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Sample records for diminished neural processing

  1. Diminished Neural Adaptation during Implicit Learning in Autism

    PubMed Central

    Schipul, Sarah E.; Just, Marcel Adam

    2015-01-01

    Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups’ brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD. PMID:26484826

  2. Diminished neural adaptation during implicit learning in autism.

    PubMed

    Schipul, Sarah E; Just, Marcel Adam

    2016-01-15

    Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups' brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD.

  3. Diminished neural responses predict enhanced intrinsic motivation and sensitivity to external incentive.

    PubMed

    Marsden, Karen E; Ma, Wei Ji; Deci, Edward L; Ryan, Richard M; Chiu, Pearl H

    2015-06-01

    The duration and quality of human performance depend on both intrinsic motivation and external incentives. However, little is known about the neuroscientific basis of this interplay between internal and external motivators. Here, we used functional magnetic resonance imaging to examine the neural substrates of intrinsic motivation, operationalized as the free-choice time spent on a task when this was not required, and tested the neural and behavioral effects of external reward on intrinsic motivation. We found that increased duration of free-choice time was predicted by generally diminished neural responses in regions associated with cognitive and affective regulation. By comparison, the possibility of additional reward improved task accuracy, and specifically increased neural and behavioral responses following errors. Those individuals with the smallest neural responses associated with intrinsic motivation exhibited the greatest error-related neural enhancement under the external contingency of possible reward. Together, these data suggest that human performance is guided by a "tonic" and "phasic" relationship between the neural substrates of intrinsic motivation (tonic) and the impact of external incentives (phasic).

  4. Neural Analog Information Processing

    NASA Astrophysics Data System (ADS)

    Hecht-Nielsen, Robert

    1982-07-01

    Neural Analog Information Processing (NAIP) is an effort to develop general purpose pattern classification architectures based upon biological information processing principles. This paper gives an overview of NAIP and its relationship to the previous work in neural modeling from which its fundamental principles are derived. It also presents a theorem concerning the stability of response of a slab (a two dimensional array of identical simple processing units) to time-invariant (spatial) patterns. An experiment (via computer emulation) demonstrating classification of a spatial pattern by a simple, but complete NAIP architecture is described. A concept for hardware implementation of NAIP architectures is briefly discussed.

  5. Neural Network Communications Signal Processing

    DTIC Science & Technology

    1994-08-01

    This final technical report describes the research and development- results of the Neural Network Communications Signal Processing (NNCSP) Program...The objectives of the NNCSP program are to: (1) develop and implement a neural network and communications signal processing simulation system for the...purpose of exploring the applicability of neural network technology to communications signal processing; (2) demonstrate several configurations of the

  6. [Neural correlates of emotional processes].

    PubMed

    Weniger, Godehard

    2014-02-12

    The investigation of emotional processes has been neglected for a long time. But with the appearance of new imaging methods, a growing interest in the neural representation of emotional processes emerged. According to recent findings, emotional information were proceed by overlapping neural networks, especially the interaction between the limbic system and heteromodal association cortices.

  7. [Fortification of food with folic acid diminishes the number of neural tube defects].

    PubMed

    Brouwer, I A

    2008-01-26

    A recent study from a research group from Quebec showed a strong decrease in the number of births affected by a neural tube defect since folic acid fortification was introduced in Canada. The prevalence decreased from 1.58 neural tube defects per 1000 births before the introduction of folic acid fortification to 0.86 per 1000 births in the period of complete fortification. Although folic acid fortification of staple food is probably the most effective way to decrease the incidence of neural tube defects, more knowledge about possible health risks should be obtained before fortification is introduced. More research is needed to determine which population groups are at risk of possible negative effects of folic acid fortification and at which level of fortification. Until then, it is important to generate more attention and publicity in order to increase awareness and knowledge concerning folic acid and to promote its use before and after conception.

  8. Metacognitive monitoring and control processes in children with autism spectrum disorder: Diminished judgement of confidence accuracy.

    PubMed

    Grainger, Catherine; Williams, David M; Lind, Sophie E

    2016-05-01

    Metacognition consists of monitoring processes (the ability to accurately represent one's own mental states) and control processes (the ability to control one's cognitive processes effectively). Both processes play vital roles in self-regulated learning. However, currently it is unclear whether these processes are impaired in individuals with autism spectrum disorders (ASDs). This study aimed to assess metacognition in thirty-two children with ASD, and 30 IQ-/age-matched neurotypical children, using a judgment of confidence task. It was found that children with ASD showed diminished accuracy in their judgments of confidence, indicating metacognitive monitoring impairments in ASD. Children with ASD also used monitoring to influence control processes significantly less than neurotypical children, despite little evidence of impairments in overall control ability.

  9. Diminished Auditory Responses during NREM Sleep Correlate with the Hierarchy of Language Processing

    PubMed Central

    Furman-Haran, Edna; Arzi, Anat; Levkovitz, Yechiel; Malach, Rafael

    2016-01-01

    Natural sleep provides a powerful model system for studying the neuronal correlates of awareness and state changes in the human brain. To quantitatively map the nature of sleep-induced modulations in sensory responses we presented participants with auditory stimuli possessing different levels of linguistic complexity. Ten participants were scanned using functional magnetic resonance imaging (fMRI) during the waking state and after falling asleep. Sleep staging was based on heart rate measures validated independently on 20 participants using concurrent EEG and heart rate measurements and the results were confirmed using permutation analysis. Participants were exposed to three types of auditory stimuli: scrambled sounds, meaningless word sentences and comprehensible sentences. During non-rapid eye movement (NREM) sleep, we found diminishing brain activation along the hierarchy of language processing, more pronounced in higher processing regions. Specifically, the auditory thalamus showed similar activation levels during sleep and waking states, primary auditory cortex remained activated but showed a significant reduction in auditory responses during sleep, and the high order language-related representation in inferior frontal gyrus (IFG) cortex showed a complete abolishment of responses during NREM sleep. In addition to an overall activation decrease in language processing regions in superior temporal gyrus and IFG, those areas manifested a loss of semantic selectivity during NREM sleep. Our results suggest that the decreased awareness to linguistic auditory stimuli during NREM sleep is linked to diminished activity in high order processing stations. PMID:27310812

  10. Neural overlap in processing music and speech.

    PubMed

    Peretz, Isabelle; Vuvan, Dominique; Lagrois, Marie-Élaine; Armony, Jorge L

    2015-03-19

    Neural overlap in processing music and speech, as measured by the co-activation of brain regions in neuroimaging studies, may suggest that parts of the neural circuitries established for language may have been recycled during evolution for musicality, or vice versa that musicality served as a springboard for language emergence. Such a perspective has important implications for several topics of general interest besides evolutionary origins. For instance, neural overlap is an important premise for the possibility of music training to influence language acquisition and literacy. However, neural overlap in processing music and speech does not entail sharing neural circuitries. Neural separability between music and speech may occur in overlapping brain regions. In this paper, we review the evidence and outline the issues faced in interpreting such neural data, and argue that converging evidence from several methodologies is needed before neural overlap is taken as evidence of sharing.

  11. Neural specializations for tonal processing.

    PubMed

    Zatorre, R J

    2001-06-01

    The processing of pitch, a central aspect of music perception, is neurally dissociable from other perceptual functions. Studies using behavioral-lesion techniques as well as brain imaging methods demonstrate that tonal processing recruits mechanisms in areas of the right auditory cortex. Specifically, the right primary auditory area appears to be crucial for fine-grained representation of pitch information. Processing of pitch patterns, such as occurs in melodies, requires higher-order cortical areas, and interactions with the frontal cortex. The latter are likely related to tonal working memory functions that are necessary for the on-line maintenance and encoding of tonal patterns. One hypothesis that may explain why right-hemisphere auditory cortices seem to be so important to tonal processing is that left auditory regions are better suited for rapidly changing broad-band stimuli, such as speech, whereas the right auditory cortex may be specialized for slower narrow-band stimuli, such as tonal patterns. Evidence favoring this hypothesis was obtained in a functional imaging study in which spectral and temporal parameters were varied independently. The hypothesis also receives support from structural studies of the auditory cortex, which indicate that spectral and temporal processing may depend on interhemispheric differences in grey/white matter distribution and other anatomical features.

  12. Neural Networks Applied to Signal Processing

    DTIC Science & Technology

    1989-09-01

    DTIC FILE COpy NAVAL POSTGRADUATE SCHOOL . Monterey, California Lf 0 (0 V’ STATES 4 THESIS NEURAL NETWORKS APPLIED TO SIGNAL PROCESSING by Mark D...FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO NO NO ACCESSION NO. 11. TITLE (Include Security Classification) NEURAL NETWORKS APPLIED TO...for public release; distribution is unlimited Neural Networks Applied to Signal Processing by Mark D. Baehre Captain, United States Army B.S., United

  13. Neural networks in the process industries

    SciTech Connect

    Ben, L.R.; Heavner, L.

    1996-12-01

    Neural networks, or more precisely, artificial neural networks (ANNs), are rapidly gaining in popularity. They first began to appear on the process-control scene in the early 1990s, but have been a research focus for more than 30 years. Neural networks are really empirical models that approximate the way man thinks neurons in the human brain work. Neural-net technology is not trying to produce computerized clones, but to model nature in an effort to mimic some of the brain`s capabilities. Modeling, for the purposes of this article, means developing a mathematical description of physical phenomena. The physics and chemistry of industrial processes are usually quite complex and sometimes poorly understood. Our process understanding, and our imperfect ability to describe complexity in mathematical terms, limit fidelity of first-principle models. Computational requirements for executing these complex models are a further limitation. It is often not possible to execute first-principle model algorithms at the high rate required for online control. Nevertheless, rigorous first principle models are commonplace design tools. Process control is another matter. Important model inputs are often not available as process measurements, making real-time application difficult. In fact, engineers often use models to infer unavailable measurements. 5 figs.

  14. Canning process that diminishes paralytic shellfish poison in naturally contaminated mussels (Mytilus galloprovincialis).

    PubMed

    Vieites, J M; Botana, L M; Vieytes, M R; Leira, F J

    1999-05-01

    Changes in toxin profile and total toxicity levels of paralytic shellfish poison (PSP)-containing mussels were monitored during the standard canning process of pickled mussels and mussels in brine using mouse bioassays and high-performance liquid chromatography. Detoxification percentages for canned mussel meat exceeded 50% of initial toxicity. Total toxicity reduction did not fully correspond to toxin destruction, which was due to the loss of PSP to cooking water and packing media of the canned product. Significant differences in detoxification percentages were due to changes in toxin profile during heat treatment in packing media. Toxin conversion phenomena should be determined to validate detoxification procedures in the canning industry.

  15. Income, neural executive processes, and preschool children's executive control.

    PubMed

    Ruberry, Erika J; Lengua, Liliana J; Crocker, Leanna Harris; Bruce, Jacqueline; Upshaw, Michaela B; Sommerville, Jessica A

    2017-02-01

    This study aimed to specify the neural mechanisms underlying the link between low household income and diminished executive control in the preschool period. Specifically, we examined whether individual differences in the neural processes associated with executive attention and inhibitory control accounted for income differences observed in performance on a neuropsychological battery of executive control tasks. The study utilized a sample of preschool-aged children (N = 118) whose families represented the full range of income, with 32% of families at/near poverty, 32% lower income, and 36% middle to upper income. Children completed a neuropsychological battery of executive control tasks and then completed two computerized executive control tasks while EEG data were collected. We predicted that differences in the event-related potential (ERP) correlates of executive attention and inhibitory control would account for income differences observed on the executive control battery. Income and ERP measures were related to performance on the executive control battery. However, income was unrelated to ERP measures. The findings suggest that income differences observed in executive control during the preschool period might relate to processes other than executive attention and inhibitory control.

  16. Neural processing of gravity information

    NASA Technical Reports Server (NTRS)

    Schor, Robert H.

    1992-01-01

    The goal of this project was to use the linear acceleration capabilities of the NASA Vestibular Research Facility (VRF) at Ames Research Center to directly examine encoding of linear accelerations in the vestibular system of the cat. Most previous studies, including my own, have utilized tilt stimuli, which at very low frequencies (e.g., 'static tilt') can be considered a reasonably pure linear acceleration (e.g., 'down'); however, higher frequencies of tilt, necessary for understanding the dynamic processing of linear acceleration information, necessarily involves rotations which can stimulate the semicircular canals. The VRF, particularly the Long Linear Sled, has promise to provide controlled pure linear accelerations at a variety of stimulus frequencies, with no confounding angular motion.

  17. Advances in Neural Information Processing Systems

    NASA Astrophysics Data System (ADS)

    Jordan, Michael I.; Lecun, Yann; Solla, Sara A.

    2001-11-01

    The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This CD-ROM contains the entire proceedings of the twelve Neural Information Processing Systems conferences from 1988 to 1999. The files are available in the DjVu image format developed by Yann LeCun and his group at AT&T Labs. The CD-ROM includes free browsers for all major platforms. Michael I. Jordan is Professor of Computer Science and of Statistics at the University of California, Berkeley. Yann LeCun is Head of the Image Processing Research Department at AT&T Labs-Research. Sara A. Solla is Professor of Physics and of Physiology at Northwestern University.

  18. Neural circuits and motivational processes for hunger.

    PubMed

    Sternson, Scott M; Nicholas Betley, J; Cao, Zhen Fang Huang

    2013-06-01

    How does an organism's internal state direct its actions? At one moment an animal forages for food with acrobatic feats such as tree climbing and jumping between branches. At another time, it travels along the ground to find water or a mate, exposing itself to predators along the way. These behaviors are costly in terms of energy or physical risk, and the likelihood of performing one set of actions relative to another is strongly modulated by internal state. For example, an animal in energy deficit searches for food and a dehydrated animal looks for water. The crosstalk between physiological state and motivational processes influences behavioral intensity and intent, but the underlying neural circuits are poorly understood. Molecular genetics along with optogenetic and pharmacogenetic tools for perturbing neuron function have enabled cell type-selective dissection of circuits that mediate behavioral responses to physiological state changes. Here, we review recent progress into neural circuit analysis of hunger in the mouse by focusing on a starvation-sensitive neuron population in the hypothalamus that is sufficient to promote voracious eating. We also consider research into the motivational processes that are thought to underlie hunger in order to outline considerations for bridging the gap between homeostatic and motivational neural circuits.

  19. Neural substrates of sublexical processing for spelling.

    PubMed

    DeMarco, Andrew T; Wilson, Stephen M; Rising, Kindle; Rapcsak, Steven Z; Beeson, Pélagie M

    2017-01-01

    We used fMRI to examine the neural substrates of sublexical phoneme-grapheme conversion during spelling in a group of healthy young adults. Participants performed a writing-to-dictation task involving irregular words (e.g., choir), plausible nonwords (e.g., kroid), and a control task of drawing familiar geometric shapes (e.g., squares). Written production of both irregular words and nonwords engaged a left-hemisphere perisylvian network associated with reading/spelling and phonological processing skills. Effects of lexicality, manifested by increased activation during nonword relative to irregular word spelling, were noted in anterior perisylvian regions (posterior inferior frontal gyrus/operculum/precentral gyrus/insula), and in left ventral occipito-temporal cortex. In addition to enhanced neural responses within domain-specific components of the language network, the increased cognitive demands associated with spelling nonwords engaged domain-general frontoparietal cortical networks involved in selective attention and executive control. These results elucidate the neural substrates of sublexical processing during written language production and complement lesion-deficit correlation studies of phonological agraphia.

  20. The role of automaticity and attention in neural processes underlying empathy for happiness, sadness, and anxiety.

    PubMed

    Morelli, Sylvia A; Lieberman, Matthew D

    2013-01-01

    Although many studies have examined the neural basis of empathy, relatively little is known about how empathic processes are affected by different attentional conditions. Thus, we examined whether instructions to empathize might amplify responses in empathy-related regions and whether cognitive load would diminish the involvement of these regions. Thirty-two participants completed a functional magnetic resonance imaging session assessing empathic responses to individuals experiencing happy, sad, and anxious events. Stimuli were presented under three conditions: watching naturally, actively empathizing, and under cognitive load. Across analyses, we found evidence for a core set of neural regions that support empathic processes (dorsomedial prefrontal cortex, DMPFC; medial prefrontal cortex, MPFC; temporoparietal junction, TPJ; amygdala; ventral anterior insula, AI; and septal area, SA). Two key regions-the ventral AI and SA-were consistently active across all attentional conditions, suggesting that they are automatically engaged during empathy. In addition, watching vs. empathizing with targets was not markedly different and instead led to similar subjective and neural responses to others' emotional experiences. In contrast, cognitive load reduced the subjective experience of empathy and diminished neural responses in several regions related to empathy and social cognition (DMPFC, MPFC, TPJ, and amygdala). The results reveal how attention impacts empathic processes and provides insight into how empathy may unfold in everyday interactions.

  1. Neural processing-type displacement sensor employing multimode waveguide

    NASA Astrophysics Data System (ADS)

    Aisawa, Shigeki; Noguchi, Kazuhiro; Matsumoto, Takao

    1991-04-01

    A novel neural processing-type displacement sensor, consisting of a multimode waveguide and a neural network, is demonstrated. This sensor detects displacement using changes in the interference output image of the waveguide. The interference image is directly processed by a three-layer perceptron neural network. Environmental change, such as the intensity fluctuation, and change of the temperature can be followed by training the neural network. Experimental results show that the sensor has a resolution of 1 micron.

  2. 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

  3. Neural Adaptation Effects in Conceptual Processing.

    PubMed

    Marino, Barbara F M; Borghi, Anna M; Gemmi, Luca; Cacciari, Cristina; Riggio, Lucia

    2015-07-31

    We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e.g., animals) after a selective adaptation of color-edge neurons in the posterior LV4 region of the visual cortex was induced by means of a McCollough effect procedure. This manipulation affected categorization: the green-vertical adaptation led to slower responses than the green-horizontal adaptation, regardless of the specific color and orientation of the to-be-categorized noun. This result suggests that the conceptual processing of natural entities may entail the activation of modality-specific neural channels with weights proportional to the reliability of the signals produced by these channels during actual perception. This finding is discussed with reference to the debate about the grounded cognition view.

  4. Neural network training as a dissipative process.

    PubMed

    Gori, Marco; Maggini, Marco; Rossi, Alessandro

    2016-09-01

    This paper analyzes the practical issues and reports some results on a theory in which learning is modeled as a continuous temporal process driven by laws describing the interactions of intelligent agents with their own environment. The classic regularization framework is paired with the idea of temporal manifolds by introducing the principle of least cognitive action, which is inspired by the related principle of mechanics. The introduction of the counterparts of the kinetic and potential energy leads to an interpretation of learning as a dissipative process. As an example, we apply the theory to supervised learning in neural networks and show that the corresponding Euler-Lagrange differential equations can be connected to the classic gradient descent algorithm on the supervised pairs. We give preliminary experiments to confirm the soundness of the theory.

