whole-brain phenomenon but changes were notably distinct in each structure. While local vasodilation appears to be the possible mechanism underlying the rapid rise in extracellular glucose levels, the driving factor for this vasodilation (central vs peripheral) remains to be clarified. The heroin-induced NAc glucose increases positively correlated with increases in intracerebral heat production determined in separate experiments using multisite temperature recordings (NAc, temporal muscle and skin). However, glucose levels rise very rapidly, preceding much slower increases in brain heat production, a measure of metabolic activation associated with glucose consumption.

  5. Category-based induction from similarity of neural activation.

    PubMed

    Weber, Matthew J; Osherson, Daniel

    2014-03-01

    The idea that similarity might be an engine of inductive inference dates back at least as far as David Hume. However, Hume's thesis is difficult to test without begging the question, since judgments of similarity may be infected by inferential processes. We present a one-parameter model of category-based induction that generates predictions about arbitrary statements of conditional probability over a predicate and a set of items. The prediction is based on the unconditional probabilities and similarities that characterize that predicate and those items. To test Hume's thesis, we collected brain activation from various regions of the ventral visual stream during a categorization task that did not invite comparison of categories. We then calculated the similarity of those activation patterns using a simple measure of vectorwise similarity and supplied those similarities to the model. The model's outputs correlated well with subjects' judgments of conditional probability. Our results represent a promising first step toward confirming Hume's thesis; similarity, assessed without reference to induction, may well drive inductive inference.

  6. Working Memory-Related Neural Activity Predicts Future Smoking Relapse

    PubMed Central

    Loughead, James; Wileyto, E Paul; Ruparel, Kosha; Falcone, Mary; Hopson, Ryan; Gur, Ruben; Lerman, Caryn

    2015-01-01

    Brief abstinence from smoking impairs cognition, particularly executive function, and this has a role in relapse to smoking. This study examined whether working memory-related brain activity predicts subsequent smoking relapse above and beyond standard clinical and behavioral measures. Eighty treatment-seeking smokers completed two functional magnetic resonance imaging sessions (smoking satiety vs 24 h abstinence challenge) during performance of a visual N-back task. Brief counseling and a short-term quit attempt followed. Relapse during the first 7 days was biochemically confirmed by the presence of the nicotine metabolite cotinine. Mean percent blood oxygen level-dependent (BOLD) signal change was extracted from a priori regions of interest: bilateral dorsolateral prefrontal cortex (DLPFC), medial frontal/cingulate gyrus, posterior cingulate cortex (PCC), and ventromedial prefrontal cortex. Signal from these brain regions and additional clinical measures were used to model outcome status, which was then validated with resampling techniques. Relapse to smoking was predicted by increased withdrawal symptoms, decreased left DLPFC and increased PCC BOLD percent signal change (abstinence vs smoking satiety). Receiver operating characteristic analysis demonstrated 81% area under the curve using these predictors, a significant improvement over the model with clinical variables only. The combination of abstinence-induced decreases in left DLPFC activation and reduced suppression of PCC may be a prognostic marker for poor outcome, specifically early smoking relapse. PMID:25469682

  7. The neural coding of expected and unexpected monetary performance outcomes: dissociations between active and observational learning.

    PubMed

    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.

  8. 12-Deoxyphorbols Promote Adult Neurogenesis by Inducing Neural Progenitor Cell Proliferation via PKC Activation

    PubMed Central

    Geribaldi-Doldán, Noelia; Flores-Giubi, Eugenia; Murillo-Carretero, Maribel; García-Bernal, Francisco; Carrasco, Manuel; Macías-Sánchez, Antonio J.; Domínguez-Riscart, Jesús; Verástegui, Cristina; Hernández-Galán, Rosario

    2016-01-01

    Background: Neuropsychiatric and neurological disorders frequently occur after brain insults associated with neuronal loss. Strategies aimed to facilitate neuronal renewal by promoting neurogenesis constitute a promising therapeutic option to treat neuronal death-associated disorders. In the adult brain, generation of new neurons occurs physiologically throughout the entire life controlled by extracellular molecules coupled to intracellular signaling cascades. Proteins participating in these cascades within neurogenic regions constitute potential pharmacological targets to promote neuronal regeneration of injured areas of the central nervous system. Methodology: We have performed in vitro and in vivo approaches to determine neural progenitor cell proliferation to understand whether activation of kinases of the protein kinase C family facilitates neurogenesis in the adult brain. Results: We have demonstrated that protein kinase C activation by phorbol-12-myristate-13-acetate induces neural progenitor cell proliferation in vitro. We also show that the nontumorogenic protein kinase C activator prostratin exerts a proliferative effect on neural progenitor cells in vitro. This effect can be reverted by addition of the protein kinase C inhibitor G06850, demonstrating that the effect of prostratin is mediated by protein kinase C activation. Additionally, we show that prostratin treatment in vivo induces proliferation of neural progenitor cells within the dentate gyrus of the hippocampus and the subventricular zone. Finally, we describe a library of diterpenes with a 12-deoxyphorbol structure similar to that of prostratin that induces a stronger effect than prostratin on neural progenitor cell proliferation both in vitro and in vivo. Conclusions: This work suggests that protein kinase C activation is a promising strategy to expand the endogenous neural progenitor cell population to promote neurogenesis and highlights the potential of 12-deoxyphorbols as pharmaceutical

  9. COMPUTATIONAL EVALUATION OF METHODS FOR MEASURING THE SPATIAL EXTENT OF NEURAL ACTIVATION

    PubMed Central

    Mahnam, Amin; Hashemi, S. Mohammad Reza; Grill, Warren M.

    2008-01-01

    Knowing of the spatial extent of neural activation around extracellular stimulating electrodes is necessary to ensure that only the desired neurons are activated or to determine which neurons are responsible for an observed response. Various approaches have been used to estimate the current-distance relationship and thereby the spatial extent of activation resulting from extracellular stimulation. However, these approaches all require underlying assumptions and simplifications, and since the actual extent of activation cannot be directly measured, the impact of deviations from these assumptions cannot be determined. We implemented a computer-based model of excitation of a population of nerve fibers and used the model to evaluate a range of approaches proposed for measuring the spatial extent of neural activation. The estimates with each method were compared with measurements of the true spatial extent of activation that were accessible in the simulations to quantify the accuracy of the estimates and to determine the dependence of accuracy on measurement parameters (interelectrode distance, stimulation amplitude, noise). A newly proposed method, based on the refractory interaction technique, provided the most accurate and most robust estimates of the spatial extent of neural activation. PMID:18606455

  10. Whole-brain mapping of behaviourally induced neural activation in mice.

    PubMed

    Vousden, Dulcie A; Epp, Jonathan; Okuno, Hiroyuki; Nieman, Brian J; van Eede, Matthijs; Dazai, Jun; Ragan, Timothy; Bito, Haruhiko; Frankland, Paul W; Lerch, Jason P; Henkelman, R Mark

    2015-07-01

    The ability to visualize behaviourally evoked neural activity patterns across the rodent brain is essential for understanding the distributed brain networks mediating particular behaviours. However, current imaging methods are limited in their spatial resolution and/or ability to obtain brain-wide coverage of functional activity. Here, we describe a new automated method for obtaining cellular-level, whole-brain maps of behaviourally induced neural activity in the mouse. This method combines the use of transgenic immediate-early gene reporter mice to visualize neural activity; serial two-photon tomography to image the entire brain at cellular resolution; advanced image processing algorithms to count the activated neurons and align the datasets to the Allen Mouse Brain Atlas; and statistical analysis to identify the network of activated brain regions evoked by behaviour. We demonstrate the use of this approach to determine the whole-brain networks activated during the retrieval of fear memories. Consistent with previous studies, we identified a large network of amygdalar, hippocampal, and neocortical brain regions implicated in fear memory retrieval. Our proposed methods can thus be used to map cellular networks involved in the expression of normal behaviours as well as to investigate in depth circuit dysfunction in mouse models of neurobiological disease.

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

    PubMed

    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.

  12. Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations

    SciTech Connect

    Marre, O.; El Boustani, S.; Fregnac, Y.; Destexhe, A.

    2009-04-03

    We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogates that reproduce the spatial and temporal correlations of a given data set.

  13. Two-stage neural algorithm for defect detection and characterization uses an active thermography

    NASA Astrophysics Data System (ADS)

    Dudzik, Sebastian

    2015-07-01

    In the paper a two-stage neural algorithm for defect detection and characterization is presented. In order to estimate the defect depth two neural networks trained on data obtained using an active thermography were employed. The first stage of the algorithm is developed to detect the defect by a classification neural network. Then the defects depth is estimated using a regressive neural network. In this work the results of experimental investigations and simulations are shown. Further, the sensitivity analysis of the presented algorithm was conducted and the impacts of emissivity error and the ambient temperature error on the depth estimation errors were studied. The results were obtained using a test sample made of material with a low thermal diffusivity.

  14. Visualizing the Hidden Activity of Artificial Neural Networks.

    PubMed

    Rauber, Paulo E; Fadel, Samuel G; Falcao, Alexandre X; Telea, Alexandru C

    2017-01-01

    In machine learning, pattern classification assigns high-dimensional vectors (observations) to classes based on generalization from examples. Artificial neural networks currently achieve state-of-the-art results in this task. Although such networks are typically used as black-boxes, they are also widely believed to learn (high-dimensional) higher-level representations of the original observations. In this paper, we propose using dimensionality reduction for two tasks: visualizing the relationships between learned representations of observations, and visualizing the relationships between artificial neurons. Through experiments conducted in three traditional image classification benchmark datasets, we show how visualization can provide highly valuable feedback for network designers. For instance, our discoveries in one of these datasets (SVHN) include the presence of interpretable clusters of learned representations, and the partitioning of artificial neurons into groups with apparently related discriminative roles.

  15. Afterimage induced neural activity during emotional face perception.

    PubMed

    Cheal, Jenna L; Heisz, Jennifer J; Walsh, Jennifer A; Shedden, Judith M; Rutherford, M D

    2014-02-26

    The N170 response differs when positive versus negative facial expressions are viewed. This neural response could be associated with the perception of emotions, or some feature of the stimulus. We used an aftereffect paradigm to clarify. Consistent with previous reports of emotional aftereffects, a neutral face was more likely to be described as happy following a sad face adaptation, and more likely to be described as sad following a happy face adaptation. In addition, similar to previous observations with actual emotional faces, we found differences in the latency of the N170 elicited by the neutral face following sad versus happy face adaptation, demonstrating that the emotion-specific effect on the N170 emerges even when emotion expressions are perceptually different but physically identical. The re-entry of emotional information from other brain regions may be driving the emotional aftereffects and the N170 latency differences.

  16. Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

    PubMed

    Li, Shuai; Li, Yangming

    2013-10-28

    The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

  17. Application of neural networks with orthogonal activation functions in control of dynamical systems

    NASA Astrophysics Data System (ADS)

    Nikolić, Saša S.; Antić, Dragan S.; Milojković, Marko T.; Milovanović, Miroslav B.; Perić, Staniša Lj.; Mitić, Darko B.

    2016-04-01

    In this article, we present a new method for the synthesis of almost and quasi-orthogonal polynomials of arbitrary order. Filters designed on the bases of these functions are generators of generalised quasi-orthogonal signals for which we derived and presented necessary mathematical background. Based on theoretical results, we designed and practically implemented generalised first-order (k = 1) quasi-orthogonal filter and proved its quasi-orthogonality via performed experiments. Designed filters can be applied in many scientific areas. In this article, generated functions were successfully implemented in Nonlinear Auto Regressive eXogenous (NARX) neural network as activation functions. One practical application of the designed orthogonal neural network is demonstrated through the example of control of the complex technical non-linear system - laboratory magnetic levitation system. Obtained results were compared with neural networks with standard activation functions and orthogonal functions of trigonometric shape. The proposed network demonstrated superiority over existing solutions in the sense of system performances.

  18. Nonsmooth finite-time stabilization of neural networks with discontinuous activations.

    PubMed

    Liu, Xiaoyang; Park, Ju H; Jiang, Nan; Cao, Jinde

    2014-04-01

    This paper is concerned with the finite-time stabilization for a class of neural networks (NNs) with discontinuous activations. The purpose of the addressed problem is to design a discontinuous controller to stabilize the states of such neural networks in finite time. Unlike the previous works, such stabilization objective will be realized for neural networks when the activations and controllers are both discontinuous. Based on the famous finite-time stability theorem of nonlinear systems and nonsmooth analysis in mathematics, sufficient conditions are established to ensure the finite-time stability of the dynamics of NNs. Then, the upper bound of the settling time for stabilization can be estimated in two forms due to two different methods of proof. Finally, two numerical examples are given to illustrate the effectiveness of the proposed design method.

  19. Exponential stability of delayed and impulsive cellular neural networks with partially Lipschitz continuous activation functions.

    PubMed

    Song, Xueli; Xin, Xing; Huang, Wenpo

    2012-05-01

    The paper discusses exponential stability of distributed delayed and impulsive cellular neural networks with partially Lipschitz continuous activation functions. By relative nonlinear measure method, some novel criteria are obtained for the uniqueness and exponential stability of the equilibrium point. Our method abandons usual assumptions on global Lipschitz continuity, boundedness and monotonicity of activation functions. Our results are generalization and improvement of some existing ones. Finally, two examples and their simulations are presented to illustrate the correctness of our analysis.

  20. Electronic bypass of spinal lesions: activation of lower motor neurons directly driven by cortical neural signals

    PubMed Central

    2014-01-01

    Background Lower motor neurons in the spinal cord lose supraspinal inputs after complete spinal cord injury, leading to a loss of volitional control below the injury site. Extensive locomotor training with spinal cord stimulation can restore locomotion function after spinal cord injury in humans and animals. However, this locomotion is non-voluntary, meaning that subjects cannot control stimulation via their natural “intent”. A recent study demonstrated an advanced system that triggers a stimulator using forelimb stepping electromyographic patterns to restore quadrupedal walking in rats with spinal cord transection. However, this indirect source of “intent” may mean that other non-stepping forelimb activities may false-trigger the spinal stimulator and thus produce unwanted hindlimb movements. Methods We hypothesized that there are distinguishable neural activities in the primary motor cortex during treadmill walking, even after low-thoracic spinal transection in adult guinea pigs. We developed an electronic spinal bridge, called “Motolink”, which detects these neural patterns and triggers a “spinal” stimulator for hindlimb movement. This hardware can be head-mounted or carried in a backpack. Neural data were processed in real-time and transmitted to a computer for analysis by an embedded processor. Off-line neural spike analysis was conducted to calculate and preset the spike threshold for “Motolink” hardware. Results We identified correlated activities of primary motor cortex neurons during treadmill walking of guinea pigs with spinal cord transection. These neural activities were used to predict the kinematic states of the animals. The appropriate selection of spike threshold value enabled the “Motolink” system to detect the neural “intent” of walking, which triggered electrical stimulation of the spinal cord and induced stepping-like hindlimb movements. Conclusion We present a direct cortical “intent”-driven electronic spinal

  1. Using Perfusion fMRI to Measure Continuous Changes in Neural Activity with Learning

    ERIC Educational Resources Information Center

    Olson, Ingrid R.; Rao, Hengyi; Moore, Katherine Sledge; Wang, Jiongjiong; Detre, John A.; Aguirre, Geoffrey K.

    2006-01-01

    In this study, we examine the suitability of a relatively new imaging technique, "arterial spin labeled perfusion imaging," for the study of continuous, gradual changes in neural activity. Unlike BOLD imaging, the perfusion signal is stable over long time-scales, allowing for accurate assessment of continuous performance. In addition, perfusion…

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

    ERIC Educational Resources Information Center

    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,…

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

    ERIC Educational Resources Information Center

    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…

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

    PubMed

    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.

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

    PubMed

    Gong, Pulin; van Leeuwen, Cees

    2009-12-01

    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.

  6. Decoding of the sound frequency from the steady-state neural activities in rat auditory cortex.

    PubMed

    Shiramatsu, Tomoyo I; Noda, Takahiro; Kanzaki, Ryohei; Takahashi, Hirokazu

    2013-01-01

    In the auditory cortex, onset activities have been extensively investigated as a cortical representation of sound information such as sound frequency. Yet, less attention has been paid to date to steady-state activities following the onset activities. In this study, we used machine learning to investigate whether steady-state activities in the presence of continuous sounds represent the sound frequency. Sparse Logistic Regression (SLR) decoded the sound frequency from band specific power or phase locking value (PLV) of local field potentials (LFP) from the fourth layer of the auditory cortex of anesthetized rats. Consequently, we found that SLR was able to decode the sound frequency from steady-state neural activities as well as onset activities. This result demonstrates that the steady-state activities contain information about the sound such as sound frequency.

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

    PubMed

    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.

  8. Comparative aspects of adult neural stem cell activity in vertebrates.

    PubMed

    Grandel, Heiner; Brand, Michael

    2013-03-01

    At birth or after hatching from the egg, vertebrate brains still contain neural stem cells which reside in specialized niches. In some cases, these stem cells are deployed for further postnatal development of parts of the brain until the final structure is reached. In other cases, postnatal neurogenesis continues as constitutive neurogenesis into adulthood leading to a net increase of the number of neurons with age. Yet, in other cases, stem cells fuel neuronal turnover. An example is protracted development of the cerebellar granular layer in mammals and birds, where neurogenesis continues for a few weeks postnatally until the granular layer has reached its definitive size and stem cells are used up. Cerebellar growth also provides an example of continued neurogenesis during adulthood in teleosts. Again, it is the granular layer that grows as neurogenesis continues and no definite adult cerebellar size is reached. Neuronal turnover is most clearly seen in the telencephalon of male canaries, where projection neurons are replaced in nucleus high vocal centre each year before the start of a new mating season--circuitry reconstruction to achieve changes of the song repertoire in these birds? In this review, we describe these and other examples of adult neurogenesis in different vertebrate taxa. We also compare the structure of the stem cell niches to find common themes in their organization despite different functions adult neurogenesis serves in different species. Finally, we report on regeneration of the zebrafish telencephalon after injury to highlight similarities and differences of constitutive neurogenesis and neuronal regeneration.

  9. Optical imaging of neural activity: from neuron to brain

    NASA Astrophysics Data System (ADS)

    Luo, Qingming; Zeng, Shaoqun; Gong, Hui

    2003-12-01

    This paper introduces the optical imaging approaches at three levels in cognitive neuroscience in the Key Laboratory of Biomedical Photonics of Ministry of Education of China. In molecular and cellular level, the advances in microscopy, molecular optical marker, and sample preparations have made possible studies that characterize the form and function of neurons in unprecedented detail. The development of two-photon excitation has enabled fluorescent imaging of small structures in the midst of highly scattering media with little photodamage. The combination of MPE and multi-electrode array provides a powerful approach for neuronal networks imaging. Intrinsic signal imaging (ISI) and laser speckle imaging (LSI) are effective approaches for intrinsic signal imaging at a given cortical site. No alternative imaging technique for the visualization of functional organization in the living brain provides a comparable spatial resolution. It is this level of resolution that reveals where processing is performed - a necessary step for the understanding of the neural code at the population level. Completely noninvasive optical imaging through the intact human skull, such as functional near infrared imaging may provide an imaging tool offering both the spatial and the temporal resolutions required to expand our knowledge of the principles underlying the remarkable performance of the human cerebral cortex.

  10. Time structure of the activity in neural network models

    NASA Astrophysics Data System (ADS)

    Gerstner, Wulfram

    1995-01-01

    Several neural network models in continuous time are reconsidered in the framework of a general mean-field theory which is exact in the limit of a large and fully connected network. The theory assumes pointlike spikes which are generated by a renewal process. The effect of spikes on a receiving neuron is described by a linear response kernel which is the dominant term in a weak-coupling expansion. It is shown that the resulting ``spike response model'' is the most general renewal model with linear inputs. The standard integrate-and-fire model forms a special case. In a network structure with several pools of identical spiking neurons, the global states and the dynamic evolution are determined by a nonlinear integral equation which describes the effective interaction within and between different pools. We derive explicit stability criteria for stationary (incoherent) and oscillatory (coherent) solutions. It is shown that the stationary state of noiseless systems is ``almost always'' unstable. Noise suppresses fast oscillations and stabilizes the system. Furthermore, collective oscillations are stable only if the firing occurs while the synaptic potential is increasing. In particular, collective oscillations in a network with delayless excitatory interaction are at most semistable. Inhibitory interactions with short delays or excitatory interactions with long delays lead to stable oscillations. Our general results allow a straightforward application to different network models with spiking neurons. Furthermore, the theory allows an estimation of the errors introduced in firing rate or ``graded-response'' models.

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

    PubMed

    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.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  14. Absolute exponential stability of recurrent neural networks with generalized activation function.

    PubMed

    Xu, Jun; Cao, Yong-Yan; Sun, Youxian; Tang, Jinshan

    2008-06-01

    In this paper, the recurrent neural networks (RNNs) with a generalized activation function class is proposed. In this proposed model, every component of the neuron's activation function belongs to a convex hull which is bounded by two odd symmetric piecewise linear functions that are convex or concave over the real space. All of the convex hulls are composed of generalized activation function classes. The novel activation function class is not only with a more flexible and more specific description of the activation functions than other function classes but it also generalizes some traditional activation function classes. The absolute exponential stability (AEST) of the RNN with a generalized activation function class is studied through three steps. The first step is to demonstrate the global exponential stability (GES) of the equilibrium point of original RNN with a generalized activation function being equivalent to that of RNN under all vertex functions of convex hull. The second step transforms the RNN under every vertex activation function into neural networks under an array of saturated linear activation functions. Because the GES of the equilibrium point of three systems are equivalent, the next stability analysis focuses on the GES of the equilibrium point of RNN system under an array of saturated linear activation functions. The last step is to study both the existence of equilibrium point and the GES of the RNN under saturated linear activation functions using the theory of M-matrix. In the end, a two-neuron RNN with a generalized activation function is constructed to show the effectiveness of our results.

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

    PubMed

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

    2017-03-04

    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.

  16. Complexin2 modulates working memory-related neural activity in patients with schizophrenia.

    PubMed

    Hass, Johanna; Walton, Esther; Kirsten, Holger; Turner, Jessica; Wolthusen, Rick; Roessner, Veit; Sponheim, Scott R; Holt, Daphne; Gollub, Randy; Calhoun, Vince D; Ehrlich, Stefan

    2015-03-01

    The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 (CPLX2) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. We examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as 'neural inefficiency,' these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.

  17. Complexin2 modulates working memory-related neural activity in patients with schizophrenia

    SciTech Connect

    Hass, Johanna; Walton, Esther; Kirsten, Holger; Turner, Jessica; Wolthusen, Rick; Roessner, Veit; Sponheim, Scott R.; Holt, Daphne; Gollub, Randy; Calhoun, Vince D.; Ehrlich, Stefan

    2014-10-09

    The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 (CPLX2) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms by investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. In this paper, we examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Finally, since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as ‘neural inefficiency,’ these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.

  18. Complexin2 modulates working memory-related neural activity in patients with schizophrenia

    DOE PAGES

    Hass, Johanna; Walton, Esther; Kirsten, Holger; ...

    2014-10-09

    The specific contribution of risk or candidate gene variants to the complex phenotype of schizophrenia is largely unknown. Studying the effects of such variants on brain function can provide insight into disease-associated mechanisms on a neural systems level. Previous studies found common variants in the complexin2 (CPLX2) gene to be highly associated with cognitive dysfunction in schizophrenia patients. Similarly, cognitive functioning was found to be impaired in Cplx2 gene-deficient mice if they were subjected to maternal deprivation or mild brain trauma during puberty. Here, we aimed to study seven common CPLX2 single-nucleotide polymorphisms (SNPs) and their neurogenetic risk mechanisms bymore » investigating their relationship to a schizophrenia-related functional neuroimaging intermediate phenotype. In this paper, we examined functional MRI and genotype data collected from 104 patients with DSM-IV-diagnosed schizophrenia and 122 healthy controls who participated in the Mind Clinical Imaging Consortium study of schizophrenia. Seven SNPs distributed over the whole CPLX2 gene were tested for association with working memory-elicited neural activity in a frontoparietal neural network. Three CPLX2 SNPs were significantly associated with increased neural activity in the dorsolateral prefrontal cortex and intraparietal sulcus in the schizophrenia sample, but showed no association in healthy controls. Finally, since increased working memory-related neural activity in individuals with or at risk for schizophrenia has been interpreted as ‘neural inefficiency,’ these findings suggest that certain variants of CPLX2 may contribute to impaired brain function in schizophrenia, possibly combined with other deleterious genetic variants, adverse environmental events, or developmental insults.« less

  19. Predicting Neural Activity Patterns Associated with Sentences Using a Neurobiologically Motivated Model of Semantic Representation.

    PubMed

    Anderson, Andrew James; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Aguilar, Mario; Wang, Xixi; Doko, Donias; Raizada, Rajeev D S

    2016-08-12

    We introduce an approach that predicts neural representations of word meanings contained in sentences then superposes these to predict neural representations of new sentences. A neurobiological semantic model based on sensory, motor, social, emotional, and cognitive attributes was used as a foundation to define semantic content. Previous studies have predominantly predicted neural patterns for isolated words, using models that lack neurobiological interpretation. Fourteen participants read 240 sentences describing everyday situations while undergoing fMRI. To connect sentence-level fMRI activation patterns to the word-level semantic model, we devised methods to decompose the fMRI data into individual words. Activation patterns associated with each attribute in the model were then estimated using multiple-regression. This enabled synthesis of activation patterns for trained and new words, which were subsequently averaged to predict new sentences. Region-of-interest analyses revealed that prediction accuracy was highest using voxels in the left temporal and inferior parietal cortex, although a broad range of regions returned statistically significant results, showing that semantic information is widely distributed across the brain. The results show how a neurobiologically motivated semantic model can decompose sentence-level fMRI data into activation features for component words, which can be recombined to predict activation patterns for new sentences.

  20. Optogenetics and thermogenetics: technologies for controlling the activity of targeted cells within intact neural circuits.

    PubMed

    Bernstein, Jacob G; Garrity, Paul A; Boyden, Edward S

    2012-02-01

    In recent years, interest has grown in the ability to manipulate, in a temporally precise fashion, the electrical activity of specific neurons embedded within densely wired brain circuits, in order to reveal how specific neurons subserve behaviors and neural computations, and to open up new horizons on the clinical treatment of brain disorders. Technologies that enable temporally precise control of electrical activity of specific neurons, and not these neurons' neighbors-whose cell bodies or processes might be just tens to hundreds of nanometers away-must involve two components. First, they require as a trigger a transient pulse of energy that supports the temporal precision of the control. Second, they require a molecular sensitizer that can be expressed in specific neurons and which renders those neurons specifically responsive to the triggering energy delivered. Optogenetic tools, such as microbial opsins, can be used to activate or silence neural activity with brief pulses of light. Thermogenetic tools, such as thermosensitive TRP channels, can be used to drive neural activity downstream of increases or decreases in temperature. We here discuss the principles underlying the operation of these two recently developed, but widely used, toolboxes, as well as the directions being taken in the use and improvement of these toolboxes.

  1. Computerized cognitive training restores neural activity within the reality monitoring network in schizophrenia.

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  3. Persistent neural activity in the prefrontal cortex: a mechanism by which BDNF regulates working memory?

    PubMed

    Galloway, Evan M; Woo, Newton H; Lu, Bai

    2008-01-01

    Working memory is the ability to maintain representations of task-relevant information for short periods of time to guide subsequent actions or make decisions. Neurons of the prefrontal cortex exhibit persistent firing during the delay period of working memory tasks. Despite extensive studies, the mechanisms underlying this persistent neural activity remain largely obscure. The neurotransmitter systems of dopamine, NMDA, and GABA have been implicated, but further investigations are necessary to establish their precise roles and relationships. Recent research has suggested a new component: brain-derived neurotrophic factor (BDNF) and its high-affinity receptor, TrkB. We review the research on persistent activity and suggest that BDNF/TrkB signaling in a distinct class of interneurons plays an important role in organizing persistent neural activity at the single-neuron and network levels.

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

    PubMed

    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.

  5. Wide-field optical mapping of neural activity and brain haemodynamics: considerations and novel approaches

    PubMed Central

    Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Thibodeaux, David N.; Zhao, Hanzhi T.; Yu, Hang

    2016-01-01

    Although modern techniques such as two-photon microscopy can now provide cellular-level three-dimensional imaging of the intact living brain, the speed and fields of view of these techniques remain limited. Conversely, two-dimensional wide-field optical mapping (WFOM), a simpler technique that uses a camera to observe large areas of the exposed cortex under visible light, can detect changes in both neural activity and haemodynamics at very high speeds. Although WFOM may not provide single-neuron or capillary-level resolution, it is an attractive and accessible approach to imaging large areas of the brain in awake, behaving mammals at speeds fast enough to observe widespread neural firing events, as well as their dynamic coupling to haemodynamics. Although such wide-field optical imaging techniques have a long history, the advent of genetically encoded fluorophores that can report neural activity with high sensitivity, as well as modern technologies such as light emitting diodes and sensitive and high-speed digital cameras have driven renewed interest in WFOM. To facilitate the wider adoption and standardization of WFOM approaches for neuroscience and neurovascular coupling research, we provide here an overview of the basic principles of WFOM, considerations for implementation of wide-field fluorescence imaging of neural activity, spectroscopic analysis and interpretation of results. This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’. PMID:27574312

  6. Statistical modelling of higher-order correlations in pools of neural activity

    NASA Astrophysics Data System (ADS)

    Montani, Fernando; Phoka, Elena; Portesi, Mariela; Schultz, Simon R.

    2013-07-01

    Simultaneous recordings from multiple neural units allow us to investigate the activity of very large neural ensembles. To understand how large ensembles of neurons process sensory information, it is necessary to develop suitable statistical models to describe the response variability of the recorded spike trains. Using the information geometry framework, it is possible to estimate higher-order correlations by assigning one interaction parameter to each degree of correlation, leading to a (2N-1)-dimensional model for a population with N neurons. However, this model suffers greatly from a combinatorial explosion, and the number of parameters to be estimated from the available sample size constitutes the main intractability reason of this approach. To quantify the extent of higher than pairwise spike correlations in pools of multiunit activity, we use an information-geometric approach within the framework of the extended central limit theorem considering all possible contributions from higher-order spike correlations. The identification of a deformation parameter allows us to provide a statistical characterisation of the amount of higher-order correlations in the case of a very large neural ensemble, significantly reducing the number of parameters, avoiding the sampling problem, and inferring the underlying dynamical properties of the network within pools of multiunit neural activity.

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

    PubMed

    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.

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

    PubMed

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

    2014-01-01

    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.

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

    PubMed

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

    2017-01-01

    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 [Formula: see text] 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.

  10. Human intracranial high-frequency activity during memory processing: neural oscillations or stochastic volatility?

    PubMed

    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.

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

    PubMed

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

    2016-08-17

    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.

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

    PubMed Central

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

    2015-01-01

    Purpose: Correlational and limited experimental evidence suggests that an engaged lifestyle is associated with the maintenance of cognitive vitality in old age. However, the mechanisms underlying these engagement effects are poorly understood. We hypothesized that mental effort underlies engagement effects and used fMRI to examine the impact of high-challenge activities (digital photography and quilting) compared with low-challenge activities (socializing or performing low-challenge cognitive tasks) on neural function at pretest, posttest, and one year after the engagement program. Methods: In the scanner, participants performed a semantic-classification task with two levels of difficulty to assess the modulation of brain activity in response to task demands. Results: The High-Challenge group, but not the Low-Challenge group, showed increased modulation of brain activity in medial frontal, lateral temporal, and parietal cortex—regions associated with attention and semantic processing—some of which were maintained a year later. This increased modulation stemmed from decreases in brain activity during the easy condition for the High-Challenge group and was associated with time committed to the program, age, and cognition. Conclusions: Sustained engagement in cognitively demanding activities facilitated cognition by increasing neural efficiency. Mentally-challenging activities may be neuroprotective and an important element to maintaining a healthy brain into late adulthood. PMID:26484698

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

    PubMed Central

    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

  14. Different dynamic resting state fMRI patterns are linked to different frequencies of neural activity.

    PubMed

    Thompson, Garth John; Pan, Wen-Ju; Keilholz, Shella Dawn

    2015-07-01

    Resting state functional magnetic resonance imaging (rsfMRI) results have indicated that network mapping can contribute to understanding behavior and disease, but it has been difficult to translate the maps created with rsfMRI to neuroelectrical states in the brain. Recently, dynamic analyses have revealed multiple patterns in the rsfMRI signal that are strongly associated with particular bands of neural activity. To further investigate these findings, simultaneously recorded invasive electrophysiology and rsfMRI from rats were used to examine two types of electrical activity (directly measured low-frequency/infraslow activity and band-limited power of higher frequencies) and two types of dynamic rsfMRI (quasi-periodic patterns or QPP, and sliding window correlation or SWC). The relationship between neural activity and dynamic rsfMRI was tested under three anesthetic states in rats: dexmedetomidine and high and low doses of isoflurane. Under dexmedetomidine, the lightest anesthetic, infraslow electrophysiology correlated with QPP but not SWC, whereas band-limited power in higher frequencies correlated with SWC but not QPP. Results were similar under isoflurane; however, the QPP was also correlated to band-limited power, possibly due to the burst-suppression state induced by the anesthetic agent. The results provide additional support for the hypothesis that the two types of dynamic rsfMRI are linked to different frequencies of neural activity, but isoflurane anesthesia may make this relationship more complicated. Understanding which neural frequency bands appear as particular dynamic patterns in rsfMRI may ultimately help isolate components of the rsfMRI signal that are of interest to disorders such as schizophrenia and attention deficit disorder.

  15. Social Status-Dependent Shift in Neural Circuit Activation Affects Decision Making.

    PubMed

    Miller, Thomas H; Clements, Katie; Ahn, Sungwoo; Park, Choongseok; Hye Ji, Eoon; Issa, Fadi A

    2017-02-22

    In a social group, animals make behavioral decisions that fit their social ranks. These behavioral choices are dependent on the various social cues experienced during social interactions. In vertebrates, little is known of how social status affects the underlying neural mechanisms regulating decision-making circuits that drive competing behaviors. Here, we demonstrate that social status in zebrafish (Danio rerio) influences behavioral decisions by shifting the balance in neural circuit activation between two competing networks (escape and swim). We show that socially dominant animals enhance activation of the swim circuit. Conversely, social subordinates display a decreased activation of the swim circuit, but an enhanced activation of the escape circuit. In an effort to understand how social status mediates these effects, we constructed a neurocomputational model of the escape and swim circuits. The model replicates our findings and suggests that social status-related shift in circuit dynamics could be mediated by changes in the relative excitability of the escape and swim networks. Together, our results reveal that changes in the excitabilities of the Mauthner command neuron for escape and the inhibitory interneurons that regulate swimming provide a cellular mechanism for the nervous system to adapt to changes in social conditions by permitting the animal to select a socially appropriate behavioral response.SIGNIFICANCE STATEMENT Understanding how social factors influence nervous system function is of great importance. Using zebrafish as a model system, we demonstrate how social experience affects decision making to enable animals to produce socially appropriate behavior. Based on experimental evidence and computational modeling, we show that behavioral decisions reflect the interplay between competing neural circuits whose activation thresholds shift in accordance with social status. We demonstrate this through analysis of the behavior and neural circuit

  16. Different dynamic resting state fMRI patterns are linked to different frequencies of neural activity

    PubMed Central

    Thompson, Garth John; Pan, Wen-Ju

    2015-01-01

    Resting state functional magnetic resonance imaging (rsfMRI) results have indicated that network mapping can contribute to understanding behavior and disease, but it has been difficult to translate the maps created with rsfMRI to neuroelectrical states in the brain. Recently, dynamic analyses have revealed multiple patterns in the rsfMRI signal that are strongly associated with particular bands of neural activity. To further investigate these findings, simultaneously recorded invasive electrophysiology and rsfMRI from rats were used to examine two types of electrical activity (directly measured low-frequency/infraslow activity and band-limited power of higher frequencies) and two types of dynamic rsfMRI (quasi-periodic patterns or QPP, and sliding window correlation or SWC). The relationship between neural activity and dynamic rsfMRI was tested under three anesthetic states in rats: dexmedetomidine and high and low doses of isoflurane. Under dexmedetomidine, the lightest anesthetic, infraslow electrophysiology correlated with QPP but not SWC, whereas band-limited power in higher frequencies correlated with SWC but not QPP. Results were similar under isoflurane; however, the QPP was also correlated to band-limited power, possibly due to the burst-suppression state induced by the anesthetic agent. The results provide additional support for the hypothesis that the two types of dynamic rsfMRI are linked to different frequencies of neural activity, but isoflurane anesthesia may make this relationship more complicated. Understanding which neural frequency bands appear as particular dynamic patterns in rsfMRI may ultimately help isolate components of the rsfMRI signal that are of interest to disorders such as schizophrenia and attention deficit disorder. PMID:26041826

  17. In Vivo Performance of Genetically Encoded Indicators of Neural Activity in Flies

    PubMed Central

    Reiff, Dierk F.; Ihring, Alexandra; Guerrero, Giovanna; Isacoff, Ehud Y.; Joesch, Maximilian; Nakai, Junichi; Borst, Alexander

    2006-01-01

    Genetically encoded fluorescent probes of neural activity represent new promising tools for systems neuroscience. Here, we present a comparative in vivo analysis of 10 different genetically encoded calcium indicators, as well as the pH-sensitive synapto-pHluorin. We analyzed their fluorescence changes in presynaptic boutons of the Drosophila larval neuromuscular junction. Robust neural activity did not result in any or noteworthy fluorescence changes when Flash-Pericam, Camgaroo-1, and Camgaroo-2 were expressed. However, calculated on the raw data, fractional fluorescence changes up to 18% were reported by synapto-pHluorin, Yellow Cameleon 2.0, 2.3, and 3.3, Inverse-Pericam, GCaMP1.3, GCaMP1.6, and the troponin C-based calcium sensor TN-L15. The response characteristics of all of these indicators differed considerably from each other, with GCaMP1.6 reporting high rates of neural activity with the largest and fastest fluorescence changes. However, GCaMP1.6 suffered from photobleaching, whereas the fluorescence signals of the double-chromophore indicators were in general smaller but more photostable and reproducible, with TN-L15 showing the fastest rise of the signals at lower activity rates. We show for GCaMP1.3 and YC3.3 that an expanded range of neural activity evoked fairly linear fluorescence changes and a corresponding linear increase in the signal-to-noise ratio (SNR). The expression level of the indicator biased the signal kinetics and SNR, whereas the signal amplitude was independent. The presented data will be useful for in vivo experiments with respect to the selection of an appropriate indicator, as well as for the correct interpretation of the optical signals. PMID:15888652

  18. Human activities recognition by head movement using partial recurrent neural network

    NASA Astrophysics Data System (ADS)

    Tan, Henry C. C.; Jia, Kui; De Silva, Liyanage C.