  5. Neural Adaptation Effects in Conceptual Processing

    PubMed Central

    Marino, Barbara F. M.; Borghi, Anna M.; Gemmi, Luca; Cacciari, Cristina; Riggio, Lucia

    2015-01-01

    We investigated the conceptual processing of nouns referring to objects characterized by a highly typical color and orientation. We used a go/no-go task in which we asked participants to categorize each noun as referring or not to natural entities (e.g., animals) after a selective adaptation of color-edge neurons in the posterior LV4 region of the visual cortex was induced by means of a McCollough effect procedure. This manipulation affected categorization: the green-vertical adaptation led to slower responses than the green-horizontal adaptation, regardless of the specific color and orientation of the to-be-categorized noun. This result suggests that the conceptual processing of natural entities may entail the activation of modality-specific neural channels with weights proportional to the reliability of the signals produced by these channels during actual perception. This finding is discussed with reference to the debate about the grounded cognition view. PMID:26264031

  6. Survey on Neural Networks Used for Medical Image Processing.

    PubMed

    Shi, Zhenghao; He, Lifeng; Suzuki, Kenji; Nakamura, Tsuyoshi; Itoh, Hidenori

    2009-02-01

    This paper aims to present a review of neural networks used in medical image processing. We classify neural networks by its processing goals and the nature of medical images. Main contributions, advantages, and drawbacks of the methods are mentioned in the paper. Problematic issues of neural network application for medical image processing and an outlook for the future research are also discussed. By this survey, we try to answer the following two important questions: (1) What are the major applications of neural networks in medical image processing now and in the nearby future? (2) What are the major strengths and weakness of applying neural networks for solving medical image processing tasks? We believe that this would be very helpful researchers who are involved in medical image processing with neural network techniques.

  7. Recurrent neural processing and somatosensory awareness.

    PubMed

    Auksztulewicz, Ryszard; Spitzer, Bernhard; Blankenburg, Felix

    2012-01-18

    The neural mechanisms of stimulus detection, despite extensive research, remain elusive. The recurrent processing hypothesis, a prominent theoretical account of perceptual awareness, states that, although stimuli might in principle evoke feedforward activity propagating through the visual cortex, stimuli that become consciously detected are further processed in feedforward-feedback loops established between cortical areas. To test this theory in the tactile modality, we applied dynamic causal modeling to electroencephalography (EEG) data acquired from humans in a somatosensory detection task. In the analysis of stimulation-induced event-related potentials (ERPs), we focused on model-based evidence for feedforward, feedback, and recurrent processing between primary and secondary somatosensory cortices. Bayesian model comparison revealed that, although early EEG components were well explained by both the feedforward and the recurrent models, the recurrent model outperformed the other models when later EEG segments were analyzed. Within the recurrent model, stimulus detection was characterized by a relatively early strength increase of the feedforward connection from primary to secondary somatosensory cortex (>80 ms). At longer latencies (>140 ms), also the feedback connection showed a detection-related strength increase. The modeling results on relative evidence between recurrent and feedforward model comparison support the hypothesis that the ERP responses from sensory areas arising after aware stimulus detection can be explained by increased recurrent processing within the somatosensory network in the later stages of stimulus processing.

  8. Cooperative neural processes involved in stereoscopic acuity.

    PubMed

    Westheimer, G

    1979-08-01

    Results of psychophysical experiments are reported showing that synchrony, appropriate relative placement, and absence of standing disparity are important conditions to be met by members of a target configuration if they are to participate in the cooperative neural processes leading to the best disparity discrimination. Consecutive binocular presentation of the members of a stereo target decreases stereoacuity by a factor of about 10, and a step disparity displacement of a single line target needs to be larger still to be detected as a depth stimulus. A standing disaprity of even one minute of arc at least doubles the disaprity disxrimination threshold. It is postulated that a differencing mechanism operates on the depth signal of individual features; the temporal and spatial optima of target presentation for stereoscopic acuity outline the character of the concerned operations.

  9. Feedback neural networks for ARTIST ionogram processing

    NASA Astrophysics Data System (ADS)

    Galkin, Ivan A.; Reinisch, Bodo W.; Ososkov, Gennadii A.; Zaznobina, Elena G.; Neshyba, Steven P.

    1996-09-01

    Modern pattern recognition techniques are applied to achieve high quality automatic processing of Digisonde ionograms. An artificial neural network (ANN) was found to be a promising technique for ionospheric echo tracing. A modified rotor model was tested to construct the Hopfield ANN with the mean field theory updating scheme. Tests of the models against various ionospheric data showed that the modified rotor model gives good results where conventional tracing techniques have difficulties. Use of the ANN made it possible to implement a robust scheme of trace interpretation that considers local trace inclination angles available after ANN completes tracing. The interpretation scheme features a new algorithm for ƒ0F1 identification that estimates an α angle for the trace segments in the vicinity of the critical frequency ƒ0F1. First results from off-line tests suggest the potential of implementing new operational autoscaling software in the worldwide Digisonde network.

  10. Neural Networks for Signal Processing and Control

    NASA Astrophysics Data System (ADS)

    Hesselroth, Ted Daniel

    Neural networks are developed for controlling a robot-arm and camera system and for processing images. The networks are based upon computational schemes that may be found in the brain. In the first network, a neural map algorithm is employed to control a five-joint pneumatic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm employed shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a network representing the three-dimensional workspace embedded in a four-dimensional system of coordinates from the two cameras, and learned a set of pressures corresponding to the end effector positions, as well as a set of Jacobian matrices for interpolating between these positions. Because of the properties of the rubber-tube actuators of the arm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel (~3 mm) after two hundred learning steps. Applications of repeated corrections in each step via the Jacobian matrices leads to a very robust control algorithm since the Jacobians learned by the network have to satisfy the weak requirement that they yield a reduction of the distance between gripper and target. The second network is proposed as a model for the mammalian vision system in which backward connections from the primary visual cortex (V1) to the lateral geniculate nucleus play a key role. The application of hebbian learning to the forward and backward connections causes the formation of receptive fields which are sensitive to edges, bars, and spatial frequencies of preferred orientations. The receptive fields are learned in such a way as to maximize the rate of transfer of information from the LGN to V1. Orientational preferences are organized into a feature map in the primary visual

  11. Using neural networks for dynamic light scattering time series processing

    NASA Astrophysics Data System (ADS)

    Chicea, Dan

    2017-04-01

    A basic experiment to record dynamic light scattering (DLS) time series was assembled using basic components. The DLS time series processing using the Lorentzian function fit was considered as reference. A Neural Network was designed and trained using simulated frequency spectra for spherical particles in the range 0–350 nm, assumed to be scattering centers, and the neural network design and training procedure are described in detail. The neural network output accuracy was tested both on simulated and on experimental time series. The match with the DLS results, considered as reference, was good serving as a proof of concept for using neural networks in fast DLS time series processing.

  12. Nonlinear neural networks. II. Information processing

    NASA Astrophysics Data System (ADS)

    van Hemmen, J. L.; Grensing, D.; Huber, A.; Kühn, R.

    1988-01-01

    Information processing in nonlinear neural networks with a finite number q of stored patterns is studied. Each network is characterized completely by its synaptic kernel Q. At low temperatures, the nonlinearity typically results in 2q-2- q metastable, pure states in addition to the q retrieval states that are associated with the q stored patterns. These spurious states start appearing at a temperaturetilde T_q , which depends on q. We give sufficient conditions to guarantee that the retrieval states bifurcate first at a critical temperature T c and thattilde T_q / T c → 0 as q→∞. Hence, there is a large temperature range where only the retrieval states and certain symmetric mixtures thereof exist. The latter are unstable, as they appear at T c . For clipped synapses, the bifurcation and stability structure is analyzed in detail and shown to approach that of the (linear) Hopfield model as q→∞. We also investigate memories that forget and indicate how forgetfulness can be explained in terms of the eigenvalue spectrum of the synaptic kernel Q.

  13. Reducing neural network training time with parallel processing

    NASA Technical Reports Server (NTRS)

    Rogers, James L., Jr.; Lamarsh, William J., II

    1995-01-01

    Obtaining optimal solutions for engineering design problems is often expensive because the process typically requires numerous iterations involving analysis and optimization programs. Previous research has shown that a near optimum solution can be obtained in less time by simulating a slow, expensive analysis with a fast, inexpensive neural network. A new approach has been developed to further reduce this time. This approach decomposes a large neural network into many smaller neural networks that can be trained in parallel. Guidelines are developed to avoid some of the pitfalls when training smaller neural networks in parallel. These guidelines allow the engineer: to determine the number of nodes on the hidden layer of the smaller neural networks; to choose the initial training weights; and to select a network configuration that will capture the interactions among the smaller neural networks. This paper presents results describing how these guidelines are developed.

  14. Exposure therapy triggers lasting reorganization of neural fear processing.

    PubMed

    Hauner, Katherina K; Mineka, Susan; Voss, Joel L; Paller, Ken A

    2012-06-05

    A single session of exposure therapy can eliminate recalcitrant and disabling fear of phobogenic objects or situations. We studied neural mechanisms of this remarkable outcome by monitoring changes in brain activity as a result of successful 2-h treatment. Before treatment, phobogenic images excited activity in a network of regions, including amygdala, insula, and cingulate cortex, relative to neutral images. Successful therapy dampened responsiveness in this fear-sensitive network while concomitantly heightening prefrontal involvement. Six months later, dampened fear-network activity persisted but without prefrontal engagement. Additionally, individual differences in the magnitude of visual cortex activations recorded shortly after therapy predicted therapeutic outcomes 6 mo later, which involved persistently diminished visual responsiveness to phobogenic images. Successful therapy thus entailed stable reorganization of neural responses to initially feared stimuli. These effects were linked to fear-extinction mechanisms identified in animal models, thus opening new opportunities for the treatment and prevention of debilitating anxiety disorders.

  15. Powder processing of hybrid titanium neural electrodes

    NASA Astrophysics Data System (ADS)

    Lopez, Jose Luis, Jr.

    A preliminary investigation into the powder production of a novel hybrid titanium neural electrode for EEG is presented. The rheological behavior of titanium powder suspensions using sodium alginate as a dispersant are examined for optimal slip casting conditions. Electrodes were slip cast and sintered at 950°C for 1 hr, 1000°C for 1, 3, and 6 hrs, and 1050°C for 1 hr. Residual porosities from sintering are characterized using Archimedes' technique and image analysis. The pore network is gel impregnated by submerging the electrodes in electrically conductive gel and placing them in a chamber under vacuum. Gel evaporation of the impregnated electrodes is examined. Electrodes are characterized in the dry and gelled states using impedance spectrometry and compared to a standard silver- silver chloride electrode. Power spectral densities for the sensors in the dry and gelled state are also compared. Residual porosities for the sintered specimens were between 50.59% and 44.81%. Gel evaporation tests show most of the impregnated gel evaporating within 20 min of exposure to atmospheric conditions with prolonged evaporation times for electrodes with higher impregnated gel mass. Impedance measurements of the produced electrodes indicate the low impedance of the hybrid electrodes are due to the increased contact area of the porous electrode. Power spectral densities of the titanium electrode behave similar to a standard silver-silver chloride electrode. Tests suggest the powder processed hybrid titanium electrode's performance is better than current dry contact electrodes and comparable to standard gelled silver-silver chloride electrodes.

  16. The neural basis of first and second language processing.

    PubMed

    Perani, Daniela; Abutalebi, Jubin

    2005-04-01

    Fundamental breakthroughs in the neurosciences, combined with technical innovations for measuring brain activity, are shedding new light on the neural basis of second language (L2) processing, and on its relationship to native language processing (L1). The long-held assumption that L1 and L2 are necessarily represented in different brain regions in bilinguals has not been confirmed. On the contrary, the available evidence indicates that L1 and L2 are processed by the same neural devices. The neural differences in L1 and L2 representations are only related to the specific computational demands, which vary according to the age of acquisition, the degree of mastery and the level of exposure to each language. Finally, the acquisition of L2 could be considered as a dynamic process, requiring additional neural resources in specific circumstances.

  17. Neural networks in windprofiler data processing

    NASA Astrophysics Data System (ADS)

    Weber, H.; Richner, H.; Kretzschmar, R.; Ruffieux, D.

    2003-04-01

    Wind profilers are basically Doppler radars yielding 3-dimensional wind profiles that are deduced from the Doppler shift caused by turbulent elements in the atmosphere. These signals can be contaminated by other airborne elements such as birds or hydrometeors. Using a feed-forward neural network with one hidden layer and one output unit, birds and hydrometeors can be successfully identified in non-averaged single spectra; theses are subsequently removed in the wind computation. An infrared camera was used to identify birds in one of the beams of the wind profiler. After training the network with about 6000 contaminated data sets, it was able to identify contaminated data in a test data set with a reliability of 96 percent. The assumption was made that the neural network parameters obtained in the beam for which bird data was collected can be transferred to the other beams (at least three beams are needed for computing wind vectors). Comparing the evolution of a wind field with and without the neural network shows a significant improvement of wind data quality. Current work concentrates on training the network also for hydrometeors. It is hoped that the instrument's capability can thus be expanded to measure not only correct winds, but also observe bird migration, estimate precipitation and -- by combining precipitation information with vertical velocity measurement -- the monitoring of the height of the melting layer.

  18. The Diminishing Apple.

    ERIC Educational Resources Information Center

    Kelly, Catherine

    2002-01-01

    Introduces the Apple Ocean activity which teaches about the diminishing natural resources of the earth including drinkable water, habitable land, and productive areas while working with fractions, ratios, and proportions. (YDS)

  19. Characteristic Functions and Process Identification by Neural Networks.

    PubMed

    Vilela Mendes, Rui; Dente, Joaquim A.

    1997-11-01

    Principal component analysis (PCA) algorithms use neural networks to extract the eigenvectors of the correlation matrix from the data. However, if the process is non-Gaussian, PCA algorithms or their higher order generalisations provide only incomplete or misleading information on the statistical properties of the data. To handle such situations we propose neural network algorithms, with an hybrid (supervised and unsupervised) learning scheme, which constructs the characteristic function of the probability distribution and the transition functions of the stochastic process. Illustrative examples are presented, which include Cauchy and Lévy-type processes.

  20. High level cognitive information processing in neural networks

    NASA Technical Reports Server (NTRS)

    Barnden, John A.; Fields, Christopher A.

    1992-01-01

    Two related research efforts were addressed: (1) high-level connectionist cognitive modeling; and (2) local neural circuit modeling. The goals of the first effort were to develop connectionist models of high-level cognitive processes such as problem solving or natural language understanding, and to understand the computational requirements of such models. The goals of the second effort were to develop biologically-realistic model of local neural circuits, and to understand the computational behavior of such models. In keeping with the nature of NASA's Innovative Research Program, all the work conducted under the grant was highly innovative. For instance, the following ideas, all summarized, are contributions to the study of connectionist/neural networks: (1) the temporal-winner-take-all, relative-position encoding, and pattern-similarity association techniques; (2) the importation of logical combinators into connection; (3) the use of analogy-based reasoning as a bridge across the gap between the traditional symbolic paradigm and the connectionist paradigm; and (4) the application of connectionism to the domain of belief representation/reasoning. The work on local neural circuit modeling also departs significantly from the work of related researchers. In particular, its concentration on low-level neural phenomena that could support high-level cognitive processing is unusual within the area of biological local circuit modeling, and also serves to expand the horizons of the artificial neural net field.

  1. Neural Correlates of Semantic Competition during Processing of Ambiguous Words

    ERIC Educational Resources Information Center

    Bilenko, Natalia Y.; Grindrod, Christopher M.; Myers, Emily B.; Blumstein, Sheila E.

    2009-01-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous…

  2. Neural networks for process control and optimization: two industrial applications.

    PubMed

    Bloch, Gérard; Denoeux, Thierry

    2003-01-01

    The two most widely used neural models, multilayer perceptron (MLP) and radial basis function network (RBFN), are presented in the framework of system identification and control. The main steps for building such nonlinear black box models are regressor choice, selection of internal architecture, and parameter estimation. The advantages of neural network models are summarized: universal approximation capabilities, flexibility, and parsimony. Two applications are described in steel industry and water treatment, respectively, the control of alloying process in a hot dipped galvanizing line and the control of a coagulation process in a drinking water treatment plant. These examples highlight the interest of neural techniques, when complex nonlinear phenomena are involved, but the empirical knowledge of control operators can be learned.

  3. Further results in multiset processing with neural networks.

    PubMed

    McGregor, Simon

    2008-08-01

    This paper presents new experimental results on the variadic neural network (VNN) [McGregor, S. (2007). Neural network processing for multiset data. In Proceedings: Vol. 4668. Artificial neural networks - ICANN 2007, 17th international conference (pp. 460-470). Springer]. The inputs to a variadic network are an arbitrary-length list of n-tuples of real numbers, where n is fixed, and the function computed by the network is unaffected by permutation of the inputs. This paper describes improvements in the training algorithm for the variadic perceptron, based on a constructive cascade topology, and performance of the improved networks on geometric problems inspired by vector graphics. Further development may allow practical application of these or similar networks to vector graphics processing and statistical analysis.

  4. Thermotaxis of C. elegans as a model for temperature perception, neural information processing and neural plasticity.

    PubMed

    Kimata, Tsubasa; Sasakura, Hiroyuki; Ohnishi, Noriyuki; Nishio, Nana; Mori, Ikue

    2012-01-01

    Thermotaxis is a model to elucidate how nervous systems sense and memorize environmental conditions to regulate behavioral strategies in Caenorhabditis elegans. The genetic and neural imaging analyses revealed molecular and cellular bases of this experience-dependent behavior. Surprisingly, thermosensory neurons themselves memorize the sensed temperatures. Recently developed techniques for optical manipulation of neuronal activity have facilitated the revelation that there is a sophisticated information flow between sensory neurons and interneurons. Further studies on thermotaxis will allow us to understand the fundamental logics of neural processing from sensory perceptions to behavioral outputs.

  5. Thermotaxis of C. elegans as a model for temperature perception, neural information processing and neural plasticity

    PubMed Central

    Kimata, Tsubasa; Sasakura, Hiroyuki; Ohnishi, Noriyuki; Nishio, Nana; Mori, Ikue

    2012-01-01

    Thermotaxis is a model to elucidate how nervous systems sense and memorize environmental conditions to regulate behavioral strategies in Caenorhabditis elegans. The genetic and neural imaging analyses revealed molecular and cellular bases of this experience-dependent behavior. Surprisingly, thermosensory neurons themselves memorize the sensed temperatures. Recently developed techniques for optical manipulation of neuronal activity have facilitated the revelation that there is a sophisticated information flow between sensory neurons and interneurons. Further studies on thermotaxis will allow us to understand the fundamental logics of neural processing from sensory perceptions to behavioral outputs. PMID:24058821

  6. Studying the role of synchronized and chaotic spiking neural ensembles in neural information processing.

    PubMed

    Rosselló, Josep L; Canals, Vicens; Oliver, Antoni; Morro, Antoni

    2014-08-01

    The brain is characterized by performing many diverse processing tasks ranging from elaborate processes such as pattern recognition, memory or decision making to more simple functionalities such as linear filtering in image processing. Understanding the mechanisms by which the brain is able to produce such a different range of cortical operations remains a fundamental problem in neuroscience. Here we show a study about which processes are related to chaotic and synchronized states based on the study of in-silico implementation of Stochastic Spiking Neural Networks (SSNN). The measurements obtained reveal that chaotic neural ensembles are excellent transmission and convolution systems since mutual information between signals is minimized. At the same time, synchronized cells (that can be understood as ordered states of the brain) can be associated to more complex nonlinear computations. In this sense, we experimentally show that complex and quick pattern recognition processes arise when both synchronized and chaotic states are mixed. These measurements are in accordance with in vivo observations related to the role of neural synchrony in pattern recognition and to the speed of the real biological process. We also suggest that the high-level adaptive mechanisms of the brain that are the Hebbian and non-Hebbian learning rules can be understood as processes devoted to generate the appropriate clustering of both synchronized and chaotic ensembles. The measurements obtained from the hardware implementation of different types of neural systems suggest that the brain processing can be governed by the superposition of these two complementary states with complementary functionalities (nonlinear processing for synchronized states and information convolution and parallelization for chaotic).