    2003-06-01

    Traditionally, human activities recognition has been achieved mainly by the statistical pattern recognition methods or the Hidden Markov Model (HMM). In this paper, we propose a novel use of the connectionist approach for the recognition of ten simple human activities: walking, sitting down, getting up, squatting down and standing up, in both lateral and frontal views, in an office environment. By means of tracking the head movement of the subjects over consecutive frames from a database of different color image sequences, and incorporating the Elman model of the partial recurrent neural network (RNN) that learns the sequential patterns of relative change of the head location in the images, the proposed system is able to robustly classify all the ten activities performed by unseen subjects from both sexes, of different race and physique, with a recognition rate as high as 92.5%. This demonstrates the potential of employing partial RNN to recognize complex activities in the increasingly popular human-activities-based applications.

  19. Neural activation during processing of aversive faces predicts treatment outcome in alcoholism.

    PubMed

    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.

  20. Oxytocin reduces neural activity in the pain circuitry when seeing pain in others

    PubMed Central

    Hermans, Erno J.; Keysers, Christian; van Honk, Jack

    2015-01-01

    Our empathetic abilities allow us to feel the pain of others. This phenomenon of vicarious feeling arises because the neural circuitry of feeling pain and seeing pain in others is shared. The neuropeptide oxytocin (OXT) is considered a robust facilitator of empathy, as intranasal OXT studies have repeatedly been shown to improve cognitive empathy (e.g. mind reading and emotion recognition). However, OXT has not yet been shown to increase neural empathic responses to pain in others, a core aspect of affective empathy. Effects of OXT on empathy for pain are difficult to predict, because OXT evidently has pain-reducing properties. Accordingly, OXT might paradoxically decrease empathy for pain. Here, using functional neuroimaging we show robust activation in the neural circuitry of pain (insula and sensorimotor regions) when subjects observe pain in others. Crucially, this empathy-related activation in the neural circuitry of pain is strongly reduced after intranasal OXT, specifically in the left insula. OXT on the basis of our neuroimaging data thus remarkably decreases empathy for pain, but further research including behavioral measures are necessary to draw definite conclusions. PMID:25818690

  1. Similar patterns of neural activity predict memory function during encoding and retrieval.

    PubMed

    Kragel, James E; Ezzyat, Youssef; Sperling, Michael R; Gorniak, Richard; Worrell, Gregory A; Berry, Brent M; Inman, Cory; Lin, Jui-Jui; Davis, Kathryn A; Das, Sandhitsu R; Stein, Joel M; Jobst, Barbara C; Zaghloul, Kareem A; Sheth, Sameer A; Rizzuto, Daniel S; Kahana, Michael J

    2017-04-01

    Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval.

  2. Thermal dependence of neural activity in the hamster hippocampal slice preparation

    NASA Technical Reports Server (NTRS)

    Horowitz, J. M.; Thomas, M. P.; Eckerman, P.

    1987-01-01

    1. Neural activity was recorded in an in vitro hamster hippocampal slice preparation while the temperature of the Ringer's solution bathing in the slice was controlled at selected levels. 2. The amplitude of the population spike (action potentials from a group of pyramidal cells) was measured as bath temperature was lowered from 35 degrees C to temperatures where a response could not be evoked. 3. Plots of population spike amplitude versus temperature have bell-shaped curves. The population spikes increased in amplitude as temperature was lowered from 35 degrees C, reached a peak amplitude between 25 and 20 degrees C, and then decreased until a response could not be evoked when temperature was further lowered. 4. These in vitro results obtained in the slice preparation are related to in vivo hippocampal studies. Results are interpreted as consistent with the proposal reviewed here that neural activity in the hippocampus plays a role at specific stages of entrance into and arousal from hibernation.

  3. Modeling the Dynamics of Human Brain Activity with Recurrent Neural Networks

    PubMed Central

    Güçlü, Umut; van Gerven, Marcel A. J.

    2017-01-01

    Encoding models are used for predicting brain activity in response to sensory stimuli with the objective of elucidating how sensory information is represented in the brain. Encoding models typically comprise a nonlinear transformation of stimuli to features (feature model) and a linear convolution of features to responses (response model). While there has been extensive work on developing better feature models, the work on developing better response models has been rather limited. Here, we investigate the extent to which recurrent neural network models can use their internal memories for nonlinear processing of arbitrary feature sequences to predict feature-evoked response sequences as measured by functional magnetic resonance imaging. We show that the proposed recurrent neural network models can significantly outperform established response models by accurately estimating long-term dependencies that drive hemodynamic responses. The results open a new window into modeling the dynamics of brain activity in response to sensory stimuli. PMID:28232797

  4. Single-cell transcriptome analyses reveal signals to activate dormant neural stem cells.

    PubMed

    Luo, Yuping; Coskun, Volkan; Liang, Aibing; Yu, Juehua; Cheng, Liming; Ge, Weihong; Shi, Zhanping; Zhang, Kunshan; Li, Chun; Cui, Yaru; Lin, Haijun; Luo, Dandan; Wang, Junbang; Lin, Connie; Dai, Zachary; Zhu, Hongwen; Zhang, Jun; Liu, Jie; Liu, Hailiang; deVellis, Jean; Horvath, Steve; Sun, Yi Eve; Li, Siguang

    2015-05-21

    The scarcity of tissue-specific stem cells and the complexity of their surrounding environment have made molecular characterization of these cells particularly challenging. Through single-cell transcriptome and weighted gene co-expression network analysis (WGCNA), we uncovered molecular properties of CD133(+)/GFAP(-) ependymal (E) cells in the adult mouse forebrain neurogenic zone. Surprisingly, prominent hub genes of the gene network unique to ependymal CD133(+)/GFAP(-) quiescent cells were enriched for immune-responsive genes, as well as genes encoding receptors for angiogenic factors. Administration of vascular endothelial growth factor (VEGF) activated CD133(+) ependymal neural stem cells (NSCs), lining not only the lateral but also the fourth ventricles and, together with basic fibroblast growth factor (bFGF), elicited subsequent neural lineage differentiation and migration. This study revealed the existence of dormant ependymal NSCs throughout the ventricular surface of the CNS, as well as signals abundant after injury for their activation.

  5. Elevated reward-related neural activation as a unique biological marker of bipolar disorder: assessment and treatment implications.

    PubMed

    Nusslock, Robin; Young, Christina B; Damme, Katherine S F

    2014-11-01

    Growing evidence indicates that risk for bipolar disorder is characterized by elevated activation in a fronto-striatal reward neural circuit involving the ventral striatum and orbitofrontal cortex, among other regions. It is proposed that individuals with abnormally elevated reward-related neural activation are at risk for experiencing an excessive increase in approach-related motivation during life events involving rewards or goal striving and attainment. In the extreme, this increase in motivation is reflected in hypomanic/manic symptoms. By contrast, unipolar depression (without a history of hypomania/mania) is characterized by decreased reward responsivity and decreased reward-related neural activation. Collectively, this suggests that risk for bipolar disorder and unipolar depression are characterized by distinct and opposite profiles of reward processing and reward-related neural activation. The objective of the present paper is threefold. First, we review the literature on reward processing and reward-related neural activation in bipolar disorder, and in particular risk for hypomania/mania. Second, we propose that reward-related neural activation reflects a biological marker of differential risk for bipolar disorder versus unipolar depression that may help facilitate psychiatric assessment and differential diagnosis. We also discuss, however, the challenges to using neuroscience techniques and biological markers in a clinical setting for assessment and diagnostic purposes. Lastly, we address the pharmacological and psychosocial treatment implications of research on reward-related neural activation in bipolar disorder.

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

    PubMed

    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.

  7. Intranasal oxytocin reduces social perception in women: Neural activation and individual variation.

    PubMed

    Hecht, Erin E; Robins, Diana L; Gautam, Pritam; King, Tricia Z

    2017-02-15

    Most intranasal oxytocin research to date has been carried out in men, but recent studies indicate that females' responses can differ substantially from males'. This randomized, double-blind, placebo-controlled study involved an all-female sample of 28 women not using hormonal contraception. Participants viewed animations of geometric shapes depicting either random movement or social interactions such as playing, chasing, or fighting. Probe questions asked whether any shapes were "friends" or "not friends." Social videos were preceded by cues to attend to either social relationships or physical size changes. All subjects received intranasal placebo spray at scan 1. While the experimenter was not blinded to nasal spray contents at Scan 1, the participants were. Scan 2 followed a randomized, double-blind design. At scan 2, half received a second placebo dose while the other half received 24 IU of intranasal oxytocin. We measured neural responses to these animations at baseline, as well as the change in neural activity induced by oxytocin. Oxytocin reduced activation in early visual cortex and dorsal-stream motion processing regions for the social > size contrast, indicating reduced activity related to social attention. Oxytocin also reduced endorsements that shapes were "friends" or "not friends," and this significantly correlated with reduction in neural activation. Furthermore, participants who perceived fewer social relationships at baseline were more likely to show oxytocin-induced increases in a broad network of regions involved in social perception and social cognition, suggesting that lower social processing at baseline may predict more positive neural responses to oxytocin.

  8. Global asymptotical stability of continuous-time delayed neural networks without global Lipschitz activation functions

    NASA Astrophysics Data System (ADS)

    Tan, Yong; Tan, Mingjia

    2009-11-01

    This paper investigates the global asymptotic stability of equilibrium for a class of continuous-time neural networks with delays. Based on suitable Lyapunov functionals and the homeomorphism theory, some sufficient conditions for the existence and uniqueness of the equilibrium point are derived. These results extend the previously works without assuming boundedness and Lipschitz conditions of the activation functions and any symmetry of interconnections. A numerical example is also given to show the improvements of the paper.

  9. Current steering to activate targeted neural pathways during deep brain stimulation of the subthalamic region

    PubMed Central

    Chaturvedi, Ashutosh; Foutz, Thomas J.; McIntyre, Cameron C.

    2012-01-01

    Deep brain stimulation (DBS) has steadily evolved into an established surgical therapy for numerous neurological disorders, most notably Parkinson’s disease (PD). Traditional DBS technology relies on voltage-controlled stimulation with a single source; however, recent engineering advances are providing current-controlled devices with multiple independent sources. These new stimulators deliver constant current to the brain tissue, irrespective of impedance changes that occur around the electrode, and enable more specific steering of current towards targeted regions of interest. In this study, we examined the impact of current steering between multiple electrode contacts to directly activate three distinct neural populations in the subthalamic region commonly stimulated for the treatment of PD: projection neurons of the subthalamic nucleus (STN), globus pallidus internus (GPi) fibers of the lenticular fasiculus, and internal capsule (IC) fibers of passage. We used three-dimensional finite element electric field models, along with detailed multi-compartment cable models of the three neural populations to determine their activations using a wide range of stimulation parameter settings. Our results indicate that selective activation of neural populations largely depends on the location of the active electrode(s). Greater activation of the GPi and STN populations (without activating any side-effect related IC fibers) was achieved by current steering with multiple independent sources, compared to a single current source. Despite this potential advantage, it remains to be seen if these theoretical predictions result in a measurable clinical effect that outweighs the added complexity of the expanded stimulation parameter search space generated by the more flexible technology. PMID:22277548

  10. The BDNF Val66Met Polymorphism Influences Reading Ability and Patterns of Neural Activation in Children

    PubMed Central

    Jasińska, Kaja K.; Molfese, Peter J.; Kornilov, Sergey A.; Mencl, W. Einar; Frost, Stephen J.; Lee, Maria; Pugh, Kenneth R.; Grigorenko, Elena L.; Landi, Nicole

    2016-01-01

    Understanding how genes impact the brain’s functional activation for learning and cognition during development remains limited. We asked whether a common genetic variant in the BDNF gene (the Val66Met polymorphism) modulates neural activation in the young brain during a critical period for the emergence and maturation of the neural circuitry for reading. In animal models, the bdnf variation has been shown to be associated with the structure and function of the developing brain and in humans it has been associated with multiple aspects of cognition, particularly memory, which are relevant for the development of skilled reading. Yet, little is known about the impact of the Val66Met polymorphism on functional brain activation in development, either in animal models or in humans. Here, we examined whether the BDNF Val66Met polymorphism (dbSNP rs6265) is associated with children’s (age 6–10) neural activation patterns during a reading task (n = 81) using functional magnetic resonance imaging (fMRI), genotyping, and standardized behavioral assessments of cognitive and reading development. Children homozygous for the Val allele at the SNP rs6265 of the BDNF gene outperformed Met allele carriers on reading comprehension and phonological memory, tasks that have a strong memory component. Consistent with these behavioral findings, Met allele carriers showed greater activation in reading–related brain regions including the fusiform gyrus, the left inferior frontal gyrus and left superior temporal gyrus as well as greater activation in the hippocampus during a word and pseudoword reading task. Increased engagement of memory and spoken language regions for Met allele carriers relative to Val/Val homozygotes during reading suggests that Met carriers have to exert greater effort required to retrieve phonological codes. PMID:27551971

  11. Reconstruction of Neural Activity from EEG Data Using Dynamic Spatiotemporal Constraints.

    PubMed

    Giraldo-Suarez, E; Martinez-Vargas, J D; Castellanos-Dominguez, G

    2016-11-01

    We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of potentially active brain regions. In turn, we enhance the time resolution by adding the Markovian assumption for brain activity estimation at each time period. Moreover, to deal with applications that have either distributed or localized neural activity, the spatiotemporal constraints are expressed through [Formula: see text] and [Formula: see text] norms, respectively. For the purpose of validation, we estimate the neural reconstruction performance in time and space separately. Experimental testing is carried out on artificial data, simulating stationary and non-stationary EEG signals. Also, validation is accomplished on two real-world databases, one holding Evoked Potentials and another with EEG data of focal epilepsy. Moreover, responses of functional magnetic resonance imaging for the former EEG data have been measured in advance, allowing to contrast our findings. Obtained results show that the [Formula: see text]-based IRA produces a spatial resolution that is comparable to the one achieved by some widely used sparse-based estimators of brain activity. At the same time, the [Formula: see text]-based IRA outperforms other similar smooth solutions, providing a spatial resolution that is lower than the sparse [Formula: see text]-based solution. As a result, the proposed IRA is a promising method for improving the accuracy of brain activity reconstruction.

  12. Fast optical recording of light-flash evoked neural activation in amphibian retina

    NASA Astrophysics Data System (ADS)

    Yao, Xin-Cheng; George, John S.

    2005-08-01

    Imaging of fast intrinsic optical responses closely associated with neural activation promises important technical advantages over traditional single and multi-channel electrophysiological techniques for dynamic measurements of visual processing and early detection of eye diseases. We have developed a fast, no-moving-parts optical coherence tomography (OCT), system based on an electro-optic phase modulator, and used it to record dynamic near infrared (NIR) light scattering changes in frog retina activated by a visible light-flash. We also employed transmitted light for highly sensitive measurement and imaging of neural activation, and to optimize illumination and optical configuration. Using a photodiode detector, we routinely measured dynamic NIR transmitted optical responses in single passes. When the whole retina was illuminated by a visible light-flash, a positive peak was typically observed in transmitted light measurements. CCD image sequences disclosed larger fractional responses, in some cases exceeding 0.5% in individual pixels, and showed evidence of multiple response components with both negative- and positive-going signals with different timescales and complex but consistent spatial organization. The fast negative-going signals are highly correlated with the a-wave of the electrophysiological signals, and may reflect the activation of photoreceptors. The fast positive-going responses are related to the b-wave of the electrophysiological signals, and may result from the activation of ON bipolar cells. Slow optical responses may signal metabolic changes of retinal tissue. Our experimental results and theoretical analysis suggest that the optical responses may result from dynamic volume changes associated with neural activation, corresponding to ion and water flow across the cell membrane.

  13. The BDNF Val66Met Polymorphism Influences Reading Ability and Patterns of Neural Activation in Children.

    PubMed

    Jasińska, Kaja K; Molfese, Peter J; Kornilov, Sergey A; Mencl, W Einar; Frost, Stephen J; Lee, Maria; Pugh, Kenneth R; Grigorenko, Elena L; Landi, Nicole

    2016-01-01

    Understanding how genes impact the brain's functional activation for learning and cognition during development remains limited. We asked whether a common genetic variant in the BDNF gene (the Val66Met polymorphism) modulates neural activation in the young brain during a critical period for the emergence and maturation of the neural circuitry for reading. In animal models, the bdnf variation has been shown to be associated with the structure and function of the developing brain and in humans it has been associated with multiple aspects of cognition, particularly memory, which are relevant for the development of skilled reading. Yet, little is known about the impact of the Val66Met polymorphism on functional brain activation in development, either in animal models or in humans. Here, we examined whether the BDNF Val66Met polymorphism (dbSNP rs6265) is associated with children's (age 6-10) neural activation patterns during a reading task (n = 81) using functional magnetic resonance imaging (fMRI), genotyping, and standardized behavioral assessments of cognitive and reading development. Children homozygous for the Val allele at the SNP rs6265 of the BDNF gene outperformed Met allele carriers on reading comprehension and phonological memory, tasks that have a strong memory component. Consistent with these behavioral findings, Met allele carriers showed greater activation in reading-related brain regions including the fusiform gyrus, the left inferior frontal gyrus and left superior temporal gyrus as well as greater activation in the hippocampus during a word and pseudoword reading task. Increased engagement of memory and spoken language regions for Met allele carriers relative to Val/Val homozygotes during reading suggests that Met carriers have to exert greater effort required to retrieve phonological codes.

  14. Theoretical analysis on relationship between the neural activity and the EEG.

    PubMed

    Kitazoe, Y; Hiraoka, N; Ueta, H; Ogura, H; Yamamoto, K; Seto, K; Saito, H

    1983-10-21

    Firstly, a collective oscillation mode of the neural activity is derived from the neural network system by using the multicompartment equation and the projection operator technique. This technique takes into account higher order interactions among neurons. The solution of the equation gives a chain structure with an infinite number of circuit loops in which each of them is only composed of four neurons. The obtained eigenvalues are quite similar to the spectrum of frequencies of the EEG. Secondly, the time-dependent behavior of the observed EEG is simulated by starting from the elementary process of action potential trains of neurons, which includes the effect of the collective oscillation mode mentioned above. This gives a comprehensive derivation of the EEG from the neural activity of action potentials. The simulation assumes that information of the action potential trains can be transmitted to the EEG through the intermediate states of the postsynaptic potential trains and the slow waves. The paper reports that a slightly modulated activity of a relatively small amount of neurons can cause a strong influence on the shape of the global EEG and that the calculated results reproduce the characteristic features of the EEG in a rat such as the theta rhythm, the spindle wave and the arousal wave.

  15. Temporal evolution of neural activity underlying auditory discrimination of frequency increase and decrease.

    PubMed

    Noguchi, Yasuki; Fujiwara, Mana; Hamano, Saki

    2015-05-01

    Discriminating a direction of frequency change is an important ability of the human auditory system, although temporal dynamics of neural activity underlying this discrimination remains unclear. In the present study, we recorded auditory-evoked potentials when human subjects explicitly judged a direction of a relative frequency change between two successive tones. A comparison of two types of trials with ascending and descending tone pairs revealed that neural activity discriminating a direction of frequency changes appeared as early as the P1 component of auditory-evoked potentials (latency 50 ms). Those differences between the ascending and descending trials were also observed in subsequent electroencephalographic components such as the N1 (100 ms) and P2 (200 ms). Furthermore, amplitudes of the P2 were significantly modulated by behavioral responses (upward/downward judgments) of subjects in the direction discrimination task, while those of the P1 were not. Those results indicate that, while the neural responses encoding a direction of frequency changes can be observed in an early component of electroencephalographic responses (50 ms after the change), the activity associated (correlated) with behavioral judgments evolves over time, being shaped in a later time period (around 200 ms) of the auditory processing.

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

    PubMed

    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.

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Reduced respiratory neural activity elicits a long-lasting decrease in the CO2 threshold for apnea in anesthetized rats.

    PubMed

    Baertsch, N A; Baker, T L

    2017-01-01

    Two critical parameters that influence breathing stability are the levels of arterial pCO2 at which breathing ceases and subsequently resumes - termed the apneic and recruitment thresholds (AT and RT, respectively). Reduced respiratory neural activity elicits a chemoreflex-independent, long-lasting increase in phrenic burst amplitude, a form of plasticity known as inactivity-induced phrenic motor facilitation (iPMF). The physiological significance of iPMF is unknown. To determine if iPMF and neural apnea have long-lasting physiological effects on breathing, we tested the hypothesis that patterns of neural apnea that induce iPMF also elicit changes in the AT and RT. Phrenic nerve activity and end-tidal CO2 were recorded in urethane-anesthetized, ventilated rats to quantify phrenic nerve burst amplitude and the AT and RT before and after three patterns of neural apnea that differed in their duration and ability to elicit iPMF: brief intermittent neural apneas, a single brief "massed" neural apnea, or a prolonged neural apnea. Consistent with our hypothesis, we found that patterns of neural apnea that elicited iPMF also resulted in changes in the AT and RT. Specifically, intermittent neural apneas progressively decreased the AT with each subsequent neural apnea, which persisted for at least 60min. Similarly, a prolonged neural apnea elicited a long-lasting decrease in the AT. In both cases, the magnitude of the AT decrease was proportional to iPMF. In contrast, the RT was transiently decreased following prolonged neural apnea, and was not proportional to iPMF. No changes in the AT or RT were observed following a single brief neural apnea. Our results indicate that the AT and RT are differentially altered by neural apnea and suggest that specific patterns of neural apnea that elicit plasticity may stabilize breathing via a decrease in the AT.

  19. Differences in Neural Activation for Object-Directed Grasping in Chimpanzees and Humans

    PubMed Central

    Murphy, Lauren E.; Gutman, David A.; Votaw, John R.; Schuster, David M.; Preuss, Todd M.; Orban, Guy A.; Stout, Dietrich; Parr, Lisa A.

    2013-01-01

    The human faculty for object-mediated action, including tool use and imitation, exceeds that of even our closest primate relatives and is a key foundation of human cognitive and cultural uniqueness. In humans and macaques, observing object-directed grasping actions activates a network of frontal, parietal, and occipitotemporal brain regions, but differences in human and macaque activation suggest that this system has been a focus of selection in the primate lineage. To study the evolution of this system, we performed functional neuroimaging in humans' closest living relatives, chimpanzees. We compare activations during performance of an object-directed manual grasping action, observation of the same action, and observation of a mimed version of the action that consisted of only movements without results. Performance and observation of the same action activated a distributed frontoparietal network similar to that reported in macaques and humans. Like humans and unlike macaques, these regions were also activated by observing movements without results. However, in a direct chimpanzee/human comparison, we also identified unique aspects of human neural responses to observed grasping. Chimpanzee activation showed a prefrontal bias, including significantly more activity in ventrolateral prefrontal cortex, whereas human activation was more evenly distributed across more posterior regions, including significantly more activation in ventral premotor cortex, inferior parietal cortex, and inferotemporal cortex. This indicates a more “bottom-up” representation of observed action in the human brain and suggests that the evolution of tool use, social learning, and cumulative culture may have involved modifications of frontoparietal interactions. PMID:23986247

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

    NASA Astrophysics Data System (ADS)

    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.

  1. A Neural Mechanism for Nonconscious Activation of Conditioned Placebo and Nocebo Responses.

    PubMed

    Jensen, Karin B; Kaptchuk, Ted J; Chen, Xiaoyan; Kirsch, Irving; Ingvar, Martin; Gollub, Randy L; Kong, Jian

    2015-10-01

    Fundamental aspects of human behavior operate outside of conscious awareness. Yet, theories of conditioned responses in humans, such as placebo and nocebo effects on pain, have a strong emphasis on conscious recognition of contextual cues that trigger the response. Here, we investigated the neural pathways involved in nonconscious activation of conditioned pain responses, using functional magnetic resonance imaging in healthy participants. Nonconscious compared with conscious activation of conditioned placebo analgesia was associated with increased activation of the orbitofrontal cortex, a structure with direct connections to affective brain regions and basic reward processing. During nonconscious nocebo, there was increased activation of the thalamus, amygdala, and hippocampus. In contrast to previous assumptions about conditioning in humans, our results show that conditioned pain responses can be elicited independently of conscious awareness and our results suggest a hierarchical activation of neural pathways for nonconscious and conscious conditioned responses. Demonstrating that the human brain has a nonconscious mechanism for responding to conditioned cues has major implications for the role of associative learning in behavioral medicine and psychiatry. Our results may also open up for novel approaches to translational animal-to-human research since human consciousness and animal cognition is an inherent paradox in all behavioral science.

  2. Traumatic Brain Injury Stimulates Neural Stem Cell Proliferation via Mammalian Target of Rapamycin Signaling Pathway Activation

    PubMed Central

    Seekaew, Pich

    2016-01-01

    Abstract Neural stem cells in the adult brain possess the ability to remain quiescent until needed in tissue homeostasis or repair. It was previously shown that traumatic brain injury (TBI) stimulated neural stem cell (NSC) proliferation in the adult hippocampus, indicating an innate repair mechanism, but it is unknown how TBI promotes NSC proliferation. In the present study, we observed dramatic activation of mammalian target of rapamycin complex 1 (mTORC1) in the hippocampus of mice with TBI from controlled cortical impact (CCI). The peak of mTORC1 activation in the hippocampal subgranular zone, where NSCs reside, is 24–48 h after trauma, correlating with the peak of TBI-enhanced NSC proliferation. By use of a Nestin-GFP transgenic mouse, in which GFP is ectopically expressed in the NSCs, we found that TBI activated mTORC1 in NSCs. With 5-bromo-2′-deoxyuridine labeling, we observed that TBI increased mTORC1 activation in proliferating NSCs. Furthermore, administration of rapamycin abolished TBI-promoted NSC proliferation. Taken together, these data indicate that mTORC1 activation is required for NSC proliferation postinjury, and thus might serve as a therapeutic target for interventions to augment neurogenesis for brain repair after TBI. PMID:27822507

  3. Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition

    PubMed Central

    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

  4. a Hybrid-Type Active Vibration Isolation System Using Neural Networks

    NASA Astrophysics Data System (ADS)

    Ahn, K. G.; Pahk, H. J.; Jung, M. Y.; Cho, D. W.

    1996-05-01

    Vibration isolation of mechanical systems is achieved through either passive or active vibration control systems. Although a passive vibration isolation system offers simple and reliable means to protect mechanical systems from a vibration environment, it has inherent performance limitations, that is, its controllable frequency range is limited and the shape of its transmissibility does not change. Recently, in some applications, such as active suspensions or precise vibration systems, active vibration isolation systems have been employed to overcome the limitations of the passive systems. In this paper, a hybrid-type active vibration isolation system that uses electromagnetic and pneumatic force is developed, and a new control algorithm adopting neural networks is proposed. The characteristics of the hybrid system proposed in the paper were investigated via computer simulation and experiments. It was shown that the transmissibility of the vibration isolation system could be kept below 0.63 over the entire frequency range, including the resonance frequency.

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

    PubMed

    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.

  6. Differential neural activation for updating rule versus stimulus information in working memory

    PubMed Central

    Montojo, Caroline; Courtney, Susan M.

    2008-01-01

    Summary Establishing what information is actively maintained in working memory (WM) and how it is represented and controlled is essential to understanding how such information guides future behavior. WM has traditionally been investigated in terms of the maintenance of stimulus-specific information, such as locations or words. More recently, investigators have emphasized the importance of rules that establish relationships between those stimuli and the pending response. The current study used a mental arithmetic task with fMRI to test whether updating of numbers (i.e. stimuli) and updating of mathematical operations (i.e. rules) in WM relies on the same neural system. Results indicate that while a common network is activated by both types of updating, rule updating preferentially activates prefrontal cortex while number updating preferentially activates parietal cortex. The results suggest that both numbers and rules are maintained in WM, but they are different types of information that are controlled independently. PMID:18614038

  7. Imaging Neural Activity Using Thy1-GCaMP Transgenic mice

    PubMed Central

    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

    2014-01-01

    Summary The ability to chronically monitor neuronal activity in the living brain is essential for understanding the organization and function of the nervous system. The genetically encoded green fluorescent protein based calcium sensor GCaMP provides a powerful tool for detecting calcium transients in neuronal somata, processes, and synapses that are triggered 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 and in vivo studies show that calcium transients induced by spontaneous and stimulus-evoked neuronal activities can be readily detected at the level of individual cells and synapses in acute brain slices, as well as chronically in awake behaving animals. These GCaMP transgenic mice allow investigation of activity patterns in defined neuronal populations in the living brain, and will greatly facilitate dissecting complex structural and functional relationships of neural networks. PMID:23083733

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

    PubMed

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

    PubMed Central

    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

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

    PubMed

    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.

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

    PubMed

    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.

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

    SciTech Connect

    Zhu, Liang; Dong, Chuanming; Sun, Chenxi; Ma, Rongjie; Yang, Danjing; Zhu, Hongwen; Xu, Jun

    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.

  13. Noise influence on spike activation in a Hindmarsh-Rose small-world neural network

    NASA Astrophysics Data System (ADS)

    Zhe, Sun; Micheletto, Ruggero

    2016-07-01

    We studied the role of noise in neural networks, especially focusing on its relation to the propagation of spike activity in a small sized system. We set up a source of information using a single neuron that is constantly spiking. This element called initiator x o feeds spikes to the rest of the network that is initially quiescent and subsequently reacts with vigorous spiking after a transitional period of time. We found that noise quickly suppresses the initiator’s influence and favors spontaneous spike activity and, using a decibel representation of noise intensity, we established a linear relationship between noise amplitude and the interval from the initiator’s first spike and the rest of the network activation. We studied the same process with networks of different sizes (number of neurons) and found that the initiator x o has a measurable influence on small networks, but as the network grows in size, spontaneous spiking emerges disrupting its effects on networks of more than about N = 100 neurons. This suggests that the mechanism of internal noise generation allows information transmission within a small neural neighborhood, but decays for bigger network domains. We also analyzed the Fourier spectrum of the whole network membrane potential and verified that noise provokes the reduction of main θ and α peaks before transitioning into chaotic spiking. However, network size does not reproduce a similar phenomena; instead we recorded a reduction in peaks’ amplitude, a better sharpness and definition of Fourier peaks, but not the evident degeneration to chaos observed with increasing external noise. This work aims to contribute to the understanding of the fundamental mechanisms of propagation of spontaneous spiking in neural networks and gives a quantitative assessment of how noise can be used to control and modulate this phenomenon in Hindmarsh-Rose (H-R) neural networks.

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

    PubMed

    Bidelman, Gavin M

    2017-02-15

    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.

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

    PubMed Central

    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. PMID:27147955

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

    PubMed

    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.

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

    PubMed Central

    Zanon, Marco; Battaglini, Piero P.; Jarmolowska, Joanna; Pizzolato, Gilberto; Busan, Pierpaolo

    2013-01-01

    The premotor cortex is one of the fundamental structures composing the neural networks of the human brain. It is implicated in many behaviors and cognitive tasks, ranging from movement to attention and eye-related activity. Therefore, neural circuits that are related to premotor cortex have been studied to clarify their connectivity and/or role in different tasks. In the present work, we aimed to investigate the propagation of the neural activity evoked in the dorsal premotor cortex using transcranial magnetic stimulation/electroencephalography (TMS/EEG). Toward this end, interest was focused on the neural dynamics elicited in long-ranging temporal and spatial networks. Twelve healthy volunteers underwent a single-pulse TMS protocol in a resting condition with eyes closed, and the evoked activity, measured by EEG, was compared to a sham condition in a time window ranging from 45 ms to about 200 ms after TMS. Spatial and temporal investigations were carried out with sLORETA. TMS was found to induce propagation of neural activity mainly in the contralateral sensorimotor and frontal cortices, at about 130 ms after delivery of the stimulus. Different types of analyses showed propagated activity also in posterior, mainly visual, regions, in a time window between 70 and 130 ms. Finally, a likely “rebounding” activation of the sensorimotor and frontal regions, was observed in various time ranges. Taken together, the present findings further characterize the neural circuits that are driven by dorsal premotor cortex activation in healthy humans. PMID:24324426

  18. Role of low voltage activated calcium channels in neuritogenesis and active migration of embryonic neural progenitor cells.

    PubMed

    Louhivuori, Lauri M; Louhivuori, Verna; Wigren, Henna-Kaisa; Hakala, Elina; Jansson, Linda C; Nordström, Tommy; Castrén, Maija L; Akerman, Karl E

    2013-04-15

    The central role of calcium influx and electrical activity in embryonic development raises important questions about the role and regulation of voltage-dependent calcium influx. Using cultured neural progenitor cell (NPC) preparations, we recorded barium currents through voltage-activated channels using the whole-cell configuration of the patch-clamp technique and monitored intracellular free calcium concentrations with Fura-2 digital imaging. We found that NPCs as well as expressing high-voltage-activated (HVA) calcium channels express functional low-threshold voltage-dependent calcium channels in the very early stages of differentiation (5 h to 1 day). The size of the currents recorded at -50 versus -20 mV after 1 day in differentiation was dependent on the nature of the charge carrier. Peak currents measured at -20 mV in the presence 10 mM Ca2+ instead of 10 mM Ba2+ had a tendency to be smaller, whereas the nature of the divalent species did not influence the amplitude measured at -50 mV. The T-type channel blockers mibefradil and NNC 55-0396 significantly reduced the calcium responses elicited by depolarizing with extracellular potassium, while the overall effect of the HVA calcium channel blockers was small at differentiation day 1. At differentiation day 20, the calcium responses were effectively blocked by nifedipine. Time-lapse imaging of differentiating neurospheres cultured in the presence of low-voltage-activated (LVA) blockers showed a significant decrease in the number of active migrating neuron-like cells and neurite extensions. Together, these data provide evidence that LVA calcium channels are involved in the physiology of differentiating and migrating NPCs.

  19. Chemogenetic Activation of an Extinction Neural Circuit Reduces Cue-Induced Reinstatement of Cocaine Seeking

    PubMed Central

    Augur, Isabel F.; Wyckoff, Andrew R.; Aston-Jones, Gary; Kalivas, Peter W.

    2016-01-01

    The ventromedial prefrontal cortex (vmPFC) has been shown to negatively regulate cocaine-seeking behavior, but the precise conditions by which vmPFC activity can be exploited to reduce cocaine relapse are currently unknown. We used viral-mediated gene transfer of designer receptors (DREADDs) to activate vmPFC neurons and examine the consequences on cocaine seeking in a rat self-administration model of relapse. Activation of vmPFC neurons with the Gq-DREADD reduced reinstatement of cocaine seeking elicited by cocaine-associated cues, but not by cocaine itself. We used a retro-DREADD approach to confine the Gq-DREADD to vmPFC neurons that project to the medial nucleus accumbens shell, confirming that these neurons are responsible for the decreased cue-induced reinstatement of cocaine seeking. The effects of vmPFC activation on cue-induced reinstatement depended on prior extinction training, consistent with the reported role of this structure in extinction memory. These data help define the conditions under which chemogenetic activation of extinction neural circuits can be exploited to reduce relapse triggered by reminder cues. SIGNIFICANCE STATEMENT The ventromedial prefrontal cortex (vmPFC) projection to the nucleus accumbens shell is important for extinction of cocaine seeking, but its anatomical proximity to the relapse-promoting projection from the dorsomedial prefrontal cortex to the nucleus accumbens core makes it difficult to selectively enhance neuronal activity in one pathway or the other using traditional pharmacotherapy (e.g., systemically administered drugs). Viral-mediated gene delivery of an activating Gq-DREADD to vmPFC and/or vmPFC projections to the nucleus accumbens shell allows the chemogenetic exploitation of this extinction neural circuit to reduce cocaine seeking and was particularly effective against relapse triggered by cocaine reminder cues. PMID:27683912

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

    PubMed

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, 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 (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. 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 sensitivity of critical states and the predictability and timing of oscillations for efficient information

  1. Bioimpedance Harmonic Analysis as a Diagnostic Tool to Assess Regional Circulation and Neural Activity

    NASA Astrophysics Data System (ADS)

    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.

  2. Emergence of spatially heterogeneous burst suppression in a neural field model of electrocortical activity

    PubMed Central

    Bojak, Ingo; Stoyanov, Zhivko V.; Liley, David T. J.

    2015-01-01

    Burst suppression in the electroencephalogram (EEG) is a well-described phenomenon that occurs during deep anesthesia, 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 characterization 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 anesthesia at the whole cortex level. Simulations reveal heterogeneous bursting over the model cortex and complex spatiotemporal dynamics during simulated anesthetic action, and provide forward predictions of neuroimaging signals for subsequent empirical comparisons and more detailed characterization. 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 anesthetic 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. PMID:25767438

  3. Neural activities associated with emotion recognition observed in men and women.

    PubMed

    Lee, T M C; Liu, H-L; Chan, C C H; Fang, S-Y; Gao, J-H

    2005-05-01

    Previous studies have suggested that men and women process emotional stimuli differently. In this study, we examined if there would be any consistency in regions of activation in men and women when processing stimuli portraying happy or sad emotions presented in the form of facial expressions, scenes, and words. A blocked design BOLD functional magnetic resonance imaging paradigm was employed to monitor the neural activities of male and female healthy volunteers while they were presented with the experimental stimuli. The imaging data revealed that the right insula and left thalamus were consistently activated for men, but not women, during emotion recognition of all forms of stimuli studied. To further understand the imaging data acquired, we conducted the protocol analysis method to identify the cognitive processes engaged while the men and women were viewing the emotional stimuli and deciding whether they were happy or sad. The findings suggest that men rely on the recall of past emotional experiences to evaluate current emotional experiences. This may explain why the insula, a structure important for self-induced or internally generated recalled emotions, was consistently activated in men while processing emotional stimuli. Our findings suggest possible gender-related neural responses to emotional stimuli.

  4. Neural cell adhesion molecule-mediated Fyn activation promotes GABAergic synapse maturation in postnatal mouse cortex.

    PubMed

    Chattopadhyaya, Bidisha; Baho, Elie; Huang, Z Josh; Schachner, Melitta; Di Cristo, Graziella

    2013-04-03

    GABAergic basket interneurons form perisomatic synapses, which are essential for regulating neural networks, and their alterations are linked to various cognitive dysfunction. Maturation of basket synapses in postnatal cortex is activity dependent. In particular, activity-dependent downregulation of polysialiac acid carried by the neural cell adhesion molecule (NCAM) regulates the timing of their maturation. Whether and how NCAM per se affects GABAergic synapse development is unknown. Using single-cell genetics to knock out NCAM in individual basket interneurons in mouse cortical slice cultures, at specific developmental time periods, we found that NCAM loss during perisomatic synapse formation impairs the process of basket cell axonal branching and bouton formation. However, loss of NCAM once the synapses are already formed did not show any effect. We further show that NCAM120 and NCAM140, but not the NCAM180 isoform, rescue the phenotype. Finally, we demonstrate that a dominant-negative form of Fyn kinase mimics, whereas a constitutively active form of Fyn kinase rescues, the effects of NCAM knockdown. Altogether, our data suggest that NCAM120/NCAM140-mediated Fyn activation promotes GABAergic synapse maturation in postnatal cortex.

  5. Telencephalic neural activation following passive avoidance learning in a terrestrial toad.

    PubMed

    Puddington, Martín M; Daneri, M Florencia; Papini, Mauricio R; Muzio, Rubén N

    2016-12-15

    The present study explores passive avoidance learning and its neural basis in toads (Rhinella arenarum). In Experiment 1, two groups of toads learned to move from a lighted compartment into a dark compartment. After responding, animals in the experimental condition were exposed to an 800-mM strongly hypertonic NaCl solution that leads to weight loss. Control animals received exposure to a 300-mM slightly hypertonic NaCl solution that leads to neither weight gain nor loss. After 10 daily acquisition trials, animals in the experimental group showed significantly longer latency to enter the dark compartment. Additionally, 10 daily trials in which both groups received the 300-mM NaCl solution after responding eliminated this group effect. Thus, experimental animals showed gradual acquisition and extinction of a passive avoidance respond. Experiment 2 replicated the gradual acquisition effect, but, after the last trial, animals were sacrificed and neural activation was assessed in five brain regions using AgNOR staining for nucleoli-an index of brain activity. Higher activation in the experimental animals, relative to controls, was observed in the amygdala and striatum. Group differences in two other regions, lateral pallium and septum, were borderline, but nonsignificant, whereas group differences in the medial pallium were nonsignificant. These preliminary results suggest that a striatal-amygdala activation could be a key component of the brain circuit controlling passive avoidance learning in amphibians. The results are discussed in relation to the results of analogous experiments with other vertebrates.

  6. Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks.

    PubMed

    Zhang, Jie; Osan, Remus

    2016-05-01

    In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.

  7. Analytically tractable studies of traveling waves of activity in integrate-and-fire neural networks

    NASA Astrophysics Data System (ADS)

    Zhang, Jie; Osan, Remus

    2016-05-01

    In contrast to other large-scale network models for propagation of electrical activity in neural tissue that have no analytical solutions for their dynamics, we show that for a specific class of integrate and fire neural networks the acceleration depends quadratically on the instantaneous speed of the activity propagation. We use this property to analytically compute the network spike dynamics and to highlight the emergence of a natural time scale for the evolution of the traveling waves. These results allow us to examine other applications of this model such as the effect that a nonconductive gap of tissue has on further activity propagation. Furthermore we show that activity propagation also depends on local conditions for other more general connectivity functions, by converting the evolution equations for network dynamics into a low-dimensional system of ordinary differential equations. This approach greatly enhances our intuition into the mechanisms of the traveling waves evolution and significantly reduces the simulation time for this class of models.

  8. Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure.

    PubMed

    Li, Xiumin; Small, Michael

    2012-06-01

    Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both in vivo and in vitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

  9. Neuronal avalanches of a self-organized neural network with active-neuron-dominant structure

    NASA Astrophysics Data System (ADS)

    Li, Xiumin; Small, Michael

    2012-06-01

    Neuronal avalanche is a spontaneous neuronal activity which obeys a power-law distribution of population event sizes with an exponent of -3/2. It has been observed in the superficial layers of cortex both invivo and invitro. In this paper, we analyze the information transmission of a novel self-organized neural network with active-neuron-dominant structure. Neuronal avalanches can be observed in this network with appropriate input intensity. We find that the process of network learning via spike-timing dependent plasticity dramatically increases the complexity of network structure, which is finally self-organized to be active-neuron-dominant connectivity. Both the entropy of activity patterns and the complexity of their resulting post-synaptic inputs are maximized when the network dynamics are propagated as neuronal avalanches. This emergent topology is beneficial for information transmission with high efficiency and also could be responsible for the large information capacity of this network compared with alternative archetypal networks with different neural connectivity.

  10. Right hemisphere neural activations in the recall of waking fantasies and of dreams.

    PubMed

    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.

  11. Interfacing with Neural Activity via Femtosecond Laser Stimulation of Drug-Encapsulating Liposomal Nanostructures

    PubMed Central

    Mackay, Sean M.; Wui Tan, Eng

    2016-01-01

    External control over rapid and precise release of chemicals in the brain potentially provides a powerful interface with neural activity. Optical manipulation techniques, such as optogenetics and caged compounds, enable remote control of neural activity and behavior with fine spatiotemporal resolution. However, these methods are limited to chemicals that are naturally present in the brain or chemically suitable for caging. Here, we demonstrate the ability to interface with neural functioning via a wide range of neurochemicals released by stimulating loaded liposomal nanostructures with femtosecond lasers. Using a commercial two-photon microscope, we released inhibitory or excitatory neurochemicals to evoke subthreshold and suprathreshold changes in membrane potential in a live mouse brain slice. The responses were repeatable and could be controlled by adjusting laser stimulation characteristics. We also demonstrate the release of a wider range of chemicals—which previously were impossible to release by optogenetics or uncaging—including synthetic analogs of naturally occurring neurochemicals. In particular, we demonstrate the release of a synthetic receptor-specific agonist that exerts physiological effects on long-term synaptic plasticity. Further, we show that the loaded liposomal nanostructures remain functional for weeks in a live mouse. In conclusion, we demonstrate new techniques capable of interfacing with live neurons, and extendable to in vivo applications. PMID:27896311

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

    PubMed

    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.

  13. When your friends make you cringe: social closeness modulates vicarious embarrassment-related neural activity

    PubMed Central

    Müller-Pinzler, Laura; Rademacher, Lena; Paulus, Frieder M.

    2016-01-01

    Social closeness is a potent moderator of vicarious affect and specifically vicarious embarrassment. The neural pathways of how social closeness to another person affects our experience of vicarious embarrassment for the other’s public flaws, failures and norm violations are yet unknown. To bridge this gap, we examined the neural response of participants while witnessing threats to either a friend’s or a stranger’s social integrity. The results show consistent responses of the anterior insula (AI) and anterior cingulate cortex (ACC), shared circuits of the aversive quality of affect, as well as the medial prefrontal cortex and temporal pole, central structures of the mentalizing network. However, the ACC/AI network activation was increased during vicarious embarrassment in response to a friend’s failures. At the same time, the precuneus, a brain region associated with self-related thoughts, showed a specific activation and an increase in functional connectivity with the shared circuits in the frontal lobe while observing friends. This might indicate a neural systems mechanism for greater affective sharing and self-involvement while people interact with close others that are relevant to oneself. PMID:26516170

  14. Neural regions that underlie reinforcement learning are also active for social expectancy violations.

    PubMed

    Harris, Lasana T; Fiske, Susan T

    2010-01-01

    Prediction error, the difference between an expected and an actual outcome, serves as a learning signal that interacts with reward and punishment value to direct future behavior during reinforcement learning. We hypothesized that similar learning and valuation signals may underlie social expectancy violations. Here, we explore the neural correlates of social expectancy violation signals along the universal person-perception dimensions trait warmth and competence. In this context, social learning may result from expectancy violations that occur when a target is inconsistent with an a priori schema. Expectancy violation may activate neural regions normally implicated in prediction error and valuation during appetitive and aversive conditioning. Using fMRI, we first gave perceivers high warmth or competence behavioral information that led to dispositional or situational attributions for the behavior. Participants then saw pictures of people responsible for the behavior; they represented social groups either inconsistent (rated low on either warmth or competence) or consistent (rated high on either warmth or competence) with the behavior information. Warmth and competence expectancy violations activate striatal regions that represent evaluative and prediction error signals. Social cognition regions underlie consistent expectations. These findings suggest that regions underlying reinforcement learning may work in concert with social cognition regions in warmth and competence social expectancy. This study illustrates the neural overlap between neuroeconomics and social neuroscience.

  15. Neural encoding schemes of tactile information in afferent activity of the vibrissal system.

    PubMed

    Farfán, Fernando D; Albarracín, Ana L; Felice, Carmelo J

    2013-02-01

    When rats acquire sensory information by actively moving their vibrissae, a neural code is manifested at different levels of the sensory system. Behavioral studies in tactile discrimination agree that rats can distinguish different roughness surfaces by whisking their vibrissae. The present study explores the existence of neural encoding in the afferent activity of one vibrissal nerve. Two neural encoding schemes based on "events" were proposed (cumulative event count and median inter-event time). The events were detected by using an event detection algorithm based on multiscale decomposition of the signal (Continuous Wavelet Transform). The encoding schemes were quantitatively evaluated through the maximum amount of information which was obtained by the Shannon's mutual information formula. Moreover, the effect of difference distances between rat snout and swept surfaces on the information values was also studied. We found that roughness information was encoded by events of 0.8 ms duration in the cumulative event count and event of 1.0 to 1.6 ms duration in the median inter-event count. It was also observed that an extreme decrease of the distance between rat snout and swept surfaces significantly reduces the information values and the capacity to discriminate among the sweep situations.

  16. Unexpected activities of Smad7 in Xenopus mesodermal and neural induction

    PubMed Central

    de Almeida, Irene; Rolo, Ana; Batut, Julie; Hill, Caroline; Stern, Claudio D.; Linker, Claudia

    2009-01-01

    Neural induction is widely believed to be a direct consequence of inhibition of BMP pathways. Because of conflicting results and interpretations, we have reexamined this issue in Xenopus and chick embryos using the powerful and general TGFβ inhibitor, Smad7, which inhibits both Smad1- (BMP) and Smad2- (Nodal/Activin) mediated pathways. We confirm that Smad7 efficiently inhibits phosphorylation of Smad1 and Smad2. Surprisingly, however, over-expression of Smad7 in Xenopus ventral epidermis induces expression of the dorsal mesodermal markers Chordin and Brachyury. Neural markers are induced, but in a non-cell-autonomous manner and only when Chordin and Brachyury are also induced. Simultaneous inhibition of Smad1 and Smad2 by different approaches does not acount for Smad7 effects, indicating that Smad7 has activities other than inhibition of the TGFβ pathway. We provide evidence that these effects are independent of Wnt, FGF, Hedgehog and retinoid signalling. We also show that these effects are due to elements outside of the MH2 domain of Smad7. Together, these results indicate that BMP inhibition is not sufficient for neural induction even when Nodal/Activin is also blocked, and that Smad7 activity is considerably more complex than had previously been assumed. We suggest that experiments relying on Smad7 as an inhibitor of TGFβ-pathways should be interpreted with considerable caution. PMID:18359614

  17. Developmental effects of oxytocin on neural activation and neuropeptide release in response to social stimuli.

    PubMed

    Kramer, Kristin M; Choe, Christina; Carter, C Sue; Cushing, Bruce S

    2006-02-01

    Previous studies have revealed that the neuropeptide hormone oxytocin (OT) has developmental effects on subsequent social behavior and on mechanisms underlying social behavior such as OT neurons and estrogen receptor alpha. This suggests that OT might also have developmental effects on neural responses to social stimuli. This was tested in socially monogamous prairie voles (Microtus ochrogaster) by manipulating OT on the first day of life and then assessing the response to a heterosexual pairing in adulthood. The response to cohabitation was assessed by quantifying neural activation in regions of the brain associated with sociosexual behavior and anxiety using c-Fos immunoreactivity. Additionally, immunocytochemistry was used to label OT and vasopressin neurons and plasma was assayed for both neuropeptides. Treatment effects were evident in females, but not in males. Blockade of OT receptors with an OT antagonist on the first day of life resulted in neural activation of the central amygdala in response to a pairing with a novel male in adulthood. The central amygdala does not normally express c-Fos after a heterosexual pairing in reproductively naïve prairie voles. Treatment effects also were observed in vasopressin immunoreactivity in the SON with OT-treated females showing a decrease.

  18. Persistent neural activity during the maintenance of spatial position in working memory.

    PubMed

    Srimal, Riju; Curtis, Clayton E

    2008-01-01

    The mechanism for the short-term maintenance of information involves persistent neural activity during the retention interval, which forms a bridge between the cued memoranda and its later contingent response. Here, we used event-related functional magnetic resonance imaging to identify cortical areas with activity that persists throughout working memory delays with the goal of testing if such activity represents visuospatial attention or prospective saccade goals. We did so by comparing two spatial working memory tasks. During a memory-guided saccade (MGS) task, a location was maintained during a delay after which a saccade was generated to the remembered location. During a spatial item recognition (SIR) task identical to MGS until after the delay, a button press indicated whether a newly cued location matched the remembered location. Activity in frontal and parietal areas persisted above baseline and was greater in the hemisphere contralateral to the cued visual field. However, delay-period activity did not differ between the tasks. Notably, in the putative frontal eye field (FEF), delay period activity did not differ despite that the precise metrics of the memory-guided saccade were known during the MGS delay and saccades were never made in SIR. Persistent FEF activity may therefore represent a prioritized attentional map of space, rather than the metrics for saccades.

  19. Optimal waist-to-hip ratios in women activate neural reward centers in men.

    PubMed

    Platek, Steven M; Singh, Devendra

    2010-02-05

    Secondary sexual characteristics convey information about reproductive potential. In the same way that facial symmetry and masculinity, and shoulder-to-hip ratio convey information about reproductive/genetic quality in males, waist-to-hip-ratio (WHR) is a phenotypic cue to fertility, fecundity, neurodevelopmental resources in offspring, and overall health, and is indicative of "good genes" in women. Here, using fMRI, we found that males show activation in brain reward centers in response to naked female bodies when surgically altered to express an optimal (approximately 0.7) WHR with redistributed body fat, but relatively unaffected body mass index (BMI). Relative to presurgical bodies, brain activation to postsurgical bodies was observed in bilateral orbital frontal cortex. While changes in BMI only revealed activation in visual brain substrates, changes in WHR revealed activation in the anterior cingulate cortex, an area associated with reward processing and decision-making. When regressing ratings of attractiveness on brain activation, we observed activation in forebrain substrates, notably the nucleus accumbens, a forebrain nucleus highly involved in reward processes. These findings suggest that an hourglass figure (i.e., an optimal WHR) activates brain centers that drive appetitive sociality/attention toward females that represent the highest-quality reproductive partners. This is the first description of a neural correlate implicating WHR as a putative honest biological signal of female reproductive viability and its effects on men's neurological processing.

  20. Anti-glycated activity prediction of polysaccharides from two guava fruits using artificial neural networks.

    PubMed

    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.

  1. Negative stereotype activation alters interaction between neural correlates of arousal, inhibition and cognitive control

    PubMed Central

    Cox, Christine L.; Schmader, Toni; Ryan, Lee

    2012-01-01

    Priming negative stereotypes of African Americans can bias perceptions toward novel Black targets, but less is known about how these perceptions ultimately arise. Examining how neural regions involved in arousal, inhibition and control covary when negative stereotypes are activated can provide insight into whether individuals attempt to downregulate biases. Using fMRI, White egalitarian-motivated participants were shown Black and White faces at fast (32 ms) or slow (525 ms) presentation speeds. To create a racially negative stereotypic context, participants listened to violent and misogynistic rap (VMR) in the background. No music (NM) and death metal (DM) were used as control conditions in separate blocks. Fast exposure of Black faces elicited amygdala activation in the NM and VMR conditions (but not DM), that also negatively covaried with activation in prefrontal regions. Only in VMR, however, did amygdala activation for Black faces persist during slow exposure and positively covary with activation in dorsolateral prefrontal cortex while negatively covarying with activation in orbitofrontal cortex. Findings suggest that contexts that prime negative racial stereotypes seem to hinder the downregulation of amygdala activation that typically occurs when egalitarian perceivers are exposed to Black faces. PMID:21954239

  2. Negative stereotype activation alters interaction between neural correlates of arousal, inhibition and cognitive control.

    PubMed

    Forbes, Chad E; Cox, Christine L; Schmader, Toni; Ryan, Lee

    2012-10-01

    Priming negative stereotypes of African Americans can bias perceptions toward novel Black targets, but less is known about how these perceptions ultimately arise. Examining how neural regions involved in arousal, inhibition and control covary when negative stereotypes are activated can provide insight into whether individuals attempt to downregulate biases. Using fMRI, White egalitarian-motivated participants were shown Black and White faces at fast (32 ms) or slow (525 ms) presentation speeds. To create a racially negative stereotypic context, participants listened to violent and misogynistic rap (VMR) in the background. No music (NM) and death metal (DM) were used as control conditions in separate blocks. Fast exposure of Black faces elicited amygdala activation in the NM and VMR conditions (but not DM), that also negatively covaried with activation in prefrontal regions. Only in VMR, however, did amygdala activation for Black faces persist during slow exposure and positively covary with activation in dorsolateral prefrontal cortex while negatively covarying with activation in orbitofrontal cortex. Findings suggest that contexts that prime negative racial stereotypes seem to hinder the downregulation of amygdala activation that typically occurs when egalitarian perceivers are exposed to Black faces.

  3. "I remember thinking …": Neural activity associated with subsequent memory for stimulus-evoked internal mentations.

    PubMed

    Gilead, Michael; Liberman, Nira; Maril, Anat

    2014-01-01

    Conscious thought involves an interpretive inner monologue pertaining to our waking experiences. Previous studies focused on the mechanisms that allow us to remember externally presented stimuli, but the neurobiological basis of the ability to remember one's internal mentations remains unknown. In order to investigate this question, we presented participants with sentences and scanned their neural activity using functional magnetic resonance imaging (fMRI) as they incidentally produced spontaneous internal mentations. After the scan, we presented the sentences again and asked participants to describe the specific thoughts they had during the initial presentation of each sentence. We categorized experimental trials for each participant according to whether they resulted in subsequently reported internal mentations or not. The results show that activation within classic language processing areas was associated with participants' ability to recollect their thoughts. Activation within mostly right lateralized and medial "default-mode network" regions was associated with not reporting such thoughts.

  4. Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Abdeljaber, Osama; Avci, Onur; Inman, Daniel J.

    2016-02-01

    The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates is discussed. An intelligent neural network based controller is designed to control the optimal voltage applied on the piezoelectric patches. The control technique utilizes a neurocontroller along with a Kalman Filter to compute the appropriate actuator command. The neurocontroller is trained based on an algorithm that incorporates a set of emulator neural networks which are also trained to predict the future response of the cantilever plate. Then, the neurocontroller is evaluated by comparing the uncontrolled and controlled responses under several types of dynamic excitations. It is observed that the neurocontroller reduced the vibration response of the flexible cantilever plate significantly; the results demonstrated the success and robustness of the neurocontroller independent of the type and distribution of the excitation force.

  5. Uniformity and nonuniformity of neural activities correlated to different insight problem solving.

    PubMed

    Zhao, Q; Li, Y; Shang, X; Zhou, Z; Han, L

    2014-06-13

    Previous studies on the neural basis of insight reflected weak consistency except for the anterior cingulate cortex. The present work adopted the semantic and homophonic punny riddle to explore the uniformity and nonuniformity of neural activities correlated to different insight problem solving. Results showed that in the early period of insight solving, the semantic and homophonic punny riddles induced a common N350-500 over the central scalp. However, during -400 to 0 ms before the riddles were solved, the semantic punny riddles induced a positive event-related potential (ERP) deflection over the temporal cortex for retrieving the extensive semantic information, while the homophonic punny riddles induced a positive ERP deflection over the temporal cortex and a negative one in the left frontal cortex which might reflect the semantic and phonological information processing respectively. Our study indicated that different insight problem solving should have the same cognitive process of detecting cognitive conflicts, but have different ways to solve the conflicts.

  6. Determination of DPPH free radical scavenging activity: application of artificial neural networks.

    PubMed

    Musa, Khalid Hamid; Abdullah, Aminah; Al-Haiqi, Ahmed

    2016-03-01

    A new computational approach for the determination of 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity (DPPH-RSA) in food is reported, based on the concept of machine learning. Trolox standard was mix with DPPH at different concentrations to produce different colors from purple to yellow. Artificial neural network (ANN) was trained on a typical set of images of the DPPH radical reacting with different levels of Trolox. This allowed the neural network to classify future images of any sample into the correct class of RSA level. The ANN was then able to determine the DPPH-RSA of cinnamon, clove, mung bean, red bean, red rice, brown rice, black rice and tea extract and the results were compared with data obtained using a spectrophotometer. The application of ANN correlated well to the spectrophotometric classical procedure and thus do not require the use of spectrophotometer, and it could be used to obtain semi-quantitative results of DPPH-RSA.

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

    PubMed

    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.

  8. Neural activity tied to reading predicts individual differences in extended-text comprehension

    PubMed Central

    Mossbridge, Julia A.; Grabowecky, Marcia; Paller, Ken A.; Suzuki, Satoru

    2013-01-01

    Reading comprehension depends on neural processes supporting the access, understanding, and storage of words over time. Examinations of the neural activity correlated with reading have contributed to our understanding of reading comprehension, especially for the comprehension of sentences and short passages. However, the neural activity associated with comprehending an extended text is not well-understood. Here we describe a current-source-density (CSD) index that predicts individual differences in the comprehension of an extended text. The index is the difference in CSD-transformed event-related potentials (ERPs) to a target word between two conditions: a comprehension condition with words from a story presented in their original order, and a scrambled condition with the same words presented in a randomized order. In both conditions participants responded to the target word, and in the comprehension condition they also tried to follow the story in preparation for a comprehension test. We reasoned that the spatiotemporal pattern of difference-CSDs would reflect comprehension-related processes beyond word-level processing. We used a pattern-classification method to identify the component of the difference-CSDs that accurately (88%) discriminated good from poor comprehenders. The critical CSD index was focused at a frontal-midline scalp site, occurred 400–500 ms after target-word onset, and was strongly correlated with comprehension performance. Behavioral data indicated that group differences in effort or motor preparation could not explain these results. Further, our CSD index appears to be distinct from the well-known P300 and N400 components, and CSD transformation seems to be crucial for distinguishing good from poor comprehenders using our experimental paradigm. Once our CSD index is fully characterized, this neural signature of individual differences in extended-text comprehension may aid the diagnosis and remediation of reading comprehension deficits. PMID

  9. Long-term effects of axotomy on neural activity during cat locomotion.

    PubMed Central

    Gordon, T; Hoffer, J A; Jhamandas, J; Stein, R B

    1980-01-01

    1. Neural activity was recorded from cats during locomotion on a treadmill using electrodes in Silastic cuffs placed around the sciatic nerve and the lateral gastrocnemius-soleus, medial gastrocnemius, common peroneal and tibial nerve branches. Each branch gave characteristic patterns of activity which were studied before and after it was cut distal to the recording cuffs. Sensory and motor components were separated and measured using cross-correlation techniques. The amplitude of the cross-correlation peaks was compared with the amplitude of compound action potentials evoked by electrical stimulation and recorded from the same sites in the anaesthetized animal. 2. Sensory activity declined rapidly following axotomy and did not recover unless reinnervation occurred. Sensory activity even 5 months after nerve section and resuture had recovered to only a fraction of the control values. This reduction is attributed to a decline in the evoked compound potentials and to many fibres being unsuccessful in regenerating to appropriate sensory organs. 3. Motor activity declined more than could be accounted for by a decline in evoked potentials over the first month after axotomy. The extra reduction represents a decline in the number of impulses generated by alpha-motoneurones after axotomy. If regeneration was permitted, motor activity recovered to higher levels than did the evoked potentials for the whole nerve. Even if regeneration was prevented by nerve ligation, motoneurones continued to generate activity at a stable level over a period of months during which whole nerve compound potentials continued to decline. 4. The modulation of motor activity in ligated nerves during the step cycle was still appropriate to the required movement. Thus, activity recorded from severed nerves in human amputees may be useful in controlling powered artificial limbs. The persistence of motor activity may be responsible for the lesser degree of atrophy found in motor fibres than in sensory

  10. Perceptual Salience and Reward Both Influence Feedback-Related Neural Activity Arising from Choice

    PubMed Central

    Lou, Bin; Hsu, Wha-Yin

    2015-01-01

    expected reward. Here, we use electroencephelography to identify trial-by-trial neural activity of perceived stimulus salience, showing that this activity can be combined with the value of choice options to form a representation of expected reward. Our results provide insight into the neural processing governing the interaction between salience and value and the formation of subjective expected reward and prediction error. This work is potentially important for identifying neural markers of abnormal sensory/value processing, as is seen in some cases of psychiatric illnesses. PMID:26400937

  11. Sex-dependent modulation of activity in the neural networks engaged during emotional speech comprehension.

    PubMed

    Beaucousin, Virginie; Zago, Laure; Hervé, Pierre-Yves; Strelnikov, Kuzma; Crivello, Fabrice; Mazoyer, Bernard; Tzourio-Mazoyer, Nathalie

    2011-05-16

    Studies using event related potentials have shown that men are more likely than women to rely on semantic cues when understanding emotional speech. In a previous functional Magnetic Resonance Imaging (fMRI) study, using an affective sentence classification task, we were able to separate areas involved in semantic processing and areas involved in the processing of affective prosody (Beaucousin et al., 2007). Here we searched for sex-related differences in the neural networks active during emotional speech processing in groups of men and women. The ortholinguistic abilities of the participants did not differ when evaluated with a large battery of tests. Although the neural networks engaged by men and women during emotional sentence classification were largely overlapping, sex-dependent modulations were detected during emotional sentence classification, but not during grammatical sentence classification. Greater activity was observed in men, compared with women, in inferior frontal cortical areas involved in emotional labeling and in attentional areas. In conclusion, at equivalent linguistic abilities and performances, men activate semantic and attentional cortical areas to a larger extent than women during emotional speech processing.

  12. Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia

    NASA Astrophysics Data System (ADS)

    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.

  13. Trait Approach and Avoidance Motivation: Lateralized Neural Activity Associated with Executive Function

    PubMed Central

    Spielberg, Jeffrey M.; Miller, Gregory A.; Engels, Anna S.; Herrington, John D.; Sutton, Bradley P.; Banich, Marie T.; Heller, Wendy

    2010-01-01

    Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals. PMID:20728552

  14. Trait approach and avoidance motivation: lateralized neural activity associated with executive function.

    PubMed

    Spielberg, Jeffrey M; Miller, Gregory A; Engels, Anna S; Herrington, John D; Sutton, Bradley P; Banich, Marie T; Heller, Wendy

    2011-01-01

    Motivation and executive function are both necessary for the completion of goal-directed behavior. Research investigating the manner in which these processes interact is beginning to emerge and has implicated middle frontal gyrus (MFG) as a site of interaction for relevant neural mechanisms. However, this research has focused on state motivation, and it has not examined functional lateralization. The present study examined the impact of trait levels of approach and avoidance motivation on neural processes associated with executive function. Functional magnetic resonance imaging was conducted while participants performed a color-word Stroop task. Analyses identified brain regions in which trait approach and avoidance motivation (measured by questionnaires) moderated activation associated with executive control. Approach was hypothesized to be associated with left-lateralized MFG activation, whereas avoidance was hypothesized to be associated with right-lateralized MFG activation. Results supported both hypotheses. Present findings implicate areas of middle frontal gyrus in top-down control to guide behavior in accordance with motivational goals.

  15. Optical Recording of Suprathreshold Neural Activity with Single-cell and Single-spike Resolution

    PubMed Central

    Ranganathan, Gayathri Nattar; Koester, Helmut J.

    2012-01-01

    Signaling of information in the vertebrate central nervous system is often carried by populations of neurons rather than individual neurons. Also propagation of suprathreshold spiking activity involves populations of neurons. Empirical studies addressing cortical function directly thus require recordings from populations of neurons with high resolution. Here we describe an optical method and a deconvolution algorithm to record neural activity from up to 100 neurons with single-cell and single-spike resolution. This method relies on detection of the transient increases in intracellular somatic calcium concentration associated with suprathreshold electrical spikes (action potentials) in cortical neurons. High temporal resolution of the optical recordings is achieved by a fast random-access scanning technique using acousto-optical deflectors (AODs)1. Two-photon excitation of the calcium-sensitive dye results in high spatial resolution in opaque brain tissue2. Reconstruction of spikes from the fluorescence calcium recordings is achieved by a maximum-likelihood method. Simultaneous electrophysiological and optical recordings indicate that our method reliably detects spikes (>97% spike detection efficiency), has a low rate of false positive spike detection (< 0.003 spikes/sec), and a high temporal precision (about 3 msec) 3. This optical method of spike detection can be used to record neural activity in vitro and in anesthetized animals in vivo3,4. PMID:22972033

  16. Social exclusion in middle childhood: rejection events, slow-wave neural activity, and ostracism distress.

    PubMed

    Crowley, Michael J; Wu, Jia; Molfese, Peter J; Mayes, Linda C

    2010-01-01

    This study examined neural activity with event-related potentials (ERPs) in middle childhood during a computer-simulated ball-toss game, Cyberball. After experiencing fair play initially, children were ultimately excluded by the other players. We focused specifically on “not my turn” events within fair play and rejection events within social exclusion. Dense-array ERPs revealed that rejection events are perceived rapidly. Condition differences (“not my turn” vs. rejection) were evident in a posterior ERP peaking at 420 ms consistent, with a larger P3 effect for rejection events indicating that in middle childhood rejection events are differentiated in <500 ms. Condition differences were evident for slow-wave activity (500-900 ms) in the medial frontal cortical region and the posterior occipital-parietal region, with rejection events more negative frontally and more positive posteriorly. Distress from the rejection experience was associated with a more negative frontal slow wave and a larger late positive slow wave, but only for rejection events. Source modeling with Geosouce software suggested that slow-wave neural activity in cortical regions previously identified in functional imaging studies of ostracism, including subgenual cortex, ventral anterior cingulate cortex, and insula, was greater for rejection events vs. “not my turn” events.

  17. Artificial neural network based characterization of the volume of tissue activated during deep brain stimulation

    NASA Astrophysics Data System (ADS)

    Chaturvedi, Ashutosh; Luján, J. Luis; McIntyre, Cameron C.

    2013-10-01

    Objective. Clinical deep brain stimulation (DBS) systems can be programmed with thousands of different stimulation parameter combinations (e.g. electrode contact(s), voltage, pulse width, frequency). Our goal was to develop novel computational tools to characterize the effects of stimulation parameter adjustment for DBS. Approach. The volume of tissue activated (VTA) represents a metric used to estimate the spatial extent of DBS for a given parameter setting. Traditional methods for calculating the VTA rely on activation function (AF)-based approaches and tend to overestimate the neural response when stimulation is applied through multiple electrode contacts. Therefore, we created a new method for VTA calculation that relied on artificial neural networks (ANNs). Main results. The ANN-based predictor provides more accurate descriptions of the spatial spread of activation compared to AF-based approaches for monopolar stimulation. In addition, the ANN was able to accurately estimate the VTA in response to multi-contact electrode configurations. Significance. The ANN-based approach may represent a useful method for fast computation of the VTA in situations with limited computational resources, such as a clinical DBS programming application on a tablet computer.