  7. Neural Correlates of Bridging Inferences and Coherence Processing

    ERIC Educational Resources Information Center

    Kim, Sung-il; Yoon, Misun; Kim, Wonsik; Lee, Sunyoung; Kang, Eunjoo

    2012-01-01

    We explored the neural correlates of bridging inferences and coherence processing during story comprehension using Positron Emission Tomography (PET). Ten healthy right-handed volunteers were visually presented three types of stories (Strong Coherence, Weak Coherence, and Control) consisted of three sentences. The causal connectedness among…

  8. Culture, gaze and the neural processing of fear expressions.

    PubMed

    Adams, Reginald B; Franklin, Robert G; Rule, Nicholas O; Freeman, Jonathan B; Kveraga, Kestutis; Hadjikhani, Nouchine; Yoshikawa, Sakiko; Ambady, Nalini

    2010-06-01

    The direction of others' eye gaze has important influences on how we perceive their emotional expressions. Here, we examined differences in neural activation to direct- versus averted-gaze fear faces as a function of culture of the participant (Japanese versus US Caucasian), culture of the stimulus face (Japanese versus US Caucasian), and the relation between the two. We employed a previously validated paradigm to examine differences in neural activation in response to rapidly presented direct- versus averted-fear expressions, finding clear evidence for a culturally determined role of gaze in the processing of fear. Greater neural responsivity was apparent to averted- versus direct-gaze fear in several regions related to face and emotion processing, including bilateral amygdalae, when posed on same-culture faces, whereas greater response to direct- versus averted-gaze fear was apparent in these same regions when posed on other-culture faces. We also found preliminary evidence for intercultural variation including differential responses across participants to Japanese versus US Caucasian stimuli, and to a lesser degree differences in how Japanese and US Caucasian participants responded to these stimuli. These findings reveal a meaningful role of culture in the processing of eye gaze and emotion, and highlight their interactive influences in neural processing.

  9. Neural Correlates of Sublexical Processing in Phonological Working Memory

    ERIC Educational Resources Information Center

    McGettigan, Carolyn; Warren, Jane E.; Eisner, Frank; Marshall, Chloe R.; Shanmugalingam, Pradheep; Scott, Sophie K.

    2011-01-01

    This study investigated links between working memory and speech processing systems. We used delayed pseudoword repetition in fMRI to investigate the neural correlates of sublexical structure in phonological working memory (pWM). We orthogonally varied the number of syllables and consonant clusters in auditory pseudowords and measured the neural…

  10. Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

    ERIC Educational Resources Information Center

    Moisl, Hermann

    It is argued that pessimistic assessments of the adequacy of artificial neural networks (ANNs) for natural language processing (NLP) on the grounds that they have a finite state architecture are unjustified, and that their adequacy in this regard is an empirical issue. First, arguments that counter standard objections to finite state NLP on the…

  11. Applications of neural networks to process control and modeling

    SciTech Connect

    Barnes, C.W.; Brown, S.K.; Flake, G.W.; Jones, R.D.; O'Rourke, M.K.; Lee, Y.C.

    1991-01-01

    Modeling and control of physical processes are universal parts of modern life, from control of chemical plants to riding a bicycle. Often, an effective model of the process is not known so that traditional control theory is of little use. If a process can be represented by a set of a data which captures it behavior over a range of parameter settings, a neural net can inductively model the process and form the basis of an optimization procedure. We present a neural network architecture which is particularly effective in process modeling and control. We discuss its effectiveness in several application areas as well as some of the non-ideal characteristics present in real control problems which effect the form and style of the network architecture and learning algorithm. 8 refs., 6 figs.

  12. A new neural framework for visuospatial processing.

    PubMed

    Kravitz, Dwight J; Saleem, Kadharbatcha S; Baker, Chris I; Mishkin, Mortimer

    2011-04-01

    The division of cortical visual processing into distinct dorsal and ventral streams is a key framework that has guided visual neuroscience. The characterization of the ventral stream as a 'What' pathway is relatively uncontroversial, but the nature of dorsal stream processing is less clear. Originally proposed as mediating spatial perception ('Where'), more recent accounts suggest it primarily serves non-conscious visually guided action ('How'). Here, we identify three pathways emerging from the dorsal stream that consist of projections to the prefrontal and premotor cortices, and a major projection to the medial temporal lobe that courses both directly and indirectly through the posterior cingulate and retrosplenial cortices. These three pathways support both conscious and non-conscious visuospatial processing, including spatial working memory, visually guided action and navigation, respectively.

  13. Natural Language Processing Neural Network Considering Deep Cases

    NASA Astrophysics Data System (ADS)

    Sagara, Tsukasa; Hagiwara, Masafumi

    In this paper, we propose a novel neural network considering deep cases. It can learn knowledge from natural language documents and can perform recall and inference. Various techniques of natural language processing using Neural Network have been proposed. However, natural language sentences used in these techniques consist of about a few words, and they cannot handle complicated sentences. In order to solve these problems, the proposed network divides natural language sentences into a sentence layer, a knowledge layer, ten kinds of deep case layers and a dictionary layer. It can learn the relations among sentences and among words by dividing sentences. The advantages of the method are as follows: (1) ability to handle complicated sentences; (2) ability to restructure sentences; (3) usage of the conceptual dictionary, Goi-Taikei, as the long term memory in a brain. Two kinds of experiments were carried out by using goo dictionary and Wikipedia as knowledge sources. Superior performance of the proposed neural network has been confirmed.

  14. Neural correlates of processing "self-conscious" vs. "basic" emotions.

    PubMed

    Gilead, Michael; Katzir, Maayan; Eyal, Tal; Liberman, Nira

    2016-01-29

    Self-conscious emotions are prevalent in our daily lives and play an important role in both normal and pathological behavior. Despite their immense significance, the neural substrates that are involved in the processing of such emotions are surprisingly under-studied. In light of this, we conducted an fMRI study in which participants thought of various personal events which elicited feelings of negative and positive self-conscious (i.e., guilt, pride) or basic (i.e., anger, joy) emotions. We performed a conjunction analysis to investigate the neural correlates associated with processing events that are related to self-conscious vs. basic emotions, irrespective of valence. The results show that processing self-conscious emotions resulted in activation within frontal areas associated with self-processing and self-control, namely, the mPFC extending to the dACC, and within the lateral-dorsal prefrontal cortex. Processing basic emotions resulted in activation throughout relatively phylogenetically-ancient regions of the cortex, namely in visual and tactile processing areas and in the insular cortex. Furthermore, self-conscious emotions differentially activated the mPFC such that the negative self-conscious emotion (guilt) was associated with a more dorsal activation, and the positive self-conscious emotion (pride) was associated with a more ventral activation. We discuss how these results shed light on the nature of mental representations and neural systems involved in self-reflective and affective processing.

  15. Psychological Processing in Chronic Pain: A Neural Systems Approach

    PubMed Central

    Simons, Laura; Elman, Igor; Borsook, David

    2014-01-01

    Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementation of psychology-based treatments may be better understood. In this review we evaluate some of the principle processes that may be altered as a consequence of chronic pain in the context of localized and integrated neural networks. These changes are ongoing, vary in their magnitude, and their hierarchical manifestations, and may be temporally and sequentially altered by treatments, and all contribute to an overall pain phenotype. Furthermore, we link altered psychological processes to specific evidence-based treatments to put forth a model of pain neuroscience psychology. PMID:24374383

  16. Psychological processing in chronic pain: a neural systems approach.

    PubMed

    Simons, Laura E; Elman, Igor; Borsook, David

    2014-02-01

    Our understanding of chronic pain involves complex brain circuits that include sensory, emotional, cognitive and interoceptive processing. The feed-forward interactions between physical (e.g., trauma) and emotional pain and the consequences of altered psychological status on the expression of pain have made the evaluation and treatment of chronic pain a challenge in the clinic. By understanding the neural circuits involved in psychological processes, a mechanistic approach to the implementation of psychology-based treatments may be better understood. In this review we evaluate some of the principle processes that may be altered as a consequence of chronic pain in the context of localized and integrated neural networks. These changes are ongoing, vary in their magnitude, and their hierarchical manifestations, and may be temporally and sequentially altered by treatments, and all contribute to an overall pain phenotype. Furthermore, we link altered psychological processes to specific evidence-based treatments to put forth a model of pain neuroscience psychology.

  17. Review of neural network modelling of cracking process

    NASA Astrophysics Data System (ADS)

    Rosli, M. N.; Aziz, N.

    2016-11-01

    Cracking process is a very important process that converts low value products into high value products such as conversion of naphtha into ethylene and propylene. The process is nonlinear with extensive reaction network. Thus, nonlinear technique such as artificial neural network is explored to develop the model of the system. The paper will review and discuss the research works done on the technique in modelling cracking process using artificial neural network starting from early 1990s until recent development in 2015. Timeline is provided to show progression of work done throughout the years, the main issues addressed, and the proposed techniques for each. In the next section, the main objective of each work and each techniques explored by previous researchers is discussed in more detail. A table that summarizes previous works is provided to show common works done throughout the years. Lastly, potential gap for future works in the area is highlighted.

  18. Individual differences in speech-in-noise perception parallel neural speech processing and attention in preschoolers.

    PubMed

    Thompson, Elaine C; Woodruff Carr, Kali; White-Schwoch, Travis; Otto-Meyer, Sebastian; Kraus, Nina

    2017-02-01

    From bustling classrooms to unruly lunchrooms, school settings are noisy. To learn effectively in the unwelcome company of numerous distractions, children must clearly perceive speech in noise. In older children and adults, speech-in-noise perception is supported by sensory and cognitive processes, but the correlates underlying this critical listening skill in young children (3-5 year olds) remain undetermined. Employing a longitudinal design (two evaluations separated by ∼12 months), we followed a cohort of 59 preschoolers, ages 3.0-4.9, assessing word-in-noise perception, cognitive abilities (intelligence, short-term memory, attention), and neural responses to speech. Results reveal changes in word-in-noise perception parallel changes in processing of the fundamental frequency (F0), an acoustic cue known for playing a role central to speaker identification and auditory scene analysis. Four unique developmental trajectories (speech-in-noise perception groups) confirm this relationship, in that improvements and declines in word-in-noise perception couple with enhancements and diminishments of F0 encoding, respectively. Improvements in word-in-noise perception also pair with gains in attention. Word-in-noise perception does not relate to strength of neural harmonic representation or short-term memory. These findings reinforce previously-reported roles of F0 and attention in hearing speech in noise in older children and adults, and extend this relationship to preschool children.

  19. Impaired neural reward processing in children and adolescents with reactive attachment disorder: A pilot study.

    PubMed

    Mizuno, Kei; Takiguchi, Shinichiro; Yamazaki, Mika; Asano, Mizuki; Kato, Shiho; Kuriyama, Kikuko; Watanabe, Yasuyoshi; Sadato, Norihiro; Tomoda, Akemi

    2015-10-01

    Reactive attachment disorder (RAD) is characterized by markedly disturbed and developmentally inappropriate social relatedness due to parental maltreatment. RAD patients often display a high number of comorbid attention deficit/hyperactivity disorder (ADHD) symptoms, and certain RAD symptoms are difficult to discriminate from ADHD. One of the core characteristics of ADHD is a decrease in neural reward processing due to dopamine dysfunction. The aim of the present study was to determine whether the brain activity involved in reward processing in RAD patients is impaired in comparison with ADHD patients and typically developed controls. Five RAD patients, 17 typically developed (TD) controls and 17 ADHD patients aged 10-16 years performed tasks with high and low monetary reward while undergoing functional magnetic resonance imaging. ADHD patients were tested before and after 3 months treatment with osmotic release oral system-methylphenidate. Before treatment, ADHD patients showed that striatal and thalamus activities only in the tasks with low monetary reward were lower than TD controls. RAD patients showed decrease in activity of the caudate, putamen and thalamus during both the high and low monetary reward conditions in comparison with all the other groups. In RAD patients, the activity of the putamen was associated with the severity of posttraumatic stress and overt dissociation. Reward sensitivity was markedly decreased in children and adolescents with RAD, as evidenced by a diminished neural response during reward perception. This suggests that dopaminergic dysfunction exists in these patients, and may inform future dopaminergic treatment strategies for RAD.

  20. Attenuated Neural Processing of Risk in Young Adults at Risk for Stimulant Dependence

    PubMed Central

    Reske, Martina; Stewart, Jennifer L.; Flagan, Taru M.; Paulus, Martin P.

    2015-01-01

    critical for performance monitoring, reward processing and interoceptive awareness. Marijuana had additive effects by diminishing neural risk differentiation. PMID:26076493

  1. Nutritional state modulates the neural processing of visual motion.

    PubMed

    Longden, Kit D; Muzzu, Tomaso; Cook, Daniel J; Schultz, Simon R; Krapp, Holger G

    2014-04-14

    Food deprivation alters the processing of sensory information, increasing neural activity in the olfactory and gustatory systems in animals across phyla. Neural signaling is metabolically costly, and a hungry animal has limited energy reserves, so we hypothesized that neural activity in other systems may be downregulated by food deprivation. We investigated this hypothesis in the motion vision pathway of the blowfly. Like other animals, flies augment their motion vision when moving: they increase the resting activity and gain of visual interneurons supporting the control of locomotion and gaze. In the present study, walking-induced changes in visual processing depended on the nutritional state-they decreased with food deprivation and recovered after subsequent feeding. We found that changes in the motion vision pathway depended on walking speed in a manner dependent on the nutritional state. Walking also reduced response latencies in visual interneurons, an effect not altered by food deprivation. Finally, the optomotor reflex that compensates for visual wide-field motion was reduced in food-deprived flies. Thus, walking augmented motion vision, but the effect was decreased when energy reserves were low. Our results suggest that energy limitations may drive the rebalancing of neural activity with changes in the nutritional state.

  2. A neural network refinement of seismic data processing

    NASA Astrophysics Data System (ADS)

    Fernandez, Francisco Brito

    Seismic reflection data processing that is widely applied to oil exploration uses data acquired with low frequency ranges that are in the order of tens to hundreds hertz. This range of frequencies allow very deep penetration and low resolution data acquisition. Engineering and environmental applications require high resolution shallow subsurface seismic reflection data acquired using frequencies that range on the order of thousands hertz. Processing of high resolution shallow subsurface seismic reflection data has not been addressed in detail in the seismic exploration literature. This research presents a technique including Artificial Neural Networks to process high resolution shallow subsurface seismic reflection data. This technique is applied to locate oyster reefs and paleochannels in a seismic reflection survey performed by The Mississippi Mineral Resources Institute near Cat Island, Mississippi. Artificial Neural Networks that allow the selection of positive picks and the enhancement of reflectors in seismic reflection data are developed and applied to seismic reflection data processing. Seismic sections of the subsurface of the studied area are developed and maps depicting the location of oyster reefs and paleochannels near Cat Island, Mississippi are produced. A stepwise procedure to apply Artificial Neural Networks to the seismic data processing is also presented.

  3. Neural processes distinguishing elite from expert and novice athletes.

    PubMed

    Callan, Daniel E; Naito, Eiichi

    2014-12-01

    This commentary builds on a companion article in which Kim et al compare brain activation in elite, expert, and novice archers during a simulated target aiming task (Kim et al. 2014. Cogn Behav Neurol. 27:173-182). With the archery study as our starting point, we address 4 neural processes that may be responsible in general for elite athletes' superior performance over experts and novices: neural efficiency, cortical expansion, specialized processes, and internal models. In Kim et al's study, the elite archers' brains showed more activity in the supplementary motor area and the cerebellum than those of the novices and experts, and showed minimal widespread activity, especially in frontal areas involved with executive control. Kim et al's results are consistent with the idea of specialized neural processes that help coordinate motor planning and control. As athletes become more skilled, these processes may mediate the reduction in widespread activity in regions mapping executive control, and may produce a shift toward more automated processing. Kim et al's finding that activity in the cerebellum rose with increasing skill is consistent both with expansion of the finger representational area in the cerebellum and with internal models that simulate how archers manipulate the bow and arrow when aiming. Kim et al prepare the way for testing of neuromodulation techniques to improve athletic performance, refine highly technical job skills, and rehabilitate patients.

  4. Neural mechanisms of spatiotemporal signal processing

    NASA Astrophysics Data System (ADS)

    Khanbabaie Shoub, Shaban (Reza)

    We have studied the synaptic, dendritic, and network mechanisms of spatiotemporal signal processing underlying the computation of visual motion in the avian tectum. Such mechanisms are critical for information processing in all vertebrates, but have been difficult to elucidate in mammals because of anatomical limitations. We have therefore developed a chick tectal slice preparation, which has features that help us circumvent these limitations. Using single-electrode multi-pulse synaptic stimulation experiments we found that the SGC-I cell responds to synaptic stimulation in a binary manner and its response is phasic in a time dependent probabilistic manner over large time scales. Synaptic inputs at two locations typically interact in a mutually exclusive manner when delivered within the "interaction time" of approximately 30 ms. Then we constructed a model of SGC-I cell and the retinal inputs to examine the role of the observed non-linear cellular properties in shaping the response of SGC-I neurons to assumed retinal representations of dynamic spatiotemporal visual stimuli. We found that by these properties, SGC-I cells can classify different stimuli. Especially without the phasic synaptic signal transfer the model SGC-I cell fails to distinguish between the static stationary stimuli and dynamic spatiotemporal stimuli. Based on one-site synaptic response probability and the assumption of independent neighboring dendritic endings we predicted the response probability of SGC-I cells to multiple synaptic inputs. We tested this independence-based model prediction and found that the independency assumption is not valid. The measured SGC-I response probability to multiple synaptic inputs does not increase with the number of synaptic inputs. The presence of GABAergic horizontal cells in layer 5 suggest an inhibitory effect of these cells on the SGC-I retino-tectal synaptic responses. In our experiment we found that the measured SGC-I response probability to multiple

  5. Using neural modeling and functional neuroimaging to study the neural basis of auditory object processing

    NASA Astrophysics Data System (ADS)

    Horwitz, Barry; Husain, Fatima T.

    2003-04-01

    The neural basis of auditory object processing in the human cerebral cortex was investigated by combining neural modeling and functional neuroimaging. We developed a large-scale, neurobiologically realistic network model of auditory pattern recognition that relates neuronal dynamics of cortical auditory processing of frequency-modulated (FM) sweeps to functional neuroimaging data obtained using functional magnetic resonance imaging (fMRI). FM sweeps are ubiquitous in animal communication. Areas included in the model extend from primary auditory to prefrontal cortex. The electrical activities of the model neuronal units were constrained to agree with data from the neurophysiological literature regarding FM sweep perception. A fMRI experiment using stimuli and tasks similar to those used in our simulations was performed. The regional integrated synaptic activities of the model were used to determine simulated regional fMRI activities, and generally agreed with the experimentally observed fMRI data. Our results demonstrate that the model is capable of exhibiting the salient features of both electrophysiological neuronal activities and fMRI values that are in agreement with empirically observed data. These findings provide support for our hypotheses concerning how auditory objects are processed by primate neocortex. This type of approach offers the potential for understanding the neural basis of human speech perception.