  18. Neural Activities Underlying the Feedback Express Salience Prediction Errors for Appetitive and Aversive Stimuli

    PubMed Central

    Gu, Yan; Hu, Xueping; Pan, Weigang; Yang, Chun; Wang, Lijun; Li, Yiyuan; Chen, Antao

    2016-01-01

    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. PMID:27694920

  19. Anesthetic action on extra-synaptic receptors: effects in neural population models of EEG activity

    PubMed Central

    Hashemi, Meysam; Hutt, Axel; Sleigh, Jamie

    2014-01-01

    The role of extra-synaptic receptors in the regulation of excitation and inhibition in the brain has attracted increasing attention. Because activity in the extra-synaptic receptors plays a role in regulating the level of excitation and inhibition in the brain, they may be important in determining the level of consciousness. This paper reviews briefly the literature on extra-synaptic GABA and NMDA receptors and their affinity to anesthetic drugs. We propose a neural population model that illustrates how the effect of the anesthetic drug propofol on GABAergic extra-synaptic receptors results in changes in neural population activity and the electroencephalogram (EEG). Our results show that increased tonic inhibition in inhibitory cortical neurons cause a dramatic increase in the power of both δ− and α− bands. Conversely, the effects of increased tonic inhibition in cortical excitatory neurons and thalamic relay neurons have the opposite effect and decrease the power in these bands. The increased δ-activity is in accord with observed data for deepening propofol anesthesia; but is absolutely dependent on the inclusion of extrasynaptic (tonic) GABA action in the model. PMID:25540612

  20. Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity

    PubMed Central

    Waddington, Amelia; Appleby, Peter A.; De Kamps, Marc; Cohen, Netta

    2012-01-01

    Synfire chains have long been proposed to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been argued that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure. PMID:23162457

  1. Altered neural activity of magnitude estimation processing in adults with the fragile X premutation.

    PubMed

    Kim, So-Yeon; Hashimoto, Ryu-ichiro; Tassone, Flora; Simon, Tony J; Rivera, Susan M

    2013-12-01

    Mutations of the fragile X mental retardation 1 (FMR1) gene are the genetic cause of fragile X syndrome (FXS). Expanded CGG trinucleotide repeat (>200 repeats) result in transcriptional silencing of the FMR1 gene and deficiency/absence of the FMR1 protein (FMRP). Carriers with a premutation allele (55-200 CGG repeats) are often associated with mildly reduced levels of FMRP and/or elevated levels of FMR1 mRNA, and are associated with the risk of developing a neurodegenerative disorder known as fragile X-associated tremor/ataxia syndrome (FXTAS). While impairments in numerical processing have been well documented in FXS, recent behavioral research suggests that premutation carriers also present with subtle but significant impairments in numerical processing. Using fMRI, the current study examined whether asymptomatic adults with the premutation would show aberrant neural correlates of magnitude estimation processing in the fronto-parietal area. Using a magnitude estimation task, we demonstrated that activity in the intraparietal sulcus and inferior frontal gyrus, associated with magnitude estimation processing, was significantly attenuated in premutation carriers compared to their neurotypical counterparts despite their comparable behavioral performance. Further, multiple regression analysis using CGG repeat size and FMR1 mRNA indicated that increased CGG repeat size is a primary factor for the decreased fronto-parietal activity, suggesting that reduced FMRP, rather than a toxic gain-of-function effect from elevated mRNA, contributes to altered neural activity of magnitude estimation processing in premutation carriers. In conclusion, we provide the first evidence on the aberrant neural correlates of magnitude estimation processing in premutation carriers accounted for by their FMR1 gene expression.

  2. Neural activations are related to body-shape, anxiety, and outcomes in adolescent anorexia nervosa.

    PubMed

    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.

  3. Neural network versus activity-specific prediction equations for energy expenditure estimation in children.

    PubMed

    Ruch, Nicole; Joss, Franziska; Jimmy, Gerda; Melzer, Katarina; Hänggi, Johanna; Mäder, Urs

    2013-11-01

    The aim of this study was to compare the energy expenditure (EE) estimations of activity-specific prediction equations (ASPE) and of an artificial neural network (ANNEE) based on accelerometry with measured EE. Forty-three children (age: 9.8 ± 2.4 yr) performed eight different activities. They were equipped with one tri-axial accelerometer that collected data in 1-s epochs and a portable gas analyzer. The ASPE and the ANNEE were trained to estimate the EE by including accelerometry, age, gender, and weight of the participants. To provide the activity-specific information, a decision tree was trained to recognize the type of activity through accelerometer data. The ASPE were applied to the activity-type-specific data recognized by the tree (Tree-ASPE). The Tree-ASPE precisely estimated the EE of all activities except cycling [bias: -1.13 ± 1.33 metabolic equivalent (MET)] and walking (bias: 0.29 ± 0.64 MET; P < 0.05). The ANNEE overestimated the EE of stationary activities (bias: 0.31 ± 0.47 MET) and walking (bias: 0.61 ± 0.72 MET) and underestimated the EE of cycling (bias: -0.90 ± 1.18 MET; P < 0.05). Biases of EE in stationary activities (ANNEE: 0.31 ± 0.47 MET, Tree-ASPE: 0.08 ± 0.21 MET) and walking (ANNEE 0.61 ± 0.72 MET, Tree-ASPE: 0.29 ± 0.64 MET) were significantly smaller in the Tree-ASPE than in the ANNEE (P < 0.05). The Tree-ASPE was more precise in estimating the EE than the ANNEE. The use of activity-type-specific information for subsequent EE prediction equations might be a promising approach for future studies.

  4. Application of an artificial neural network for evaluation of activity concentration exemption limits in NORM industry.

    PubMed

    Wiedner, Hannah; Peyrés, Virginia; Crespo, Teresa; Mejuto, Marcos; García-Toraño, Eduardo; Maringer, Franz Josef

    2016-12-27

    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.

  5. Relations among pure-tone sound stimuli, neural activity, and the loudness sensation

    NASA Technical Reports Server (NTRS)

    Howes, W. L.

    1972-01-01

    Both the physiological and psychological responses to pure-tone sound stimuli are used to derive formulas which: (1) relate the loudness, loudness level, and sound-pressure level of pure tones; (2) apply continuously over most of the acoustic regime, including the loudness threshold; and (3) contain no undetermined coefficients. Some of the formulas are fundamental for calculating the loudness of any sound. Power-law formulas relating the pure-tone sound stimulus, neural activity, and loudness are derived from published data.

  6. Striatal Activity and Reward Relativity: Neural Signals Encoding Dynamic Outcome Valuation

    PubMed Central

    Webber, Emily S.; Mankin, David E.

    2016-01-01

    Abstract 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. PMID:27822506

  7. Striatal Activity and Reward Relativity: Neural Signals Encoding Dynamic Outcome Valuation.

    PubMed

    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.

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

    PubMed Central

    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

  9. A wearable sensor module with a neural-network-based activity classification algorithm for daily energy expenditure estimation.

    PubMed

    Lin, Che-Wei; Yang, Ya-Ting C; Wang, Jeen-Shing; Yang, Yi-Ching

    2012-09-01

    This paper presents a wearable module and neural-network-based activity classification algorithm for energy expenditure estimation. The purpose of our design is first to categorize physical activities with similar intensity levels, and then to construct energy expenditure regression (EER) models using neural networks in order to optimize the estimation performance. The classification of physical activities for EER model construction is based on the acceleration and ECG signal data collected by wearable sensor modules developed by our research lab. The proposed algorithm consists of procedures for data collection, data preprocessing, activity classification, feature selection, and construction of EER models using neural networks. In order to reduce the computational load and achieve satisfactory estimation performance, we employed sequential forward and backward search strategies for feature selection. Two representative neural networks, a radial basis function network (RBFN) and a generalized regression neural network (GRNN), were employed as EER models for performance comparisons. Our experimental results have successfully validated the effectiveness of our wearable sensor module and its neural-network-based activity classification algorithm for energy expenditure estimation. In addition, our results demonstrate the superior performance of GRNN as compared to RBFN.

  10. Quantitative modeling of the neural representation of objects: how semantic feature norms can account for fMRI activation.

    PubMed

    Chang, Kai-min Kevin; Mitchell, Tom; Just, Marcel Adam

    2011-05-15

    Recent multivariate analyses of fMRI activation have shown that discriminative classifiers such as Support Vector Machines (SVM) are capable of decoding fMRI-sensed neural states associated with the visual presentation of categories of various objects. However, the lack of a generative model of neural activity limits the generality of these discriminative classifiers for understanding the underlying neural representation. In this study, we propose a generative classifier that models the hidden factors that underpin the neural representation of objects, using a multivariate multiple linear regression model. The results indicate that object features derived from an independent behavioral feature norming study can explain a significant portion of the systematic variance in the neural activity observed in an object-contemplation task. Furthermore, the resulting regression model is useful for classifying a previously unseen neural activation vector, indicating that the distributed pattern of neural activities encodes sufficient signal to discriminate differences among stimuli. More importantly, there appears to be a double dissociation between the two classifier approaches and within- versus between-participants generalization. Whereas an SVM-based discriminative classifier achieves the best classification accuracy in within-participants analysis, the generative classifier outperforms an SVM-based model which does not utilize such intermediate representations in between-participants analysis. This pattern of results suggests the SVM-based classifier may be picking up some idiosyncratic patterns that do not generalize well across participants and that good generalization across participants may require broad, large-scale patterns that are used in our set of intermediate semantic features. Finally, this intermediate representation allows us to extrapolate the model of the neural activity to previously unseen words, which cannot be done with a discriminative classifier.

  11. Reiterative AP2a activity controls sequential steps in the neural crest gene regulatory network.

    PubMed

    de Crozé, Noémie; Maczkowiak, Frédérique; Monsoro-Burq, Anne H

    2011-01-04

    The neural crest (NC) emerges from combinatorial inductive events occurring within its progenitor domain, the neural border (NB). Several transcription factors act early at the NB, but the initiating molecular events remain elusive. Recent data from basal vertebrates suggest that ap2 might have been critical for NC emergence; however, the role of AP2 factors at the NB remains unclear. We show here that AP2a initiates NB patterning and is sufficient to elicit a NB-like pattern in neuralized ectoderm. In contrast, the other early regulators do not participate in ap2a initiation at the NB, but cooperate to further establish a robust NB pattern. The NC regulatory network uses a multistep cascade of secreted inducers and transcription factors, first at the NB and then within the NC progenitors. Here we report that AP2a acts at two distinct steps of this cascade. As the earliest known NB specifier, AP2a mediates Wnt signals to initiate the NB and activate pax3; as a NC specifier, AP2a regulates further NC development independent of and downstream of NB patterning. Our findings reconcile conflicting observations from various vertebrate organisms. AP2a provides a paradigm for the reiterated use of multifunctional molecules, thereby facilitating emergence of the NC in vertebrates.

  12. Out-of-sync: disrupted neural activity in emotional circuitry during film viewing in melancholic depression

    PubMed Central

    Guo, Christine C.; Nguyen, Vinh T.; Hyett, Matthew P.; Parker, Gordon B.; Breakspear, Michael J.

    2015-01-01

    While a rich body of research in controlled experiments has established changes in the neural circuitry of emotion in major depressive disorders, little is known as to how such alterations might translate into complex, naturalistic settings - namely involving dynamic multimodal stimuli with rich contexts, such as those provided by films. Neuroimaging paradigms employing dynamic natural stimuli alleviate the anxiety often associated with complex tasks and eschew the need for laboratory-style abstractions, hence providing an ecologically valid means of elucidating neural underpinnings of neuropsychiatric disorders. To probe the neurobiological signature of refined depression subtypes, we acquired functional neuroimaging data in patients with the melancholic subtype of major depressive disorder during free viewing of emotionally salient films. We found a marked disengagement of ventromedial prefrontal cortex during natural viewing of a film with negative emotional valence in patients with melancholia. This effect significantly correlated with depression severity. Such changes occurred on the background of diminished consistency of neural activity in visual and auditory sensory networks, as well as higher-order networks involved in emotion and attention, including bilateral intraparietal sulcus and right anterior insula. These findings may reflect a failure to re-allocate resources and diminished reactivity to external emotional stimuli in melancholia. PMID:26112251

  13. Mild blast events alter anxiety, memory, and neural activity patterns in the anterior cingulate cortex.

    PubMed

    Xie, Kun; Kuang, Hui; Tsien, Joe Z

    2013-01-01

    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.

  14. Reduction in Neural Performance following Recovery from Anoxic Stress Is Mimicked by AMPK Pathway Activation

    PubMed Central

    Money, Tomas G. A.; Sproule, Michael K. J.; Hamour, Amr F.; Robertson, R. Meldrum

    2014-01-01

    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. PMID:24533112

  15. Motivation alters response bias and neural activation patterns in a perceptual decision-making task.

    PubMed

    Reckless, G E; Bolstad, I; Nakstad, P H; Andreassen, O A; Jensen, J

    2013-05-15

    Motivation has been demonstrated to affect individuals' response strategies in economic decision-making, however, little is known about how motivation influences perceptual decision-making behavior or its related neural activity. Given the important role motivation plays in shaping our behavior, a better understanding of this relationship is needed. A block-design, continuous performance, perceptual decision-making task where participants were asked to detect a picture of an animal among distractors was used during functional magnetic resonance imaging (fMRI). The effect of positive and negative motivation on sustained activity within regions of the brain thought to underlie decision-making was examined by altering the monetary contingency associated with the task. In addition, signal detection theory was used to investigate the effect of motivation on detection sensitivity, response bias and response time. While both positive and negative motivation resulted in increased sustained activation in the ventral striatum, fusiform gyrus, left dorsolateral prefrontal cortex (DLPFC) and ventromedial prefrontal cortex, only negative motivation resulted in the adoption of a more liberal, closer to optimal response bias. This shift toward a liberal response bias correlated with increased activation in the left DLPFC, but did not result in improved task performance. The present findings suggest that motivation alters aspects of the way perceptual decisions are made. Further, this altered response behavior is reflected in a change in left DLPFC activation, a region involved in the computation of perceptual decisions.

  16. Chronic social stress in puberty alters appetitive male sexual behavior and neural metabolic activity.

    PubMed

    Bastida, Christel C; Puga, Frank; Gonzalez-Lima, Francisco; Jennings, Kimberly J; Wommack, Joel C; Delville, Yvon

    2014-07-01

    Repeated social subjugation in early puberty lowers testosterone levels. We used hamsters to investigate the effects of social subjugation on male sexual behavior and metabolic activity within neural systems controlling social and motivational behaviors. Subjugated animals were exposed daily to aggressive adult males in early puberty for postnatal days 28 to 42, while control animals were placed in empty clean cages. On postnatal day 45, they were tested for male sexual behavior in the presence of receptive female. Alternatively, they were tested for mate choice after placement at the base of a Y-maze containing a sexually receptive female in one tip of the maze and an ovariectomized one on the other. Social subjugation did not affect the capacity to mate with receptive females. Although control animals were fast to approach females and preferred ovariectomized individuals, subjugated animals stayed away from them and showed no preference. Cytochrome oxidase activity was reduced within the preoptic area and ventral tegmental area in subjugated hamsters. In addition, the correlation of metabolic activity of these areas with the bed nucleus of the stria terminalis and anterior parietal cortex changed significantly from positive in controls to negative in subjugated animals. These data show that at mid-puberty, while male hamsters are capable of mating, their appetitive sexual behavior is not fully mature and this aspect of male sexual behavior is responsive to social subjugation. Furthermore, metabolic activity and coordination of activity in brain areas related to sexual behavior and motivation were altered by social subjugation.

  17. Quantifying Time-Varying Multiunit Neural Activity Using Entropy-Based Measures

    PubMed Central

    Choi, Young-Seok; Koenig, Matthew A.; Jia, Xiaofeng

    2011-01-01

    Modern microelectrode arrays make it possible to simultaneously record population neural activity. However, methods to analyze multiunit activity (MUA), which reflects the aggregate spiking activity of a population of neurons, have remained underdeveloped in comparison to those used for studying single unit activity (SUA). In scenarios where SUA is hard to record and maintain or is not representative of brain’s response, MUA is informative in deciphering the brain’s complex time-varying response to stimuli or to clinical insults. Here, we present two quantitative methods of analysis of the time-varying dynamics of MUA without spike detection. These methods are based on the multiresolution discrete wavelet transform (DWT) of an envelope of MUA (eMUA) followed by information theoretic measures: multiresolution entropy (MRE) and the multiresolution Kullback–Leibler distance (MRKLD).We test the proposed quantifiers on both simulated and experimental MUA recorded from rodent cortex in an experimental model of global hypoxic–ischemic brain injury. First, our results validate the use of the eMUA as an alternative to detecting and analyzing transient and complex spike activity. Second, the MRE and MRKLD are shown to respond to dynamic changes due to the brain’s response to global injury and to identify the transient changes in the MUA. PMID:20460201

  18. CXCL12-mediated murine neural progenitor cell movement requires PI3Kβ activation.

    PubMed

    Holgado, Borja L; Martínez-Muñoz, Laura; Sánchez-Alcañiz, Juan Antonio; Lucas, Pilar; Pérez-García, Vicente; Pérez, Gema; Rodríguez-Frade, José Miguel; Nieto, Marta; Marín, Oscar; Carrasco, Yolanda R; Carrera, Ana C; Alvarez-Dolado, Manuel; Mellado, Mario

    2013-08-01

    The migratory route of neural progenitor/precursor cells (NPC) has a central role in central nervous system development. Although the role of the chemokine CXCL12 in NPC migration has been described, the intracellular signaling cascade involved remains largely unclear. Here we studied the molecular mechanisms that promote murine NPC migration in response to CXCL12, in vitro and ex vivo. Migration was highly dependent on signaling by the CXCL12 receptor, CXCR4. Although the JAK/STAT pathway was activated following CXCL12 stimulation of NPC, JAK activity was not necessary for NPC migration in vitro. Whereas CXCL12 activated the PI3K catalytic subunits p110α and p110β in NPC, only p110β participated in CXCL12-mediated NPC migration. Ex vivo experiments using organotypic slice cultures showed that p110β blockade impaired NPC exit from the medial ganglionic eminence. In vivo experiments using in utero electroporation nonetheless showed that p110β is dispensable for radial migration of pyramidal neurons. We conclude that PI3K p110β is activated in NPC in response to CXCL12, and its activity is necessary for immature interneuron migration to the cerebral cortex.

  19. Neural correlates of episodic memory: associative memory and confidence drive hippocampus activations.

    PubMed

    Kuchinke, Lars; Fritzemeier, Steffen; Hofmann, Markus J; Jacobs, Arthur M

    2013-10-01

    The present study used a study-test recognition memory task to examine the brain regions engaged in episodic and associative memory processes. Participants evaluated on a six-point rating scale how confident they were on whether or not an item was presented in a previous study phase. Neural activations for high- and low-confidence decisions were examined in old and new items at two levels of between-item-associations. Items had different amounts of associations within the stimulus set, while associations were defined by co-occurrence statistics. The medial frontal gyrus, the posterior cingulate gyrus, the superior temporal gyrus and the right hippocampus revealed U-shaped activation functions with greater activations for high-confidence OLD and NEW decisions. This was independent of the associative memory manipulation, which suggests that not episodic memory, but rather processes related to confidence account for the activation in these brain regions. In contrast, left hippocampus followed a different activation pattern that was modulated by the amount of associations. This provides evidence for the role of the left hippocampus in associative memory.

  20. A spinal opsin controls early neural activity and drives a behavioral light response

    PubMed Central

    Friedmann, Drew; Hoagland, Adam; Berlin, Shai; Isacoff, Ehud Y.

    2014-01-01

    Non-visual detection of light by the vertebrate hypothalamus, pineal, and retina is known to govern seasonal and circadian behaviors [1]. However, the expression of opsins in multiple other brain structures [2–4] suggests a more expansive repertoire for light-regulation of physiology, behavior, and development. Translucent zebrafish embryos express extra-retinal opsins early on [5, 6], at a time when spontaneous activity in the developing central nervous system plays a role in neuronal maturation and circuit formation [7]. Though the presence of extra-retinal opsins is well documented, the function of direct photoreception by the central nervous system remains largely unknown. Here we show that early activity in the zebrafish spinal central pattern generator (CPG) and the earliest locomotory behavior are dramatically inhibited by physiological levels of environmental light. We find that the photo-sensitivity of this circuit is conferred by vertebrate ancient long opsin (VALopA), which we show to be a Gαi-coupled receptor that is expressed in the neurons of the spinal network. Sustained photo-activation of VALopA not only suppresses spontaneous activity but also alters the maturation of time-locked correlated network patterns. These results uncover a novel role for non-visual opsins and a mechanism for environmental regulation of spontaneous motor behavior and neural activity in a circuit previously thought to be governed only by intrinsic developmental programs. PMID:25484291

  1. Individual Differences in Neural Activity During A Facial Expression vs. Identity Working Memory Task

    PubMed Central

    Neta, Maital; Whalen, Paul J.

    2011-01-01

    Facial expressions of emotion constitute a critical portion of our non-verbal social interactions. In addition, the identity of the individual displaying this expression is critical to these interactions as they embody the context in which these expressions will be interpreted. To identify any overlapping and/or unique brain circuitry involved in the processing of these two information streams in a laboratory setting, participants performed a working memory (WM) task (i.e., N-back) in which they were instructed to monitor either the expression (EMO) or the identity (ID) of the same set of face stimuli. Consistent with previous work, during both the EMO and ID tasks, we found a significant increase in activity in dorsolateral prefrontal cortex (DLPFC) supporting its generalized role in WM. Further, individuals that showed greater DLPFC activity during both tasks also showed increased amygdala activity during the EMO task and increased lateral fusiform gyrus activity during the ID task. Importantly, the level of activity in these regions significantly correlated with performance on the respective tasks. These findings provide support for two separate neural circuitries, both involving the DLPFC, supporting working memory for these two distinct aspects of face processing/memory. PMID:21349341

  2. Bayesian inference for neural electromagnetic source localization: analysis of MEG visual evoked activity

    NASA Astrophysics Data System (ADS)

    Schmidt, David M.; George, John S.; Wood, C. C.

    1999-05-01

    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 sampling 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 surface, within a sphere centered on some location in cortex. The number and radii 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.

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

    SciTech Connect

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

    PubMed

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

    2012-04-21

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

  5. Systemic Administration of Induced Neural Stem Cells Regulates Complement Activation in Mouse Closed Head Injury Models

    PubMed Central

    Gao, Mou; Dong, Qin; Yao, Hui; Lu, Yingzhou; Ji, Xinchao; Zou, Mingming; Yang, Zhijun; Xu, Minhui; Xu, Ruxiang

    2017-01-01

    Complement activation plays important roles in the pathogenesis of central nervous system (CNS) diseases. Patients face neurological disorders due to the development of complement activation, which contributes to cell apoptosis, brain edema, blood-brain barrier dysfunction and inflammatory infiltration. We previously reported that induced neural stem cells (iNSCs) can promote neurological functional recovery in closed head injury (CHI) animals. Remarkably, we discovered that local iNSC grafts have the potential to modulate CNS inflammation post-CHI. In this study, we aimed to explore the role of systemically delivered iNSCs in complement activation following CNS injury. Our data showed that iNSC grafts decreased the levels of sera C3a and C5a and down-regulated the expression of C3d, C9, active Caspase-3 and Bax in the brain, kidney and lung tissues of CHI mice. Furthermore, iNSC grafts decreased the levels of C3d+/NeuN+, C5b-9+/NeuN+, C3d+/Map2+ and C5b-9+/Map2+ neurons in the injured cortices of CHI mice. Subsequently, we explored the mechanisms underlying these effects. With flow cytometry analysis, we observed a dramatic increase in complement receptor type 1-related protein y (Crry) expression in iNSCs after CHI mouse serum treatment. Moreover, both in vitro and in vivo loss-of-function studies revealed that iNSCs could modulate complement activation via Crry expression. PMID:28383046

  6. Forecast and restoration of geomagnetic activity indices by using the software-computational neural network complex

    NASA Astrophysics Data System (ADS)

    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

  7. Differences between Neural Activity in Prefrontal Cortex and Striatum during Learning of Novel, Abstract Categories

    PubMed Central

    Antzoulatos, Evan G.; Miller, Earl K.

    2011-01-01

    Summary Learning to classify diverse experiences into meaningful groups, like categories, is fundamental to normal cognition. To understand its neural basis, we simultaneously recorded from multiple electrodes in the lateral prefrontal cortex and dorsal striatum, two interconnected brain structures critical for learning. Each day, monkeys learned to associate novel, abstract dot-based categories with a right vs. left saccade. Early on, when they could acquire specific stimulus-response associations, striatum activity was an earlier predictor of the corresponding saccade. However, as the number of exemplars was increasing, and monkeys had to learn to classify them, PFC began predicting the saccade associated with each category before the striatum. While monkeys were categorizing novel exemplars at a high rate, PFC activity was a strong predictor of their corresponding saccade early in the trial, before the striatal neurons. These results suggest that striatum plays a greater role in stimulus-response association and PFC in abstraction of categories. PMID:21791284

  8. Multistability of complex-valued neural networks with discontinuous activation functions.

    PubMed

    Liang, Jinling; Gong, Weiqiang; Huang, Tingwen

    2016-12-01

    In this paper, based on the geometrical properties of the discontinuous activation functions and the Brouwer's fixed point theory, the multistability issue is tackled for the complex-valued neural networks with discontinuous activation functions and time-varying delays. To address the network with discontinuous functions, Filippov solution of the system is defined. Through rigorous analysis, several sufficient criteria are obtained to assure the existence of 25(n) equilibrium points. Among them, 9(n) points are locally stable and 16(n)-9(n) equilibrium points are unstable. Furthermore, to enlarge the attraction basins of the 9(n) equilibrium points, some mild conditions are imposed. Finally, one numerical example is provided to illustrate the effectiveness of the obtained results.

  9. Rapid, parallel path planning by propagating wavefronts of spiking neural activity.

    PubMed

    Ponulak, Filip; Hopfield, John J

    2013-01-01

    Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware.

  10. Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)

    PubMed Central

    Myint, Kyaw Z.; Xie, Xiang-Qun

    2015-01-01

    This chapter focuses on the fingerprint-based artificial neural networks QSAR (FANN-QSAR) approach to predict biological activities of structurally diverse compounds. Three types of fingerprints, namely ECFP6, FP2, and MACCS, were used as inputs to train the FANN-QSAR models. The results were benchmarked against known 2D and 3D QSAR methods, and the derived models were used to predict cannabinoid (CB) ligand binding activities as a case study. In addition, the FANN-QSAR model was used as a virtual screening tool to search a large NCI compound database for lead cannabinoid compounds. We discovered several compounds with good CB2 binding affinities ranging from 6.70 nM to 3.75 μM. The studies proved that the FANN-QSAR method is a useful approach to predict bioactivities or properties of ligands and to find novel lead compounds for drug discovery research. PMID:25502380

  11. Rapid, parallel path planning by propagating wavefronts of spiking neural activity

    PubMed Central

    Ponulak, Filip; Hopfield, John J.

    2013-01-01

    Efficient path planning and navigation is critical for animals, robotics, logistics and transportation. We study a model in which spatial navigation problems can rapidly be solved in the brain by parallel mental exploration of alternative routes using propagating waves of neural activity. A wave of spiking activity propagates through a hippocampus-like network, altering the synaptic connectivity. The resulting vector field of synaptic change then guides a simulated animal to the appropriate selected target locations. We demonstrate that the navigation problem can be solved using realistic, local synaptic plasticity rules during a single passage of a wavefront. Our model can find optimal solutions for competing possible targets or learn and navigate in multiple environments. The model provides a hypothesis on the possible computational mechanisms for optimal path planning in the brain, at the same time it is useful for neuromorphic implementations, where the parallelism of information processing proposed here can fully be harnessed in hardware. PMID:23882213

  12. Multistability of second-order competitive neural networks with nondecreasing saturated activation functions.

    PubMed

    Nie, Xiaobing; Cao, Jinde

    2011-11-01

    In this paper, second-order interactions are introduced into competitive neural networks (NNs) and the multistability is discussed for second-order competitive NNs (SOCNNs) with nondecreasing saturated activation functions. Firstly, based on decomposition of state space, Cauchy convergence principle, and inequality technique, some sufficient conditions ensuring the local exponential stability of 2N equilibrium points are derived. Secondly, some conditions are obtained for ascertaining equilibrium points to be locally exponentially stable and to be located in any designated region. Thirdly, the theory is extended to more general saturated activation functions with 2r corner points and a sufficient criterion is given under which the SOCNNs can have (r+1)N locally exponentially stable equilibrium points. Even if there is no second-order interactions, the obtained results are less restrictive than those in some recent works. Finally, three examples with their simulations are presented to verify the theoretical analysis.

  13. Phase locked neural activity in the human brainstem predicts preference for musical consonance

    PubMed Central

    Bones, Oliver; Hopkins, Kathryn; Krishnan, Ananthanarayan; Plack, Christopher J.

    2014-01-01

    When musical notes are combined to make a chord, the closeness of fit of the combined spectrum to a single harmonic series (the ‘harmonicity’ of the chord) predicts the perceived consonance (how pleasant and stable the chord sounds; McDermott, Lehr, & Oxenham, 2010). The distinction between consonance and dissonance is central to Western musical form. Harmonicity is represented in the temporal firing patterns of populations of brainstem neurons. The current study investigates the role of brainstem temporal coding of harmonicity in the perception of consonance. Individual preference for consonant over dissonant chords was measured using a rating scale for pairs of simultaneous notes. In order to investigate the effects of cochlear interactions, notes were presented in two ways: both notes to both ears or each note to different ears. The electrophysiological frequency following response (FFR), reflecting sustained neural activity in the brainstem synchronised to the stimulus, was also measured. When both notes were presented to both ears the perceptual distinction between consonant and dissonant chords was stronger than when the notes were presented to different ears. In the condition in which both notes were presented to the both ears additional low-frequency components, corresponding to difference tones resulting from nonlinear cochlear processing, were observable in the FFR effectively enhancing the neural harmonicity of consonant chords but not dissonant chords. Suppressing the cochlear envelope component of the FFR also suppressed the additional frequency components. This suggests that, in the case of consonant chords, difference tones generated by interactions between notes in the cochlea enhance the perception of consonance. Furthermore, individuals with a greater distinction between consonant and dissonant chords in the FFR to individual harmonics had a stronger preference for consonant over dissonant chords. Overall, the results provide compelling

  14. Phase locked neural activity in the human brainstem predicts preference for musical consonance.

    PubMed

    Bones, Oliver; Hopkins, Kathryn; Krishnan, Ananthanarayan; Plack, Christopher J

    2014-05-01

    When musical notes are combined to make a chord, the closeness of fit of the combined spectrum to a single harmonic series (the 'harmonicity' of the chord) predicts the perceived consonance (how pleasant and stable the chord sounds; McDermott, Lehr, & Oxenham, 2010). The distinction between consonance and dissonance is central to Western musical form. Harmonicity is represented in the temporal firing patterns of populations of brainstem neurons. The current study investigates the role of brainstem temporal coding of harmonicity in the perception of consonance. Individual preference for consonant over dissonant chords was measured using a rating scale for pairs of simultaneous notes. In order to investigate the effects of cochlear interactions, notes were presented in two ways: both notes to both ears or each note to different ears. The electrophysiological frequency following response (FFR), reflecting sustained neural activity in the brainstem synchronised to the stimulus, was also measured. When both notes were presented to both ears the perceptual distinction between consonant and dissonant chords was stronger than when the notes were presented to different ears. In the condition in which both notes were presented to the both ears additional low-frequency components, corresponding to difference tones resulting from nonlinear cochlear processing, were observable in the FFR effectively enhancing the neural harmonicity of consonant chords but not dissonant chords. Suppressing the cochlear envelope component of the FFR also suppressed the additional frequency components. This suggests that, in the case of consonant chords, difference tones generated by interactions between notes in the cochlea enhance the perception of consonance. Furthermore, individuals with a greater distinction between consonant and dissonant chords in the FFR to individual harmonics had a stronger preference for consonant over dissonant chords. Overall, the results provide compelling evidence

  15. Dissociation between Neural Signatures of Stimulus and Choice in Population Activity of Human V1 during Perceptual Decision-Making

    PubMed Central

    Choe, Kyoung Whan; Blake, Randolph

    2014-01-01

    Primary visual cortex (V1) forms the initial cortical representation of objects and events in our visual environment, and it distributes information about that representation to higher cortical areas within the visual hierarchy. Decades of work have established tight linkages between neural activity occurring in V1 and features comprising the retinal image, but it remains debatable how that activity relates to perceptual decisions. An actively debated question is the extent to which V1 responses determine, on a trial-by-trial basis, perceptual choices made by observers. By inspecting the population activity of V1 from human observers engaged in a difficult visual discrimination task, we tested one essential prediction of the deterministic view: choice-related activity, if it exists in V1, and stimulus-related activity should occur in the same neural ensemble of neurons at the same time. Our findings do not support this prediction: while cortical activity signifying the variability in choice behavior was indeed found in V1, that activity was dissociated from activity representing stimulus differences relevant to the task, being advanced in time and carried by a different neural ensemble. The spatiotemporal dynamics of population responses suggest that short-term priors, perhaps formed in higher cortical areas involved in perceptual inference, act to modulate V1 activity prior to stimulus onset without modifying subsequent activity that actually represents stimulus features within V1. PMID:24523561

  16. Phospholipase B activity and organophosphorus compound toxicity in cultured neural cells

    SciTech Connect

    Read, David J.; Langford, Lynda; Barbour, Helen R.; Forshaw, Philip J.; Glynn, Paul . E-mail: pg8@le.ac.uk

    2007-03-15

    Organophosphorus compounds (OP) such as phenyl saligenin phosphate (PSP) and mipafox (MPX) which cause delayed neuropathy, inhibit neuropathy target esterase (NTE), while OPs such as paraoxon (PXN) react more readily with acetylcholinesterase. In yeast and mammalian cell lines, NTE has been shown to have phospholipase B (PLB) activity which deacylates intracellular phosphatidylcholine to glycerophosphocholine (GroPCho) and can be detected by metabolic labeling with [{sup 14}C]choline. Here we investigated PLB activity in primary cultures of mouse neural cells. In cortical and cerebellar granule neurons and astrocytes, [{sup 14}C]GroPCho labeling was inhibited by PSP and MPX: phenyl dipentylphosphinate (PDPP), a non-neuropathic NTE inhibitor, was more potent, while PXN, was substantially less so. In all three cell types, conversion of [{sup 14}C]phosphatidylcholine to [{sup 14}C]GroPCho over 24 h was relatively small (2.3-14%). Consequently, even with > 80% inhibition of [{sup 14}C]GroPCho production, increased [{sup 14}C]phosphatidylcholine was not detected. At concentrations of 1-10 {mu}M, only PSP was cytotoxic to cortical and cerebellar granule neurons after 24-h exposure. Moreover, dramatic changes in glial cell morphology were induced by PSP, but not PDPP or MPX, with rapid (2-3 h) rounding up of astrocytes and of Schwann cells in cultures of dissociated mouse dorsal root ganglia. We conclude that PLB activity is present in a variety of cultured mouse neural cell types but that acute loss of this activity is not cytotoxic. Conversely, the rapid toxic effects of PSP in vitro suggest that a serine hydrolase distinct from NTE is required continuously by neurons and glia.

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

    PubMed Central

    Doll, Caleb A.; Broadie, Kendal

    2014-01-01

    Early-use activity during circuit-specific critical periods refines brain circuitry by the coupled processes of eliminating inappropriate synapses and strengthening maintained synapses. We theorize these activity-dependent (A-D) developmental processes are specifically impaired in autism spectrum disorders (ASDs). ASD genetic models in both mouse and Drosophila have pioneered our insights into normal A-D 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 A-D 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 A-D 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 A-D 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 A-D mechanisms in normal versus ASD brain development, particularly utilizing the well-established Drosophila FXS disease model. PMID:24570656

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

    PubMed Central

    Aue, Tatjana; Hoeppli, Marie-Eve; Piguet, Camille; Sterpenich, Virginie; Vuilleumier, Patrik

    2013-01-01

    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. PMID:23754994

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

    PubMed Central

    Allen, Micah; Dietz, Martin; Blair, Karina S.; van Beek, Martijn; Rees, Geraint; Vestergaard-Poulsen, Peter; Lutz, Antoine; Roepstorff, Andreas

    2015-01-01

    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 on attention through interoceptive salience and attentional control mechanisms, but until now conflicting evidence from behavioral and neural measures has made it difficult to distinguish the role of these mechanisms. To resolve this question we conducted a fully randomized 6-week longitudinal trial of MT, explicitly controlling for cognitive and treatment effects with an active control group. We measured behavioral metacognition and whole-brain Blood Oxygenation Level Dependent (BOLD) signals using functional MRI during an affective Stroop task before and after intervention. Although both groups improved significantly on a response-inhibition task, only the MT group showed reduced affective Stroop conflict. Moreover, the MT group displayed greater dorsolateral prefrontal cortex (DLPFC) responses during executive processing, consistent with increased recruitment of top-down mechanisms to resolve conflict. In contrast, we did not observe overall group by time interactions on negative affect-related RTs or BOLD responses. However, only participants with the greatest amount of MT practice showed improvements in response-inhibition and increased recruitment of dorsal anterior cingulate cortex (dACC), medial prefrontal cortex (mPFC), and right anterior insula during negative valence processing. Collectively our findings highlight the importance of active control in MT research, and indicate unique neural mechanisms for progressive stages of mindfulness training. PMID:23115195

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

    PubMed

    Allen, Micah; Dietz, Martin; Blair, Karina S; van Beek, Martijn; Rees, Geraint; Vestergaard-Poulsen, Peter; Lutz, Antoine; Roepstorff, Andreas

    2012-10-31

    Mindfulness meditation is a set of attention-based, regulatory, and self-inquiry training regimes. Although the impact of mindfulness training (MT) on self-regulation is well established, the neural mechanisms supporting such plasticity are poorly understood. MT is thought to act through interoceptive salience and attentional control mechanisms, but until now conflicting evidence from behavioral and neural measures renders difficult distinguishing their respective roles. To resolve this question we conducted a fully randomized 6 week longitudinal trial of MT, explicitly controlling for cognitive and treatment effects with an active-control group. We measured behavioral metacognition and whole-brain blood oxygenation level-dependent (BOLD) signals using functional MRI during an affective Stroop task before and after intervention in healthy human subjects. Although both groups improved significantly on a response-inhibition task, only the MT group showed reduced affective Stroop conflict. Moreover, the MT group displayed greater dorsolateral prefrontal cortex responses during executive processing, consistent with increased recruitment of top-down mechanisms to resolve conflict. In contrast, we did not observe overall group-by-time interactions on negative affect-related reaction times or BOLD responses. However, only participants with the greatest amount of MT practice showed improvements in response inhibition and increased recruitment of dorsal anterior cingulate cortex, medial prefrontal cortex, 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 on context, contrary to a one-size-fits-all approach.