  6. Neural-net Processed Electronic Holography for Rotating Machines

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.

    2003-01-01

    This report presents the results of an R&D effort to apply neural-net processed electronic holography to NDE of rotors. Electronic holography was used to generate characteristic patterns or mode shapes of vibrating rotors and rotor components. Artificial neural networks were trained to identify damage-induced changes in the characteristic patterns. The development and optimization of a neural-net training method were the most significant contributions of this work, and the training method and its optimization are discussed in detail. A second positive result was the assembly and testing of a fiber-optic holocamera. A major disappointment was the inadequacy of the high-speed-holography hardware selected for this effort, but the use of scaled holograms to match the low effective resolution of an image intensifier was one interesting attempt to compensate. This report also discusses in some detail the physics and environmental requirements for rotor electronic holography. The major conclusions were that neural-net and electronic-holography inspections of stationary components in the laboratory and the field are quite practical and worthy of continuing development, but that electronic holography of moving rotors is still an expensive high-risk endeavor.

  7. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, C.Y.

    1996-07-23

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

  8. Process for forming synapses in neural networks and resistor therefor

    DOEpatents

    Fu, Chi Y.

    1996-01-01

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

  9. Adaptive training diminishes distractibility in aging across species.

    PubMed

    Mishra, Jyoti; de Villers-Sidani, Etienne; Merzenich, Michael; Gazzaley, Adam

    2014-12-03

    Aging is associated with deficits in the ability to ignore distractions, which has not yet been remediated by any neurotherapeutic approach. Here, in parallel auditory experiments with older rats and humans, we evaluated a targeted cognitive training approach that adaptively manipulated distractor challenge. Training resulted in enhanced discrimination abilities in the setting of irrelevant information in both species that was driven by selectively diminished distraction-related errors. Neural responses to distractors in auditory cortex were selectively reduced in both species, mimicking the behavioral effects. Sensory receptive fields in trained rats exhibited improved spectral and spatial selectivity. Frontal theta measures of top-down engagement with distractors were selectively restrained in trained humans. Finally, training gains generalized to group and individual level benefits in aspects of working memory and sustained attention. Thus, we demonstrate converging cross-species evidence for training-induced selective plasticity of distractor processing at multiple neural scales, benefitting distractor suppression and cognitive control.

  10. Self-organized phase transitions in neural networks as a neural mechanism of information processing.

    PubMed Central

    Hoshino, O; Kashimori, Y; Kambara, T

    1996-01-01

    Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on the Hebbian learning rule are the driving force for the transition. The phase transition between the following two dynamical stable states is studied in detail, the state where the firing pattern is changed temporally so as to itinerate among several patterns and the state where the firing pattern is fixed to one of several patterns. The phase transition from the pattern itinerant state to a pattern fixed state may be induced by the Hebbian learning process under a weak input relevant to the fixed pattern. The reverse transition may be induced by the Hebbian unlearning process without input. The former transition is considered as recognition of the input stimulus, while the latter is considered as clearing of the used input data to get ready for new input. To ensure that information processing based on the phase transition can be made by the infinitesimal and short-term synaptic changes, it is absolutely necessary that the network always stays near the critical state corresponding to the phase transition point. PMID:8622933

  11. Neural language processing in adolescent first-language learners.

    PubMed

    Ferjan Ramirez, Naja; Leonard, Matthew K; Torres, Christina; Hatrak, Marla; Halgren, Eric; Mayberry, Rachel I

    2014-10-01

    The relation between the timing of language input and development of neural organization for language processing in adulthood has been difficult to tease apart because language is ubiquitous in the environment of nearly all infants. However, within the congenitally deaf population are individuals who do not experience language until after early childhood. Here, we investigated the neural underpinnings of American Sign Language (ASL) in 2 adolescents who had no sustained language input until they were approximately 14 years old. Using anatomically constrained magnetoencephalography, we found that recently learned signed words mainly activated right superior parietal, anterior occipital, and dorsolateral prefrontal areas in these 2 individuals. This spatiotemporal activity pattern was significantly different from the left fronto-temporal pattern observed in young deaf adults who acquired ASL from birth, and from that of hearing young adults learning ASL as a second language for a similar length of time as the cases. These results provide direct evidence that the timing of language experience over human development affects the organization of neural language processing.

  12. Engaged listeners: shared neural processing of powerful political speeches.

    PubMed

    Schmälzle, Ralf; Häcker, Frank E K; Honey, Christopher J; Hasson, Uri

    2015-08-01

    Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners' brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages.

  13. Engaged listeners: shared neural processing of powerful political speeches

    PubMed Central

    Häcker, Frank E. K.; Honey, Christopher J.; Hasson, Uri

    2015-01-01

    Powerful speeches can captivate audiences, whereas weaker speeches fail to engage their listeners. What is happening in the brains of a captivated audience? Here, we assess audience-wide functional brain dynamics during listening to speeches of varying rhetorical quality. The speeches were given by German politicians and evaluated as rhetorically powerful or weak. Listening to each of the speeches induced similar neural response time courses, as measured by inter-subject correlation analysis, in widespread brain regions involved in spoken language processing. Crucially, alignment of the time course across listeners was stronger for rhetorically powerful speeches, especially for bilateral regions of the superior temporal gyri and medial prefrontal cortex. Thus, during powerful speeches, listeners as a group are more coupled to each other, suggesting that powerful speeches are more potent in taking control of the listeners’ brain responses. Weaker speeches were processed more heterogeneously, although they still prompted substantially correlated responses. These patterns of coupled neural responses bear resemblance to metaphors of resonance, which are often invoked in discussions of speech impact, and contribute to the literature on auditory attention under natural circumstances. Overall, this approach opens up possibilities for research on the neural mechanisms mediating the reception of entertaining or persuasive messages. PMID:25653012

  14. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  15. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  16. A fuzzy neural network for intelligent data processing

    NASA Astrophysics Data System (ADS)

    Xie, Wei; Chu, Feng; Wang, Lipo; Lim, Eng Thiam

    2005-03-01

    In this paper, we describe an incrementally generated fuzzy neural network (FNN) for intelligent data processing. This FNN combines the features of initial fuzzy model self-generation, fast input selection, partition validation, parameter optimization and rule-base simplification. A small FNN is created from scratch -- there is no need to specify the initial network architecture, initial membership functions, or initial weights. Fuzzy IF-THEN rules are constantly combined and pruned to minimize the size of the network while maintaining accuracy; irrelevant inputs are detected and deleted, and membership functions and network weights are trained with a gradient descent algorithm, i.e., error backpropagation. Experimental studies on synthesized data sets demonstrate that the proposed Fuzzy Neural Network is able to achieve accuracy comparable to or higher than both a feedforward crisp neural network, i.e., NeuroRule, and a decision tree, i.e., C4.5, with more compact rule bases for most of the data sets used in our experiments. The FNN has achieved outstanding results for cancer classification based on microarray data. The excellent classification result for Small Round Blue Cell Tumors (SRBCTs) data set is shown. Compared with other published methods, we have used a much fewer number of genes for perfect classification, which will help researchers directly focus their attention on some specific genes and may lead to discovery of deep reasons of the development of cancers and discovery of drugs.

  17. Fault detection and classification in chemical processes based on neural networks with feature extraction.

    PubMed

    Zhou, Yifeng; Hahn, Juergen; Mannan, M Sam

    2003-10-01

    Feed forward neural networks are investigated here for fault diagnosis in chemical processes, especially batch processes. The use of the neural model prediction error as the residual for fault diagnosis of sensor and component is analyzed. To reduce the training time required for the neural process model, an input feature extraction process for the neural model is implemented. An additional radial basis function neural classifier is developed to isolate faults from the residual generated, and results are presented to demonstrate the satisfactory detection and isolation of faults using this approach.

  18. Neural Networks for Signal Processing VII Proceeding of the 1997 IEEE Workshop

    DTIC Science & Technology

    2007-11-02

    Fu, Hsin-Chia and Xu, Y. Y. 626 Neural Networks for Engine Fault Diagnostics Dong, Dawei W., Hopfield , John J., and Unnikrishnan, K. P. 636...June 98 REPORT TYPE AND DATES COVERED Final \\^Q\\ Cf\\ - M DteC ^ TITLE AND SUBTITLE Neural Networks for Signal Processing VII Proceeding...sponsored by the Neural Networks Technical Committee of the IEEE Signal Processing Society, in cooperation with the IEEE Neural Networks Council and

  19. Signal Processing in Periodically Forced Gradient Frequency Neural Networks.

    PubMed

    Kim, Ji Chul; Large, Edward W

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing.

  20. Modeling cognitive and emotional processes: a novel neural network architecture.

    PubMed

    Khashman, Adnan

    2010-12-01

    In our continuous attempts to model natural intelligence and emotions in machine learning, many research works emerge with different methods that are often driven by engineering concerns and have the common goal of modeling human perception in machines. This paper aims to go further in that direction by investigating the integration of emotion at the structural level of cognitive systems using the novel emotional DuoNeural Network (DuoNN). This network has hidden layer DuoNeurons, where each has two embedded neurons: a dorsal neuron and a ventral neuron for cognitive and emotional data processing, respectively. When input visual stimuli are presented to the DuoNN, the dorsal cognitive neurons process local features while the ventral emotional neurons process the entire pattern. We present the computational model and the learning algorithm of the DuoNN, the input information-cognitive and emotional-parallel streaming method, and a comparison between the DuoNN and a recently developed emotional neural network. Experimental results show that the DuoNN architecture, configuration, and the additional emotional information processing, yield higher recognition rates and faster learning and decision making.

  1. Forecasting financial asset processes: stochastic dynamics via learning neural networks.

    PubMed

    Giebel, S; Rainer, M

    2010-01-01

    Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

  2. Signal Processing in Periodically Forced Gradient Frequency Neural Networks

    PubMed Central

    Kim, Ji Chul; Large, Edward W.

    2015-01-01

    Oscillatory instability at the Hopf bifurcation is a dynamical phenomenon that has been suggested to characterize active non-linear processes observed in the auditory system. Networks of oscillators poised near Hopf bifurcation points and tuned to tonotopically distributed frequencies have been used as models of auditory processing at various levels, but systematic investigation of the dynamical properties of such oscillatory networks is still lacking. Here we provide a dynamical systems analysis of a canonical model for gradient frequency neural networks driven by a periodic signal. We use linear stability analysis to identify various driven behaviors of canonical oscillators for all possible ranges of model and forcing parameters. The analysis shows that canonical oscillators exhibit qualitatively different sets of driven states and transitions for different regimes of model parameters. We classify the parameter regimes into four main categories based on their distinct signal processing capabilities. This analysis will lead to deeper understanding of the diverse behaviors of neural systems under periodic forcing and can inform the design of oscillatory network models of auditory signal processing. PMID:26733858

  3. Refractory pulse counting processes in stochastic neural computers.

    PubMed

    McNeill, Dean K; Card, Howard C

    2005-03-01

    This letter quantitiatively investigates the effect of a temporary refractory period or dead time in the ability of a stochastic Bernoulli processor to record subsequent pulse events, following the arrival of a pulse. These effects can arise in either the input detectors of a stochastic neural network or in subsequent processing. A transient period is observed, which increases with both the dead time and the Bernoulli probability of the dead-time free system, during which the system reaches equilibrium. Unless the Bernoulli probability is small compared to the inverse of the dead time, the mean and variance of the pulse count distributions are both appreciably reduced.

  4. Can Intrinsic Fluctuations Increase Efficiency in Neural Information Processing?

    NASA Astrophysics Data System (ADS)

    Liljenström, Hans

    2003-05-01

    All natural processes are accompanied by fluctuations, characterized as noise or chaos. Biological systems, which have evolved during billions of years, are likely to have adapted, not only to cope with such fluctuations, but also to make use of them. We investigate how the complex dynamics of the brain, including oscillations, chaos and noise, can affect the efficiency of neural information processing. In particular, we consider the amplification and functional role of internal fluctuations. Using computer simulations of a neural network model of the olfactory cortex and hippocampus, we demonstrate how microscopic fluctuations can result in global effects at the network level. We show that the rate of information processing in associative memory tasks can be maximized for optimal noise levels, analogous to stochastic resonance phenomena. Noise can also induce transitions between different dynamical states, which could be of significance for learning and memory. A chaotic-like behavior, induced by noise or by an increase in neuronal excitability, can enhance system performance if it is transient and converges to a limit cycle memory state. We speculate whether this dynamical behavior perhaps could be related to (creative) thinking.

  5. Living ordered neural networks as model systems for signal processing

    NASA Astrophysics Data System (ADS)

    Villard, C.; Amblard, P. O.; Becq, G.; Gory-Fauré, S.; Brocard, J.; Roth, S.

    2007-06-01

    Neural circuit architecture is a fundamental characteristic of the brain, and how architecture is bound to biological functions is still an open question. Some neuronal geometries seen in the retina or the cochlea are intriguing: information is processed in parallel by several entities like in "pooling" networks which have recently drawn the attention of signal processing scientists. These systems indeed exhibit the noise-enhanced processing effect, which is also actively discussed in the neuroscience community at the neuron scale. The aim of our project is to use in-vitro ordered neuron networks as living paradigms to test ideas coming from the computational science. The different technological bolts that have to be solved are enumerated and the first results are presented. A neuron is a polarised cell, with an excitatory axon and a receiving dendritic tree. We present how soma confinement and axon differentiation can be induced by surface functionalization techniques. The recording of large neuron networks, ordered or not, is also detailed and biological signals shown. The main difficulty to access neural noise in the case of weakly connected networks grown on micro electrode arrays is explained. This open the door to a new detection technology suitable for sub-cellular analysis and stimulation, whose development will constitute the next step of this project.

  6. Musical training enhances neural processing of binaural sounds.

    PubMed

    Parbery-Clark, Alexandra; Strait, Dana L; Hittner, Emily; Kraus, Nina

    2013-10-16

    While hearing in noise is a complex task, even in high levels of noise humans demonstrate remarkable hearing ability. Binaural hearing, which involves the integration and analysis of incoming sounds from both ears, is an important mechanism that promotes hearing in complex listening environments. Analyzing inter-ear differences helps differentiate between sound sources--a key mechanism that facilitates hearing in noise. Even when both ears receive the same input, known as diotic hearing, speech intelligibility in noise is improved. Although musicians have better speech-in-noise perception compared with non-musicians, we do not know to what extent binaural processing contributes to this advantage. Musicians often demonstrate enhanced neural responses to sound, however, which may undergird their speech-in-noise perceptual enhancements. Here, we recorded auditory brainstem responses in young adult musicians and non-musicians to a speech stimulus for which there was no musician advantage when presented monaurally. When presented diotically, musicians demonstrated faster neural timing and greater intertrial response consistency relative to non-musicians. Furthermore, musicians' enhancements to the diotically presented stimulus correlated with speech-in-noise perception. These data provide evidence for musical training's impact on biological processes and suggest binaural processing as a possible contributor to more proficient hearing in noise.

  7. Towards a neural basis of processing musical semantics

    NASA Astrophysics Data System (ADS)

    Koelsch, Stefan

    2011-06-01

    Processing of meaning is critical for language perception, and therefore the majority of research on meaning processing has focused on the semantic, lexical, conceptual, and propositional processing of language. However, music is another a means of communication, and meaning also emerges from the interpretation of musical information. This article provides a framework for the investigation of the processing of musical meaning, and reviews neuroscience studies investigating this issue. These studies reveal two neural correlates of meaning processing, the N400 and the N5 (which are both components of the event-related electric brain potential). Here I argue that the N400 can be elicited by musical stimuli due to the processing of extra-musical meaning, whereas the N5 can be elicited due to the processing of intra-musical meaning. Notably, whereas the N400 can be elicited by both linguistic and musical stimuli, the N5 has so far only been observed for the processing of meaning in music. Thus, knowledge about both the N400 and the N5 can advance our understanding of how the human brain processes meaning information.

  8. Neural networks in front-end processing and control

    SciTech Connect

    Lister, J.B.; Schnurrenberger, H.; Staeheli, N.; Stockhammer, N.; Duperrex, P.A.; Moret, J.M. )

    1992-04-01

    Research into neural networks has gained a large following in recent years. In spite of the long term timescale of this Artificial Intelligence research, the tools which the community is developing can already find useful applications to real practical problems in experimental research. One of the main advantages of the parallel algorithms being developed in AI is the structural simplicity of the required hardware implementation, and the simple nature of the calculations involved. This makes these techniques ideal for problems in which both speed and data volume reduction are important, the case for most front-end processing tasks. In this paper the authors illustrate the use of a particular neural network known as the Multi-Layer Perceptron as a method for solving several different tasks, all drawn from the field of Tokamak research. The authors also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. The authors outline the type of problem which can be usefully addressed by these techniques, even before the large-scale parallel processing hardware currently under development becomes cheaply available. The authors also present some of the difficulties encountered in applying these networks.

  9. Incomplete fuzzy data processing systems using artificial neural network

    NASA Technical Reports Server (NTRS)

    Patyra, Marek J.

    1992-01-01

    In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

  10. BOOK REVIEW: Theory of Neural Information Processing Systems

    NASA Astrophysics Data System (ADS)

    Galla, Tobias

    2006-04-01

    It is difficult not to be amazed by the ability of the human brain to process, to structure and to memorize information. Even by the toughest standards the behaviour of this network of about 1011 neurons qualifies as complex, and both the scientific community and the public take great interest in the growing field of neuroscience. The scientific endeavour to learn more about the function of the brain as an information processing system is here a truly interdisciplinary one, with important contributions from biology, computer science, physics, engineering and mathematics as the authors quite rightly point out in the introduction of their book. The role of the theoretical disciplines here is to provide mathematical models of information processing systems and the tools to study them. These models and tools are at the centre of the material covered in the book by Coolen, Kühn and Sollich. The book is divided into five parts, providing basic introductory material on neural network models as well as the details of advanced techniques to study them. A mathematical appendix complements the main text. The range of topics is extremely broad, still the presentation is concise and the book well arranged. To stress the breadth of the book let me just mention a few keywords here: the material ranges from the basics of perceptrons and recurrent network architectures to more advanced aspects such as Bayesian learning and support vector machines; Shannon's theory of information and the definition of entropy are discussed, and a chapter on Amari's information geometry is not missing either. Finally the statistical mechanics chapters cover Gardner theory and the replica analysis of the Hopfield model, not without being preceded by a brief introduction of the basic concepts of equilibrium statistical physics. The book also contains a part on effective theories of the macroscopic dynamics of neural networks. Many dynamical aspects of neural networks are usually hard to find in the

  11. Neural Signaling of Food Healthiness Associated with Emotion Processing

    PubMed Central

    Herwig, Uwe; Dhum, Matthias; Hittmeyer, Anna; Opialla, Sarah; Scherpiet, Sigrid; Keller, Carmen; Brühl, Annette B.; Siegrist, Michael

    2016-01-01

    The ability to differentiate healthy from unhealthy foods is important in order to promote good health. Food, however, may have an emotional connotation, which could be inversely related to healthiness. The neurobiological background of differentiating healthy and unhealthy food and its relations to emotion processing are not yet well understood. We addressed the neural activations, particularly considering the single subject level, when one evaluates a food item to be of a higher, compared to a lower grade of healthiness with a particular view on emotion processing brain regions. Thirty-seven healthy subjects underwent functional magnetic resonance imaging while evaluating the healthiness of food presented as photographs with a subsequent rating on a visual analog scale. We compared individual evaluations of high and low healthiness of food items and also considered gender differences. We found increased activation when food was evaluated to be healthy in the left dorsolateral prefrontal cortex and precuneus in whole brain analyses. In ROI analyses, perceived and rated higher healthiness was associated with lower amygdala activity and higher ventral striatal and orbitofrontal cortex activity. Females exerted a higher activation in midbrain areas when rating food items as being healthy. Our results underline the close relationship between food and emotion processing, which makes sense considering evolutionary aspects. Actively evaluating and deciding whether food is healthy is accompanied by neural signaling associated with reward and self-relevance, which could promote salutary nutrition behavior. The involved brain regions may be amenable to mechanisms of emotion regulation in the context of psychotherapeutic regulation of food intake. PMID:26903859

  12. Dynamic Neural Processing of Linguistic Cues Related to Death

    PubMed Central

    Ma, Yina; Qin, Jungang; Han, Shihui

    2013-01-01

    Behavioral studies suggest that humans evolve the capacity to cope with anxiety induced by the awareness of death’s inevitability. However, the neurocognitive processes that underlie online death-related thoughts remain unclear. Our recent functional MRI study found that the processing of linguistic cues related to death was characterized by decreased neural activity in human insular cortex. The current study further investigated the time course of neural processing of death-related linguistic cues. We recorded event-related potentials (ERP) to death-related, life-related, negative-valence, and neutral-valence words in a modified Stroop task that required color naming of words. We found that the amplitude of an early frontal/central negativity at 84–120 ms (N1) decreased to death-related words but increased to life-related words relative to neutral-valence words. The N1 effect associated with death-related and life-related words was correlated respectively with individuals’ pessimistic and optimistic attitudes toward life. Death-related words also increased the amplitude of a frontal/central positivity at 124–300 ms (P2) and of a frontal/central positivity at 300–500 ms (P3). However, the P2 and P3 modulations were observed for both death-related and negative-valence words but not for life-related words. The ERP results suggest an early inverse coding of linguistic cues related to life and death, which is followed by negative emotional responses to death-related information. PMID:23840787

  13. Neural primacy of the salience processing system in schizophrenia.

    PubMed

    Palaniyappan, Lena; Simmonite, Molly; White, Thomas P; Liddle, Elizabeth B; Liddle, Peter F

    2013-08-21

    For effective information processing, two large-scale distributed neural networks appear to be critical: a multimodal executive system anchored on the dorsolateral prefrontal cortex (DLPFC) and a salience system anchored on the anterior insula. Aberrant interaction among distributed networks is a feature of psychiatric disorders such as schizophrenia. We used whole-brain Granger causal modeling using resting fMRI and observed a significant failure of both the feedforward and reciprocal influence between the insula and the DLPFC in schizophrenia. Further, a significant failure of directed influence from bilateral visual cortices to the insula was also seen in patients. These findings provide compelling evidence for a breakdown of the salience-execution loop in the clinical expression of psychosis. In addition, this offers a parsimonious explanation for the often-observed "frontal inefficiency," the failure to recruit prefrontal system when salient or novel information becomes available in patients with schizophrenia.

  14. Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

    PubMed

    Orbán, Levente L; Chartier, Sylvain

    2015-01-01

    Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

  15. Image processing and analysis using neural networks for optometry area

    NASA Astrophysics Data System (ADS)

    Netto, Antonio V.; Ferreira de Oliveira, Maria C.

    2002-11-01

    In this work we describe the framework of a functional system for processing and analyzing images of the human eye acquired by the Hartmann-Shack technique (HS), in order to extract information to formulate a diagnosis of eye refractive errors (astigmatism, hypermetropia and myopia). The analysis is to be carried out using an Artificial Intelligence system based on Neural Nets, Fuzzy Logic and Classifier Combination. The major goal is to establish the basis of a new technology to effectively measure ocular refractive errors that is based on methods alternative those adopted in current patented systems. Moreover, analysis of images acquired with the Hartmann-Shack technique may enable the extraction of additional information on the health of an eye under exam from the same image used to detect refraction errors.

  16. Neural Processing of Emotional Musical and Nonmusical Stimuli in Depression

    PubMed Central

    Atchley, Ruth Ann; Chrysikou, Evangelia; Martin, Laura E.; Clair, Alicia A.; Ingram, Rick E.; Simmons, W. Kyle; Savage, Cary R.

    2016-01-01

    Background Anterior cingulate cortex (ACC) and striatum are part of the emotional neural circuitry implicated in major depressive disorder (MDD). Music is often used for emotion regulation, and pleasurable music listening activates the dopaminergic system in the brain, including the ACC. The present study uses functional MRI (fMRI) and an emotional nonmusical and musical stimuli paradigm to examine how neural processing of emotionally provocative auditory stimuli is altered within the ACC and striatum in depression. Method Nineteen MDD and 20 never-depressed (ND) control participants listened to standardized positive and negative emotional musical and nonmusical stimuli during fMRI scanning and gave subjective ratings of valence and arousal following scanning. Results ND participants exhibited greater activation to positive versus negative stimuli in ventral ACC. When compared with ND participants, MDD participants showed a different pattern of activation in ACC. In the rostral part of the ACC, ND participants showed greater activation for positive information, while MDD participants showed greater activation to negative information. In dorsal ACC, the pattern of activation distinguished between the types of stimuli, with ND participants showing greater activation to music compared to nonmusical stimuli, while MDD participants showed greater activation to nonmusical stimuli, with the greatest response to negative nonmusical stimuli. No group differences were found in striatum. Conclusions These results suggest that people with depression may process emotional auditory stimuli differently based on both the type of stimulation and the emotional content of that stimulation. This raises the possibility that music may be useful in retraining ACC function, potentially leading to more effective and targeted treatments. PMID:27284693

  17. Acoustic richness modulates the neural networks supporting intelligible speech processing.

    PubMed

    Lee, Yune-Sang; Min, Nam Eun; Wingfield, Arthur; Grossman, Murray; Peelle, Jonathan E

    2016-03-01

    The information contained in a sensory signal plays a critical role in determining what neural processes are engaged. Here we used interleaved silent steady-state (ISSS) functional magnetic resonance imaging (fMRI) to explore how human listeners cope with different degrees of acoustic richness during auditory sentence comprehension. Twenty-six healthy young adults underwent scanning while hearing sentences that varied in acoustic richness (high vs. low spectral detail) and syntactic complexity (subject-relative vs. object-relative center-embedded clause structures). We manipulated acoustic richness by presenting the stimuli as unprocessed full-spectrum speech, or noise-vocoded with 24 channels. Importantly, although the vocoded sentences were spectrally impoverished, all sentences were highly intelligible. These manipulations allowed us to test how intelligible speech processing was affected by orthogonal linguistic and acoustic demands. Acoustically rich speech showed stronger activation than acoustically less-detailed speech in a bilateral temporoparietal network with more pronounced activity in the right hemisphere. By contrast, listening to sentences with greater syntactic complexity resulted in increased activation of a left-lateralized network including left posterior lateral temporal cortex, left inferior frontal gyrus, and left dorsolateral prefrontal cortex. Significant interactions between acoustic richness and syntactic complexity occurred in left supramarginal gyrus, right superior temporal gyrus, and right inferior frontal gyrus, indicating that the regions recruited for syntactic challenge differed as a function of acoustic properties of the speech. Our findings suggest that the neural systems involved in speech perception are finely tuned to the type of information available, and that reducing the richness of the acoustic signal dramatically alters the brain's response to spoken language, even when intelligibility is high.

  18. Neural bases of syntax-semantics interface processing.

    PubMed

    Malaia, Evguenia; Newman, Sharlene

    2015-06-01

    The binding problem-question of how information between the modules of the linguistic system is integrated during language processing-is as yet unresolved. The remarkable speed of language processing and comprehension (Pulvermüller et al. 2009) suggests that at least coarse semantic information (e.g. noun animacy) and syntactically-relevant information (e.g. verbal template) are integrated rapidly to allow for coarse comprehension. This EEG study investigated syntax-semantics interface processing during word-by-word sentence reading. As alpha-band neural activity serves as an inhibition mechanism for local networks, we used topographical distribution of alpha power to help identify the timecourse of the binding process. We manipulated the syntactic parameter of verbal event structure, and semantic parameter of noun animacy in reduced relative clauses (RRCs, e.g. "The witness/mansion seized/protected by the agent was in danger"), to investigate the neural bases of interaction between syntactic and semantic networks during sentence processing. The word-by-word stimulus presentation method in the present experiment required manipulation of both syntactic structure and semantic features in the working memory. The results demonstrated a gradient distribution of early components (biphasic posterior P1-N2 and anterior N1-P2) over function words "by" and "the", and the verb, corresponding to facilitation or conflict resulting from the syntactic (telicity) and semantic (animacy) cues in the preceding portion of the sentence. This was followed by assimilation of power distribution in the α band at the second noun. The flattened distribution of α power during the mental manipulation with high demand on working memory-thematic role re-assignment-demonstrates a state of α equilibrium with strong functional coupling between posterior and anterior regions. These results demonstrate that the processing of semantic and syntactic features during sentence comprehension proceeds

  19. Comparison enhances size sensitivity: neural correlates of outcome magnitude processing.

    PubMed

    Luo, Qiuling; Qu, Chen

    2013-01-01

    Magnitude is a critical feature of outcomes. In the present study, two event-related potential (ERP) experiments were implemented to explore the neural substrates of outcome magnitude processing. In Experiment 1, we used an adapted gambling paradigm where physical area symbols were set to represent potential relative outcome magnitudes in order to exclude the possibility that the participants would be ignorant of the magnitudes. The context was manipulated as total monetary amount: ¥4 and ¥40. In these two contexts, the relative outcome magnitudes were ¥1 versus ¥3, and ¥10 versus ¥30, respectively. Experiment 2, which provided two area symbols with similar outcome magnitudes, was conducted to exclude the possible interpretation of physical area symbol for magnitude effect of feedback-related negativity (FRN) in Experiment 1. Our results showed that FRN responded to the relative outcome magnitude but not to the context or area symbol, with larger amplitudes for relatively small outcomes. A larger FRN effect (the difference between losses and wins) was found for relatively large outcomes than relatively small outcomes. Relatively large outcomes evoked greater positive ERP waves (P300) than relatively small outcomes. Furthermore, relatively large outcomes in a high amount context elicited a larger P300 than those in a low amount context. The current study indicated that FRN is sensitive to variations in magnitude. Moreover, relative magnitude was integrated in both the early and late stages of feedback processing, while the monetary amount context was processed only in the late stage of feedback processing.

  20. Neural network feature detector for real-time video signal processing.

    PubMed

    Naylor, D; Jones, S; Myers, D; Vincent, J

    1993-12-01

    The application of artificial neural networks to real-time image processing tasks requires the use of dedicated, high performance hardware. A linear array processor called HANNIBAL has been developed which implements the backpropagation neural learning algorithm on-chip. This paper considers the design of a complete neural system which integrates HANNIBAL into an existing image processing environment. The goals for the design of the system have been set partly by the primary application, namely feature recognition, but mainly by the desire for a flexible, high performance hardware tool for the study and evaluation of range of neural image processing applications.

  1. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    SciTech Connect

    Saini, K. K.; Saini, Sanju

    2008-10-07

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  2. The Application of Neural Networks with Artificial Intelligence Technique in the Modeling of Industrial Processes

    NASA Astrophysics Data System (ADS)

    Saini, K. K.; Saini, Sanju

    2008-10-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can "learn," automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  3. Retinal vessel extraction using Lattice Neural Networks with Dendritic Processing.

    PubMed

    Vega, Roberto; Sanchez-Ante, Gildardo; Falcon-Morales, Luis E; Sossa, Humberto; Guevara, Elizabeth

    2015-03-01

    Retinal images can be used to detect and follow up several important chronic diseases. The classification of retinal images requires an experienced ophthalmologist. This has been a bottleneck to implement routine screenings performed by general physicians. It has been proposed to create automated systems that can perform such task with little intervention from humans, with partial success. In this work, we report advances in such endeavor, by using a Lattice Neural Network with Dendritic Processing (LNNDP). We report results using several metrics, and compare against well known methods such as Support Vector Machines (SVM) and Multilayer Perceptrons (MLP). Our proposal shows better performance than other approaches reported in the literature. An additional advantage is that unlike those other tools, LNNDP requires no parameters, and it automatically constructs its structure to solve a particular problem. The proposed methodology requires four steps: (1) Pre-processing, (2) Feature computation, (3) Classification and (4) Post-processing. The Hotelling T(2) control chart was used to reduce the dimensionality of the feature vector, from 7 that were used before to 5 in this work. The experiments were run on images of DRIVE and STARE databases. The results show that on average, F1-Score is better in LNNDP, compared with SVM and MLP implementations. Same improvement is observed for MCC and the accuracy.

  4. fMRI Scanner Noise Interaction with Affective Neural Processes

    PubMed Central

    Skouras, Stavros; Gray, Marcus; Critchley, Hugo; Koelsch, Stefan

    2013-01-01

    The purpose of the present study was the investigation of interaction effects between functional MRI scanner noise and affective neural processes. Stimuli comprised of psychoacoustically balanced musical pieces, expressing three different emotions (fear, neutral, joy). Participants (N=34, 19 female) were split into two groups, one subjected to continuous scanning and another subjected to sparse temporal scanning that features decreased scanner noise. Tests for interaction effects between scanning group (sparse/quieter vs continuous/noisier) and emotion (fear, neutral, joy) were performed. Results revealed interactions between the affective expression of stimuli and scanning group localized in bilateral auditory cortex, insula and visual cortex (calcarine sulcus). Post-hoc comparisons revealed that during sparse scanning, but not during continuous scanning, BOLD signals were significantly stronger for joy than for fear, as well as stronger for fear than for neutral in bilateral auditory cortex. During continuous scanning, but not during sparse scanning, BOLD signals were significantly stronger for joy than for neutral in the left auditory cortex and for joy than for fear in the calcarine sulcus. To the authors' knowledge, this is the first study to show a statistical interaction effect between scanner noise and affective processes and extends evidence suggesting scanner noise to be an important factor in functional MRI research that can affect and distort affective brain processes. PMID:24260420

  5. Signal processing using artificial neural network for BOTDA sensor system.

    PubMed

    Azad, Abul Kalam; Wang, Liang; Guo, Nan; Tam, Hwa-Yaw; Lu, Chao

    2016-03-21

    We experimentally demonstrate the use of artificial neural network (ANN) to process sensing signals obtained from Brillouin optical time domain analyzer (BOTDA). The distributed temperature information is extracted directly from the local Brillouin gain spectra (BGSs) along the fiber under test without the process of determination of Brillouin frequency shift (BFS) and hence conversion from BFS to temperature. Unlike our previous work for short sensing distance where ANN is trained by measured BGSs, here we employ ideal BGSs with different linewidths to train the ANN in order to take the linewidth variation due to different conditions from the training and testing phases into account, making it feasible for long distance sensing. Moreover, the performance of ANN is compared with other two techniques, Lorentzian curve fitting and cross-correlation method, and our results show that ANN has higher accuracy and larger tolerance to measurement error, especially at large frequency scanning step. We also show that the temperature extraction from BOTDA measurements employing ANN is significantly faster than the other two approaches. Hence ANN can be an excellent alternative tool to process BGSs measured by BOTDA and obtain temperature distribution along the fiber, especially when large frequency scanning step is adopted to significantly reduce the measurement time but without sacrifice of sensing accuracy.

  6. Ventral striatal hypoactivation is associated with apathy but not diminished expression in patients with schizophrenia

    PubMed Central

    Kirschner, Matthias; Hager, Oliver M.; Bischof, Martin; Hartmann, Matthias N.; Kluge, Agne; Seifritz, Erich; Tobler, Philippe N.; Kaiser, Stefan

    2016-01-01

    Background Negative symptoms of schizophrenia can be grouped in 2 dimensions: apathy and diminished expression. Increasing evidence suggests that negative symptoms are associated with altered neural activity of subcortical and cortical regions in the brain reward system. However, the neurobiological basis of the distinct symptom dimensions within negative symptoms is still poorly understood. The primary aim of our study was to examine the neural correlates of the negative symptom dimensions apathy and diminished expression during a reward processing task. Methods Patients with schizophrenia and healthy controls underwent event-related fMRI while performing a variant of the Monetary Incentive Delay Task. We assessed negative symptom dimensions using the Brief Negative Symptom Scale. Results We included 27 patients and 25 controls in our study. Both groups showed neural activation indicated by blood oxygen–level dependent signal in the ventral striatum during reward anticipation. Ventral striatal activation during reward anticipation showed a strong negative correlation with apathy. Importantly, this effect was not driven by cognitive ability, medication, depressive or positive symptoms. In contrast, no significant correlation with the diminished expression dimension was observed. Limitations Although the results remain significant when controlling for chlorpromazine equivalents, we cannot fully exclude potential confounding effects of medication with atypical antipsychotics. Conclusion The specific correlation of ventral striatal hypoactivation during reward anticipation with apathy demonstrates a differentiation of apathy and diminished expression on a neurobiological level and provides strong evidence for different pathophysiological mechanisms underlying these 2 negative symptom dimensions. Our findings contribute to a multilevel framework in which apathy and motivational impairment in patients with schizophrenia can be described on psychopathological

  7. The neural transfer effect of working memory training to enhance hedonic processing in individuals with social anhedonia

    PubMed Central

    Li, Xu; Li, Zhi; Li, Ke; Zeng, Ya-wei; Shi, Hai-song; Xie, Wen-lan; Yang, Zhuo-ya; Lui, Simon S. Y.; Cheung, Eric F. C.; Leung, Ada W. S.; Chan, Raymond C. K.

    2016-01-01

    Anhedonia, the diminished ability to experience pleasure, is a challenging negative symptom in patients with schizophrenia and can be observed in at-risk individuals with schizotypy. Deficits in hedonic processing have been postulated to be related to decreased motivation to engage in potentially rewarding events. It remains unclear whether non-pharmacological interventions, such as cognitive training, could improve anhedonia. The present study aimed to examine the neural mechanism for alleviating hedonic deficits with working memory (WM) training in individuals with social anhedonia. Fifteen individuals with social anhedonia were recruited and received 20 sessions of training on a dual n-back task, five sessions a week. Functional imaging paradigms of the Monetary Incentive Delay (MID) and the Affective Incentive Delay (AID) tasks were administered both before and after the training to evaluate the neural transfer effects on hedonic processing ability. Enhanced brain activations related to anticipation were observed at the anterior cingulate cortex, the left dorsal striatum and the left precuneus with the AID task, and at the dorsolateral prefrontal cortex and the supramarginal gyrus with the MID task. The present findings support that WM training may improve monetary-based and affective-based hedonic processing in individuals with social anhedonia. PMID:27752140

  8. It's all about money: oral contraception alters neural reward processing.

    PubMed

    Bonenberger, Martina; Groschwitz, Rebecca C; Kumpfmueller, Daniela; Groen, Georg; Plener, Paul L; Abler, Birgit

    2013-12-04

    Mating preferences in phases of the natural menstrual cycle with a low probability to conceive have been associated with lower interest in characteristics promising genetic benefits but increased search for safety and future security. We hypothesized that this effect would also be evident under oral contraception and may therefore alter neural processing of monetary rewards as a proxy for potential safety. Our aim was to assess the activation of reward-related brain areas using a monetary incentive task in women with functional MRI (fMRI). We compared fMRI activation of 12 young women taking oral contraceptives with 12 women with a natural hormonal cycle in their follicular phase during the expectation of monetary rewards. Women under hormonal contraception who have already shown decreased anterior insula activation upon erotic stimulation in a previous study of the same sample now showed enhanced activation during monetary reward expectation in the anterior insula/inferior lateral prefrontal cortex (t=2.84; P<0.05) relative to young normal cycling women in the follicular phase. Our finding supports the notion that the switch in mating preferences related to different hormonal states in women is mirrored by a switch in the stimulus-dependent excitability of reward-related brain regions. Beyond highlighting hormonal effects on reward processing, our data underline the importance of monitoring hormonal states in fMRI research in women.