  1. Non-invasive imaging of neuroanatomical structures and neural activation with high-resolution MRI.

    PubMed

    Herberholz, Jens; Mishra, Subrata H; Uma, Divya; Germann, Markus W; Edwards, Donald H; Potter, Kimberlee

    2011-01-01

    Several years ago, manganese-enhanced magnetic resonance imaging (MEMRI) was introduced as a new powerful tool to image active brain areas and to identify neural connections in living, non-human animals. Primarily restricted to studies in rodents and later adapted for bird species, MEMRI has recently been discovered as a useful technique for neuroimaging of invertebrate animals. Using crayfish as a model system, we highlight the advantages of MEMRI over conventional techniques for imaging of small nervous systems. MEMRI can be applied to image invertebrate nervous systems at relatively high spatial resolution, and permits identification of stimulus-evoked neural activation non-invasively. Since the selection of specific imaging parameters is critical for successful in vivo micro-imaging, we present an overview of different experimental conditions that are best suited for invertebrates. We also compare the effects of hardware and software specifications on image quality, and provide detailed descriptions of the steps necessary to prepare animals for successful imaging sessions. Careful consideration of hardware, software, experiments, and specimen preparation will promote a better understanding of this novel technique and facilitate future MEMRI studies in other laboratories.

  2. Inca: a novel p21-activated kinase-associated protein required for cranial neural crest development.

    PubMed

    Luo, Ting; Xu, Yanhua; Hoffman, Trevor L; Zhang, Tailin; Schilling, Thomas; Sargent, Thomas D

    2007-04-01

    Inca (induced in neural crest by AP2) is a novel protein discovered in a microarray screen for genes that are upregulated in Xenopus embryos by the transcriptional activator protein Tfap2a. It has no significant similarity to any known protein, but is conserved among vertebrates. In Xenopus, zebrafish and mouse embryos, Inca is expressed predominantly in the premigratory and migrating neural crest (NC). Knockdown experiments in frog and fish using antisense morpholinos reveal essential functions for Inca in a subset of NC cells that form craniofacial cartilage. Cells lacking Inca migrate successfully but fail to condense into skeletal primordia. Overexpression of Inca disrupts cortical actin and prevents formation of actin "purse strings", which are required for wound healing in Xenopus embryos. We show that Inca physically interacts with p21-activated kinase 5 (PAK5), a known regulator of the actin cytoskeleton that is co-expressed with Inca in embryonic ectoderm, including in the NC. These results suggest that Inca and PAK5 cooperate in restructuring cytoskeletal organization and in the regulation of cell adhesion in the early embryo and in NC cells during craniofacial development.

  3. Patterns of neural circuit activation and behavior during dominance hierarchy formation in freely behaving crayfish.

    PubMed

    Herberholz, J; Issa, F A; Edwards, D H

    2001-04-15

    Creation of a dominance hierarchy within a population of animals typically involves a period of agonistic activity in which winning and losing decide relative positions in the hierarchy. Among crayfish, fighting between size-matched animals leads to an abrupt change of behavior as the new subordinate retreats and escapes from the attacks and approaches of the dominant (Issa et al., 1999). We used high-speed videography and electrical recordings of aquarium field potentials to monitor the release of aggressive and defensive behavior, including the activation of neural circuits for four different tail-flip behaviors. We found that the sequence of tail-flip circuit excitation traced the development of their dominance hierarchy. Offensive tail flipping, attacks, and approaches by both animals were followed by a sharp rise in the frequency of nongiant and medial giant escape tail flips and a fall in the frequency of offensive tail flips of the new subordinate. These changes suggest that sudden, coordinated changes in the excitability of a set of neural circuits in one animal produce the changes in behavior that mark its transition to subordinate status.

  4. Human facial neural activities and gesture recognition for machine-interfacing applications.

    PubMed

    Hamedi, M; Salleh, Sh-Hussain; Tan, T S; Ismail, K; Ali, J; Dee-Uam, C; Pavaganun, C; Yupapin, P P

    2011-01-01

    The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human-machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2-11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers.

  5. Perceived moral traits of others differentiate the neural activation that underlies inequity-aversion

    PubMed Central

    Nakatani, Hironori; Ogawa, Akitoshi; Suzuki, Chisato; Asamizuya, Takeshi; Ueno, Kenichi; Cheng, Kang; Okanoya, Kazuo

    2017-01-01

    We have a social preference to reduce inequity in the outcomes between oneself and others. Such a preference varies according to others. We performed functional magnetic resonance imaging during an economic game to investigate how the perceived moral traits of others modulate the neural activities that underlie inequity-aversion. The participants unilaterally allocated money to three partners (good, neutral, and bad). During presentation of the good and neutral partners, the anterior region of the rostral medial frontal cortex (arMFC) showed increased functional connectivity with the caudate head and the anterior insula, respectively. Following this, participants allocated more money to the good partner, and less to the bad partner, compared with the neutral partner. The caudate head and anterior insula showed greater activation during fair allocation to the good and unfair allocation to the neutral partners, respectively. However, these regions were silent during allocations to the bad partner. Therefore, the arMFC-caudate/insula circuit encompasses distinct neural processes that underlie inequity-aversion in monetary allocations that the different moral traits of others can modulate. PMID:28230155

  6. Trait self-esteem and neural activities related to self-evaluation and social feedback

    PubMed Central

    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

  7. Deep brain optical measurements of cell type-specific neural activity in behaving mice.

    PubMed

    Cui, Guohong; Jun, Sang Beom; Jin, Xin; Luo, Guoxiang; Pham, Michael D; Lovinger, David M; Vogel, Steven S; Costa, Rui M

    2014-01-01

    Recent advances in genetically encoded fluorescent sensors enable the monitoring of cellular events from genetically defined groups of neurons in vivo. In this protocol, we describe how to use a time-correlated single-photon counting (TCSPC)-based fiber optics system to measure the intensity, emission spectra and lifetime of fluorescent biosensors expressed in deep brain structures in freely moving mice. When combined with Cre-dependent selective expression of genetically encoded Ca(2+) indicators (GECIs), this system can be used to measure the average neural activity from a specific population of cells in mice performing complex behavioral tasks. As an example, we used viral expression of GCaMPs in striatal projection neurons (SPNs) and recorded the fluorescence changes associated with calcium spikes from mice performing a lever-pressing operant task. The whole procedure, consisting of virus injection, behavior training and optical recording, takes 3-4 weeks to complete. With minor adaptations, this protocol can also be applied to recording cellular events from other cell types in deep brain regions, such as dopaminergic neurons in the ventral tegmental area. The simultaneously recorded fluorescence signals and behavior events can be used to explore the relationship between the neural activity of specific brain circuits and behavior.

  8. Human facial neural activities and gesture recognition for machine-interfacing applications

    PubMed Central

    Hamedi, M; Salleh, Sh-Hussain; Tan, TS; Ismail, K; Ali, J; Dee-Uam, C; Pavaganun, C; Yupapin, PP

    2011-01-01

    The authors present a new method of recognizing different human facial gestures through their neural activities and muscle movements, which can be used in machine-interfacing applications. Human–machine interface (HMI) technology utilizes human neural activities as input controllers for the machine. Recently, much work has been done on the specific application of facial electromyography (EMG)-based HMI, which have used limited and fixed numbers of facial gestures. In this work, a multipurpose interface is suggested that can support 2–11 control commands that can be applied to various HMI systems. The significance of this work is finding the most accurate facial gestures for any application with a maximum of eleven control commands. Eleven facial gesture EMGs are recorded from ten volunteers. Detected EMGs are passed through a band-pass filter and root mean square features are extracted. Various combinations of gestures with a different number of gestures in each group are made from the existing facial gestures. Finally, all combinations are trained and classified by a Fuzzy c-means classifier. In conclusion, combinations with the highest recognition accuracy in each group are chosen. An average accuracy >90% of chosen combinations proved their ability to be used as command controllers. PMID:22267930

  9. BDNFval66met affects neural activation pattern during fear conditioning and 24 h delayed fear recall

    PubMed Central

    Golkar, Armita; Lindström, Kara M.; Haaker, Jan; Öhman, Arne; Schalling, Martin; Ingvar, Martin

    2015-01-01

    Brain-derived neurotrophic factor (BDNF), the most abundant neutrophin in the mammalian central nervous system, is critically involved in synaptic plasticity. In both rodents and humans, BDNF has been implicated in hippocampus- and amygdala-dependent learning and memory and has more recently been linked to fear extinction processes. Fifty-nine healthy participants, genotyped for the functional BDNFval66met polymorphism, underwent a fear conditioning and 24h-delayed extinction protocol while skin conductance and blood oxygenation level dependent (BOLD) responses (functional magnetic resonance imaging) were acquired. We present the first report of neural activation pattern during fear acquisition ‘and’ extinction for the BDNFval66met polymorphism using a differential conditioned stimulus (CS)+ > CS− comparison. During conditioning, we observed heightened allele dose-dependent responses in the amygdala and reduced responses in the subgenual anterior cingulate cortex in BDNFval66met met-carriers. During early extinction, 24h later, we again observed heightened responses in several regions ascribed to the fear network in met-carriers as opposed to val-carriers (insula, amygdala, hippocampus), which likely reflects fear memory recall. No differences were observed during late extinction, which likely reflects learned extinction. Our data thus support previous associations of the BDNFval66met polymorphism with neural activation in the fear and extinction network, but speak against a specific association with fear extinction processes. PMID:25103087

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

    PubMed Central

    Hu, Man-Li; Qiu, Zheng-Ying

    2016-01-01

    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. PMID:27429635

  11. Patterns of Longitudinal Neural Activity Linked to Different Cognitive Profiles in Parkinson's Disease

    PubMed Central

    Nagano-Saito, Atsuko; Al-Azzawi, Mohamed S.; Hanganu, Alexandru; Degroot, Clotilde; Mejia-Constain, Béatriz; Bedetti, Christophe; Lafontaine, Anne-Louise; Soland, Valérie; Chouinard, Sylvain; Monchi, Oury

    2016-01-01

    Mild cognitive impairment in Parkinson's disease (PD) has been linked with functional brain changes. Previously, using functional magnetic resonance imaging (fMRI), we reported reduced cortico-striatal activity in patients with PD who also had mild cognitive impairment (MCI) vs. those who did not (non-MCI). We followed up these patients to investigate the longitudinal effect on the neural activity. Twenty-four non-demented patients with Parkinson's disease (non-MCI: 12, MCI: 12) were included in the study. Each participant underwent two fMRIs while performing the Wisconsin Card Sorting Task 20 months apart. The non-MCI patients recruited the usual cognitive corticostriatal loop at the first and second sessions (Time 1 and Time 2, respectively). However, decreased activity was observed in the cerebellum and occipital area and increased activity was observed in the medial prefrontal cortex and parietal lobe during planning set-shift at Time 2. Increased activity in the precuneus was also demonstrated while executing set-shifts at Time 2. The MCI patients revealed more activity in the frontal, parietal and occipital lobes during planning set-shifts, and in the parietal and occipital lobes, precuneus, and cerebellum, during executing set-shift at Time 2. Analysis regrouping of both groups of PD patients revealed that hippocampal and thalamic activity at Time 1 was associated with less cognitive decline over time. Our results reveal that functional alteration along the time-points differed between the non-MCI and MCI patients. They also underline the importance of preserving thalamic and hippocampal function with respect to cognitive decline over time. PMID:27932974

  12. Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks.

    PubMed

    Park, Jinhee; Javier, Rios Jesus; Moon, Taesup; Kim, Youngwook

    2016-11-24

    Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN) directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost.

  13. Effects of negative air ions on activity of neural substrates involved in autonomic regulation in rats

    NASA Astrophysics Data System (ADS)

    Suzuki, Satoko; Yanagita, Shinya; Amemiya, Seiichiro; Kato, Yumi; Kubota, Natsuko; Ryushi, Tomoo; Kita, Ichiro

    2008-07-01

    The neural mechanism by which negative air ions (NAI) mediate the regulation of autonomic nervous system activity is still unknown. We examined the effects of NAI on physiological responses, such as blood pressure (BP), heart rate (HR), and heart rate variability (HRV) as well as neuronal activity, in the paraventricular nucleus of the hypothalamus (PVN), locus coeruleus (LC), nucleus ambiguus (NA), and nucleus of the solitary tract (NTS) with c-Fos immunohistochemistry in anesthetized, spontaneously breathing rats. In addition, we performed cervical vagotomy to reveal the afferent pathway involved in mediating the effects of NAI on autonomic regulation. NAI significantly decreased BP and HR, and increased HF power of the HRV spectrum. Significant decreases in c-Fos positive nuclei in the PVN and LC, and enhancement of c-Fos expression in the NA and NTS were induced by NAI. After vagotomy, these physiological and neuronal responses to NAI were not observed. These findings suggest that NAI can modulate autonomic regulation through inhibition of neuronal activity in PVN and LC as well as activation of NA neurons, and that these effects of NAI might be mediated via the vagus nerves.

  14. Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks

    PubMed Central

    Park, Jinhee; Javier, Rios Jesus; Moon, Taesup; Kim, Youngwook

    2016-01-01

    Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on water using radar has not been extensively studied, unlike the case on dry ground, due to its unique challenge. Namely, not only is the radar cross section of a human on water small, but the micro-Doppler signatures are much noisier due to water drops and waves. In this paper, we first investigate whether discriminative signatures could be obtained for activities on water through a simulation study. Then, we show how we can effectively achieve high classification accuracy by applying deep convolutional neural networks (DCNN) directly to the spectrogram of real measurement data. From the five-fold cross-validation on our dataset, which consists of five aquatic activities, we report that the conventional feature-based scheme only achieves an accuracy of 45.1%. In contrast, the DCNN trained using only the collected data attains 66.7%, and the transfer learned DCNN, which takes a DCNN pre-trained on a RGB image dataset and fine-tunes the parameters using the collected data, achieves a much higher 80.3%, which is a significant performance boost. PMID:27886151

  15. Reward expectancy-related prefrontal neuronal activities: are they neural substrates of "affective" working memory?

    PubMed

    Watanabe, Masataka; Hikosaka, Kazuo; Sakagami, Masamichi; Shirakawa, Shu-ichiro

    2007-01-01

    Primate prefrontal delay neurons are involved in retaining task-relevant cognitive information in working memory (WM). Recent studies have also revealed primate prefrontal delay neurons that are related to reward/omission-of-reward expectancy. Such reward-related delay activities might constitute "affective WM" (Davidson, 2002). "Affective" and "cognitive" WM are both concerned with representing not what is currently being presented, but rather what was presented previously or might be presented in the future. However, according to the original and widely accepted definition, WM is the "temporary storage and manipulation of information for complex cognitive tasks". Reward/omission-of-reward expectancy-related neuronal activity is neither prerequisite nor essential for accurate task performance; thus, such activity is not considered to comprise the neural substrates of WM. Also, "affective WM" might not be an appropriate usage of the term "WM". We propose that WM- and reward/omission-of-reward expectancy-related neuronal activity are concerned with representing which response should be performed in order to attain a goal (reward) and the goal of the response, respectively. We further suggest that the prefrontal cortex (PFC) plays a crucial role in the integration of cognitive (for example, WM-related) and motivational (for example, reward expectancy-related) operations for goal-directed behaviour. The PFC could then send this integrated information to other brain areas to control the behaviour.

  16. Relationship between neural activation and electric field distribution during deep brain stimulation.

    PubMed

    Åström, Mattias; Diczfalusy, Elin; Martens, Hubert; Wårdell, Karin

    2015-02-01

    Models and simulations are commonly used to study deep brain stimulation (DBS). Simulated stimulation fields are often defined and visualized by electric field isolevels or volumes of tissue activated (VTA). The aim of the present study was to evaluate the relationship between stimulation field strength as defined by the electric potential V, the electric field E, and the divergence of the electric field ∇(2) V, and neural activation. Axon cable models were developed and coupled to finite-element DBS models in three-dimensional (3-D). Field thresholds ( VT , ET, and ∇(2) VT ) were derived at the location of activation for various stimulation amplitudes (1 to 5 V), pulse widths (30 to 120 μs), and axon diameters (2.0 to 7.5 μm). Results showed that thresholds for VT and ∇(2) VT were highly dependent on the stimulation amplitude while ET were approximately independent of the amplitude for large axons. The activation field strength thresholds presented in this study may be used in future studies to approximate the VTA during model-based investigations of DBS without the need of computational axon models.

  17. Classification of human activity on water through micro-Dopplers using deep convolutional neural networks

    NASA Astrophysics Data System (ADS)

    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. Neural stem cells secrete factors facilitating brain regeneration upon constitutive Raf-Erk activation

    PubMed Central

    Rhee, Yong-Hee; Yi, Sang-Hoon; Kim, Joo Yeon; Chang, Mi-Yoon; Jo, A-Young; Kim, Jinyoung; Park, Chang-Hwan; Cho, Je-Yoel; Choi, Young-Jin; Sun, Woong; Lee, Sang-Hun

    2016-01-01

    The intracellular Raf-Erk signaling pathway is activated during neural stem cell (NSC) proliferation, and neuronal and astrocytic differentiation. A key question is how this signal can evoke multiple and even opposing NSC behaviors. We show here, using a constitutively active Raf (ca-Raf), that Raf-Erk activation in NSCs induces neuronal differentiation in a cell-autonomous manner. By contrast, it causes NSC proliferation and the formation of astrocytes in an extrinsic autocrine/paracrine manner. Thus, treatment of NSCs with medium (CM) conditioned in ca-Raf-transduced NSCs (Raf-CM; RCM) became activated to form proliferating astrocytes resembling radial glial cells (RGCs) or adult-type NSCs. Infusion of Raf-CM into injured mouse brains caused expansion of the NSC population in the subventricular zone, followed by the formation of new neurons that migrated to the damaged site. Our study shows an example how molecular mechanisms dissecting NSC behaviors can be utilized to develop regenerative therapies in brain disorders. PMID:27554447

  19. Constitutively active Notch1 converts cranial neural crest-derived frontonasal mesenchyme to perivascular cells in vivo

    PubMed Central

    Miller, Sophie R.; Perera, Surangi N.; Baker, Clare V. H.

    2017-01-01

    ABSTRACT 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. PMID:28183698

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

    PubMed

    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

  1. DNA methyltransferase activity is required for memory-related neural plasticity in the lateral amygdala.

    PubMed

    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.

  2. Altered neural activity in the 'when' pathway during temporal processing in fragile X premutation carriers.

    PubMed

    Kim, So-Yeon; Tassone, Flora; Simon, Tony J; Rivera, Susan M

    2014-03-15

    Mutations of the fragile X mental retardation 1 (FMR1) gene are the genetic cause of fragile X syndrome (FXS). Large expansions of the CGG repeat (>200 repeats) consequently result in transcriptional silencing of the FMR1 gene and deficiency/absence of the FMR1 protein (FMRP). Carriers with a premutation allele (55-200 of CGG repeats) are often associated with mildly reduced levels of FMRP and/or elevated levels of FMR1 mRNA. Recent studies have shown that infants with FXS exhibit severely reduced resolution of temporal attention, whereas spatial resolution of attention is not impaired. Following from these findings in the full mutation, the current study used fMRI to examine whether premutation carriers would exhibit atypical temporal processing at behavioral and/or neural levels. Using spatial and temporal working memory (SWM and TWM) tasks, separately tagging spatial and temporal processing, we demonstrated that neurotypical adults showed greater activation in the 'when pathway' (i.e., the right temporoparietal junction: TPJ) during TWM retrieval than SWM retrieval. However, premutation carriers failed to show this increased involvement of the right TPJ during retrieval of temporal information. Further, multiple regression analyses on right TPJ activation and FMR1 gene expression (i.e., CGG repeat size and FMR1 mRNA) suggests that elevated FMR1 mRNA level is a powerful predictor accounting for reduced right TPJ activation associated with temporal processing in premutation carriers. In conclusion, the current study provides the first evidence on altered neural correlates of temporal processing in adults with the premutation, explained by their FMR1 gene expression.

  3. Effects of aripiprazole on caffeine-induced hyperlocomotion and neural activation in the striatum.

    PubMed

    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.

  4. Seasonal prediction of tropical cyclone activity over the north Indian Ocean using three artificial neural networks

    NASA Astrophysics Data System (ADS)

    Nath, Sankar; Kotal, S. D.; Kundu, P. K.

    2016-12-01

    Three artificial neural network (ANN) methods, namely, multilayer perceptron (MLP), radial basis function (RBF) and generalized regression neural network (GRNN) are utilized to predict the seasonal tropical cyclone (TC) activity over the north Indian Ocean (NIO) during the post-monsoon season (October, November, December). The frequency of TC and large-scale climate variables derived from NCEP/NCAR reanalysis dataset of resolution 2.5° × 2.5° were analyzed for the period 1971-2013. Data for the years 1971-2002 were used for the development of the models, which were tested with independent sample data for the year 2003-2013. Using the correlation analysis, the five large-scale climate variables, namely, geopotential height at 500 hPa, relative humidity at 500 hPa, sea-level pressure, zonal wind at 700 hPa and 200 hPa for the preceding month September, are selected as potential predictors of the post-monsoon season TC activity. The result reveals that all the three different ANN methods are able to provide satisfactory forecast in terms of the various metrics, such as root mean-square error (RMSE), standard deviation (SD), correlation coefficient ( r), and bias and index of agreement ( d). Additionally, leave-one-out cross validation (LOOCV) method is also performed and the forecast skill is evaluated. The results show that the MLP model is found to be superior to the other two models (RBF, GRNN). The (MLP) is expected to be very useful to operational forecasters for prediction of TC activity.

  5. AICAR induces astroglial differentiation of neural stem cells via activating the JAK/STAT3 pathway independently of AMP-activated protein kinase.

    PubMed

    Zang, Yi; Yu, Li-Fang; Pang, Tao; Fang, Lei-Ping; Feng, Xu; Wen, Tie-Qiao; Nan, Fa-Jun; Feng, Lin-Yin; Li, Jia

    2008-03-07

    Neural stem cell differentiation and the determination of lineage decision between neuronal and glial fates have important implications in the study of developmental, pathological, and regenerative processes. Although small molecule chemicals with the ability to control neural stem cell fate are considered extremely useful tools in this field, few were reported. AICAR is an adenosine analog and extensively used to activate AMP-activated protein kinase (AMPK), a metabolic "fuel gauge" of the biological system. In the present study, we found an unrecognized astrogliogenic activity of AICAR on not only immortalized neural stem cell line C17.2 (C17.2-NSC), but also primary neural stem cells (NSCs) derived from post-natal (P0) rat hippocampus (P0-NSC) and embryonic day 14 (E14) rat embryonic cortex (E14-NSC). However, another AMPK activator, Metformin, did not alter either the C17.2-NSC or E14-NSC undifferentiated state although both Metformin and AICAR can activate the AMPK pathway in NSC. Furthermore, overexpression of dominant-negative mutants of AMPK in C17.2-NSC was unable to block the gliogenic effects of AICAR. We also found AICAR could activate the Janus kinase (JAK) STAT3 pathway in both C17.2-NSC and E14-NSC but Metformin fails. JAK inhibitor I abolished the gliogenic effects of AICAR. Taken together, these results suggest that the astroglial differentiation effect of AICAR on neural stem cells was acting independently of AMPK and that the JAK-STAT3 pathway is essential for the gliogenic effect of AICAR.

  6. What shall I be, what must I be: neural correlates of personal goal activation

    PubMed Central

    Strauman, Timothy J.; Detloff, Allison M.; Sestokas, Rima; Smith, David V.; Goetz, Elena L.; Rivera, Christine; Kwapil, Lori

    2013-01-01

    How is the brain engaged when people are thinking about their hopes, dreams, and obligations? Regulatory focus theory postulates two classes of personal goals and motivational systems for pursuing them. Ideal goals, such as hopes and aspirations, are pursued via the promotion system through “making good things happen.” Ought goals, such as obligations or responsibilities, are pursued via the prevention system through “keeping bad things from happening.” This study investigated the neural correlates of ideal and ought goal priming using an event-related fMRI design with rapid masked stimulus presentations. We exposed participants to their self-identified ideal and ought goals, yoked-control words and non-words. We also examined correlations between goal-related activation and measures of regulatory focus, behavioral activation/inhibition, and negative affect. Ideal priming led to activation in frontal and occipital regions as well as caudate and thalamus, whereas prevention goal priming was associated with activation in precuneus and posterior cingulate cortex. Individual differences in dysphoric/anxious affect and regulatory focus, but not differences in BAS/BIS strength, were predictive of differential activation in response to goal priming. The regions activated in response to ideal and ought goal priming broadly map onto the cortical midline network that has been shown to index processing of self-referential stimuli. Individual differences in regulatory focus and negative affect impact this network and appeared to influence the strength and accessibility of the promotion and prevention systems. The results support a fundamental distinction between promotion and prevention and extend our understanding of how personal goals influence behavior. PMID:23316145

  7. Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

    PubMed

    Howe, P D; Bryant, S R; Shreeve, T G

    2007-10-01

    We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

  8. An Intelligent Active Video Surveillance System Based on the Integration of Virtual Neural Sensors and BDI Agents

    NASA Astrophysics Data System (ADS)

    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.

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

    PubMed Central

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

    2015-01-01

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

  10. Neural-activity mapping of memory-based dominance in the crow: neural networks integrating individual discrimination and social behaviour control.

    PubMed

    Nishizawa, K; Izawa, E-I; Watanabe, S

    2011-12-01

    Large-billed crows (Corvus macrorhynchos), highly social birds, form stable dominance relationships based on the memory of win/loss outcomes of first encounters and on individual discrimination. This socio-cognitive behaviour predicts the existence of neural mechanisms for integration of social behaviour control and individual discrimination. This study aimed to elucidate the neural substrates of memory-based dominance in crows. First, the formation of dominance relationships was confirmed between males in a dyadic encounter paradigm. Next, we examined whether neural activities in 22 focal nuclei of pallium and subpallium were correlated with social behaviour and stimulus familiarity after exposure to dominant/subordinate familiar individuals and unfamiliar conspecifics. Neural activity was determined by measuring expression level of the immediate-early-gene (IEG) protein Zenk. Crows displayed aggressive and/or submissive behaviour to opponents less frequently but more discriminatively in subsequent encounters, suggesting stable dominance based on memory, including win/loss outcomes of the first encounters and individual discrimination. Neural correlates of aggressive and submissive behaviour were found in limbic subpallium including septum, bed nucleus of the striae terminalis (BST), and nucleus taeniae of amygdala (TnA), but also those to familiarity factor in BST and TnA. Contrastingly, correlates of social behaviour were little in pallium and those of familiarity with exposed individuals were identified in hippocampus, medial meso-/nidopallium, and ventro-caudal nidopallium. Given the anatomical connection and neural response patterns of the focal nuclei, neural networks connecting pallium and limbic subpallium via hippocampus could be involved in the integration of individual discrimination and social behaviour control in memory-based dominance in the crow.

  11. Maximizing the entropy of histogram bar heights to explore neural activity: a simulation study on auditory and tactile fibers.

    PubMed

    Güçlü, Burak

    2005-01-01

    Neurophysiologists often use histograms to explore patterns of activity in neural spike trains. The bin size selected to construct a histogram is crucial: too large bin widths result in coarse histograms, too small bin widths expand unimportant detail. Peri-stimulus time (PST) histograms of simulated nerve fibers were studied in the current article. This class of histograms gives information about neural activity in the temporal domain and is a density estimate for the spike rate. Scott's rule based on modem statistical theory suggests that the optimal bin size is inversely proportional to the cube root of sample size. However, this estimate requires a priori knowledge about the density function. Moreover, there are no good algorithms for adaptive-mesh histograms, which have variable bin sizes to minimize estimation errors. Therefore, an unconventional technique is proposed here to help experimenters in practice. This novel method maximizes the entropy of histogram-bar heights to find the unique bin size, which generates the highest disorder in a histogram (i.e., the most complex histogram), and is useful as a starting point for neural data mining. Although the proposed method is ad hoc from a density-estimation point of view, it is simple, efficient and more helpful in the experimental setting where no prior statistical information on neural activity is available. The results of simulations based on the entropy method are also discussed in relation to Ellaway's cumulative-sum technique, which can detect subtle changes in neural activity in certain conditions.

  12. Estradiol selectively reduces central neural activation induced by hypertonic NaCl infusion in ovariectomized rats.

    PubMed

    Jones, Alexis B; Bass, Eryn E; Fan, Liming; Curtis, Kathleen S

    2012-09-10

    We recently reported that the latency to begin drinking water during slow, intravenous infusion of a concentrated NaCl solution was shorter in estradiol-treated ovariectomized rats compared to oil vehicle-treated rats, despite comparably elevated plasma osmolality. To test the hypothesis that the decreased latency to begin drinking is attributable to enhanced detection of increased plasma osmolality by osmoreceptors located in the CNS, the present study used immunocytochemical methods to label fos, a marker of neural activation. Increased plasma osmolality did not activate the subfornical organ (SFO), organum vasculosum of the lamina terminalis (OVLT), or the nucleus of the solitary tract (NTS) in either oil vehicle-treated rats or estradiol-treated rats. In contrast, hyperosmolality increased fos labeling in the area postrema (AP), the paraventricular nucleus of the hypothalamus (PVN) and the rostral ventrolateral medulla (RVLM) in both groups; however, the increase was blunted in estradiol-treated rats. These results suggest that estradiol has selective effects on the sensitivity of a population of osmo-/Na(+)-receptors located in the AP, which, in turn, alters activity in other central areas associated with responses to increased osmolality. In conjunction with previous reports that hyperosmolality increases blood pressure and that elevated blood pressure inhibits drinking, the current findings of reduced activation in AP, PVN, and RVLM-areas involved in sympathetic nerve activity-raise the possibility that estradiol blunts HS-induced blood pressure changes. Thus, estradiol may eliminate or reduce the initial inhibition of water intake that occurs during increased osmolality, and facilitate a more rapid behavioral response, as we observed in our recent study.

  13. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network.

    PubMed

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-10-13

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods.

  14. Fault Diagnosis Based on Chemical Sensor Data with an Active Deep Neural Network

    PubMed Central

    Jiang, Peng; Hu, Zhixin; Liu, Jun; Yu, Shanen; Wu, Feng

    2016-01-01

    Big sensor data provide significant potential for chemical fault diagnosis, which involves the baseline values of security, stability and reliability in chemical processes. A deep neural network (DNN) with novel active learning for inducing chemical fault diagnosis is presented in this study. It is a method using large amount of chemical sensor data, which is a combination of deep learning and active learning criterion to target the difficulty of consecutive fault diagnosis. DNN with deep architectures, instead of shallow ones, could be developed through deep learning to learn a suitable feature representation from raw sensor data in an unsupervised manner using stacked denoising auto-encoder (SDAE) and work through a layer-by-layer successive learning process. The features are added to the top Softmax regression layer to construct the discriminative fault characteristics for diagnosis in a supervised manner. Considering the expensive and time consuming labeling of sensor data in chemical applications, in contrast to the available methods, we employ a novel active learning criterion for the particularity of chemical processes, which is a combination of Best vs. Second Best criterion (BvSB) and a Lowest False Positive criterion (LFP), for further fine-tuning of diagnosis model in an active manner rather than passive manner. That is, we allow models to rank the most informative sensor data to be labeled for updating the DNN parameters during the interaction phase. The effectiveness of the proposed method is validated in two well-known industrial datasets. Results indicate that the proposed method can obtain superior diagnosis accuracy and provide significant performance improvement in accuracy and false positive rate with less labeled chemical sensor data by further active learning compared with existing methods. PMID:27754386

  15. Lateralization of expression of neural sympathetic activity to the vessels and effects of carotid baroreceptor stimulation

    PubMed Central

    Diedrich, André; Porta, Alberto; Barbic, Franca; Brychta, Robert J.; Bonizzi, Pietro; Diedrich, Laura; Cerutti, Sergio; Robertson, David; Furlan, Raffaello

    2009-01-01

    Human studies suggest that cardiovascular neural sympathetic control is predominantly modulated by the right cerebral hemisphere. It is unknown whether post-ganglionic sympathetic activity [muscle sympathetic nerve activity (MSNA)] shows any functional asymmetry. Eight right-handed volunteers (3 women and 5 men, 32 ± 2 yr of age) underwent ECG, beat-by-beat blood pressure, respiratory activity, and simultaneous right and left MSNA recordings during spontaneous and controlled breathing (CB, 15 breaths/min, 0.25 Hz). Dynamic carotid baroreceptor stimulation was obtained by 0.1-Hz sinusoidal suction, from 0 to −50 mmHg, randomly applied to the right, left, and combined right and left sides of the neck during CB. Laterality was assessed by changes in the MSNA burst rate (in bursts/min, and bursts/100 beats), strength [amplitude (A) and area (AA)], and the oscillatory component at 0.1 Hz during baroreceptor stimulation. Amplitude parameters were normalized by CB burst mean amplitude and area of the same side. At rest, the right and left MSNA burst rate and total MSNA activity were similar. Conversely, the right MSNA normalized burst AN (1.36 ± 0.18) and AAN (1.31 ± 0.16) were larger than the left MSNA AN (1.04 ± 0.09) and AAN (1.02 ± 0.08). Unilateral and bilateral carotid baroreflex stimulation abolished the right prevalence of AN and AAN. In conclusion, the right lateralization of sympathetic activity to the vessels is indicated by normalized burst strength parameters of bilateral MSNA recordings at rest during spontaneous breathing. Carotid baroreceptor stimulation disrupted such expression of MSNA lateralization possibly by disturbing the synchronizing action of right cerebral hemisphere. PMID:19363133

  16. Transient neural activation in human amygdala involved in aversive conditioning of face and voice.

    PubMed

    Iidaka, Tetsuya; Saito, Daisuke N; Komeda, Hidetsugu; Mano, Yoko; Kanayama, Noriaki; Osumi, Takahiro; Ozaki, Norio; Sadato, Norihiro

    2010-09-01

    Elucidating the neural mechanisms involved in aversive conditioning helps find effective treatments for psychiatric disorders such as anxiety disorder and phobia. Previous studies using fMRI and human subjects have reported that the amygdala plays a role in this phenomenon. However, the noxious stimuli that were used as unconditioned stimuli in previous studies (e.g., electric shock) might have been ecologically invalid because we seldom encounter such stimuli in daily life. Therefore, we investigated whether a face stimulus could be conditioned by using a voice that had negative emotional valence and was collected from a real-life environment. A skin conductance response showed that healthy subjects were conditioned by using these stimuli. In an fMRI study, there was greater amygdala activation in response to the faces that had been paired with the voice than to those that had not. The right amygdala showed transient activity in the early stage of acquisition. A psychophysiological interaction analysis indicated that the subcortical pathway from the medial geniculate body to the amygdala played a role in conditioning. Modulation of the subcortical pathway by voice stimuli preceded the transient activity in the amygdala. The finding that an ecologically valid stimulus elicited the conditioning and amygdala response suggests that our brain is automatically processing unpleasant stimuli in daily life.

  17. Adolescent-specific patterns of behavior and neural activity during social reinforcement learning.

    PubMed

    Jones, Rebecca M; Somerville, Leah H; Li, Jian; Ruberry, Erika J; Powers, Alisa; Mehta, Natasha; Dyke, Jonathan; Casey, B J

    2014-06-01

    Humans are sophisticated social beings. Social cues from others are exceptionally salient, particularly during adolescence. Understanding how adolescents interpret and learn from variable social signals can provide insight into the observed shift in social sensitivity during this period. The present study tested 120 participants between the ages of 8 and 25 years on a social reinforcement learning task where the probability of receiving positive social feedback was parametrically manipulated. Seventy-eight of these participants completed the task during fMRI scanning. Modeling trial-by-trial learning, children and adults showed higher positive learning rates than did adolescents, suggesting that adolescents demonstrated less differentiation in their reaction times for peers who provided more positive feedback. Forming expectations about receiving positive social reinforcement correlated with neural activity within the medial prefrontal cortex and ventral striatum across age. Adolescents, unlike children and adults, showed greater insular activity during positive prediction error learning and increased activity in the supplementary motor cortex and the putamen when receiving positive social feedback regardless of the expected outcome, suggesting that peer approval may motivate adolescents toward action. While different amounts of positive social reinforcement enhanced learning in children and adults, all positive social reinforcement equally motivated adolescents. Together, these findings indicate that sensitivity to peer approval during adolescence goes beyond simple reinforcement theory accounts and suggest possible explanations for how peers may motivate adolescent behavior.

  18. Neural Activation During Risky Decision-Making in Youth at High Risk for Substance Use Disorders

    PubMed Central

    Hulvershorn, Leslie A.; Hummer, Tom A.; Fukunaga, Rena; Leibenluft, Ellen; Finn, Peter; Cyders, Melissa A.; Anand, Amit; Overhage, Lauren; Dir, Allyson; Brown, Joshua

    2015-01-01

    Risky decision-making, particularly in the context of reward-seeking behavior, is strongly associated with the presence of substance use disorders (SUDs). However, there has been little research on the neural substrates underlying reward-related decision-making in drug-naïve youth who are at elevated risk for SUDs. Participants comprised 23 high-risk (HR) youth with a well-established SUD risk phenotype and 27 low-risk healthy comparison (HC) youth, aged 10–14. Participants completed the balloon analog risk task (BART), a task designed to examine risky decision-making, during functional magnetic resonance imaging. The HR group had faster reaction times, but otherwise showed no behavioral differences from the HC group. HR youth experienced greater activation when processing outcome, as the chances of balloon explosion increased, relative to HC youth, in ventromedial prefrontal cortex (vmPFC). As explosion probability increased, group-by-condition interactions in the ventral striatum/anterior cingulate and the anterior insula showed increasing activation in HR youth, specifically on trials when explosions occurred. Thus, atypical activation increased with increasing risk of negative outcome (i.e., balloon explosion) in a cortico-striatal network in the HR group. These findings identify candidate neurobiological markers of addiction risk in youth at high familial and phenotypic risk for SUDs. PMID:26071624

  19. Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.

    PubMed

    Hoogi, Assaf; Subramaniam, Arjun; Veerapaneni, Rishi; Rubin, Daniel

    2016-11-11

    In this paper, we propose a generalization of the level set segmentation approach by supplying a novel method for adaptive estimation of active contour parameters. The presented segmentation method is fully automatic once the lesion has been detected. First, the location of the level set contour relative to the lesion is estimated using a convolutional neural network (CNN). The CNN has two convolutional layers for feature extraction, which lead into dense layers for classification. Second, the output CNN probabilities are then used to adaptively calculate the parameters of the active contour functional during the segmentation process. Finally, the adaptive window size surrounding each contour point is re-estimated by an iterative process that considers lesion size and spatial texture. We demonstrate the capabilities of our method on a dataset of 164 MRI and 112 CT images of liver lesions that includes low contrast and heterogeneous lesions as well as noisy images. To illustrate the strength of our method, we evaluated it against state of the art CNNbased and active contour techniques. For all cases, our method, as assessed by Dice similarity coefficients, performed significantly better than currently available methods. An average Dice improvement of 0.27 was found across the entire dataset over all comparisons. We also analyzed two challenging subsets of lesions and obtained a significant Dice improvement of ����.�������� with our method (p < 0.001, Wilcoxon).

  20. Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.

    PubMed

    Hoogi, Assaf; Subramaniam, Arjun; Veerapaneni, Rishi; Rubin, Daniel

    2016-11-11

    In this paper, we propose a generalization of the level set segmentation approach by supplying a novel method for adaptive estimation of active contour parameters. The presented segmentation method is fully automatic once the lesion has been detected. First, the location of the level set contour relative to the lesion is estimated using a convolutional neural network (CNN). The CNN has two convolutional layers for feature extraction, which lead into dense layers for classification. Second, the output CNN probabilities are then used to adaptively calculate the parameters of the active contour functional during the segmentation process. Finally, the adaptive window size surrounding each contour point is re-estimated by an iterative process that considers lesion size and spatial texture. We demonstrate the capabilities of our method on a dataset of 164 MRI and 112 CT images of liver lesions that includes low contrast and heterogeneous lesions as well as noisy images. To illustrate the strength of our method, we evaluated it against state of the art CNNbased and active contour techniques. For all cases, our method, as assessed by Dice similarity coefficients, performed significantly better than currently available methods. An average Dice improvement of 0.27 was found across the entire dataset over all comparisons. We also analyzed two challenging subsets of lesions and obtained a significant Dice improvement of 0.24 with our method (p < 0.001, Wilcoxon).

  1. Intersubject Variability in Fearful Face Processing: The Link Between Behavior and Neural Activation

    PubMed Central

    Doty, Tracy J.; Japee, Shruti; Ingvar, Martin; Ungerleider, Leslie G.

    2014-01-01

    Stimuli that signal threat show considerable variability in the extent to which they enhance behavior, even among healthy individuals. However, the neural underpinning of this behavioral variability is not well understood. By manipulating expectation of threat in an fMRI study of fearful vs. neutral face categorization, we uncovered a network of areas underlying variability in threat processing in healthy adults. We explicitly altered expectation by presenting face images at three different expectation levels: 80%, 50%, and 20%. Subjects were instructed to report as fast and as accurately as possible whether the face was fearful (signaled threat) or not. An uninformative cue preceded each face by 4 seconds (s). By taking the difference between response times (RT) to fearful compared to neutral faces, we quantified an overall fear RT bias (i.e. faster to fearful than neutral faces) for each subject. This bias correlated positively with late trial fMRI activation (8 s after the face) during unexpected fearful face trials in bilateral ventromedial prefrontal cortex, the left subgenual cingulate cortex, and the right caudate nucleus and correlated negatively with early trial fMRI activation (4 s after the cue) during expected neutral face trials in bilateral dorsal striatum and the right ventral striatum. These results demonstrate that the variability in threat processing among healthy adults is reflected not only in behavior but also in the magnitude of activation in medial prefrontal and striatal regions that appear to encode affective value. PMID:24841078

  2. Abnormal Neural Activation to Faces in the Parents of Children with Autism.

    PubMed

    Yucel, G H; Belger, A; Bizzell, J; Parlier, M; Adolphs, R; Piven, J

    2015-12-01

    Parents of children with an autism spectrum disorder (ASD) show subtle deficits in aspects of social behavior and face processing, which resemble those seen in ASD, referred to as the "Broad Autism Phenotype " (BAP). While abnormal activation in ASD has been reported in several brain structures linked to social cognition, little is known regarding patterns in the BAP. We compared autism parents with control parents with no family history of ASD using 2 well-validated face-processing tasks. Results indicated increased activation in the autism parents to faces in the amygdala (AMY) and the fusiform gyrus (FG), 2 core face-processing regions. Exploratory analyses revealed hyper-activation of lateral occipital cortex (LOC) bilaterally in autism parents with aloof personality ("BAP+"). Findings suggest that abnormalities of the AMY and FG are related to underlying genetic liability for ASD, whereas abnormalities in the LOC and right FG are more specific to behavioral features of the BAP. Results extend our knowledge of neural circuitry underlying abnormal face processing beyond those previously reported in ASD to individuals with shared genetic liability for autism and a subset of genetically related individuals with the BAP.

  3. Improving quantitative structure-activity relationship models using Artificial Neural Networks trained with dropout

    NASA Astrophysics Data System (ADS)

    Mendenhall, Jeffrey; Meiler, Jens

    2016-02-01

    Dropout is an Artificial Neural Network (ANN) training technique that has been shown to improve ANN performance across canonical machine learning (ML) datasets. Quantitative Structure Activity Relationship (QSAR) datasets used to relate chemical structure to biological activity in Ligand-Based Computer-Aided Drug Discovery pose unique challenges for ML techniques, such as heavily biased dataset composition, and relatively large number of descriptors relative to the number of actives. To test the hypothesis that dropout also improves QSAR ANNs, we conduct a benchmark on nine large QSAR datasets. Use of dropout improved both enrichment false positive rate and log-scaled area under the receiver-operating characteristic curve (logAUC) by 22-46 % over conventional ANN implementations. Optimal dropout rates are found to be a function of the signal-to-noise ratio of the descriptor set, and relatively independent of the dataset. Dropout ANNs with 2D and 3D autocorrelation descriptors outperform conventional ANNs as well as optimized fingerprint similarity search methods.

  4. Artificial neural network optimization of Althaea rosea seeds polysaccharides and its antioxidant activity.

    PubMed

    Liu, Feng; Liu, Wenhui; Tian, Shuge

    2014-09-01

    A combination of an orthogonal L16(4)4 test design and a three-layer artificial neural network (ANN) model was applied to optimize polysaccharides from Althaea rosea seeds extracted by hot water method. The highest optimal experimental yield of A. rosea seed polysaccharides (ARSPs) of 59.85 mg/g was obtained using three extraction numbers, 113 min extraction time, 60.0% ethanol concentration, and 1:41 solid-liquid ratio. Under these optimized conditions, the ARSP experimental yield was very close to the predicted yield of 60.07 mg/g and was higher than the orthogonal test results (40.86 mg/g). Structural characterizations were conducted using physicochemical property and FTIR analysis. In addition, the study of ARSP antioxidant activity demonstrated that polysaccharides exhibited high superoxide dismutase activity, strong reducing power, and positive scavenging activity on superoxide anion, hydroxyl radical, 2,2-diphenyl-1-picrylhydrazyl, and reducing power. Our results indicated that ANNs were efficient quantitative tools for predicting the total ARSP content.

  5. Adolescent-specific patterns of behavior and neural activity during social reinforcement learning

    PubMed Central

    Jones, Rebecca M.; Somerville, Leah H.; Li, Jian; Ruberry, Erika J.; Powers, Alisa; Mehta, Natasha; Dyke, Jonathan; Casey, BJ

    2014-01-01

    Humans are sophisticated social beings. Social cues from others are exceptionally salient, particularly during adolescence. Understanding how adolescents interpret and learn from variable social signals can provide insight into the observed shift in social sensitivity during this period. The current study tested 120 participants between the ages of 8 and 25 years on a social reinforcement learning task where the probability of receiving positive social feedback was parametrically manipulated. Seventy-eight of these participants completed the task during fMRI scanning. Modeling trial-by-trial learning, children and adults showed higher positive learning rates than adolescents, suggesting that adolescents demonstrated less differentiation in their reaction times for peers who provided more positive feedback. Forming expectations about receiving positive social reinforcement correlated with neural activity within the medial prefrontal cortex and ventral striatum across age. Adolescents, unlike children and adults, showed greater insular activity during positive prediction error learning and increased activity in the supplementary motor cortex and the putamen when receiving positive social feedback regardless of the expected outcome, suggesting that peer approval may motivate adolescents towards action. While different amounts of positive social reinforcement enhanced learning in children and adults, all positive social reinforcement equally motivated adolescents. Together, these findings indicate that sensitivity to peer approval during adolescence goes beyond simple reinforcement theory accounts and suggests possible explanations for how peers may motivate adolescent behavior. PMID:24550063

  6. DETECTING ACTIVE GALACTIC NUCLEI USING MULTI-FILTER IMAGING DATA. II. INCORPORATING ARTIFICIAL NEURAL NETWORKS

    SciTech Connect

    Dong, X. Y.; De Robertis, M. M.

    2013-10-01

    This is the second paper of the series Detecting Active Galactic Nuclei Using Multi-filter Imaging Data. In this paper we review shapelets, an image manipulation algorithm, which we employ to adjust the point-spread function (PSF) of galaxy images. This technique is used to ensure the image in each filter has the same and sharpest PSF, which is the preferred condition for detecting AGNs using multi-filter imaging data as we demonstrated in Paper I of this series. We apply shapelets on Canada-France-Hawaii Telescope Legacy Survey Wide Survey ugriz images. Photometric parameters such as effective radii, integrated fluxes within certain radii, and color gradients are measured on the shapelets-reconstructed images. These parameters are used by artificial neural networks (ANNs) which yield: photometric redshift with an rms of 0.026 and a regression R-value of 0.92; galaxy morphological types with an uncertainty less than 2 T types for z ≤ 0.1; and identification of galaxies as AGNs with 70% confidence, star-forming/starburst (SF/SB) galaxies with 90% confidence, and passive galaxies with 70% confidence for z ≤ 0.1. The incorporation of ANNs provides a more reliable technique for identifying AGN or SF/SB candidates, which could be very useful for large-scale multi-filter optical surveys that also include a modest set of spectroscopic data sufficient to train neural networks.

  7. Effects of binary taste stimuli on the neural activity of the hamster chorda tympani

    PubMed Central

    1980-01-01

    Binary mixtures of taste stimuli were applied to the tongue of the hamster and the reaction of the whole corda tympani was recorded. Some of the chemicals that were paired in mixtures (HCl, NH4Cl, NaCl, CaCl2, sucrose, and D-phenylalanine) have similar tastes to human and/or hamster, and/or common stimulatory effects on individual fibers of the hamster chorda tympani; other pairs of these chemicals have dissimilar tastes and/or distinct neural stimulatory effects. The molarity of each chemical with approximately the same effect on the activity of the nerve as 0.01 M NaCl was selected, and an established relation between stimulus concentration and response allowed estimation of the effect of a "mixture" of two concentrations of one chemical. Each mixture elicited a response that was smaller than the sum of the responses to its components. However, responses to some mixtures approached this sum, and responses to other mixtures closely approached the response to a "mixture" of two concentrations of one chemical. Responses of the former variety were generated by mixtures of an electrolyte and a nonelectrolyte and the latter by mixtures of two electrolytes or two nonelectrolytes. But, beyond the distinction between electrolytes and nonelectrolytes, the whole-nerve response to a mixture could not be predicted from the known neural or psychophysical effects of its components. PMID:7411114

  8. Cutaneous retinal activation and neural entrainment in transcranial alternating current stimulation: A systematic review.

    PubMed

    Schutter, Dennis J L G

    2016-10-15

    Transcranial alternating current stimulation (tACS) applies exogenous oscillatory electric field potentials to entrain neural rhythms and is used to investigate brain-function relationships and its potential to enhance perceptual and cognitive performance. However, due to current spread tACS can cause cutaneous activation of the retina and phosphenes. Several lines of evidence suggest that retinal phosphenes are capable of inducing neural entrainment, making the contributions of central and peripheral stimulation to the effects in the brain difficult to disentangle. In this literature review, the importance of this issue is further illustrated by the fact that photic stimulation can have a direct impact on perceptual and cognitive performance. This leaves open the possibility that peripheral photic stimulation can at least in part explain the central effects that are attributed to tACS. The extent to which phosphene perception contributes to the effects of exogenous oscillatory electric fields in the brain and influence perception and cognitive performance needs to be examined to understand the working mechanisms of tACS in neurophysiology and behaviour.

  9. Detection of micro solder balls using active thermography and probabilistic neural network

    NASA Astrophysics Data System (ADS)

    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.

  10. Differential neural activation of vascular alpha-adrenoceptors in oral tissues of cats.

    PubMed

    Koss, Michael C

    2002-04-05

    The aim of this study was to determine the relative contribution of alpha(1)- and alpha(2)-adrenoceptors involved in sympathetic-evoked vasoconstrictor responses in tissues perfused by the lingual arterial circulation in pentobarbital anesthetized cats. Blood flow in the lingual artery was measured by ultrasonic flowmetry. Laser-Doppler flowmetry was utilized to measure oral tissue vasoconstrictor responses in the maxillary gingiva and from the surface of the tongue. Electrical stimulation of the preganglionic superior cervical sympathetic nerve resulted in frequency-dependent blood flow decreases at all three sites. These responses were stable over time and were uniformly antagonized by administration of phentolamine (0.3 - 3.0 mg kg(-1)). The selective alpha(1)-adrenoceptor antagonist, prazosin (10 - 300 microg kg(-1)), attenuated vasoconstriction in the lingual artery and gingiva, but was ineffective in blocking vasoconstriction in the tongue. Subsequent administration of rauwolscine (300 microg kg(-1)) antagonized remaining vasoconstrictor responses. In contrast, rauwolscine (10 - 300 microg kg(-1)), given alone, blocked evoked vasoconstriction in the tongue, and was without effect on gingival or lingual artery vasoconstrictor responses. Subsequent administration of prazosin (300 microg kg(-1)) largely antagonized remaining neurally elicited responses. These results suggest that neural vasoconstrictor responses in some regional vascular beds in the cat oral cavity are mediated by both alpha(1)- and alpha(2)-adrenoceptors. In contrast, tongue surface vasoconstrictor responses to sympathetic nerve activation appear to be mediated primarily by alpha(2)-adrenoceptors.

  11. Neural correlates of envy: Regional homogeneity of resting-state brain activity predicts dispositional envy.

    PubMed

    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.

  12. Artificial neural network modelling of the antioxidant activity and phenolic compounds of bananas submitted to different drying treatments.

    PubMed

    Guiné, Raquel P F; Barroca, Maria João; Gonçalves, Fernando J; Alves, Mariana; Oliveira, Solange; Mendes, Mateus

    2015-02-01

    Bananas (cv. Musa nana and Musa cavendishii) fresh and dried by hot air at 50 and 70°C and lyophilisation were analysed for phenolic contents and antioxidant activity. All samples were subject to six extractions (three with methanol followed by three with acetone/water solution). The experimental data served to train a neural network adequate to describe the experimental observations for both output variables studied: total phenols and antioxidant activity. The results show that both bananas are similar and air drying decreased total phenols and antioxidant activity for both temperatures, whereas lyophilisation decreased the phenolic content in a lesser extent. Neural network experiments showed that antioxidant activity and phenolic compounds can be predicted accurately from the input variables: banana variety, dryness state and type and order of extract. Drying state and extract order were found to have larger impact in the values of antioxidant activity and phenolic compounds.

  13. Adipose Tissue and Energy Expenditure: Central and Peripheral Neural Activation Pathways.

    PubMed

    Blaszkiewicz, Magdalena; Townsend, Kristy L

    2016-06-01

    Increasing energy expenditure is an appealing therapeutic target for the prevention and reversal of metabolic conditions such as obesity or type 2 diabetes. However, not enough research has investigated how to exploit pre-existing neural pathways, both in the central nervous system (CNS) and peripheral nervous system (PNS), in order to meet these needs. Here, we review several research areas in this field, including centrally acting pathways known to drive the activation of sympathetic nerves that can increase lipolysis and browning in white adipose tissue (WAT) or increase thermogenesis in brown adipose tissue (BAT), as well as other central and peripheral pathways able to increase energy expenditure of these tissues. In addition, we describe new work investigating the family of transient receptor potential (TRP) channels on metabolically important sensory nerves, as well as the role of the vagus nerve in regulating energy balance.

  14. Stress-related noradrenergic activity prompts large-scale neural network reconfiguration.

    PubMed

    Hermans, Erno J; van Marle, Hein J F; Ossewaarde, Lindsey; Henckens, Marloes J A G; Qin, Shaozheng; van Kesteren, Marlieke T R; Schoots, Vincent C; Cousijn, Helena; Rijpkema, Mark; Oostenveld, Robert; Fernández, Guillén

    2011-11-25

    Acute stress shifts the brain into a state that fosters rapid defense mechanisms. Stress-related neuromodulators are thought to trigger this change by altering properties of large-scale neural populations throughout the brain. We investigated this brain-state shift in humans. During exposure to a fear-related acute stressor, responsiveness and interconnectivity within a network including cortical (frontoinsular, dorsal anterior cingulate, inferotemporal, and temporoparietal) and subcortical (amygdala, thalamus, hypothalamus, and midbrain) regions increased as a function of stress response magnitudes. β-adrenergic receptor blockade, but not cortisol synthesis inhibition, diminished this increase. Thus, our findings reveal that noradrenergic activation during acute stress results in prolonged coupling within a distributed network that integrates information exchange between regions involved in autonomic-neuroendocrine control and vigilant attentional reorienting.

  15. Global Mittag-Leffler synchronization of fractional-order neural networks with discontinuous activations.

    PubMed

    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.

  16. Repetition-Related Reductions in Neural Activity during Emotional Simulations of Future Events

    PubMed Central

    2015-01-01

    Simulations of future experiences are often emotionally arousing, and the tendency to repeatedly simulate negative future outcomes has been identified as a predictor of the onset of symptoms of anxiety. Nonetheless, next to nothing is known about how the healthy human brain processes repeated simulations of emotional future events. In this study, we present a paradigm that can be used to study repeated simulations of the emotional future in a manner that overcomes phenomenological confounds between positive and negative events. The results show that pulvinar nucleus and orbitofrontal cortex respectively demonstrate selective reductions in neural activity in response to frequently as compared to infrequently repeated simulations of negative and positive future events. Implications for research on repeated simulations of the emotional future in both non-clinical and clinical populations are discussed. PMID:26390294

  17. Feelings of warmth correlate with neural activity in right anterior insular cortex.

    PubMed

    Olausson, H; Charron, J; Marchand, S; Villemure, C; Strigo, I A; Bushnell, M C

    2005-11-25

    The neural coding of perception can differ from that for the physical attributes of a stimulus. Recent studies suggest that activity in right anterior insular cortex may underlie thermal perception, particularly that of cold. We now examine whether this region is also important for the perception of warmth. We applied cutaneous warm stimuli on the left leg (warmth) in normal subjects (n = 7) during functional magnetic resonance imaging (fMRI). After each stimulus, subjects rated their subjective intensity of the stimulus using a visual analogue scale (VAS), and correlations were determined between the fMRI signal and the VAS ratings. We found that intensity ratings of warmth correlated with the fMRI signal in the right (contralateral to stimulation) anterior insular cortex. These results, in conjunction with previous reports, suggest that the right anterior insular cortex is important for different types of thermal perception.

  18. Outsourcing neural active control to passive composite mechanics: a tissue engineered cyborg ray

    NASA Astrophysics Data System (ADS)

    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".

  19. Is Neural Activity Detected by ERP-Based Brain-Computer Interfaces Task Specific?

    PubMed Central

    Wenzel, Markus A.; Almeida, Inês; Blankertz, Benjamin

    2016-01-01

    Objective 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. Approach 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. Results 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). Significance 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. PMID:27792781

  20. False memory for face in short-term memory and neural activity in human amygdala.

    PubMed

    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.

  1. Neural activity patterns evoked by a spouse's incongruent emotional reactions when recalling marriage-relevant experiences.

    PubMed

    Petrican, Raluca; Rosenbaum, Rachel Shayna; Grady, Cheryl

    2015-10-01

    Resonance with the inner states of another social actor is regarded as a hallmark of emotional closeness. Nevertheless, sensitivity to potential incongruities between one's own and an intimate partner's subjective experience is reportedly also important for close relationship quality. Here, we tested whether perceivers show greater neurobehavioral responsiveness to a spouse's positive (rather than negative) context-incongruent emotions, and whether this effect is influenced by the perceiver's satisfaction with the relationship. Thus, we used fMRI to scan older long-term married female perceivers while they judged either their spouse's or a stranger's affect, based on incongruent nonverbal and verbal cues. The verbal cues were selected to evoke strongly polarized affective responses. Higher perceiver marital satisfaction predicted greater neural processing of the spouse's (rather than the strangers) nonverbal cues. Nevertheless, across all perceivers, greater neural processing of a spouse's (rather than a stranger's) nonverbal behavior was reliably observed only when the behavior was positive and the context was negative. The spouse's positive (rather than negative) nonverbal behavior evoked greater activity in putative mirror neuron areas, such as the bilateral inferior parietal lobule (IPL). This effect was related to a stronger inhibitory influence of cognitive control areas on mirror system activity in response to a spouse's negative nonverbal cues, an effect that strengthened with increasing perceiver marital satisfaction. Our valence-asymmetric findings imply that neurobehavioral responsiveness to a close other's emotions may depend, at least partly, on cognitive control resources, which are used to support the perceiver's interpersonal goals (here, goals that are relevant to relationship stability).

  2. Distinct Neural Activities in Premotor Cortex during Natural Vocal Behaviors in a New World Primate, the Common Marmoset (Callithrix jacchus).

    PubMed

    Roy, Sabyasachi; Zhao, Lingyun; Wang, Xiaoqin

    2016-11-30

    Although evidence from human studies has long indicated the crucial role of the frontal cortex in speech production, it has remained uncertain whether the frontal cortex in nonhuman primates plays a similar role in vocal communication. Previous studies of prefrontal and premotor cortices of macaque monkeys have found neural signals associated with cue- and reward-conditioned vocal production, but not with self-initiated or spontaneous vocalizations (Coudé et al., 2011; Hage and Nieder, 2013), which casts doubt on the role of the frontal cortex of the Old World monkeys in vocal communication. A recent study of marmoset frontal cortex observed modulated neural activities associated with self-initiated vocal production (Miller et al., 2015), but it did not delineate whether these neural activities were specifically attributed to vocal production or if they may result from other nonvocal motor activity such as orofacial motor movement. In the present study, we attempted to resolve these issues and examined single neuron activities in premotor cortex during natural vocal exchanges in the common marmoset (Callithrix jacchus), a highly vocal New World primate. Neural activation and suppression were observed both before and during self-initiated vocal production. Furthermore, by comparing neural activities between self-initiated vocal production and nonvocal orofacial motor movement, we identified a subpopulation of neurons in marmoset premotor cortex that was activated or suppressed by vocal production, but not by orofacial movement. These findings provide clear evidence of the premotor cortex's involvement in self-initiated vocal production in natural vocal behaviors of a New World primate.

  3. Neural Response during the Activation of the Attachment System in Patients with Borderline Personality Disorder: An fMRI Study.

    PubMed

    Buchheim, Anna; Erk, Susanne; George, Carol; Kächele, Horst; Martius, Philipp; Pokorny, Dan; Spitzer, Manfred; Walter, Henrik

    2016-01-01

    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 (fMRI). Eleven female patients with BPD without posttraumatic stress disorder (PTSD) and 17 healthy female controls matched for age and education were telling stories in the scanner in response to the Adult Attachment Projective Picture System (AAP), 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 2 min. 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 (DLPFC) and the rostral cingulate zone (RCZ). 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.

  4. Neural Response during the Activation of the Attachment System in Patients with Borderline Personality Disorder: An fMRI Study

    PubMed Central

    Buchheim, Anna; Erk, Susanne; George, Carol; Kächele, Horst; Martius, Philipp; Pokorny, Dan; Spitzer, Manfred; Walter, Henrik

    2016-01-01

    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 (fMRI). Eleven female patients with BPD without posttraumatic stress disorder (PTSD) and 17 healthy female controls matched for age and education were telling stories in the scanner in response to the Adult Attachment Projective Picture System (AAP), 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 2 min. 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 (DLPFC) and the rostral cingulate zone (RCZ). 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. PMID:27531977

  5. Temporal relation between neural activity and neurite pruning on a numerical model and a microchannel device with micro electrode array.

    PubMed

    Kondo, Yohei; Yada, Yuichiro; Haga, Tatsuya; Takayama, Yuzo; Isomura, Takuya; Jimbo, Yasuhiko; Fukayama, Osamu; Hoshino, Takayuki; Mabuchi, Kunihiko

    2017-04-29

    Synapse elimination and neurite pruning are essential processes for the formation of neuronal circuits. These regressive events depend on neural activity and occur in the early postnatal days known as the critical period, but what makes this temporal specificity is not well understood. One possibility is that the neural activities during the developmentally regulated shift of action of GABA inhibitory transmission lead to the critical period. Moreover, it has been reported that the shifting action of the inhibitory transmission on immature neurons overlaps with synapse elimination and neurite pruning and that increased inhibitory transmission by drug treatment could induce temporal shift of the critical period. However, the relationship among these phenomena remains unclear because it is difficult to experimentally show how the developmental shift of inhibitory transmission influences neural activities and whether the activities promote synapse elimination and neurite pruning. In this study, we modeled synapse elimination in neuronal circuits using the modified Izhikevich's model with functional shifting of GABAergic transmission. The simulation results show that synaptic pruning within a specified period like the critical period is spontaneously generated as a function of the developmentally shifting inhibitory transmission and that the specific firing rate and increasing synchronization of neural circuits are seen at the initial stage of the critical period. This temporal relationship was experimentally supported by an in vitro primary culture of rat cortical neurons in a microchannel on a multi-electrode array (MEA). The firing rate decreased remarkably between the 18-25 days in vitro (DIV), and following these changes in the firing rate, the neurite density was slightly reduced. Our simulation and experimental results suggest that decreasing neural activity due to developing inhibitory synaptic transmission could induce synapse elimination and neurite pruning

  6. Optical and electrical recording of neural activity evoked by graded contrast visual stimulus

    PubMed Central

    Rovati, Luigi; Salvatori, Giorgia; Bulf, Luca; Fonda, Sergio

    2007-01-01

    Background Brain activity has been investigated by several methods with different principles, notably optical ones. Each method may offer information on distinct physiological or pathological aspects of brain function. The ideal instrument to measure brain activity should include complementary techniques and integrate the resultant information. As a "low cost" approach towards this objective, we combined the well-grounded electroencephalography technique with the newer near infrared spectroscopy methods to investigate human visual function. Methods The article describes an embedded instrumentation combining a continuous-wave near-infrared spectroscopy system and an electroencephalography system to simultaneously monitor functional hemodynamics and electrical activity. Near infrared spectroscopy (NIRS) signal depends on the light absorption spectra of haemoglobin and measures the blood volume and blood oxygenation regulation supporting the neural activity. The NIRS and visual evoked potential (VEP) are concurrently acquired during steady state visual stimulation, at 8 Hz, with a b/w "windmill" pattern, in nine human subjects. The pattern contrast is varied (1%, 10%, 100%) according to a stimulation protocol. Results In this study, we present the measuring system; the results consist in concurrent recordings of hemodynamic changes and evoked potential responses emerging from different contrast levels of a patterned stimulus. The concentration of [HbO2] increases and [HHb] decreases after the onset of the stimulus. Their variation shows a clear relationship with the contrast value: large contrast produce huge difference in concentration, while low contrast provokes small concentration difference. This behaviour is similar to the already known relationship between VEP response amplitude and contrast. Conclusion The simultaneous recording and analysis of NIRS and VEP signals in humans during visual stimulation with a b/w pattern at variable contrast, demonstrates a

  7. A High Aspect Ratio Microelectrode Array for Mapping Neural Activity in-vitro

    PubMed Central

    Kibler, Andrew B.; Jamieson, Brian G.; Durand, Dominique M.

    2011-01-01

    A novel high-aspect-ratio penetrating microelectrode array was designed and fabricated for the purpose of recording neural activity. The array allows two dimensional recording of 64 sites in vitro with high aspect ratio penetrating electrodes. Traditional surface electrode arrays, although easy to fabricate, do not penetrate to the viable tissue such as central hippocampus slices and thus have a lower signal/noise ratio and lower selectivity than a penetrating array. In the unfolded hippocampus preparation, the CA1–CA3 pyramidal cell layer in the whole unfolded rodent hippocampus preparation is encased by the alveus on one side and the Schaffer tract on the other and requires penetrating electrodes for high signal to noise ratio recording. An array of 64 electrode spikes, each with a target height of 200 μm and diameter of 20μm, was fabricated in silicon on a transparent glass substrate. The impedance of the individual electrodes was measured to be approximately 1.5MΩ± 497kΩ. The signal to noise ratio was measured and found to be 19.4 ± 3 dB compared to 3.9 ± 0.8 dB S/N for signals obtained with voltage sensitive dye RH414. A mouse unfolded hippocampus preparation was bathed in solution containing 50 micro-molar 4-Amino Pyridine and a complex two dimensional wave of activity was recorded using the array. These results indicate that this novel penetrating electrode array is able to obtain data superior to that of voltage sensitive dye techniques for broad field two-dimensional neuronal activity recording. When used with the unfolded hippocampus preparation, the combination forms a uniquely capable tool for imaging hippocampal network activity in the entire hippocampus. PMID:22179041

  8. Investigating age-related changes in anterior and posterior neural activity throughout the information processing stream

    PubMed Central

    Alperin, Brittany R.; Tusch, Erich S.; Mott, Katherine K.; Holcomb, Phillip J.; Daffner, Kirk R.

    2015-01-01

    Event-related potential (ERP) and other functional imaging studies often demonstrate age-related increases in anterior neural activity and decreases in posterior activity while subjects carry out task demands. It remains unclear whether this “anterior shift” is limited to late cognitive operations like those indexed by the P3 component, or is evident during other stages of information processing. The temporal resolution of ERPs provided an opportunity to address this issue. Temporospatial principal component analysis (PCA) was used to identify underlying components that may be obscured by overlapping ERP waveforms. ERPs were measured during a visual oddball task in 26 young, 26 middle-aged, and 29 old subjects who were well-matched for IQ, executive function, education, and task performance. PCA identified six anterior factors peaking between ~140 ms and 810 ms, and four posterior factors peaking between ~300 ms and 810 ms. There was an age-related increase in the amplitude of anterior factors between ~200 and 500 ms, and an age-associated decrease in amplitude of posterior factors after ~ 500 ms. The increase in anterior processing began as early as middle-age, was sustained throughout old age, and appeared to be linear in nature. These results suggest that age-associated increases in anterior activity occur after early sensory processing has taken place, and are most prominent during a period in which attention is being marshaled to evaluate a stimulus. In contrast, age-related decreases in posterior activity manifest during operations involved in stimulus categorization, post-decision monitoring, and preparation for an upcoming event. PMID:26295684

  9. Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

    PubMed

    Wang, Dongshu; Huang, Lihong

    2014-03-01

    In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results.

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

    NASA Astrophysics Data System (ADS)

    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.

  11. Drosophila Grainyhead specifies late programmes of neural proliferation by regulating the mitotic activity and Hox-dependent apoptosis of neuroblasts.

    PubMed

    Cenci, Caterina; Gould, Alex P

    2005-09-01

    The Drosophila central nervous system is generated by stem-cell-like progenitors called neuroblasts. Early in development, neuroblasts switch through a temporal series of transcription factors modulating neuronal fate according to the time of birth. At later stages, it is known that neuroblasts switch on expression of Grainyhead (Grh) and maintain it through many subsequent divisions. We report that the function of this conserved transcription factor is to specify the regionalised patterns of neurogenesis that are characteristic of postembryonic stages. In the thorax, Grh prolongs neural proliferation by maintaining a mitotically active neuroblast. In the abdomen, Grh terminates neural proliferation by regulating the competence of neuroblasts to undergo apoptosis in response to Abdominal-A expression. This study shows how a factor specific to late-stage neural progenitors can regulate the time at which neural proliferation stops, and identifies mechanisms linking it to the Hox axial patterning system.

  12. Optimization of a GCaMP calcium indicator for neural activity imaging.

    PubMed

    Akerboom, Jasper; Chen, Tsai-Wen; Wardill, Trevor J; Tian, Lin; Marvin, Jonathan S; Mutlu, Sevinç; Calderón, Nicole Carreras; Esposti, Federico; Borghuis, Bart G; Sun, Xiaonan Richard; Gordus, Andrew; Orger, Michael B; Portugues, Ruben; Engert, Florian; Macklin, John J; Filosa, Alessandro; Aggarwal, Aman; Kerr, Rex A; Takagi, Ryousuke; Kracun, Sebastian; Shigetomi, Eiji; Khakh, Baljit S; Baier, Herwig; Lagnado, Leon; Wang, Samuel S-H; Bargmann, Cornelia I; Kimmel, Bruce E; Jayaraman, Vivek; Svoboda, Karel; Kim, Douglas S; Schreiter, Eric R; Looger, Loren L

    2012-10-03

    Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Recent efforts in protein engineering have significantly increased the performance of GECIs. The state-of-the art single-wavelength GECI, GCaMP3, has been deployed in a number of model organisms and can reliably detect three or more action potentials in short bursts in several systems in vivo. Through protein structure determination, targeted mutagenesis, high-throughput screening, and a battery of in vitro assays, we have increased the dynamic range of GCaMP3 by severalfold, creating a family of "GCaMP5" sensors. We tested GCaMP5s in several systems: cultured neurons and astrocytes, mouse retina, and in vivo in Caenorhabditis chemosensory neurons, Drosophila larval neuromuscular junction and adult antennal lobe, zebrafish retina and tectum, and mouse visual cortex. Signal-to-noise ratio was improved by at least 2- to 3-fold. In the visual cortex, two GCaMP5 variants detected twice as many visual stimulus-responsive cells as GCaMP3. By combining in vivo imaging with electrophysiology we show that GCaMP5 fluorescence provides a more reliable measure of neuronal activity than its predecessor GCaMP3. GCaMP5 allows more sensitive detection of neural activity in vivo and may find widespread applications for cellular imaging in general.