  9. Biospeckle image stack process based on artificial neural networks.

    PubMed

    Meschino, Gustavo; Murialdo, Silvia; Passoni, Lucia; Rabal, Hector; Trivi, Marcelo

    2010-01-01

    This paper proposes the identification of regions of interest in biospeckle patterns using unsupervised neural networks of the type Self-Organizing Maps. Segmented images are obtained from the acquisition and processing of laser speckle sequences. The dynamic speckle is a phenomenon that occurs when a beam of coherent light illuminates a sample in which there is some type of activity, not visible, which results in a variable pattern over time. In this particular case the method is applied to the evaluation of bacterial chemotaxis. Image stacks provided by a set of experiments are processed to extract features of the intensity dynamics. A Self-Organizing Map is trained and its cells are colored according to a criterion of similarity. During the recall stage the features of patterns belonging to a new biospeckle sample impact on the map, generating a new image using the color of the map cells impacted by the sample patterns. It is considered that this method has shown better performance to identify regions of interest than those that use a single descriptor. To test the method a chemotaxis assay experiment was performed, where regions were differentiated according to the bacterial motility within the sample.

  10. Neural correlates of semantic competition during processing of ambiguous words.

    PubMed

    Bilenko, Natalia Y; Grindrod, Christopher M; Myers, Emily B; Blumstein, Sheila E

    2009-05-01

    The current study investigated the neural correlates that underlie the processing of ambiguous words and the potential effects of semantic competition on that processing. Participants performed speeded lexical decisions on semantically related and unrelated prime-target pairs presented in the auditory modality. The primes were either ambiguous words (e.g., ball) or unambiguous words (e.g., athlete), and targets were either semantically related to the dominant (i.e., most frequent) meaning of the ambiguous prime word (e.g., soccer) or to the subordinate (i.e., less frequent) meaning (e.g., dance). Results showed increased activation in the bilateral inferior frontal gyrus (IFG) for ambiguous-related compared to unambiguous-related stimulus pairs, demonstrating that prefrontal areas are activated even in an implicit task where participants are not required to explicitly analyze the semantic content of the stimuli and to make an overt selection of a particular meaning based on this analysis. Additionally, increased activation was found in the left IFG and the left cingulate gyrus for subordinate meaning compared to dominant meaning conditions, suggesting that additional resources are recruited in order to resolve increased competition demands in accessing the subordinate meaning of an ambiguous word.

  11. Childhood Social Inequalities Influences Neural Processes in Young Adult Caregiving

    PubMed Central

    Kim, Pilyoung; Ho, S. Shaun; Evans, Gary W.; Liberzon, Israel; Swain, James E.

    2016-01-01

    Childhood poverty is associated with harsh parenting with a risk of transmission to the next generation. This prospective study examined the relations between childhood poverty and non-parent adults’ neural responses to infant cry sounds. While no main effects of poverty were revealed in contrasts of infant cry vs. acoustically matched white noise, a gender by childhood poverty interaction emerged. In females, childhood poverty was associated with increased neural activations in the posterior insula, striatum, calcarine sulcus, hippocampus and fusiform gyrus, while, in males, childhood poverty was associated with reduced levels of neural responses to infant cry in the same regions. Irrespective of gender, neural activation in these regions was associated with higher levels of annoyance with the cry sound and reduced desire to approach the crying infant. The findings suggest gender differences in neural and emotional responses to infant cry sounds among young adults growing up in poverty. PMID:25981334

  12. Synthesis of neural networks for spatio-temporal spike pattern recognition and processing

    PubMed Central

    Tapson, Jonathan C.; Cohen, Greg K.; Afshar, Saeed; Stiefel, Klaus M.; Buskila, Yossi; Wang, Runchun Mark; Hamilton, Tara J.; van Schaik, André

    2013-01-01

    The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework (NEF) offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify—arbitrarily—neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times. PMID:24009550

  13. Synthesis of neural networks for spatio-temporal spike pattern recognition and processing.

    PubMed

    Tapson, Jonathan C; Cohen, Greg K; Afshar, Saeed; Stiefel, Klaus M; Buskila, Yossi; Wang, Runchun Mark; Hamilton, Tara J; van Schaik, André

    2013-01-01

    The advent of large scale neural computational platforms has highlighted the lack of algorithms for synthesis of neural structures to perform predefined cognitive tasks. The Neural Engineering Framework (NEF) offers one such synthesis, but it is most effective for a spike rate representation of neural information, and it requires a large number of neurons to implement simple functions. We describe a neural network synthesis method that generates synaptic connectivity for neurons which process time-encoded neural signals, and which makes very sparse use of neurons. The method allows the user to specify-arbitrarily-neuronal characteristics such as axonal and dendritic delays, and synaptic transfer functions, and then solves for the optimal input-output relationship using computed dendritic weights. The method may be used for batch or online learning and has an extremely fast optimization process. We demonstrate its use in generating a network to recognize speech which is sparsely encoded as spike times.

  14. Neural networks for perceptual processing: from simulation tools to theories.

    PubMed

    Gurney, Kevin

    2007-03-29

    Neural networks are modelling tools that are, in principle, able to capture the input-output behaviour of arbitrary systems that may include the dynamics of animal populations or brain circuits. While a neural network model is useful if it captures phenomenologically the behaviour of the target system in this way, its utility is amplified if key mechanisms of the model can be discovered, and identified with those of the underlying system. In this review, we first describe, at a fairly high level with minimal mathematics, some of the tools used in constructing neural network models. We then go on to discuss the implications of network models for our understanding of the system they are supposed to describe, paying special attention to those models that deal with neural circuits and brain systems. We propose that neural nets are useful for brain modelling if they are viewed in a wider computational framework originally devised by Marr. Here, neural networks are viewed as an intermediate mechanistic abstraction between 'algorithm' and 'implementation', which can provide insights into biological neural representations and their putative supporting architectures.

  15. High school music classes enhance the neural processing of speech.

    PubMed

    Tierney, Adam; Krizman, Jennifer; Skoe, Erika; Johnston, Kathleen; Kraus, Nina

    2013-01-01

    Should music be a priority in public education? One argument for teaching music in school is that private music instruction relates to enhanced language abilities and neural function. However, the directionality of this relationship is unclear and it is unknown whether school-based music training can produce these enhancements. Here we show that 2 years of group music classes in high school enhance the neural encoding of speech. To tease apart the relationships between music and neural function, we tested high school students participating in either music or fitness-based training. These groups were matched at the onset of training on neural timing, reading ability, and IQ. Auditory brainstem responses were collected to a synthesized speech sound presented in background noise. After 2 years of training, the neural responses of the music training group were earlier than at pre-training, while the neural timing of students in the fitness training group was unchanged. These results represent the strongest evidence to date that in-school music education can cause enhanced speech encoding. The neural benefits of musical training are, therefore, not limited to expensive private instruction early in childhood but can be elicited by cost-effective group instruction during adolescence.

  16. Neural correlates of emotional processing in depression: changes with cognitive behavioral therapy and predictors of treatment response.

    PubMed

    Ritchey, Maureen; Dolcos, Florin; Eddington, Kari M; Strauman, Timothy J; Cabeza, Roberto

    2011-05-01

    Major depressive disorder (MDD) is characterized by the presence of disturbances in emotional processing. However, the neural correlates of these alterations, and how they may be affected by therapeutic interventions, remain unclear. The present study addressed these issues in a preliminary investigation using functional magnetic resonance imaging (fMRI) to examine neural responses to positive, negative, and neutral pictures in unmedicated MDD patients (N = 22) versus controls (N = 14). After this initial scan, MDD patients were treated with cognitive behavioral therapy (CBT) and scanned again after treatment. Within regions that showed pre-treatment differences between patients and controls, we tested the association between pre-treatment activity and subsequent treatment response as well as activity changes from pre- to post-treatment. This study yielded three main findings. First, prior to treatment and relative to controls, patients exhibited overall reduced activity in the ventromedial prefrontal cortex (PFC), diminished discrimination between emotional and neutral items in the amygdala, caudate, and hippocampus, and enhanced responses to negative versus positive stimuli in the left anterior temporal lobe (ATL) and right dorsolateral PFC. Second, CBT-related symptom improvement in MDD patients was predicted by increased activity at baseline in ventromedial PFC as well as the valence effects in the ATL and dorsolateral PFC. Third, from pre- to post-treatment, MDD patients exhibited overall increases in ventromedial PFC activation, enhanced arousal responses in the amygdala, caudate, and hippocampus, and a reversal of valence effects in the ATL. The study was limited by the relatively small sample that was able to complete both scan sessions, as well as an inability to determine the influence of comorbid disorders within the current sample. Nevertheless, components of the neural networks corresponding to emotion processing disturbances in MDD appear to resolve

  17. Neural substrates of sensorimotor processes: letter writing and letter perception

    PubMed Central

    James, Karin H.

    2015-01-01

    Writing and perceiving letters are thought to share similar neural substrates; however, what constitutes a neural representation for letters is currently debated. One hypothesis is that letter representation develops from sensorimotor experience resulting in an integrated set of modality-specific regions, whereas an alternative account suggests that letter representations may be abstract, independent of modality. Studies reviewed suggest that letter representation consists of a network of modality-responsive brain regions that may include an abstract component. PMID:26203115

  18. Neural network post-processing of grayscale optical correlator

    NASA Technical Reports Server (NTRS)

    Lu, Thomas T; Hughlett, Casey L.; Zhoua, Hanying; Chao, Tien-Hsin; Hanan, Jay C.

    2005-01-01

    In this paper we present the use of a radial basis function neural network (RBFNN) as a post-processor to assist the optical correlator to identify the objects and to reject false alarms. Image plane features near the correlation peaks are extracted and fed to the neural network for analysis. The approach is capable of handling large number of object variations and filter sets. Preliminary experimental results are presented and the performance is analyzed.

  19. Hybrid neural network modeling of a full-scale industrial wastewater treatment process.

    PubMed

    Lee, Dae Sung; Jeon, Che Ok; Park, Jong Moon; Chang, Kun Soo

    2002-06-20

    In recent years, hybrid neural network approaches, which combine mechanistic and neural network models, have received considerable attention. These approaches are potentially very efficient for obtaining more accurate predictions of process dynamics by combining mechanistic and neural network models in such a way that the neural network model properly accounts for unknown and nonlinear parts of the mechanistic model. In this work, a full-scale coke-plant wastewater treatment process was chosen as a model system. Initially, a process data analysis was performed on the actual operational data by using principal component analysis. Next, a simplified mechanistic model and a neural network model were developed based on the specific process knowledge and the operational data of the coke-plant wastewater treatment process, respectively. Finally, the neural network was incorporated into the mechanistic model in both parallel and serial configurations. Simulation results showed that the parallel hybrid modeling approach achieved much more accurate predictions with good extrapolation properties as compared with the other modeling approaches even in the case of process upset caused by, for example, shock loading of toxic compounds. These results indicate that the parallel hybrid neural modeling approach is a useful tool for accurate and cost-effective modeling of biochemical processes, in the absence of other reasonably accurate process models.

  20. Identifying the Neural Correlates Underlying Social Pain: Implications for Developmental Processes

    ERIC Educational Resources Information Center

    Eisenberger, Naomi I.

    2006-01-01

    Although the need for social connection is critical for early social development as well as for psychological well-being throughout the lifespan, relatively little is known about the neural processes involved in maintaining social connections. The following review summarizes what is known regarding the neural correlates underlying feeling of…

  1. Effects of Modality on the Neural Correlates of Encoding Processes Supporting Recollection and Familiarity

    ERIC Educational Resources Information Center

    Gottlieb, Lauren J.; Rugg, Michael D.

    2011-01-01

    Prior research has demonstrated that the neural correlates of successful encoding ("subsequent memory effects") partially overlap with neural regions selectively engaged by the on-line demands of the study task. The primary goal of the present experiment was to determine whether this overlap is associated solely with encoding processes supporting…

  2. On dissociating the neural time course of the processing of positive emotions.

    PubMed

    daSilva, Elizabeth B; Crager, Kirsten; Puce, Aina

    2016-03-01

    Providing evidence for categorical theories of emotion mandates the inclusion of discrete emotion categories beyond the typical six "basic" emotions. Traditional neurophysiological investigations of emotion typically feature the six basic emotions with happiness as the lone positive exemplar. Here we studied how event-related potentials (ERPs) might differentiate between two positive emotional expressions: happiness and pride, and if so, at what time interval. Furthermore, given divergent findings in the ERP literature with respect to viewing emotional expressions, we explicitly examined how task type modulates neurophysiological responses when the same stimuli are viewed. While a continuous electroencephalogram (EEG) was recorded, 20 healthy participants completed two tasks: an implicit task where participants judged whether or not a face featured a brown spot (freckle), and an explicit task where they judged the face as portraying a "happy," "proud," or "neutral" expression. Behavioral performance exceeded 90% accuracy on both tasks. In the explicit task, participants responded faster and more accurately for Happy compared to Proud and Neutral expressions. Neurophysiologically, amplitudes for N170, VPP and P250 ERPs differentiated emotional from neutral expressions, but not from each other. In contrast, the late SPW component significantly differentiated Happy and Proud expressions from each other. Moreover, main effects of Task were found for the VPP, P250, LPP and SPW; additionally, Emotion X Task interactions were observed for P250 and SPW. Our data stress that task demands may magnify or diminish neural processing differences between emotion categories, which therefore cannot be disentangled with a single experimental paradigm. Additionally, some ERP differences may also reflect variations in categorization difficulty.

  3. Journey to the Edges: Social Structures and Neural Maps of Intergroup Processes

    PubMed Central

    Fiske, Susan T.

    2013-01-01

    This article explores boundaries of the intellectual map of intergroup processes, going to the macro (social structure) boundary and the micro (neural systems) boundary. Both are illustrated by with my own and others’ work on social structures and on neural structures related to intergroup processes. Analyzing the impact of social structures on intergroup processes led to insights about distinct forms of sexism and underlies current work on forms of ageism. The stereotype content model also starts with the social structure of intergroup relations (interdependence and status) and predicts images, emotions, and behaviors. Social structure has much to offer the social psychology of intergroup processes. At the other, less explored boundary, social neuroscience addresses the effects of social contexts on neural systems relevant to intergroup processes. Both social structural and neural analyses circle back to traditional social psychology as converging indicators of intergroup processes. PMID:22435843

  4. Frontotemporal neural systems supporting semantic processing in Alzheimer's disease.

    PubMed

    Peelle, Jonathan E; Powers, John; Cook, Philip A; Smith, Edward E; Grossman, Murray

    2014-03-01

    We hypothesized that semantic memory for object concepts involves both representations of visual feature knowledge in modality-specific association cortex and heteromodal regions that are important for integrating and organizing this semantic knowledge so that it can be used in a flexible, contextually appropriate manner. We examined this hypothesis in an fMRI study of mild Alzheimer's disease (AD). Participants were presented with pairs of printed words and asked whether the words matched on a given visual-perceptual feature (e.g., guitar, violin: SHAPE). The stimuli probed natural kinds and manufactured objects, and the judgments involved shape or color. We found activation of bilateral ventral temporal cortex and left dorsolateral prefrontal cortex during semantic judgments, with AD patients showing less activation of these regions than healthy seniors. Moreover, AD patients showed less ventral temporal activation than did healthy seniors for manufactured objects, but not for natural kinds. We also used diffusion-weighted MRI of white matter to examine fractional anisotropy (FA). Patients with AD showed significantly reduced FA in the superior longitudinal fasciculus and inferior frontal-occipital fasciculus, which carry projections linking temporal and frontal regions of this semantic network. Our results are consistent with the hypothesis that semantic memory is supported in part by a large-scale neural network involving modality-specific association cortex, heteromodal association cortex, and projections between these regions. The semantic deficit in AD thus arises from gray matter disease that affects the representation of feature knowledge and processing its content, as well as white matter disease that interrupts the integrated functioning of this large-scale network.

  5. Optimization of Training Sets for Neural-Net Processing of Characteristic Patterns from Vibrating Solids

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.

    2001-01-01

    Artificial neural networks have been used for a number of years to process holography-generated characteristic patterns of vibrating structures. This technology depends critically on the selection and the conditioning of the training sets. A scaling operation called folding is discussed for conditioning training sets optimally for training feed-forward neural networks to process characteristic fringe patterns. Folding allows feed-forward nets to be trained easily to detect damage-induced vibration-displacement-distribution changes as small as 10 nm. A specific application to aerospace of neural-net processing of characteristic patterns is presented to motivate the conditioning and optimization effort.

  6. Models of Innate Neural Attractors and Their Applications for Neural Information Processing.

    PubMed

    Solovyeva, Ksenia P; Karandashev, Iakov M; Zhavoronkov, Alex; Dunin-Barkowski, Witali L

    2015-01-01

    In this work we reveal and explore a new class of attractor neural networks, based on inborn connections provided by model molecular markers, the molecular marker based attractor neural networks (MMBANN). Each set of markers has a metric, which is used to make connections between neurons containing the markers. We have explored conditions for the existence of attractor states, critical relations between their parameters and the spectrum of single neuron models, which can implement the MMBANN. Besides, we describe functional models (perceptron and SOM), which obtain significant advantages over the traditional implementation of these models, while using MMBANN. In particular, a perceptron, based on MMBANN, gets specificity gain in orders of error probabilities values, MMBANN SOM obtains real neurophysiological meaning, the number of possible grandma cells increases 1000-fold with MMBANN. MMBANN have sets of attractor states, which can serve as finite grids for representation of variables in computations. These grids may show dimensions of d = 0, 1, 2,…. We work with static and dynamic attractor neural networks of the dimensions d = 0 and 1. We also argue that the number of dimensions which can be represented by attractors of activities of neural networks with the number of elements N = 10(4) does not exceed 8.

  7. Audience preferences are predicted by temporal reliability of neural processing

    PubMed Central

    Dmochowski, Jacek P.; Bezdek, Matthew A.; Abelson, Brian P.; Johnson, John S.; Schumacher, Eric H.; Parra, Lucas C.

    2014-01-01

    Naturalistic stimuli evoke highly reliable brain activity across viewers. Here we record neural activity from a group of naive individuals while viewing popular, previously-broadcast television content for which the broad audience response is characterized by social media activity and audience ratings. We find that the level of inter-subject correlation in the evoked encephalographic responses predicts the expressions of interest and preference among thousands. Surprisingly, ratings of the larger audience are predicted with greater accuracy than those of the individuals from whom the neural data is obtained. An additional functional magnetic resonance imaging study employing a separate sample of subjects shows that the level of neural reliability evoked by these stimuli covaries with the amount of blood-oxygenation-level-dependent (BOLD) activation in higher-order visual and auditory regions. Our findings suggest that stimuli which we judge favourably may be those to which our brains respond in a stereotypical manner shared by our peers. PMID:25072833

  8. Audience preferences are predicted by temporal reliability of neural processing.

    PubMed

    Dmochowski, Jacek P; Bezdek, Matthew A; Abelson, Brian P; Johnson, John S; Schumacher, Eric H; Parra, Lucas C

    2014-07-29

    Naturalistic stimuli evoke highly reliable brain activity across viewers. Here we record neural activity from a group of naive individuals while viewing popular, previously-broadcast television content for which the broad audience response is characterized by social media activity and audience ratings. We find that the level of inter-subject correlation in the evoked encephalographic responses predicts the expressions of interest and preference among thousands. Surprisingly, ratings of the larger audience are predicted with greater accuracy than those of the individuals from whom the neural data is obtained. An additional functional magnetic resonance imaging study employing a separate sample of subjects shows that the level of neural reliability evoked by these stimuli covaries with the amount of blood-oxygenation-level-dependent (BOLD) activation in higher-order visual and auditory regions. Our findings suggest that stimuli which we judge favourably may be those to which our brains respond in a stereotypical manner shared by our peers.

  9. Correspondence between stimulus encoding- and maintenance-related neural processes underlies successful working memory.

    PubMed

    Cohen, Jessica R; Sreenivasan, Kartik K; D'Esposito, Mark

    2014-03-01

    The ability to actively maintain information in working memory (WM) is vital for goal-directed behavior, but the mechanisms underlying this process remain elusive. We hypothesized that successful WM relies upon a correspondence between the neural processes associated with stimulus encoding and the neural processes associated with maintenance. Using functional magnetic resonance imaging, we identified regional activity and inter-regional connectivity during stimulus encoding and the maintenance of those stimuli when they were no longer present. We compared correspondence in these neural processes across encoding and maintenance epochs with WM performance. Critically, greater correspondence between encoding and maintenance in 1) regional activity in the lateral prefrontal cortex (PFC) and 2) connectivity between lateral PFC and extrastriate cortex was associated with increased performance. These findings suggest that the conservation of neural processes across encoding and maintenance supports the integrity of representations in WM.

  10. Neural signal processing and closed-loop control algorithm design for an implanted neural recording and stimulation system.

    PubMed

    Hamilton, Lei; McConley, Marc; Angermueller, Kai; Goldberg, David; Corba, Massimiliano; Kim, Louis; Moran, James; Parks, Philip D; Sang Chin; Widge, Alik S; Dougherty, Darin D; Eskandar, Emad N

    2015-08-01

    A fully autonomous intracranial device is built to continually record neural activities in different parts of the brain, process these sampled signals, decode features that correlate to behaviors and neuropsychiatric states, and use these features to deliver brain stimulation in a closed-loop fashion. In this paper, we describe the sampling and stimulation aspects of such a device. We first describe the signal processing algorithms of two unsupervised spike sorting methods. Next, we describe the LFP time-frequency analysis and feature derivation from the two spike sorting methods. Spike sorting includes a novel approach to constructing a dictionary learning algorithm in a Compressed Sensing (CS) framework. We present a joint prediction scheme to determine the class of neural spikes in the dictionary learning framework; and, the second approach is a modified OSort algorithm which is implemented in a distributed system optimized for power efficiency. Furthermore, sorted spikes and time-frequency analysis of LFP signals can be used to generate derived features (including cross-frequency coupling, spike-field coupling). We then show how these derived features can be used in the design and development of novel decode and closed-loop control algorithms that are optimized to apply deep brain stimulation based on a patient's neuropsychiatric state. For the control algorithm, we define the state vector as representative of a patient's impulsivity, avoidance, inhibition, etc. Controller parameters are optimized to apply stimulation based on the state vector's current state as well as its historical values. The overall algorithm and software design for our implantable neural recording and stimulation system uses an innovative, adaptable, and reprogrammable architecture that enables advancement of the state-of-the-art in closed-loop neural control while also meeting the challenges of system power constraints and concurrent development with ongoing scientific research designed

  11. Learning Process of a Stochastic Feed-Forward Neural Network

    NASA Astrophysics Data System (ADS)

    Fujiki, Sumiyoshi; Fujiki, Nahomi

    1995-03-01

    A positive reinforcement type learning algorithm is formulated for a stochastic feed-forward neural network by minimizing a relative entropic measure, and a learning equation similar to that of the Boltzmann machine is obtained. The learning of the network actually shows a similar result to that of the Boltzmann machine in the classification problems of AND and XOR, by numerical experiments.

  12. A neural manufacturing a novel concept for processing modeling, monitoring and control

    SciTech Connect

    Law, B.; Fu, C.Y.; Petrich, L.

    1995-10-01

    Semiconductor fabrication lines have become extremely costly, and achieving a good return from such a high capital investment requires efficient utilization of these expensive facilities. It is highly desirable to shorten processing development time, increase fabrication yield, enhance flexibility, improve quality, and minimize downtime. We propose that these ends can be achieved by applying recent advances in the areas of artificial neural networks, fuzzy logic, machine learning, and genetic algorithms. We use the term neural manufacturing to describe such applications. This paper describes our use of artificial neural networks to improve the monitoring and control of semiconductor process.

  13. The hemo-neural hypothesis: on the role of blood flow in information processing.

    PubMed

    Moore, Christopher I; Cao, Rosa

    2008-05-01

    Brain vasculature is a complex and interconnected network under tight regulatory control that exists in intimate communication with neurons and glia. Typically, hemodynamics are considered to exclusively serve as a metabolic support system. In contrast to this canonical view, we propose that hemodynamics also play a role in information processing through modulation of neural activity. Functional hyperemia, the basis of the functional MRI (fMRI) BOLD signal, is a localized influx of blood correlated with neural activity levels. Functional hyperemia is considered by many to be excessive from a metabolic standpoint, but may be appropriate if interpreted as having an activity-dependent neuro-modulatory function. Hemodynamics may impact neural activity through direct and indirect mechanisms. Direct mechanisms include delivery of diffusible blood-borne messengers and mechanical and thermal modulation of neural activity. Indirect mechanisms are proposed to act through hemodynamic modulation of astrocytes, which can in turn regulate neural activity. These hemo-neural mechanisms should alter the information processing capacity of active local neural networks. Here, we focus on analysis of neocortical sensory processing. We predict that hemodynamics alter the gain of local cortical circuits, modulating the detection and discrimination of sensory stimuli. This novel view of information processing-that includes hemodynamics as an active and significant participant-has implications for understanding neural representation and the construction of accurate brain models. There are also potential medical benefits of an improved understanding of the role of hemodynamics in neural processing, as it directly bears on interpretation of and potential treatment for stroke, dementia, and epilepsy.

  14. Neural field theory of nonlinear wave-wave and wave-neuron processes

    NASA Astrophysics Data System (ADS)

    Robinson, P. A.; Roy, N.

    2015-06-01

    Systematic expansion of neural field theory equations in terms of nonlinear response functions is carried out to enable a wide variety of nonlinear wave-wave and wave-neuron processes to be treated systematically in systems involving multiple neural populations. The results are illustrated by analyzing second-harmonic generation, and they can also be applied to wave-wave coalescence, multiharmonic generation, facilitation, depression, refractoriness, and other nonlinear processes.

  15. Progress Toward Adaptive Integration and Optimization of Automated and Neural Processing Systems: Establishing Neural and Behavioral Benchmarks of Optimized Performance

    DTIC Science & Technology

    2014-11-01

    into more-realistic multitasking environments. Behind the work are basic questions about the utility of rapid serial visual presentation (RSVP) and... multitasking simulator with integrated real-time electroencephalogram (EEG) processing, RSVP performance was measured. Figure 2a shows the display for the...classification of their neural signals, all within the multitasking simulation environment. These studies and the results are described in the following

  16. The Hemo-Neural Hypothesis: On The Role of Blood Flow in Information Processing

    PubMed Central

    Moore, Christopher I.; Cao, Rosa

    2012-01-01

    Brain vasculature is a complex and interconnected network under tight regulatory control that exists in intimate communication with neurons and glia. Typically, hemodynamics are considered to exclusively serve as a metabolic support system. In contrast to this canonical view, we propose that hemodynamics also play a role in information processing through modulation of neural activity. Functional hyperemia, the basis of the functional MRI (fMRI) BOLD signal, is a localized influx of blood correlated with neural activity levels. Functional hyperemia is considered by many to be excessive from a metabolic standpoint, but may be appropriate if interpreted as having an activity-dependent neuro-modulatory function. Hemodynamics may impact neural activity through direct and indirect mechanisms. Direct mechanisms include delivery of diffusible blood-borne messengers and mechanical and thermal modulation of neural activity. Indirect mechanisms are proposed to act through hemodynamic modulation of astrocytes, which can in turn regulate neural activity. These hemo-neural mechanisms should alter the information processing capacity of active local neural networks. Here, we focus on analysis of neocortical sensory processing. We predict that hemodynamics alter the gain of local cortical circuits, modulating the detection and discrimination of sensory stimuli. This novel view of information processing—that includes hemodynamics as an active and significant participant— has implications for understanding neural representation and the construction of accurate brain models. There are also potential medical benefits of an improved understanding of the role of hemodynamics in neural processing, as it directly bears on interpretation of and potential treatment for stroke, dementia, and epilepsy. PMID:17913979

  17. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING

    PubMed Central

    Zhang, Wenhao; Li, Hanyu; Yang, Minda; Mesgarani, Nima

    2017-01-01

    A characteristic property of biological neurons is their ability to dynamically change the synaptic efficacy in response to variable input conditions. This mechanism, known as synaptic depression, significantly contributes to the formation of normalized representation of speech features. Synaptic depression also contributes to the robust performance of biological systems. In this paper, we describe how synaptic depression can be modeled and incorporated into deep neural network architectures to improve their generalization ability. We observed that when synaptic depression is added to the hidden layers of a neural network, it reduces the effect of changing background activity in the node activations. In addition, we show that when synaptic depression is included in a deep neural network trained for phoneme classification, the performance of the network improves under noisy conditions not included in the training phase. Our results suggest that more complete neuron models may further reduce the gap between the biological performance and artificial computing, resulting in networks that better generalize to novel signal conditions. PMID:28286424

  18. 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

  19. 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.

  20. Parametric models to relate spike train and LFP dynamics with neural information processing

    PubMed Central

    Banerjee, Arpan; Dean, Heather L.; Pesaran, Bijan

    2012-01-01

    Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial

  1. Neural-Net Processing of Characteristic Patterns From Electronic Holograms of Vibrating Blades

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.

    1999-01-01

    Finite-element-model-trained artificial neural networks can be used to process efficiently the characteristic patterns or mode shapes from electronic holograms of vibrating blades. The models used for routine design may not yet be sufficiently accurate for this application. This document discusses the creation of characteristic patterns; compares model generated and experimental characteristic patterns; and discusses the neural networks that transform the characteristic patterns into strain or damage information. The current potential to adapt electronic holography to spin rigs, wind tunnels and engines provides an incentive to have accurate finite element models lor training neural networks.

  2. Neural-Net Processed Characteristic Patterns for Measurement of Structural Integrity of Pressure Cycled Components

    NASA Technical Reports Server (NTRS)

    Decker, A. J.

    2001-01-01

    A neural-net inspection process has been combined with a bootstrap training procedure and electronic holography to detect changes or damage in a pressure-cycled International Space Station cold plate to be used for cooling instrumentation. The cold plate was excited to vibrate in a normal mode at low amplitude, and the neural net was trained by example to flag small changes in the mode shape. The NDE (nondestructive-evaluation) technique is straightforward but in its infancy; its applications are ad-hoc and uncalibrated. Nevertheless previous research has shown that the neural net can detect displacement changes to better than 1/100 the maximum displacement amplitude. Development efforts that support the NDE technique are mentioned briefly, followed by descriptions of electronic holography and neural-net processing. The bootstrap training procedure and its application to detection of damage in a pressure-cycled cold plate are discussed. Suggestions for calibrating and quantifying the NDE procedure are presented.

  3. Characterization of neural stemness status through the neurogenesis process for bone marrow mesenchymal stem cells

    PubMed Central

    Mohammad, Maeda H; Al-shammari, Ahmed M; Al-Juboory, Ahmad Adnan; Yaseen, Nahi Y

    2016-01-01

    The in vitro isolation, identification, differentiation, and neurogenesis characterization of the sources of mesenchymal stem cells (MSCs) were investigated to produce two types of cells in culture: neural cells and neural stem cells (NSCs). These types of stem cells were used as successful sources for the further treatment of central nervous system defects and injuries. The mouse bone marrow MSCs were used as the source of the stem cells in this study. β-Mercaptoethanol (BME) was used as the main inducer of the neurogenesis pathway to induce neural cells and to identify NSCs. Three types of neural markers were used: nestin as the immaturation stage marker, neurofilament light chain as the early neural marker, and microtubule-associated protein 2 as the maturation marker through different time intervals in the neurogenesis process starting from the MSCs, (as undifferentiated cells), NSCs, production stages, and toward neuron cells (as differentiated cells). The results of different exposure times to BME of the neural markers analysis done by immunocytochemistry and real time-polymerase chain reaction helped us to identify the exact timing for the neural stemness state. The results showed that the best exposure time that may be used for the production of NSCs was 6 hours. The best maintenance media for NSCs were also identified. Furthermore, we optimized exposure to BME with different times and concentrations, which could be an interesting way to modulate specific neuronal differentiation and obtain autologous neuronal phenotypes. This study was able to characterize NSCs in culture under differentiation for neurogenesis in the pathway of the neural differentiation process by studying the expressed neural genes and the ability to maintain these NSCs in culture for further differentiation in thousands of functional neurons for the treatment of brain and spinal cord injuries and defects. PMID:27143939

  4. Neural Source Localization Using Advanced Sensor Array Signal Processing Techniques

    DTIC Science & Technology

    2001-10-25

    Singular Value Decomposition ( SVD ) of the spatial covariance matrix MxMjYR ℜ∈ of jY [7]. From a theoretic viewpoint, the information about the neural...source’s spatial amplitude distribution or “footprint” on the array side is contained in this covariance matrix. The SVD allows one to assess the P...Abstract unclassified Limitation of Abstract UU Number of Pages 4 2 of the SVD stage. The last step consists of selecting certain subbands from the full

  5. Time-dependent neural processing of auditory feedback during voice pitch error detection.

    PubMed

    Behroozmand, Roozbeh; Liu, Hanjun; Larson, Charles R

    2011-05-01

    The neural responses to sensory consequences of a self-produced motor act are suppressed compared with those in response to a similar but externally generated stimulus. Previous studies in the somatosensory and auditory systems have shown that the motor-induced suppression of the sensory mechanisms is sensitive to delays between the motor act and the onset of the stimulus. The present study investigated time-dependent neural processing of auditory feedback in response to self-produced vocalizations. ERPs were recorded in response to normal and pitch-shifted voice auditory feedback during active vocalization and passive listening to the playback of the same vocalizations. The pitch-shifted stimulus was delivered to the subjects' auditory feedback after a randomly chosen time delay between the vocal onset and the stimulus presentation. Results showed that the neural responses to delayed feedback perturbations were significantly larger than those in response to the pitch-shifted stimulus occurring at vocal onset. Active vocalization was shown to enhance neural responsiveness to feedback alterations only for nonzero delays compared with passive listening to the playback. These findings indicated that the neural mechanisms of auditory feedback processing are sensitive to timing between the vocal motor commands and the incoming auditory feedback. Time-dependent neural processing of auditory feedback may be an important feature of the audio-vocal integration system that helps to improve the feedback-based monitoring and control of voice structure through vocal error detection and correction.

  6. Neural network for processing both spatial and temporal data with time based back-propagation

    NASA Technical Reports Server (NTRS)

    Villarreal, James A. (Inventor); Shelton, Robert O. (Inventor)

    1993-01-01

    Neural networks are computing systems modeled after the paradigm of the biological brain. For years, researchers using various forms of neural networks have attempted to model the brain's information processing and decision-making capabilities. Neural network algorithms have impressively demonstrated the capability of modeling spatial information. On the other hand, the application of parallel distributed models to the processing of temporal data has been severely restricted. The invention introduces a novel technique which adds the dimension of time to the well known back-propagation neural network algorithm. In the space-time neural network disclosed herein, the synaptic weights between two artificial neurons (processing elements) are replaced with an adaptable-adjustable filter. Instead of a single synaptic weight, the invention provides a plurality of weights representing not only association, but also temporal dependencies. In this case, the synaptic weights are the coefficients to the adaptable digital filters. Novelty is believed to lie in the disclosure of a processing element and a network of the processing elements which are capable of processing temporal as well as spacial data.

  7. Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.; Fite, E. Brian; Mehmed, Oral; Thorp, Scott A.

    1997-01-01

    The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture.

  8. Distinct neural substrates for deductive and mathematical processing.

    PubMed

    Kroger, James K; Nystrom, Leigh E; Cohen, Jonathan D; Johnson-Laird, Philip N

    2008-12-03

    In an effort to clarify how deductive reasoning is accomplished, an fMRI study was performed to observe the neural substrates of logical reasoning and mathematical calculation. Participants viewed a problem statement and three premises, and then either a conclusion or a mathematical formula. They had to indicate whether the conclusion followed from the premises, or to solve the mathematical formula. Language areas of the brain (Broca's and Wernicke's area) responded as the premises and the conclusion were read, but solution of the problems was then carried out by non-language areas. Regions in right prefrontal cortex and inferior parietal lobe were more active for reasoning than for calculation, whereas regions in left prefrontal cortex and superior parietal lobe were more active for calculation than for reasoning. In reasoning, only those problems calling for a search for counterexamples to conclusions recruited right frontal pole. These results have important implications for understanding how higher cognition, including deduction, is implemented in the brain. Different sorts of thinking recruit separate neural substrates, and logical reasoning goes beyond linguistic regions of the brain.

  9. Aberrant neural processing of moral violations in criminal psychopaths.

    PubMed

    Harenski, Carla L; Harenski, Keith A; Shane, Matthew S; Kiehl, Kent A

    2010-11-01

    A defining characteristic of psychopathy is the willingness to intentionally commit moral transgressions against others without guilt or remorse. Despite this "moral insensitivity," the behavioral and neural correlates of moral decision-making in psychopathy have not been well studied. To address this issue, the authors used functional magnetic resonance imaging (fMRI) to record hemodynamic activity in 72 incarcerated male adults, stratified into psychopathic (n = 16) and nonpsychopathic (n = 16) groups based on scores from the Hare Psychopathy Checklist-Revised (R. D. Hare, 2003), while they made decisions regarding the severity of moral violations of pictures that did or did not depict moral situations. Consistent with hypotheses, an analysis of brain activity during the evaluation of pictures depicting moral violations in psychopaths versus nonpsychopaths showed atypical activity in several regions involved in moral decision-making. This included reduced moral/nonmoral picture distinctions in the ventromedial prefrontal cortex and anterior temporal cortex in psychopaths relative to nonpsychopaths. In a separate analysis, the association between severity of moral violation ratings and brain activity across participants was compared in psychopaths versus nonpsychopaths. Results revealed a positive association between amygdala activity and severity ratings that was greater in nonpsychopaths than psychopaths, and a negative association between posterior temporal activity and severity ratings that was greater in psychopaths than nonpsychopaths. These results reveal potential neural underpinnings of moral insensitivity in psychopathy and are discussed with reference to neurobiological models of morality and psychopathy.