  13. Optimization of a GCaMP calcium indicator for neural activity imaging

    PubMed Central

    Akerboom, Jasper; Chen, Tsai-Wen; Wardill, Trevor J.; Tian, Lin; Marvin, Jonathan S.; Mutlu, Sevinç; Calderón, Nicole Carreras; Esposti, Federico; Borghuis, Bart G.; Sun, Xiaonan Richard; Gordus, Andrew; Orger, Michael B.; Portugues, Ruben; Engert, Florian; Macklin, John J.; Filosa, Alessandro; Aggarwal, Aman; Kerr, Rex; Takagi, Ryousuke; Kracun, Sebastian; Shigetomi, Eiji; Khakh, Baljit S.; Baier, Herwig; Lagnado, Leon; Wang, Samuel S.-H.; Bargmann, Cornelia I.; Kimmel, Bruce E.; Jayaraman, Vivek; Svoboda, Karel; Kim, Douglas S.; Schreiter, Eric R.; Looger, Loren L.

    2012-01-01

    Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Recent efforts in protein engineering have significantly increased the performance of GECIs. The state-of-the art single-wavelength GECI, GCaMP3, has been deployed in a number of model organisms and can reliably detect three or more action potentials (APs) in short bursts in several systems in vivo. Through protein structure determination, targeted mutagenesis, high-throughput screening, and a battery of in vitro assays, we have increased the dynamic range of GCaMP3 by several-fold, creating a family of “GCaMP5” sensors. We tested GCaMP5s in several systems: cultured neurons and astrocytes, mouse retina, and in vivo in Caenorhabditis chemosensory neurons, Drosophila larval neuromuscular junction and adult antennal lobe, zebrafish retina and tectum, and mouse visual cortex. Signal-to-noise ratio was improved by at least 2–3-fold. In the visual cortex, two GCaMP5 variants detected twice as many visual stimulus-responsive cells as GCaMP3. By combining in vivo imaging with electrophysiology we show that GCaMP5 fluorescence provides a more reliable measure of neuronal activity than its predecessor GCaMP3. GCaMP5 allows more sensitive detection of neural activity in vivo and may find widespread applications for cellular imaging in general. PMID:23035093

  14. Neural substrates of contextual interference during motor learning support a model of active preparation.

    PubMed

    Cross, Emily S; Schmitt, Paul J; Grafton, Scott T

    2007-11-01

    When individuals acquire new skills, initial performance is typically better and tasks are judged to be easier when the tasks are segregated and practiced by block, compared to when different tasks are randomly intermixed in practice. However, subsequent skill retention is better for a randomly practiced group, an effect known as contextual interference (CI). The present study examined the neural substrates of CI using functional magnetic resonance imaging (fMRI). Individuals learned a set of three 4-element sequences with the left hand according to a block or random practice schedule. Behavioral retest for skill retention confirmed the presence of a typical CI effect with the random group outperforming the block group. Using a go/no-go fMRI paradigm, sequence preparation during the premovement study period was separated from movement execution. Imaging data for the two groups were compared for the first 1/3 and final 1/3 of training trials. Toward the end of training, behavioral performance between the two groups was similar, although the random group would later display a performance advantage on retention testing. During study time, the random group showed greater activity in sensorimotor and premotor regions compared to the block group. These areas are associated with motor preparation, sequencing, and response selection. This pattern of recruitment is consistent with the hypothesis that CI benefits in a sequencing task are due to improved capacity to actively prepare motor responses.

  15. Beautiful friendship: Social sharing of emotions improves subjective feelings and activates the neural reward circuitry.

    PubMed

    Wagner, Ullrich; Galli, Lisa; Schott, Björn H; Wold, Andrew; van der Schalk, Job; Manstead, Antony S R; Scherer, Klaus; Walter, Henrik

    2015-06-01

    Humans have a strong tendency to affiliate with other people, especially in emotional situations. Here, we suggest that a critical mechanism underlying this tendency is that socially sharing emotional experiences is in itself perceived as hedonically positive and thereby contributes to the regulation of individual emotions. We investigated the effect of social sharing of emotions on subjective feelings and neural activity by having pairs of friends view emotional (negative and positive) and neutral pictures either alone or with the friend. While the two friends remained physically separated throughout the experiment-with one undergoing functional magnetic resonance imaging and the other performing the task in an adjacent room-they were made aware on a trial-by-trial basis whether they were seeing pictures simultaneously with their friend (shared) or alone (unshared). Ratings of subjective feelings were improved significantly when participants viewed emotional pictures together than alone, an effect that was accompanied by activity increase in ventral striatum and medial orbitofrontal cortex, two important components of the reward circuitry. Because these effects occurred without any communication or interaction between the friends, they point to an important proximate explanation for the basic human motivation to affiliate with others, particularly in emotional situations.

  16. Beautiful friendship: Social sharing of emotions improves subjective feelings and activates the neural reward circuitry

    PubMed Central

    Galli, Lisa; Schott, Björn H.; Wold, Andrew; van der Schalk, Job; Manstead, Antony S. R.; Scherer, Klaus; Walter, Henrik

    2015-01-01

    Humans have a strong tendency to affiliate with other people, especially in emotional situations. Here, we suggest that a critical mechanism underlying this tendency is that socially sharing emotional experiences is in itself perceived as hedonically positive and thereby contributes to the regulation of individual emotions. We investigated the effect of social sharing of emotions on subjective feelings and neural activity by having pairs of friends view emotional (negative and positive) and neutral pictures either alone or with the friend. While the two friends remained physically separated throughout the experiment—with one undergoing functional magnetic resonance imaging and the other performing the task in an adjacent room—they were made aware on a trial-by-trial basis whether they were seeing pictures simultaneously with their friend (shared) or alone (unshared). Ratings of subjective feelings were improved significantly when participants viewed emotional pictures together than alone, an effect that was accompanied by activity increase in ventral striatum and medial orbitofrontal cortex, two important components of the reward circuitry. Because these effects occurred without any communication or interaction between the friends, they point to an important proximate explanation for the basic human motivation to affiliate with others, particularly in emotional situations. PMID:25298009

  17. The effects of inhibitory control training for preschoolers on reasoning ability and neural activity.

    PubMed

    Liu, Qian; Zhu, Xinyi; Ziegler, Albert; Shi, Jiannong

    2015-09-23

    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 training group (N = 20; 12 boys, mean age 4.87 ± 0.26 years) played "Fruit Ninja" on a tablet computer for 15 min/day, 4 days/week, for 3 weeks. Children in the active control group (N = 20; 10 boys, mean age 4.88 ± 0.20 years) played a coloring game on a tablet computer for 10 min/day, 1-2 days/week, for 3 weeks. Several cognitive tasks (involving inhibitory control, working memory, and fluid intelligence) were used to evaluate the transfer effects, and electroencephalography (EEG) was performed during a go/no-go task. Progress on the trained game was significant, while performance on a reasoning task (Raven's Progressive Matrices) revealed a trend-level improvement from pre- to post-test. EEG indicated that the N2 effect of the go/no-go task was enhanced after training for girls. This study is the first to show that pure response inhibition training can potentially improve reasoning ability. Furthermore, gender differences in the training-induced changes in neural activity were found in preschoolers.

  18. Adaptation to New Microphones Using Artificial Neural Networks With Trainable Activation Functions.

    PubMed

    Siniscalchi, Sabato Marco; Salerno, Valerio Mario

    2016-04-14

    Model adaptation is a key technique that enables a modern automatic speech recognition (ASR) system to adjust its parameters, using a small amount of enrolment data, to the nuances in the speech spectrum due to microphone mismatch in the training and test data. In this brief, we investigate four different adaptation schemes for connectionist (also known as hybrid) ASR systems that learn microphone-specific hidden unit contributions, given some adaptation material. This solution is made possible adopting one of the following schemes: 1) the use of Hermite activation functions; 2) the introduction of bias and slope parameters in the sigmoid activation functions; 3) the injection of an amplitude parameter specific for each sigmoid unit; or 4) the combination of 2) and 3). Such a simple yet effective solution allows the adapted model to be stored in a small-sized storage space, a highly desirable property of adaptation algorithms for deep neural networks that are suitable for large-scale online deployment. Experimental results indicate that the investigated approaches reduce word error rates on the standard Spoke 6 task of the Wall Street Journal corpus compared with unadapted ASR systems. Moreover, the proposed adaptation schemes all perform better than simple multicondition training and comparable favorably against conventional linear regression-based approaches while using up to 15 orders of magnitude fewer parameters. The proposed adaptation strategies are also effective when a single adaptation sentence is available.

  19. Higher-order correlations in common input shapes the output spiking activity of a neural population

    NASA Astrophysics Data System (ADS)

    Montangie, Lisandro; Montani, Fernando

    2017-04-01

    Recent neurophysiological experiments suggest that populations of neurons use a computational scheme in which spike timing is regulated by common non-Gaussian inputs across neurons. The presence of beyond-pairwise correlations in the neuronal inputs and the spiking outputs following a non-Gaussian statistics elicits the need of developing a new theoretical framework taking into account the complexity of synchronous activity patterns. To this end, we quantify the amount of higher-order correlations in the common neuronal inputs and outputs of a population of neurons. We provide a novel formalism, of easy numerical implementation, that can capture the subtle changes of the inputs heterogeneities. Within our approach, correlations across neurons arise from q-Gaussian inputs into threshold neurons and higher-order correlations in the spiking outputs activity are quantified by the parameter q. We present an exhaustive analysis of how input statistics are transformed in this threshold process into output statistics, and we show under which conditions higher-order correlations can lead to either bigger or smaller number of synchronized spikes in the neural population outputs.

  20. Strong geomagnetic activity forecast by neural networks under dominant southern orientation of the interplanetary magnetic field

    NASA Astrophysics Data System (ADS)

    Valach, Fridrich; Bochníček, Josef; Hejda, Pavel; Revallo, Miloš

    2014-02-01

    The paper deals with the relation of the southern orientation of the north-south component Bz of the interplanetary magnetic field to geomagnetic activity (GA) and subsequently a method is suggested of using the found facts to forecast potentially dangerous high GA. We have found that on a day with very high GA hourly averages of Bz with a negative sign occur at least 16 times in typical cases. Since it is very difficult to estimate the orientation of Bz in the immediate vicinity of the Earth one day or even a few days in advance, we have suggested using a neural-network model, which assumes the worse of the possibilities to forecast the danger of high GA - the dominant southern orientation of the interplanetary magnetic field. The input quantities of the proposed model were information about X-ray flares, type II and IV radio bursts as well as information about coronal mass ejections (CME). In comparing the GA forecasts with observations, we obtain values of the Hanssen-Kuiper skill score ranging from 0.463 to 0.727, which are usual values for similar forecasts of space weather. The proposed model provides forecasts of potentially dangerous high geomagnetic activity should the interplanetary CME (ICME), the originator of geomagnetic storms, hit the Earth under the most unfavorable configuration of cosmic magnetic fields. We cannot know in advance whether the unfavorable configuration is going to occur or not; we just know that it will occur with the probability of 31%.

  1. The effects of inhibitory control training for preschoolers on reasoning ability and neural activity

    PubMed Central

    Liu, Qian; Zhu, Xinyi; Ziegler, Albert; Shi, Jiannong

    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 training group (N = 20; 12 boys, mean age 4.87 ± 0.26 years) played “Fruit Ninja” on a tablet computer for 15 min/day, 4 days/week, for 3 weeks. Children in the active control group (N = 20; 10 boys, mean age 4.88 ± 0.20 years) played a coloring game on a tablet computer for 10 min/day, 1–2 days/week, for 3 weeks. Several cognitive tasks (involving inhibitory control, working memory, and fluid intelligence) were used to evaluate the transfer effects, and electroencephalography (EEG) was performed during a go/no-go task. Progress on the trained game was significant, while performance on a reasoning task (Raven’s Progressive Matrices) revealed a trend-level improvement from pre- to post-test. EEG indicated that the N2 effect of the go/no-go task was enhanced after training for girls. This study is the first to show that pure response inhibition training can potentially improve reasoning ability. Furthermore, gender differences in the training-induced changes in neural activity were found in preschoolers. PMID:26395158

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

    PubMed Central

    Yang, Zhou; Jackson, Todd; Huang, Chengzhi

    2016-01-01

    Fear of pain (FOP) can increase risk for chronic pain and disability but little is known about corresponding neural responses in anticipation of potential pain. In this study, more (10 women, 6 men) and less (7 women, 6 men) pain-fearful groups underwent whole-brain functional magnetic resonance imaging (fMRI) during anticipation of near pain-threshold stimulation. Groups did not differ in the proportion of stimuli judged to be painful but pain-fearful participants reported significantly more state fear prior to stimulus exposure. Within the entire sample, stronger activation was found in several pain perception regions (e.g., bilateral insula, midcingulate cortex (MCC), thalamus, superior frontal gyrus) and visual areas linked to decoding stimulus valences (inferior orbital cortex) during anticipation of “painful” stimuli. Between groups and correlation analyses indicated pain-fearful participants experienced comparatively more activity in regions implicated in evaluating potential threats and processing negative emotions during anticipation (i.e., MCC, mid occipital cortex, superior temporal pole), though group differences were not apparent in most so-called “pain matrix” regions. In sum, trait- and task-based FOP is associated with enhanced responsiveness in regions involved in threat processing and negative affect during anticipation of potentially painful stimulation. PMID:27489536

  3. Experimental evaluation of a neural-oscillator-driven active mass damper system

    NASA Astrophysics Data System (ADS)

    Iba, Daisuke; Hongu, Junichi

    2014-03-01

    This paper proposes a new active dynamic absorber control system for high-rise buildings using a neural oscillator and a map, which estimates the amplitude level of the oscillator, and shows some experimental results by using an apparatus, which realizes the proposed control algorithm. The proposed system decides the travel distance and direction of the auxiliary mass of the dynamic absorber using the output of oscillator, which is the filtering result of structure acceleration responses by the property of the oscillator, and Amplitude-Phase map (AP-map) for estimation of the structural response in specific frequency between synchronization region, and then, transfer the auxiliary mass to the predetermined location by using a position controller. In addition, the developed active dynamic absorber system is mounted on the top of the experimental single degree of freedom structure, which represents high-rise buildings, and consists of the auxiliary mass, a DC motor, a ball screw, a microcomputer, a laser displacement sensor, and an acceleration sensor. The proposed AP-map and the algorithm to determine the travel direction of the mass using the oscillator output are embedded in the microcomputer. This paper starts by illuminating the relation among subsystems of the proposed system with reference to a block diagram, and then, shows experimental responses of the whole system excited by earthquakes to confirm the validity of the proposed system.

  4. Modeling spontaneous activity across an excitable epithelium: Support for a coordination scenario of early neural evolution

    PubMed Central

    de Wiljes, Oltman O.; van Elburg, Ronald A. J.; Biehl, Michael; Keijzer, Fred A.

    2015-01-01

    Internal coordination models hold that early nervous systems evolved in the first place to coordinate internal activity at a multicellular level, most notably the use of multicellular contractility as an effector for motility. A recent example of such a model, the skin brain thesis, suggests that excitable epithelia using chemical signaling are a potential candidate as a nervous system precursor. We developed a computational model and a measure for whole body coordination to investigate the coordinative properties of such excitable epithelia. Using this measure we show that excitable epithelia can spontaneously exhibit body-scale patterns of activation. Relevant factors determining the extent of patterning are the noise level for exocytosis, relative body dimensions, and body size. In smaller bodies whole-body coordination emerges from cellular excitability and bidirectional excitatory transmission alone. Our results show that basic internal coordination as proposed by the skin brain thesis could have arisen in this potential nervous system precursor, supporting that this configuration may have played a role as a proto-neural system and requires further investigation. PMID:26441620

  5. Harnessing neural activity to promote repair of the damaged corticospinal system after spinal cord injury

    PubMed Central

    Martin, John H.

    2016-01-01

    As most spinal cord injuries (SCIs) are incomplete, an important target for promoting neural repair and recovery of lost motor function is to promote the connections of spared descending spinal pathways with spinal motor circuits. Among the pathways, the corticospinal tract (CST) is most associated with skilled voluntary functions in humans and many animals. CST loss, whether at its origin in the motor cortex or in the white matter tracts subcortically and in the spinal cord, leads to movement impairments and paralysis. To restore motor function after injury will require repair of the damaged CST. In this review, I discuss how knowledge of activity-dependent development of the CST—which establishes connectional specificity through axon pruning, axon outgrowth, and synaptic competition among CST terminals—informed a novel activity-based therapy for promoting sprouting of spared CST axons after injur in mature animals. This therapy, which comprises motor cortex electrical stimulation with and without concurrent trans-spinal direct current stimulation, leads to an increase in the gray matter axon length of spared CST axons in the rat spinal cord and, after a pyramidal tract lesion, restoration of skilled locomotor movements. I discuss how this approach is now being applied to a C4 contusion rat model. PMID:27857728

  6. Robust Long-Range Coordination of Spontaneous Neural Activity in Waking, Sleep and Anesthesia.

    PubMed

    Liu, Xiao; Yanagawa, Toru; Leopold, David A; Fujii, Naotaka; Duyn, Jeff H

    2015-09-01

    Although the emerging field of functional connectomics relies increasingly on the analysis of spontaneous fMRI signal covariation to infer the spatial fingerprint of the brain's large-scale functional networks, the nature of the underlying neuro-electrical activity remains incompletely understood. In part, this lack in understanding owes to the invasiveness of electrophysiological acquisition, the difficulty in their simultaneous recording over large cortical areas, and the absence of fully established methods for unbiased extraction of network information from these data. Here, we demonstrate a novel, data-driven approach to analyze spontaneous signal variations in electrocorticographic (ECoG) recordings from nearly entire hemispheres of macaque monkeys. Based on both broadband analysis and analysis of specific frequency bands, the ECoG signals were found to co-vary in patterns that resembled the fMRI networks reported in previous studies. The extracted patterns were robust against changes in consciousness associated with sleep and anesthesia, despite profound changes in intrinsic characteristics of the raw signals, including their spectral signatures. These results suggest that the spatial organization of large-scale brain networks results from neural activity with a broadband spectral feature and is a core aspect of the brain's physiology that does not depend on the state of consciousness.

  7. Neural activation patterns of successful episodic encoding: Reorganization during childhood, maintenance in old age.

    PubMed

    Shing, Yee Lee; Brehmer, Yvonne; Heekeren, Hauke R; Bäckman, Lars; Lindenberger, Ulman

    2016-08-01

    The two-component framework of episodic memory (EM) development posits that the contributions of medial temporal lobe (MTL) and prefrontal cortex (PFC) to successful encoding differ across the lifespan. To test the framework's hypotheses, we compared subsequent memory effects (SME) of 10-12 year-old children, younger adults, and older adults using functional magnetic resonance imaging (fMRI). Memory was probed by cued recall, and SME were defined as regional activation differences during encoding between subsequently correctly recalled versus omitted items. In MTL areas, children's SME did not differ in magnitude from those of younger and older adults. In contrast, children's SME in PFC were weaker than the corresponding SME in younger and older adults, in line with the hypothesis that PFC contributes less to successful encoding in childhood. Differences in SME between younger and older adults were negligible. The present results suggest that, among individuals with high memory functioning, the neural circuitry contributing to successful episodic encoding is reorganized from middle childhood to adulthood. Successful episodic encoding in later adulthood, however, is characterized by the ability to maintain the activation patterns that emerged in young adulthood.

  8. The role of early neural activity in the maturation of turtle retinal function

    PubMed Central

    SERNAGOR, EVELYNE; MEHTA, VANDANA

    2001-01-01

    In the developing vertebrate retina, ganglion cells fire spontaneous bursts of action potentials long before the eye becomes exposed to sensory experience at birth. These early bursts are synchronised between neighbouring retinal ganglion cells (RGCs), yielding unique spatiotemporal patterns: ‘waves’ of activity sweep across large retinal areas every few minutes. Both at retinal and extraretinal levels, these embryonic retinal waves are believed to guide the wiring of the visual system using hebbian mechanisms of synaptic strengthening. In the first part of this review, we recapitulate the evidence for a role of these embryonic spontaneous bursts of activity in shaping developing complex receptive field properties of RGCs in the turtle embryonic retina. We also discuss the role of visual experience in establishing RGC visual functions, and how spontaneous activity and visual experience interact to bring developing receptive fields to maturation. We have hypothesised that the physiological changes associated with development reflect modifications in the dendritic arbours of RGCs, the anatomical substrate of their receptive fields. We demonstrate that there is a temporal correlation between the period of receptive field expansion and that of dendritic growth. Moreover, the immature spontaneous activity contributes to dendritic growth in developing RGCs. Intracellular staining of RGCs reveals, however, that immature receptive fields only rarely show direct correlation with the layout of the corresponding dendritic tree. To investigate the possibility that not only the presence of the spontaneous activity, but even the precise spatiotemporal patterns encoded in retinal waves might contribute to the refinement of retinal neural circuitry, first we must clarify the mechanisms mediating the generation and propagation of these waves across development. In the second part of this review, we present evidence that turtle retinal waves, visualised using calcium imaging

  9. Maternal hyperglycemia activates an ASK1-FoxO3a-caspase 8 pathway that leads to embryonic neural tube defects.

    PubMed

    Yang, Peixin; Li, Xuezheng; Xu, Cheng; Eckert, Richard L; Reece, E Albert; Zielke, Horst Ronald; Wang, Fang

    2013-08-27

    Neural tube defects result from failure to completely close neural tubes during development. Maternal diabetes is a substantial risk factor for neural tube defects, and available evidence suggests that the mechanism that links hyperglycemia to neural tube defects involves oxidative stress and apoptosis. We demonstrated that maternal hyperglycemia correlated with activation of the apoptosis signal-regulating kinase 1 (ASK1) in the developing neural tube, and Ask1 gene deletion was associated with reduced neuroepithelial cell apoptosis and development of neural tube defects. ASK1 activation stimulated the activity of the transcription factor FoxO3a, which increased the abundance of the apoptosis-promoting adaptor protein TRADD, leading to activation of caspase 8. Hyperglycemia-induced apoptosis and the development of neural tube defects were reduced with genetic ablation of either FoxO3a or Casp8 or inhibition of ASK1 by thioredoxin. Examination of human neural tissues affected by neural tube defects revealed increased activation or abundance of ASK1, FoxO3a, TRADD, and caspase 8. Thus, activation of an ASK1-FoxO3a-TRADD-caspase 8 pathway participates in the development of neural tube defects, which could be prevented by inhibiting intermediates in this cascade.

  10. Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

    PubMed

    Wang, Leimin; Shen, Yi; Sheng, Yin

    2016-04-01

    This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is designed to realize the finite-time robust stabilization of DNNs with discontinuous activations and parameter uncertainties, and the upper bound of the settling time functional for stabilization is estimated. Finally, two examples are provided to demonstrate the effectiveness of the theoretical results.

  11. Prediction of arm trajectory from the neural activities of the primary motor cortex with modular connectionist architecture.

    PubMed

    Choi, Kyuwan; Hirose, Hideaki; Sakurai, Yoshio; Iijima, Toshio; Koike, Yasuharu

    2009-11-01

    In our previous study [Koike, Y., Hirose, H., Sakurai, Y., Iijima T., (2006). Prediction of arm trajectory from a small number of neuron activities in the primary motor cortex. Neuroscience Research, 55, 146-153], we succeeded in reconstructing muscle activities from the offline combination of single neuron activities recorded in a serial manner in the primary motor cortex of a monkey and in reconstructing the joint angles from the reconstructed muscle activities during a movement condition using an artificial neural network. However, the joint angles during a static condition were not reconstructed. The difficulties of reconstruction under both static and movement conditions mainly arise due to muscle properties such as the velocity-tension relationship and the length-tension relationship. In this study, in order to overcome the limitations due to these muscle properties, we divided an artificial neural network into two networks: one for movement control and the other for posture control. We also trained the gating network to switch between the two neural networks. As a result, the gating network switched the modules properly, and the accuracy of the estimated angles improved compared to the case of using only one artificial neural network.

  12. Global exponential stability of neural networks with globally Lipschitz continuous activations and its application to linear variational inequality problem.

    PubMed

    Liang, X B; Si, J

    2001-01-01

    This paper investigates the existence, uniqueness, and global exponential stability (GES) of the equilibrium point for a large class of neural networks with globally Lipschitz continuous activations including the widely used sigmoidal activations and the piecewise linear activations. The provided sufficient condition for GES is mild and some conditions easily examined in practice are also presented. The GES of neural networks in the case of locally Lipschitz continuous activations is also obtained under an appropriate condition. The analysis results given in the paper extend substantially the existing relevant stability results in the literature, and therefore expand significantly the application range of neural networks in solving optimization problems. As a demonstration, we apply the obtained analysis results to the design of a recurrent neural network (RNN) for solving the linear variational inequality problem (VIP) defined on any nonempty and closed box set, which includes the box constrained quadratic programming and the linear complementarity problem as the special cases. It can be inferred that the linear VIP has a unique solution for the class of Lyapunov diagonally stable matrices, and that the synthesized RNN is globally exponentially convergent to the unique solution. Some illustrative simulation examples are also given.

  13. The Effects of Simulated Stuttering and Prolonged Speech on the Neural Activation Patterns of Stuttering and Nonstuttering Adults

    ERIC Educational Resources Information Center

    De Nil, Luc F.; Beal, Deryk S.; Lafaille, Sophie J.; Kroll, Robert M.; Crawley, Adrian P.; Gracco, Vincent L.

    2008-01-01

    Functional magnetic resonance imaging was used to investigate the neural correlates of passive listening, habitual speech and two modified speech patterns (simulated stuttering and prolonged speech) in stuttering and nonstuttering adults. Within-group comparisons revealed increased right hemisphere biased activation of speech-related regions…

  14. Activation in Context: Differential Conclusions Drawn from Cross-Sectional and Longitudinal Analyses of Adolescents' Cognitive Control-Related Neural Activity.

    PubMed

    McCormick, Ethan M; Qu, Yang; Telzer, Eva H

    2017-01-01

    Although immature cognitive control, subserved by late-developing prefrontal regions, has been proposed to underlie increased risk taking during adolescence, it remains unclear what patterns of PFC activation represent mature brain states: more or less activation? One challenge to drawing cogent conclusions from extant work stems from its reliance on single-time point neuroimaging and cross-sectional comparisons, which are ill-suited for assessing the complex changes that characterize adolescence. This necessitates longitudinal fMRI work to track within-subject changes in PFC function and links to risk-taking behavior, which can serve as an external marker for maturation of neural systems involved in cognitive control. In the current study, 20 healthy adolescents (13 males) completed a go/nogo task during two fMRI scans, once at age 14 years and again at age 15 years. We found that the association between cognitive control-related VLPFC activation and risk-taking behavior reversed when examining wave 1 (W1) versus longitudinal change (W2 > W1) and wave 2 (W2) in neural activation, such that increased VLPFC activation at W1 was associated with lower risk taking, whereas longitudinal increases in cognitive control-related VLPFC activation as well as heightened VLPFC activation at W2 were associated with greater risk taking. Several steps were taken to disentangle potential alternative accounts that might explain these disparate results across time. Findings highlight the necessity of considering brain-behavior relationships in the context of ongoing developmental changes and suggests that using neuroimaging data at a single time point to predict behavioral changes can introduce interpretation errors when failing to account for changes in neural trajectories.

  15. Activation in Context: Differential Conclusions Drawn from Cross-Sectional and Longitudinal Analyses of Adolescents’ Cognitive Control-Related Neural Activity

    PubMed Central

    McCormick, Ethan M.; Qu, Yang; Telzer, Eva H.

    2017-01-01

    Although immature cognitive control, subserved by late-developing prefrontal regions, has been proposed to underlie increased risk taking during adolescence, it remains unclear what patterns of PFC activation represent mature brain states: more or less activation? One challenge to drawing cogent conclusions from extant work stems from its reliance on single-time point neuroimaging and cross-sectional comparisons, which are ill-suited for assessing the complex changes that characterize adolescence. This necessitates longitudinal fMRI work to track within-subject changes in PFC function and links to risk-taking behavior, which can serve as an external marker for maturation of neural systems involved in cognitive control. In the current study, 20 healthy adolescents (13 males) completed a go/nogo task during two fMRI scans, once at age 14 years and again at age 15 years. We found that the association between cognitive control-related VLPFC activation and risk-taking behavior reversed when examining wave 1 (W1) versus longitudinal change (W2 > W1) and wave 2 (W2) in neural activation, such that increased VLPFC activation at W1 was associated with lower risk taking, whereas longitudinal increases in cognitive control-related VLPFC activation as well as heightened VLPFC activation at W2 were associated with greater risk taking. Several steps were taken to disentangle potential alternative accounts that might explain these disparate results across time. Findings highlight the necessity of considering brain-behavior relationships in the context of ongoing developmental changes and suggests that using neuroimaging data at a single time point to predict behavioral changes can introduce interpretation errors when failing to account for changes in neural trajectories. PMID:28392763

  16. Analysis of neural activity in human motor cortex -- Towards brain machine interface system

    NASA Astrophysics Data System (ADS)

    Secundo, Lavi

    , the correlation of ECoG activity to kinematic parameters of arm movement is context-dependent, an important constraint to consider in future development of BMI systems. The third chapter delves into a fundamental organizational principle of the primate motor system---cortical control of contralateral limb movements. However, ipsilateral motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in ipsilateral primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-out reaching movements, we found that the ensemble spiking activity in M1 could continuously represent ipsilateral limb position. We also recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain-machine interface.

  17. Pituitary Adenlylate Cyclase Activating Peptide Protects Adult Neural Stem Cells from a Hypoglycaemic milieu

    PubMed Central

    Mansouri, Shiva; Lietzau, Grazyna; Lundberg, Mathias; Nathanson, David; Nyström, Thomas; Patrone, Cesare

    2016-01-01

    Hypoglycaemia is a common side-effect of glucose-lowering therapies for type-2 diabetic patients, which may cause cognitive/neurological impairment. Although the effects of hypoglycaemia in the brain have been extensively studied in neurons, how hypoglycaemia impacts the viability of adult neural stem cells (NSCs) has been poorly investigated. In addition, the cellular and molecular mechanisms of how hypoglycaemia regulates NSCs survival have not been characterized. Recent work others and us have shown that the pituitary adenylate cyclase-activating polypeptide (PACAP) and the glucagon-like peptide-1 receptor (GLP-1R) agonist Exendin-4 stimulate NSCs survival against glucolipoapoptosis. The aim of this study was to establish an in vitro system where to study the effects of hypoglycaemia on NSC survival. Furthermore, we determine the potential role of PACAP and Exendin-4 in counteracting the effect of hypoglycaemia. A hypoglycaemic in vitro milieu was mimicked by exposing subventricular zone-derived NSC to low levels of glucose. Moreover, we studied the potential involvement of apoptosis and endoplasmic reticulum stress by quantifying protein levels of Bcl-2, cleaved caspase-3 and mRNA levels of CHOP. We show that PACAP via PAC-1 receptor and PKA activation counteracts impaired NSC viability induced by hypoglycaemia. The protective effect induced by PACAP correlated with endoplasmic reticulum stress, Exendin-4 was ineffective. The results show that hypoglycaemia decreases NSC viability and that this effect can be substantially counteracted by PACAP via PAC-1 receptor activation. The data supports a potential therapeutic role of PAC-1 receptor agonists for the treatment of neurological complications, based on neurogenesis impairment by hypoglycaemia. PMID:27305000

  18. Neural activities in V1 create the bottom-up saliency map of natural scenes.

    PubMed

    Chen, Cheng; Zhang, Xilin; Wang, Yizhou; Zhou, Tiangang; Fang, Fang

    2016-06-01

    A saliency map is the bottom-up contribution to the deployment of exogenous attention. It, as well as its underlying neural mechanism, is hard to identify because of the influence of top-down signals. A recent study showed that neural activities in V1 could create a bottom-up saliency map (Zhang et al. in Neuron 73(1):183-192, 2012). In this paper, we tested whether their conclusion can generalize to complex natural scenes. In order to avoid top-down influences, each image was presented with a low contrast for only 50 ms and was followed by a high contrast mask, which rendered the whole image invisible to participants (confirmed by a forced-choice test). The Posner cueing paradigm was adopted to measure the spatial cueing effect (i.e., saliency) by an orientation discrimination task. A positive cueing effect was found, and the magnitude of the cueing effect was consistent with the saliency prediction of a computational saliency model. In a following fMRI experiment, we used the same masked natural scenes as stimuli and measured BOLD signals responding to the predicted salient region (relative to the background). We found that the BOLD signal in V1, but not in other cortical areas, could well predict the cueing effect. These results suggest that the bottom-up saliency map of natural scenes could be created in V1, providing further evidence for the V1 saliency theory (Li in Trends Cogn Sci 6(1):9-16, 2002).

  19. Hippocalcin Is Required for Astrocytic Differentiation through Activation of Stat3 in Hippocampal Neural Precursor Cells

    PubMed Central

    Kang, Min-Jeong; Park, Shin-Young; Han, Joong-Soo

    2016-01-01

    Hippocalcin (Hpca) is a neuronal calcium sensor protein expressed in the mammalian brain. However, its function in neural stem/precursor cells has not yet been studied. Here, we clarify the function of Hpca in astrocytic differentiation in hippocampal neural precursor cells (HNPCs). When we overexpressed Hpca in HNPCs in the presence or absence of bFGF, expression levels of nerve-growth factors such as neurotrophin-3 (NT-3), neurotrophin-4/5 (NT-4/5), and brain-derived neurotrophic factor (BDNF), together with the proneural basic helix loop helix (bHLH) transcription factors NeuroD and neurogenin 1 (Ngn1), increased significantly. In addition, there was an increase in the number of cells expressing glial fibrillary acidic protein (GFAP), an astrocyte marker, and in branch outgrowth, indicating astrocytic differentiation of the HNPCs. Downregulation of Hpca by transfection with Hpca siRNA reduced expression of NT-3, NT-4/5, BDNF, NeuroD, and Ngn1 as well as levels of GFAP protein. Furthermore, overexpression of Hpca increased the phosphorylation of STAT3 (Ser727), and this effect was abolished by treatment with a STAT3 inhibitor (S3I-201), suggesting that STAT3 (Ser727) activation is involved in Hpca-mediated astrocytic differentiation. As expected, treatment with Stat3 siRNA or STAT3 inhibitor caused a complete inhibition of astrogliogenesis induced by Hpca overexpression. Taken together, this is the first report to show that Hpca, acting through Stat3, has an important role in the expression of neurotrophins and proneural bHLH transcription factors, and that it is an essential regulator of astrocytic differentiation and branch outgrowth in HNPCs. PMID:27840601

  20. Quantifying the Neural Elements Activated and Inhibited by Globus Pallidus Deep Brain Stimulation

    PubMed Central

    Johnson, Matthew D.; McIntyre, Cameron C.

    2008-01-01

    Deep brain stimulation (DBS) of the globus pallidus pars interna (GPi) is an effective therapy option for controlling the motor symptoms of medication-refractory Parkinson's disease and dystonia. Despite the clinical successes of GPi DBS, the precise therapeutic mechanisms are unclear and questions remain on the optimal electrode placement and stimulation parameter selection strategies. In this study, we developed a three-dimensional computational model of GPi-DBS in nonhuman primates to investigate how membrane channel dynamics, synaptic inputs, and axonal collateralization contribute to the neural responses generated during stimulation. We focused our analysis on three general neural elements that surround GPi-DBS electrodes: GPi somatodendritic segments, GPi efferent axons, and globus pallidus pars externa (GPe) fibers of passage. During high-frequency electrical stimulation (136 Hz), somatic activity in the GPi showed interpulse excitatory phases at 1–3 and 4–5.5 ms. When including stimulation-induced GABAA and AMPA receptor dynamics into the model, the somatic firing patterns continued to be entrained to the stimulation, but the overall firing rate was reduced (78.7 to 25.0 Hz, P < 0.001). In contrast, axonal output from GPi neurons remained largely time-locked to each pulse of the stimulation train. Similar entrainment was also observed in GPe efferents, a majority of which have been shown to project through GPi en route to the subthalamic nucleus. The models suggest that pallidal DBS may have broader network effects than previously realized and the modes of therapy may depend on the relative proportion of GPi and/or GPe efferents that are directly affected by the stimulation. PMID:18768645

  1. Neurally released pituitary adenylate cyclase-activating polypeptide enhances guinea pig intrinsic cardiac neurone excitability.

    PubMed

    Tompkins, John D; Ardell, Jeffrey L; Hoover, Donald B; Parsons, Rodney L

    2007-07-01

    Intracellular recordings were made in vitro from guinea-pig cardiac ganglia to determine whether endogenous neuropeptides such as pituitary adenylate cyclase-activating polypeptide (PACAP) or substance P released during tetanic neural stimulation modulate cardiac neurone excitability and/or contribute to slow excitatory postsynaptic potentials (sEPSPs). When nicotinic and muscarinic receptors were blocked by hexamethonium and atropine, 20 Hz stimulation for 10 s initiated a sEPSP in all innervated neurones. In 40% of the cells, excitability was enhanced after termination of the sEPSP. This suggested that non-cholinergic receptor-mediated mechanisms contributed to the sEPSP and modulated neuronal excitability. Exogenous PACAP and substance P initiated a slow depolarization in the neurones whereas neuronal excitability was only increased by PACAP. When ganglia were treated with the PAC1 antagonist PACAP6-38 (500 nM), the sEPSP evoked by 20 Hz stimulation was reduced by approximately 50% and an enhanced excitability occurred in only 10% of the cells. These observations suggested that PACAP released from preganglionic nerve terminals during tetanic stimulation enhanced neuronal excitability and evoked sEPSPs. After addition of 1 nM PACAP to the bath, 7 of 9 neurones exhibited a tonic firing pattern whereas in untreated preparations, the neurons had a phasic firing pattern. PACAP6-38 (500 nM) diminished the increase in excitability caused by 1 nM PACAP so that only 4 of 13 neurones exhibited a tonic firing pattern and the other 9 cells retained a phasic firing pattern. These findings indicate that PACAP can be released by tetanic neural stimulation in vitro and increase the excitability of intrinsic cardiac neurones. We hypothesize that in vivo PACAP released during preganglionic firing may modulate neurotransmission within the intrinsic cardiac ganglia.

  2. Detection of neural activity in the brains of Japanese honeybee workers during the formation of a "hot defensive bee ball".

    PubMed

    Ugajin, Atsushi; Kiya, Taketoshi; Kunieda, Takekazu; Ono, Masato; Yoshida, Tadaharu; Kubo, Takeo

    2012-01-01

    Anti-predator behaviors are essential to survival for most animals. The neural bases of such behaviors, however, remain largely unknown. Although honeybees commonly use their stingers to counterattack predators, the Japanese honeybee (Apis cerana japonica) uses a different strategy to fight against the giant hornet (Vespa mandarinia japonica). Instead of stinging the hornet, Japanese honeybees form a "hot defensive bee ball" by surrounding the hornet en masse, killing it with heat. The European honeybee (A. mellifera ligustica), on the other hand, does not exhibit this behavior, and their colonies are often destroyed by a hornet attack. In the present study, we attempted to analyze the neural basis of this behavior by mapping the active brain regions of Japanese honeybee workers during the formation of a hot defensive bee ball. First, we identified an A. cerana homolog (Acks = Apis cerana kakusei) of kakusei, an immediate early gene that we previously identified from A. mellifera, and showed that Acks has characteristics similar to kakusei and can be used to visualize active brain regions in A. cerana. Using Acks as a neural activity marker, we demonstrated that neural activity in the mushroom bodies, especially in Class II Kenyon cells, one subtype of mushroom body intrinsic neurons, and a restricted area between the dorsal lobes and the optic lobes was increased in the brains of Japanese honeybee workers involved in the formation of a hot defensive bee ball. In addition, workers exposed to 46°C heat also exhibited Acks expression patterns similar to those observed in the brains of workers involved in the formation of a hot defensive bee ball, suggesting that the neural activity observed in the brains of workers involved in the hot defensive bee ball mainly reflects thermal stimuli processing.

  3. Forecasting geomagnetic activity indices using the Boyle index through artificial neural networks

    NASA Astrophysics Data System (ADS)

    Balasubramanian, Ramkumar

    2010-11-01

    Adverse space weather conditions affect various sectors making both human lives and technologies highly susceptible. This dissertation introduces a new set of algorithms suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp, Dst and the AE index over some leading models. Kp is a 3-hour averaged global geomagnetic activity index good for midlatitude regions. The Dst index, an hourly index calculated using four ground based magnetic field measurements near the equator, measures the energy of the Earth's ring current. The Auroral Electrojet indices or AE indices are hourly indices used to characterize the global geomagnetic activity in the auroral zone. Our algorithms can predict these indices purely from the solar wind data with lead times up to 6 hours. We have trained and tested an ANN (Artificial Neural Network) over a complete solar cycle to serve this purpose. Over the last couple of decades, ANNs have been successful for temporal prediction problems amongst other advanced non-linear techniques. Our ANN-based algorithms receive near-real-time inputs either from ACE (Advanced Composition Explorer), located at L1, and a handful of ground-based magnetometers or only from ACE. The Boyle potential, phi = 10-4 (vkm/sec)2+ 11.7BnT sin3 (theta/2) kV, or the Boyle Index (BI) is an empirically-derived formula that approximates the Earth's polar cap potential and is easily derivable in real time using the solar wind data from ACE. The logarithms of both 3-hour and 1-hour averages of the Boyle Index correlate well with the subsequent Kp, Dst and AE: Kp = 8.93 log 10 - 12.55. Dst = 0.355 - 6.48, and AE = 5.87 - 83.46. Inputs to our ANN models have greatly benefitted from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. A preconditioning event tunes the magnetosphere to a specific state before an impending geomagnetic storm. The neural net not only improves the

  4. Mechanical and/or neural activity-dependent regulation of soleus muscle fibers of mdx mice

    NASA Astrophysics Data System (ADS)

    Terada, Masahiro; Kawano, Fuminori; Lan, Yong Bo; Matsuoka, Yoshikazu; Wang, Xiao Dong; Ohira, Yoshinobu

    2005-08-01

    Roles of mechanical and/or neural activity in the necrosis -regeneration cycle in the soleus muscle fibers of mdxmicewerestudied. Five-weeks-oldmalemdxand wild type (WT) mice were separated into tenotomy (T), denervation (D), and T+D groups. The distal tendons of the left plantarflexors (soleus, plantaris, and gastrocnemius) were ablated in the T group. The left sciatic nerve was transected at the gluteal region in the D group. The right limb was kept intact as the normal control. Ambulation was allowed after the surgery. Soleus muscle was sampled 14 days after the surgery and analyses were performed in cross-section of whole muscle and in single fibers removed longitudinally. The total fiber number of the untreated muscle was 913±19 (Mean±SEM) and 872±45 in WT and mdx mice, respectively. The fiber number in mdx mice was decreased 48% by T and 31-35% by D and T+D, which induced fiber atrophy, may be due to either inhibited regeneration or stimulated necrosis. Although fibers with central nuclei or necrosis were not observed in WT muscle, 25-40% of fibers (vs. 40% in the contralateral control side) in treated muscles of mdx mice, analyzed cross-sectionally, were central-nucleated. However, fibers with only central nuclei were not detected in the longitudinally isolated fibers of treated groups, may be due to the phenomenon that the fibers with necrosis were lost in the relaxing solution. But % fibers with both central and peripheral nuclei were decreased and those with peripheral nuclei alone were increased by T. In both cross-sectional and longitudinal analyses, the % distribution of the central-nucleated relative to total fiber number was not affected by D, but decreased by T in mdx mice (p>0.05). Myonuclear number per mm of fiber length was identical generally, although the number was increased by T. Furthermore, DNA fragmentation was noted in the mdx fibers with necrosis. These data suggested that the localization of myonuclei, as well as either necrosis or

  5. Early olfactory experience modifies neural activity in the antennal lobe of a social insect at the adult stage.

    PubMed

    Arenas, A; Giurfa, M; Farina, W M; Sandoz, J C

    2009-10-01

    In the antennal lobe (AL), the first olfactory centre of the insect brain, odorants are represented as spatiotemporal patterns of glomerular activity. Whether and how such patterns are modified in the long term after precocious olfactory experiences (i.e. in the first days of adulthood) remains unknown. To address this question, we used in vivo optical imaging of calcium activity in the antennal lobe of 17-day-old honeybees which either experienced an odorant associated with sucrose solution 5-8 days after emergence or were left untreated. In both cases, we imaged neural responses to the learned odor and to three novel odors varying in functional group and carbon-chain length. Two different odor concentrations were used. We also measured behavioral responses of 17-day-old honeybees, treated and untreated, to these stimuli. We show that precocious olfactory experience increased general odor-induced activity and the number of activated glomeruli in the adult AL, but also affected qualitative odor representations, which appeared shifted in the neural space of treated animals relative to control animals. Such effects were not limited to the experienced odor, but were generalized to other perceptually similar odors. A similar trend was found in behavioral experiments, in which increased responses to the learned odor extended to perceptually similar odors in treated bees. Our results show that early olfactory experiences have long-lasting effects, reflected in behavioral responses to odorants and concomitant neural activity in the adult olfactory system.

  6. Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

    PubMed

    Nie, Xiaobing; Zheng, Wei Xing

    2015-05-01

    This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results.

  7. Neural activity in macaque parietal cortex reflects temporal integration of visual motion signals during perceptual decision making.

    PubMed

    Huk, Alexander C; Shadlen, Michael N

    2005-11-09

    Decision-making often requires the accumulation and maintenance of evidence over time. Although the neural signals underlying sensory processing have been studied extensively, little is known about how the brain accrues and holds these sensory signals to guide later actions. Previous work has suggested that neural activity in the lateral intraparietal area (LIP) of the monkey brain reflects the formation of perceptual decisions in a random dot direction-discrimination task in which monkeys communicate their decisions with eye-movement responses. We tested the hypothesis that decision-related neural activity in LIP represents the time integral of the momentary motion "evidence." By briefly perturbing the strength of the visual motion stimulus during the formation of perceptual decisions, we tested whether this LIP activity reflected a persistent, integrated "memory" of these brief sensory events. We found that the responses of LIP neurons reflected substantial temporal integration. Brief pulses had persistent effects on both the monkeys' choices and the responses of neurons in LIP, lasting up to 800 ms after appearance. These results demonstrate that LIP is involved in neural time integration underlying the accumulation of evidence in this task. Additional analyses suggest that decision-related LIP responses, as well as behavioral choices and reaction times, can be explained by near-perfect time integration that stops when a criterion amount of evidence has been accumulated. Temporal integration may be a fundamental computation underlying higher cognitive functions that are dissociated from immediate sensory inputs or motor outputs.

  8. Temporal coherency between receptor expression, neural activity and AP-1-dependent transcription regulates Drosophila motoneuron dendrite development.

    PubMed

    Vonhoff, Fernando; Kuehn, Claudia; Blumenstock, Sonja; Sanyal, Subhabrata; Duch, Carsten

    2013-02-01

    Neural activity has profound effects on the development of dendritic structure. Mechanisms that link neural activity to nuclear gene expression include activity-regulated factors, such as CREB, Crest or Mef2, as well as activity-regulated immediate-early genes, such as fos and jun. This study investigates the role of the transcriptional regulator AP-1, a Fos-Jun heterodimer, in activity-dependent dendritic structure development. We combine genetic manipulation, imaging and quantitative dendritic architecture analysis in a Drosophila single neuron model, the individually identified motoneuron MN5. First, Dα7 nicotinic acetylcholine receptors (nAChRs) and AP-1 are required for normal MN5 dendritic growth. Second, AP-1 functions downstream of activity during MN5 dendritic growth. Third, using a newly engineered AP-1 reporter we demonstrate that AP-1 transcriptional activity is downstream of Dα7 nAChRs and Calcium/calmodulin-dependent protein kinase II (CaMKII) signaling. Fourth, AP-1 can have opposite effects on dendritic development, depending on the timing of activation. Enhancing excitability or AP-1 activity after MN5 cholinergic synapses and primary dendrites have formed causes dendritic branching, whereas premature AP-1 expression or induced activity prior to excitatory synapse formation disrupts dendritic growth. Finally, AP-1 transcriptional activity and dendritic growth are affected by MN5 firing only during development but not in the adult. Our results highlight the importance of timing in the growth and plasticity of neuronal dendrites by defining a developmental period of activity-dependent AP-1 induction that is temporally locked to cholinergic synapse formation and dendritic refinement, thus significantly refining prior models derived from chronic expression studies.

  9. Trichothecenes induce accumulation of glucosylceramide in neural cells by interfering with lactosylceramide synthase activity

    SciTech Connect

    Kralj, Ana; Gurgui, Mihaela; Koenig, Gabriele M.; Echten-Deckert, Gerhild van

    2007-11-15

    Trichothecenes are sesquiterpenoid metabolites produced by several fungal strains that impair human and animal health. Since sphingolipids were connected with fungal toxicity the aim of the present study was to test the influence of fungal metabolites on sphingolipid metabolism in neural cells. The crude extract of fungal strain Spicellum roseum induced accumulation of glucosylceramide (GlcCer), and simultaneous reduction of the formation of lactosylceramide (LacCer) and complex gangliosides in primary cultured neurons. Following a bioassay-guided fractionation of the respective fungal extract we could demonstrate that the two isolated trichothecene derivatives, 8-deoxy-trichothecin (8-dT) and trichodermol (Td-ol) were responsible for this effect. Thus, incubation of primary cultured neurons as well as of neuroblastoma B104 cells for 24 h with 30 {mu}M of either of the two fungal metabolites resulted in uncoupling of sphingolipid biosynthesis at the level of LacCer. For the observed reduction of LacCer synthase activity by about 90% cell integrity was crucial in both cell types. In neuroblastoma cells the amount of LacCer synthase mRNA was reduced in the presence of trichothecenes, whereas in primary cultured neurons this was not the case, suggesting a post-transcriptional mechanism of action in the latter cell type. The data also show that the compounds did not interfere with the translocation of GlcCer in neuroblastoma cells. Collectively, our results demonstrate that trichodermol and 8-deoxy-trichothecin inhibit LacCer synthase activity in a cell-type-specific manner.

  10. Genetically encoded calcium indicators for multi-color neural activity imaging and combination with optogenetics

    PubMed Central

    Akerboom, Jasper; Carreras Calderón, Nicole; Tian, Lin; Wabnig, Sebastian; Prigge, Matthias; Tolö, Johan; Gordus, Andrew; Orger, Michael B.; Severi, Kristen E.; Macklin, John J.; Patel, Ronak; Pulver, Stefan R.; Wardill, Trevor J.; Fischer, Elisabeth; Schüler, Christina; Chen, Tsai-Wen; Sarkisyan, Karen S.; Marvin, Jonathan S.; Bargmann, Cornelia I.; Kim, Douglas S.; Kügler, Sebastian; Lagnado, Leon; Hegemann, Peter; Gottschalk, Alexander; Schreiter, Eric R.; Looger, Loren L.

    2013-01-01

    Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Here we describe red, single-wavelength GECIs, “RCaMPs,” engineered from circular permutation of the thermostable red fluorescent protein mRuby. High-resolution crystal structures of mRuby, the red sensor RCaMP, and the recently published red GECI R-GECO1 give insight into the chromophore environments of the Ca2+-bound state of the sensors and the engineered protein domain interfaces of the different indicators. We characterized the biophysical properties and performance of RCaMP sensors in vitro and in vivo in Caenorhabditis elegans, Drosophila larvae, and larval zebrafish. Further, we demonstrate 2-color calcium imaging both within the same cell (registering mitochondrial and somatic [Ca2+]) and between two populations of cells: neurons and astrocytes. Finally, we perform integrated optogenetics experiments, wherein neural activation via channelrhodopsin-2 (ChR2) or a red-shifted variant, and activity imaging via RCaMP or GCaMP, are conducted simultaneously, with the ChR2/RCaMP pair providing independently addressable spectral channels. Using this paradigm, we measure calcium responses of naturalistic and ChR2-evoked muscle contractions in vivo in crawling C. elegans. We systematically compare the RCaMP sensors to R-GECO1, in terms of action potential-evoked fluorescence increases in neurons, photobleaching, and photoswitching. R-GECO1 displays higher Ca2+ affinity and larger dynamic range than RCaMP, but exhibits significant photoactivation with blue and green light, suggesting that integrated channelrhodopsin-based optogenetics using R-GECO1 may be subject to artifact. Finally, we create and test blue, cyan, and yellow variants engineered from GCaMP by rational design. This engineered set of chromatic variants facilitates new experiments in functional imaging and optogenetics. PMID:23459413

  11. Characterization of calcium responses and electrical activity in differentiating mouse neural progenitor cells in vitro.

    PubMed

    de Groot, Martje W G D M; Dingemans, Milou M L; Rus, Katinka H; de Groot, Aart; Westerink, Remco H S

    2014-02-01

    In vitro methods for developmental neurotoxicity (DNT) testing have the potential to reduce animal use and increase insight into cellular and molecular mechanisms underlying chemical-induced alterations in the development of functional neuronal networks. Mouse neural progenitor cells (mNPCs) differentiate into nervous system-specific cell types and have proven valuable to detect DNT using biochemical and morphological techniques. We therefore investigated a number of functional neuronal parameters in primary mNPCs to explore their applicability for neurophysiological in vitro DNT testing. Immunocytochemistry confirmed that mNPCs express neuronal, glial, and progenitor markers at various differentiation durations (1, 7, 14, and 21 days). Because intracellular calcium ([Ca(2+)]i) plays an essential role in neuronal development and function, we measured stimulus-evoked changes in [Ca(2+)]i at these differentiation durations using the Ca(2+)-responsive dye Fura-2. Increases in [Ca(2+)]i (averages ranging from 65 to 226 nM) were evoked by depolarization, ATP, l-glutamic acid, acetylcholine, and dopamine (up to 87%, 57%, 93%, 28%, and 37% responding cells, respectively) and to a lesser extent by serotonin and gamma-aminobutyric acid (both up to 10% responding cells). Notably, the changes in percentage of responsive cells and their response amplitudes over time indicate changes in the expression and functionality of the respective neurotransmitter receptors and related calcium signaling pathways during in vitro differentiation. The development of functional intercellular signaling pathways was confirmed using multielectrode arrays, demonstrating that mNPCs develop electrical activity within 1-2 weeks of differentiation (55% active wells at 14 days of differentiation; mean spike rate of 1.16 spikes/s/electrode). The combined data demonstrate that mNPCs develop functional neuronal characteristics in vitro, making it a promising model to study chemical-induced effects on the

  12. Neural networks to simulate regional ground water levels affected by human activities.

    PubMed

    Feng, Shaoyuan; Kang, Shaozhong; Huo, Zailin; Chen, Shaojun; Mao, Xiaomin

    2008-01-01

    In arid regions, human activities like agriculture and industry often require large ground water extractions. Under these circumstances, appropriate ground water management policies are essential for preventing aquifer overdraft, and thereby protecting critical ecologic and economic objectives. Identification of such policies requires accurate simulation capability of the ground water system in response to hydrological, meteorological, and human factors. In this research, artificial neural networks (ANNs) were developed and applied to investigate the effects of these factors on ground water levels in the Minqin oasis, located in the lower reach of Shiyang River Basin, in Northwest China. Using data spanning 1980 through 1997, two ANNs were developed to model and simulate dynamic ground water levels for the two subregions of Xinhe and Xiqu. The ANN models achieved high predictive accuracy, validating to 0.37 m or less mean absolute error. Sensitivity analyses were conducted with the models demonstrating that agricultural ground water extraction for irrigation is the predominant factor responsible for declining ground water levels exacerbated by a reduction in regional surface water inflows. ANN simulations indicate that it is necessary to reduce the size of the irrigation area to mitigate ground water level declines in the oasis. Unlike previous research, this study demonstrates that ANN modeling can capture important temporally and spatially distributed human factors like agricultural practices and water extraction patterns on a regional basin (or subbasin) scale, providing both high-accuracy prediction capability and enhanced understanding of the critical factors influencing regional ground water conditions.

  13. Social information and personal interests modulate neural activity during economic decision-making

    PubMed Central

    Moser, Anna; Gaertig, Celia; Ruz, María

    2014-01-01

    In the present study we employed electrophysiological recordings to investigate the levels of processing at which positive and negative descriptions of other people bias social decision-making in a game in which participants accepted or rejected economic offers. Besides social information, we manipulated the fairness of the assets distribution, whether offers were advantageous or not for the participant and the uncertainty of the game context. Results show that a negative description of the interaction partner enhanced the medial frontal negativity (MFN) in an additive manner with fairness evaluations. The description of the partner interacted with personal benefit considerations, showing that this positive or negative information only biased the evaluation of offers when they did not favor the participant. P300 amplitudes were enhanced by advantageous offers, suggesting their heightened motivational significance at later stages of processing. Throughout all stages, neural activity was enhanced with certainty about the personal assignments of the split. These results provide new evidence on the importance of interpersonal information and considerations of self-interests relative to others in decision-making situations. PMID:24567708

  14. The Lysine Acetyltransferase Activator Brpf1 Governs Dentate Gyrus Development through Neural Stem Cells and Progenitors

    PubMed Central

    You, Linya; Yan, Kezhi; Zhou, Jinfeng; Zhao, Hong; Bertos, Nicholas R.; Park, Morag; Wang, Edwin; Yang, Xiang-Jiao

    2015-01-01

    Lysine acetylation has recently emerged as an important post-translational modification in diverse organisms, but relatively little is known about its roles in mammalian development and stem cells. Bromodomain- and PHD finger-containing protein 1 (BRPF1) is a multidomain histone binder and a master activator of three lysine acetyltransferases, MOZ, MORF and HBO1, which are also known as KAT6A, KAT6B and KAT7, respectively. While the MOZ and MORF genes are rearranged in leukemia, the MORF gene is also mutated in prostate and other cancers and in four genetic disorders with intellectual disability. Here we show that forebrain-specific inactivation of the mouse Brpf1 gene causes hypoplasia in the dentate gyrus, including underdevelopment of the suprapyramidal blade and complete loss of the infrapyramidal blade. We trace the developmental origin to compromised Sox2+ neural stem cells and Tbr2+ intermediate neuronal progenitors. We further demonstrate that Brpf1 loss deregulates neuronal migration, cell cycle progression and transcriptional control, thereby causing abnormal morphogenesis of the hippocampus. These results link histone binding and acetylation control to hippocampus development and identify an important epigenetic regulator for patterning the dentate gyrus, a brain structure critical for learning, memory and adult neurogenesis. PMID:25757017

  15. A mathematical model relating cortical oxygenated and deoxygenated hemoglobin flows and volumes to neural activity

    NASA Astrophysics Data System (ADS)

    Cornelius, Nathan R.; Nishimura, Nozomi; Suh, Minah; Schwartz, Theodore H.; Doerschuk, Peter C.

    2015-08-01

    Objective. To describe a toolkit of components for mathematical models of the relationship between cortical neural activity and space-resolved and time-resolved flows and volumes of oxygenated and deoxygenated hemoglobin motivated by optical intrinsic signal imaging (OISI). Approach. Both blood flow and blood volume and both oxygenated and deoxygenated hemoglobin and their interconversion are accounted for. Flow and volume are described by including analogies to both resistive and capacitive electrical circuit elements. Oxygenated and deoxygenated hemoglobin and their interconversion are described by generalization of Kirchhoff's laws based on well-mixed compartments. Main results. Mathematical models built from this toolkit are able to reproduce experimental single-stimulus OISI results that are described in papers from other research groups and are able to describe the response to multiple-stimuli experiments as a sublinear superposition of responses to the individual stimuli. Significance. The same assembly of tools from the toolkit but with different parameter values is able to describe effects that are considered distinctive, such as the presence or absence of an initial decrease in oxygenated hemoglobin concentration, indicating that the differences might be due to unique parameter values in a subject rather than different fundamental mechanisms.

  16. Disrupting neural activity related to awake-state sharp wave-ripple complexes prevents hippocampal learning.

    PubMed

    Nokia, Miriam S; Mikkonen, Jarno E; Penttonen, Markku; Wikgren, Jan

    2012-01-01

    Oscillations in hippocampal local-field potentials (LFPs) reflect the crucial involvement of the hippocampus in memory trace formation: theta (4-8 Hz) oscillations and ripples (~200 Hz) occurring during sharp waves are thought to mediate encoding and consolidation, respectively. During sharp wave-ripple complexes (SPW-Rs), hippocampal cell firing closely follows the pattern that took place during the initial experience, most likely reflecting replay of that event. Disrupting hippocampal ripples using electrical stimulation either during training in awake animals or during sleep after training retards spatial learning. Here, adult rabbits were trained in trace eyeblink conditioning, a hippocampus-dependent associative learning task. A bright light was presented to the animals during the inter-trial interval (ITI), when awake, either during SPW-Rs or irrespective of their neural state. Learning was particularly poor when the light was presented following SPW-Rs. While the light did not disrupt the ripple itself, it elicited a theta-band oscillation, a state that does not usually coincide with SPW-Rs. Thus, it seems that consolidation depends on neuronal activity within and beyond the hippocampus taking place immediately after, but by no means limited to, hippocampal SPW-Rs.

  17. Dual-memory neural networks for modeling cognitive activities of humans via wearable sensors.

    PubMed

    Lee, Sang-Woo; Lee, Chung-Yeon; Kwak, Dong-Hyun; Ha, Jung-Woo; Kim, Jeonghee; Zhang, Byoung-Tak

    2017-02-20

    Wearable devices, such as smart glasses and watches, allow for continuous recording of everyday life in a real world over an extended period of time or lifelong. This possibility helps better understand the cognitive behavior of humans in real life as well as build human-aware intelligent agents for practical purposes. However, modeling the human cognitive activity from wearable-sensor data stream is challenging because learning new information often results in loss of previously acquired information, causing a problem known as catastrophic forgetting. Here we propose a deep-learning neural network architecture that resolves the catastrophic forgetting problem. Based on the neurocognitive theory of the complementary learning systems of the neocortex and hippocampus, we introduce a dual memory architecture (DMA) that, on one hand, slowly acquires the structured knowledge representations and, on the other hand, rapidly learns the specifics of individual experiences. The DMA system learns continuously through incremental feature adaptation and weight transfer. We evaluate the performance on two real-life datasets, the CIFAR-10 image-stream dataset and the 46-day Lifelog dataset collected from Google Glass, showing that the proposed model outperforms other online learning methods.

  18. Hippocampal neural activity reflects the economy of choices during goal-directed navigation.

    PubMed

    Tryon, Valerie L; Penner, Marsha R; Heide, Shawn W; King, Hunter O; Larkin, Joshua; Mizumori, Sheri J Y

    2017-02-27

    Distinguishing spatial contexts is likely essential for the well-known role of the hippocampus in episodic memory. We studied whether types of hippocampal neural organization thought to underlie context discrimination are impacted by learned economic considerations of choice behavior. Hippocampal place cells and theta activity were recorded as rats performed a maze-based probability discounting task that involved choosing between a small certain reward or a large probabilistic reward. Different spatial distributions of place fields were observed in response to changes in probability, the outcome of the rats' choice, and whether or not rats were free to make that choice. The degree to which the reward location was represented by place cells scaled with the expected probability of rewards. Theta power increased around the goal location also in proportion to the expected probability of signaled rewards. Furthermore, theta power dynamically varied as specific econometric information was obtained "on the fly" during task performance. Such an economic perspective of memory processing by hippocampal place cells expands our view of the nature of context memories retrieved by hippocampus during adaptive navigation.

  19. Development of modularity in the neural activity of childrenʼs brains

    NASA Astrophysics Data System (ADS)

    Chen, Man; Deem, Michael W.

    2015-02-01

    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 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.

  20. Aβ increases neural stem cell activity in senescence-accelerated SAMP8 mice.

    PubMed

    Díaz-Moreno, María; Hortigüela, Rafael; Gonçalves, Ania; García-Carpio, Irmina; Manich, Gemma; García-Bermúdez, Edurne; Moreno-Estellés, Mireia; Eguiluz, César; Vilaplana, Jordi; Pelegrí, Carme; Vilar, Marçal; Mira, Helena

    2013-11-01

    Neurogenesis persists in the adult brain as a form of plasticity due to the existence of neural stem cells (NSCs). Alterations in neurogenesis have been found in transgenic Alzheimer's disease (AD) mouse models, but NSC activity and neurogenesis in sporadic AD models remains to be examined. We herein describe a remarkable increase in NSC proliferation in the forebrain of SAMP8, a non-transgenic mouse strain that recapitulates the transition from healthy aging to AD. The increase in proliferation is transient, precedes AD-like symptoms such as amyloid beta 1-42 [Aβ(1-42)] increase or gliosis, and is followed by a steep decline at later stages. Interestingly, in vitro studies indicate that secreted Aβ(1-42) and PI3K signaling may account for the early boost in NSC proliferation. Our results highlight the role of soluble Aβ(1-42) peptide and PI3K in the autocrine regulation of NSCs, and further suggest that over-proliferation of NSCs before the appearance of AD pathology may underlie neurogenic failure during the age-related progression of the disease. These findings have implications for therapeutic approaches based on neurogenesis in AD.

  1. Effects of reconstructed magnetic field from sparse noisy boundary measurements on localization of active neural source.

    PubMed

    Shen, Hui-min; Lee, Kok-Meng; Hu, Liang; Foong, Shaohui; Fu, Xin

    2016-01-01

    Localization of active neural source (ANS) from measurements on head surface is vital in magnetoencephalography. As neuron-generated magnetic fields are extremely weak, significant uncertainties caused by stochastic measurement interference complicate its localization. This paper presents a novel computational method based on reconstructed magnetic field from sparse noisy measurements for enhanced ANS localization by suppressing effects of unrelated noise. In this approach, the magnetic flux density (MFD) in the nearby current-free space outside the head is reconstructed from measurements through formulating the infinite series solution of the Laplace's equation, where boundary condition (BC) integrals over the entire measurements provide "smooth" reconstructed MFD with the decrease in unrelated noise. Using a gradient-based method, reconstructed MFDs with good fidelity are selected for enhanced ANS localization. The reconstruction model, spatial interpolation of BC, parametric equivalent current dipole-based inverse estimation algorithm using reconstruction, and gradient-based selection are detailed and validated. The influences of various source depths and measurement signal-to-noise ratio levels on the estimated ANS location are analyzed numerically and compared with a traditional method (where measurements are directly used), and it was demonstrated that gradient-selected high-fidelity reconstructed data can effectively improve the accuracy of ANS localization.

  2. A wireless recording system that utilizes Bluetooth technology to transmit neural activity in freely moving animals.

    PubMed

    Hampson, Robert E; Collins, Vernell; Deadwyler, Sam A

    2009-09-15

    A new wireless transceiver is described for recording individual neuron firing from behaving rats utilizing Bluetooth transmission technology and a processor onboard for discrimination of neuronal waveforms and associated time stamps. This universal brain activity transmitter (UBAT) is attached to rodents via a backpack and amplifier headstage and can transmit 16 channels of captured neuronal firing data via a Bluetooth transceiver chip over very large and unconstrained distances. The onboard microprocessor of the UBAT allows flexible online control over waveform isolation criteria via transceiver instruction and the two-way communication capacity allows for closed-loop applications between neural events and behavioral or physiological processes which can be modified by transceiver instructions. A detailed description of the multiplexer processing of channel data as well as examples of neuronal recordings in different behavioral testing contexts is provided to demonstrate the capacity for robust transmission within almost any laboratory environment. A major advantage of the UBAT is the long transmission range and lack of object-based line of sight interference afforded by Bluetooth technology, allowing flexible recording capabilities within multiple experimental paradigms without interruption. Continuous recordings over very large distance separations from the monitor station are demonstrated providing experimenters with recording advantages not previously available with other telemetry devices.

  3. Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion

    PubMed Central

    Dunn, Timothy W; Mu, Yu; Narayan, Sujatha; Randlett, Owen; Naumann, Eva A; Yang, Chao-Tsung; Schier, Alexander F

    2016-01-01

    In the absence of salient sensory cues to guide behavior, animals must still execute sequences of motor actions in order to forage and explore. How such successive motor actions are coordinated to form global locomotion trajectories is unknown. We mapped the structure of larval zebrafish swim trajectories in homogeneous environments and found that trajectories were characterized by alternating sequences of repeated turns to the left and to the right. Using whole-brain light-sheet imaging, we identified activity relating to the behavior in specific neural populations that we termed the anterior rhombencephalic turning region (ARTR). ARTR perturbations biased swim direction and reduced the dependence of turn direction on turn history, indicating that the ARTR is part of a network generating the temporal correlations in turn direction. We also find suggestive evidence for ARTR mutual inhibition and ARTR projections to premotor neurons. Finally, simulations suggest the observed turn sequences may underlie efficient exploration of local environments. DOI: http://dx.doi.org/10.7554/eLife.12741.001 PMID:27003593

  4. Chronotype predicts activity patterns in the neural underpinnings of the motor system during the day.

    PubMed

    Peres, Isabella; Vetter, Céline; Blautzik, Janusch; Reiser, Maximilian; Pöppel, Ernst; Meindl, Thomas; Roenneberg, Till; Gutyrchik, Evgeny

    2011-12-01

    Neuroimaging is increasingly used to study the motor system in vivo. Despite many reports of time-of-day influences on motor function at the behavioral level, little is known about these influences on neural motor networks and their activations recorded in neuroimaging. Using functional magnetic resonance imaging (fMRI), the authors studied 15 healthy subjects (9 females; mean ± SD age: 23 ± 3 yrs) performing a self-paced finger-tapping task at different times of day (morning, midday, afternoon, and evening). Blood-oxygenation-level-dependent signal showed systematic differences across the day in task-related motor areas of the brain, specifically in the supplementary motor area, parietal cortex, and rolandic operculum (p(corr)< .0125). The authors found that these time-of-day-dependent hemodynamic modulations are associated with chronotype and not with homeostatic sleep pressure. These results show that consideration of time-of-day for the analysis of fMRI studies is imperative.

  5. Psychosocial versus physiological stress – meta-analyses on deactivations and activations of the neural correlates of stress reactions

    PubMed Central

    Kogler, Lydia; Mueller, Veronika I.; Chang, Amy; Eickhoff, Simon B.; Fox, Peter T.; Gur, Ruben C.; Derntl, Birgit

    2015-01-01

    Stress is present in everyday life in various forms and situations. Two stressors frequently investigated are physiological and psychosocial stress. Besides similar subjective and hormonal responses, it has been suggested that they also share common neural substrates. The current study used activation-likelihood-estimation meta-analysis to test this assumption by integrating results of previous neuroimaging studies on stress processing. Reported results are cluster-level FWE corrected. The inferior frontal gyrus (IFG) and the anterior insula (AI) were the only regions that demonstrated overlapping activation for both stressors. Analysis of physiological stress showed consistent activation of cognitive and affective components of pain processing such as the insula, striatum, or the middle cingulate cortex. Contrarily, analysis across psychosocial stress revealed consistent activation of the right superior temporal gyrus and deactivation of the striatum. Notably, parts of the striatum appeared to be functionally specified: the dorsal striatum was activated in physiological stress, whereas the ventral striatum was deactivated in psychosocial stress. Additional functional connectivity and decoding analyses further characterized this functional heterogeneity and revealed higher associations of the dorsal striatum with motor regions and of the ventral striatum with reward processing. Based on our meta-analytic approach, activation of the IFG and the AI seems to indicate a global neural stress reaction. While physiological stress activates a motoric fight-or-flight reaction, during psychosocial stress attention is shifted towards emotion regulation and goal-directed behavior, and reward processing is reduced. Our results show the significance of differentiating physiological and psychosocial stress in neural engagement. Furthermore, the assessment of deactivations in addition to activations in stress research is highly recommended. PMID:26123376

  6. Patient-specific models of deep brain stimulation: Influence of field model complexity on neural activation predictions

    PubMed Central

    Chaturvedi, Ashutosh; Butson, Christopher R.; Lempka, Scott F.; Cooper, Scott E.; McIntyre, Cameron C.

    2010-01-01

    Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become the surgical therapy of choice for medically intractable Parkinson’s disease. However, quantitative understanding of the interaction