  10. Practice strategies of musicians modulate neural processing and the learning of sound-patterns.

    PubMed

    Seppänen, M; Brattico, E; Tervaniemi, M

    2007-02-01

    Previous studies suggest that pre-attentive auditory processing of musicians differs depending on the strategies used in music practicing and performance. This study aimed at systematically revealing whether there are differences in auditory processing between musicians preferring and not-preferring aural strategies such as improvising, playing by ear, and rehearsing by listening to records. Participants were assigned to aural and non-aural groups according to how much they employ aural strategies, as determined by a questionnaire. The change-related mismatch negativity (MMN) component of event-related brain potentials (ERPs) was used to probe pre-attentive neural discrimination of simple sound features and melody-like patterns. Further, the musicians' behavioral accuracy in sound perception was tested with a discrimination task and the AMMA musicality test. The data indicate that practice strategies do not affect musicians' pre-attentive neural discrimination of changes in simple sound features but do modulate the speed of neural discrimination of interval and contour changes within melody-like patterns. Moreover, while the aural and non-aural groups did not differ in their initial neural accuracy for discriminating melody-like patterns, they differed after a focused training session. A correlation between behavioral and neural measures was also obtained. Taken together, these results suggest that auditory processing of musicians who prefer aural practice strategies differs in melodic contour and interval processing and perceptual learning, rather than in simple sound processing, in comparison to musicians preferring other practice strategies.

  11. Reading Between the Spikes: Real-Time Signal Processing in Neural Systems

    NASA Astrophysics Data System (ADS)

    Warland, David Karsten

    This thesis discusses biological strategies for real-time signal processing in neural systems. Nearly all creatures encode information about the world as patterns of identically shaped action potentials, or "spikes". As a result, all the animal's knowledge of the world is contained in the occurrence times of these discrete events. Traditional approaches to the study of neural coding emphasize the encoding process, resulting in predictions of average neural responses to a limited class of stimuli. However, these studies fail to address the relevant biological question: What can the organism "learn" about the outside world from real-time observations of its own spike trains? Therefore, this thesis approaches neural coding from the point of view of the organism itself: We learn to decode neural spike trains to obtain real-time estimates of sensory stimuli. In particular, this ability to extract continuous signals from spiking cells, together with the definition of an equivalent spectral noise level for a spiking neuron allows characterization of the information contained in patterns of neural response as well as forming the basis for the prediction of optimal neural computation strategies with spike trains. These methods are applied to the design and analysis of experiments on a single wide field, movement -sensitive neuron (H1) in the visual system of the blowfly Calliphora erythrocephela and to the filiform hair receptors of the wind-sensing system of the cricket Acheta domestica. This thesis also discusses the generalization of these strategies to collections of neurons and the applications to future work in the context of neural computation in the retina.

  12. Neural Correlates of Written Emotion Word Processing: A Review of Recent Electrophysiological and Hemodynamic Neuroimaging Studies

    ERIC Educational Resources Information Center

    Citron, Francesca M. M.

    2012-01-01

    A growing body of literature investigating the neural correlates of emotion word processing has emerged in recent years. Written words have been shown to represent a suitable means to study emotion processing and most importantly to address the distinct and interactive contributions of the two dimensions of emotion: valence and arousal. The aim of…

  13. The Role of Personal Experience in the Neural Processing of Action-Related Language

    ERIC Educational Resources Information Center

    Lyons, Ian M.; Mattarella-Micke, Andrew; Cieslak, Matthew; Nusbaum, Howard C.; Small, Steven L.; Beilock, Sian L.

    2010-01-01

    We investigated how auditory language processing is modified by a listener's previous experience with the specific activities mentioned in the speech. In particular, we asked whether neural responses related to language processing depend on one's experience with the action-based content of this language. Ice-hockey players and novices passively…

  14. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language

    PubMed Central

    Ferjan Ramirez, Naja; Leonard, Matthew K.; Davenport, Tristan S.; Torres, Christina; Halgren, Eric; Mayberry, Rachel I.

    2016-01-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772–2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience. PMID:25410427

  15. Autonomous dynamics in neural networks: the dHAN concept and associative thought processes

    NASA Astrophysics Data System (ADS)

    Gros, Claudius

    2007-02-01

    The neural activity of the human brain is dominated by self-sustained activities. External sensory stimuli influence this autonomous activity but they do not drive the brain directly. Most standard artificial neural network models are however input driven and do not show spontaneous activities. It constitutes a challenge to develop organizational principles for controlled, self-sustained activity in artificial neural networks. Here we propose and examine the dHAN concept for autonomous associative thought processes in dense and homogeneous associative networks. An associative thought-process is characterized, within this approach, by a time-series of transient attractors. Each transient state corresponds to a stored information, a memory. The subsequent transient states are characterized by large associative overlaps, which are identical to acquired patterns. Memory states, the acquired patterns, have such a dual functionality. In this approach the self-sustained neural activity has a central functional role. The network acquires a discrimination capability, as external stimuli need to compete with the autonomous activity. Noise in the input is readily filtered-out. Hebbian learning of external patterns occurs coinstantaneous with the ongoing associative thought process. The autonomous dynamics needs a long-term working-point optimization which acquires within the dHAN concept a dual functionality: It stabilizes the time development of the associative thought process and limits runaway synaptic growth, which generically occurs otherwise in neural networks with self-induced activities and Hebbian-type learning rules.

  16. Neural Language Processing in Adolescent First-Language Learners: Longitudinal Case Studies in American Sign Language.

    PubMed

    Ferjan Ramirez, Naja; Leonard, Matthew K; Davenport, Tristan S; Torres, Christina; Halgren, Eric; Mayberry, Rachel I

    2016-03-01

    One key question in neurolinguistics is the extent to which the neural processing system for language requires linguistic experience during early life to develop fully. We conducted a longitudinal anatomically constrained magnetoencephalography (aMEG) analysis of lexico-semantic processing in 2 deaf adolescents who had no sustained language input until 14 years of age, when they became fully immersed in American Sign Language. After 2 to 3 years of language, the adolescents' neural responses to signed words were highly atypical, localizing mainly to right dorsal frontoparietal regions and often responding more strongly to semantically primed words (Ferjan Ramirez N, Leonard MK, Torres C, Hatrak M, Halgren E, Mayberry RI. 2014. Neural language processing in adolescent first-language learners. Cereb Cortex. 24 (10): 2772-2783). Here, we show that after an additional 15 months of language experience, the adolescents' neural responses remained atypical in terms of polarity. While their responses to less familiar signed words still showed atypical localization patterns, the localization of responses to highly familiar signed words became more concentrated in the left perisylvian language network. Our findings suggest that the timing of language experience affects the organization of neural language processing; however, even in adolescence, language representation in the human brain continues to evolve with experience.

  17. Neural Tuning Size in a Model of Primate Visual Processing Accounts for Three Key Markers of Holistic Face Processing.

    PubMed

    Tan, Cheston; Poggio, Tomaso

    2016-01-01

    Faces are an important and unique class of visual stimuli, and have been of interest to neuroscientists for many years. Faces are known to elicit certain characteristic behavioral markers, collectively labeled "holistic processing", while non-face objects are not processed holistically. However, little is known about the underlying neural mechanisms. The main aim of this computational simulation work is to investigate the neural mechanisms that make face processing holistic. Using a model of primate visual processing, we show that a single key factor, "neural tuning size", is able to account for three important markers of holistic face processing: the Composite Face Effect (CFE), Face Inversion Effect (FIE) and Whole-Part Effect (WPE). Our proof-of-principle specifies the precise neurophysiological property that corresponds to the poorly-understood notion of holism, and shows that this one neural property controls three classic behavioral markers of holism. Our work is consistent with neurophysiological evidence, and makes further testable predictions. Overall, we provide a parsimonious account of holistic face processing, connecting computation, behavior and neurophysiology.

  18. The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading

    PubMed Central

    Wang, Xiaojuan; Zhao, Rong; Zevin, Jason D.; Yang, Jianfeng

    2016-01-01

    Visual word recognition involves mappings among orthographic, phonological, and semantic codes. In alphabetic languages, it is hard to disentangle the effects of these codes, because orthographically well-formed words are typically pronounceable, confounding orthographic and phonological processes, and orthographic cues to meaning are rare, and where they occur are morphological, confounding orthographic and semantic processes. In Chinese character recognition, it is possible to explore orthography to phonology (O-P) and orthography to semantics (O-S) processes independently by taking advantage of the distinct phonetic and semantic components in Chinese phonograms. We analyzed data from an fMRI experiment using lexical decision for Chinese characters to explore the sensitivity of areas associated with character recognition to orthographic, phonological, and semantic processing. First, a correlation approach was used to identify regions associated with reaction time, frequency, consistency and visual complexity. Then, these ROIs were examined for their responses to stimuli with different types of information available. These results revealed two neural pathways, one for O-S processing relying on left middle temporal gyrus and angular gyrus, and the other for O-P processing relying on inferior frontal gyrus and insula. The two neural routes form a shared neural network both for real and pseudo-characters, and their cooperative division of labor reflects the neural basis for processing different types of characters. Results are broadly consistent with findings from alphabetic languages, as predicted by reading models that assume the same general architecture for logographic and alphabetic scripts. PMID:27445914

  19. Examples of Current and Future Uses of Neural-Net Image Processing for Aerospace Applications

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.

    2004-01-01

    Feed forward artificial neural networks are very convenient for performing correlated interpolation of pairs of complex noisy data sets as well as detecting small changes in image data. Image-to-image, image-to-variable and image-to-index applications have been tested at Glenn. Early demonstration applications are summarized including image-directed alignment of optics, tomography, flow-visualization control of wind-tunnel operations and structural-model-trained neural networks. A practical application is reviewed that employs neural-net detection of structural damage from interference fringe patterns. Both sensor-based and optics-only calibration procedures are available for this technique. These accomplishments have generated the knowledge necessary to suggest some other applications for NASA and Government programs. A tomography application is discussed to support Glenn's Icing Research tomography effort. The self-regularizing capability of a neural net is shown to predict the expected performance of the tomography geometry and to augment fast data processing. Other potential applications involve the quantum technologies. It may be possible to use a neural net as an image-to-image controller of an optical tweezers being used for diagnostics of isolated nano structures. The image-to-image transformation properties also offer the potential for simulating quantum computing. Computer resources are detailed for implementing the black box calibration features of the neural nets.

  20. Neural Information Processing in Cognition: We Start to Understand the Orchestra, but Where is the Conductor?

    PubMed

    Palm, Günther

    2016-01-01

    Research in neural information processing has been successful in the past, providing useful approaches both to practical problems in computer science and to computational models in neuroscience. Recent developments in the area of cognitive neuroscience present new challenges for a computational or theoretical understanding asking for neural information processing models that fulfill criteria or constraints from cognitive psychology, neuroscience and computational efficiency. The most important of these criteria for the evaluation of present and future contributions to this new emerging field are listed at the end of this article.

  1. Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J. (Inventor)

    2006-01-01

    An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

  2. Application of a neural network to simulate analysis in an optimization process

    NASA Technical Reports Server (NTRS)

    Rogers, James L.; Lamarsh, William J., II

    1992-01-01

    A new experimental software package called NETS/PROSSS aimed at reducing the computing time required to solve a complex design problem is described. The software combines a neural network for simulating the analysis program with an optimization program. The neural network is applied to approximate results of a finite element analysis program to quickly obtain a near-optimal solution. Results of the NETS/PROSSS optimization process can also be used as an initial design in a normal optimization process and make it possible to converge to an optimum solution with significantly fewer iterations.

  3. The neural basis of sublexical speech and corresponding nonspeech processing: a combined EEG-MEG study.

    PubMed

    Kuuluvainen, Soila; Nevalainen, Päivi; Sorokin, Alexander; Mittag, Maria; Partanen, Eino; Putkinen, Vesa; Seppänen, Miia; Kähkönen, Seppo; Kujala, Teija

    2014-03-01

    We addressed the neural organization of speech versus nonspeech sound processing by investigating preattentive cortical auditory processing of changes in five features of a consonant-vowel syllable (consonant, vowel, sound duration, frequency, and intensity) and their acoustically matched nonspeech counterparts in a simultaneous EEG-MEG recording of mismatch negativity (MMN/MMNm). Overall, speech-sound processing was enhanced compared to nonspeech sound processing. This effect was strongest for changes which affect word meaning (consonant, vowel, and vowel duration) in the left and for the vowel identity change in the right hemisphere also. Furthermore, in the right hemisphere, speech-sound frequency and intensity changes were processed faster than their nonspeech counterparts, and there was a trend for speech-enhancement in frequency processing. In summary, the results support the proposed existence of long-term memory traces for speech sounds in the auditory cortices, and indicate at least partly distinct neural substrates for speech and nonspeech sound processing.

  4. The neural processing of voluntary completed, real and virtual violent and nonviolent computer game scenarios displaying predefined actions in gamers and nongamers.

    PubMed

    Regenbogen, Christina; Herrmann, Manfred; Fehr, Thorsten

    2010-01-01

    Studies investigating the effects of violent computer and video game playing have resulted in heterogeneous outcomes. It has been assumed that there is a decreased ability to differentiate between virtuality and reality in people that play these games intensively. FMRI data of a group of young males with (gamers) and without (controls) a history of long-term violent computer game playing experience were obtained during the presentation of computer game and realistic video sequences. In gamers the processing of real violence in contrast to nonviolence produced activation clusters in right inferior frontal, left lingual and superior temporal brain regions. Virtual violence activated a network comprising bilateral inferior frontal, occipital, postcentral, right middle temporal, and left fusiform regions. Control participants showed extended left frontal, insula and superior frontal activations during the processing of real, and posterior activations during the processing of virtual violent scenarios. The data suggest that the ability to differentiate automatically between real and virtual violence has not been diminished by a long-term history of violent video game play, nor have gamers' neural responses to real violence in particular been subject to desensitization processes. However, analyses of individual data indicated that group-related analyses reflect only a small part of actual individual different neural network involvement, suggesting that the consideration of individual learning history is sufficient for the present discussion.

  5. Current-mode implementation of processing modules in ART-based neural networks

    NASA Astrophysics Data System (ADS)

    Lopez-Alcantud, Jose-Alejandro; Hauer, Hans; Diaz-Madrid, Jose-Angel; Ruiz-Merino, Ramon

    2003-04-01

    This paper describes implementation of neural network processing layers using basic current-mode operating modules. The research work has been focused on the implementation of neural networks based on the Adaptive Resonance Theory, developed by S. Grossberg and G.A. Carpenter. The ART-based neural network whose operating modules have been choosen for development is the one called MART, proposed by F. Delgado, because of its complex architecture, auto--adaptive self-learning process, able to discard unmeaningful cathegories. Our presentation starts introducing the behaviour of MART with an analysis of its structure. The development described by this research work is focused on the monochannel block included in the main signal processing part of the MART neural network. The description of the computing algorithm of the layers inside a monochannel block are also provided in order to show what operational current-mode modules are needed (multiplier, divider, square-rooter, adder, substractor, absolute value, maximum and minimum evaluator...). Descriptions at schematic and layout levels of all the processing layers are given. All of them have been designed using AMS 0.35 micron technology with a supply voltage of 3.3 volts. The modules are designed to deal with input currents in the range of 20 to 50 microamps, showing a lineal behaviour and an output error of less than 10%, which is good enough for neural signal processing systems. The maximum frecuency of operation is around 200 kHz. Simulation results are included to show that the operation performed by the hardware designed matches the behaviour described by the MART neural network. For testing purposes we show the design of a monochannel block hardware implementation restricted to five inputs and three cathegories.

  6. A Memristive Multilayer Cellular Neural Network With Applications to Image Processing.

    PubMed

    Hu, Xiaofang; Feng, Gang; Duan, Shukai; Liu, Lu

    2016-05-13

    The memristor has been extensively studied in electrical engineering and biological sciences as a means to compactly implement the synaptic function in neural networks. The cellular neural network (CNN) is one of the most implementable artificial neural network models and capable of massively parallel analog processing. In this paper, a novel memristive multilayer CNN (Mm-CNN) model is presented along with its performance analysis and applications. In this new CNN design, the memristor crossbar circuit acts as the synapse, which realizes one signed synaptic weight with a pair of memristors and performs the synaptic weighting compactly and linearly. Moreover, the complex weighted summation is executed in an efficient way with a proper design of Mm-CNN cell circuits. The proposed Mm-CNN has several merits, such as compactness, nonvolatility, versatility, and programmability of synaptic weights. Its performance in several image processing applications is illustrated through simulations.

  7. Neural correlates of language and non-language visuospatial processing in adolescents with reading disability.

    PubMed

    Diehl, Joshua John; Frost, Stephen J; Sherman, Gordon; Mencl, W Einar; Kurian, Anish; Molfese, Peter; Landi, Nicole; Preston, Jonathan; Soldan, Anja; Fulbright, Robert K; Rueckl, Jay G; Seidenberg, Mark S; Hoeft, Fumiko; Pugh, Kenneth R

    2014-11-01

    Despite anecdotal evidence of relative visuospatial processing strengths in individuals with reading disability (RD), only a few studies have assessed the presence or the extent of these putative strengths. The current study examined the cognitive and neural bases of visuospatial processing abilities in adolescents with RD relative to typically developing (TD) peers. Using both cognitive tasks and functional magnetic resonance imaging (fMRI) we contrasted printed word recognition with non-language visuospatial processing tasks. Behaviorally, lower reading skill was related to a visuospatial processing advantage (shorter latencies and equivalent accuracy) on a geometric figure processing task, similar to findings shown in two published studies. FMRI analyses revealed key group by task interactions in patterns of cortical and subcortical activation, particularly in frontostriatal networks, and in the distributions of right and left hemisphere activation on the two tasks. The results are discussed in terms of a possible neural tradeoff in visuospatial processing in RD.

  8. Using feed-forward neural networks for estimation of microbial concentration in a simulated biochemical process.

    PubMed

    Bulsari, A; Saxén, H

    1994-01-01

    This work investigated the feasibility of using feed-forward neural networks for estimation of a state variable in a process with highly non-linear characteristics. A biochemical process was considered where the microorganism Saccharomyces cerevisiae, a yeast, grows in a chemostat on a glucose substrate and produces ethanol as a product of primary energy metabolism. Three state variables for the process are the microbial concentration, substrate concentration and product concentration. The Levenberg-Marquardt Method was used to train the neural networks by minimising the sum of squares of the residuals. The inputs to the networks were the measured variable (product concentration) and the control variable (dilution rate). The output of the network was an estimate for the microbial concentration. Earlier work had shown that system identification of this biochemical process could be performed quite well using feed-forward neural networks. This work demonstrated that state estimation can also be performed successfully using feed-forward neural networks. Knowledge of the process model is not required. The method is simple, reliable and accurate enough for engineering purposes. It can save a lot of expense on sensors, their installation and maintenance.

  9. A preferential design approach for energy-efficient and robust implantable neural signal processing hardware.

    PubMed

    Narasimhan, Seetharam; Chiel, Hillel J; Bhunia, Swarup

    2009-01-01

    For implantable neural interface applications, it is important to compress data and analyze spike patterns across multiple channels in real time. Such a computational task for online neural data processing requires an innovative circuit-architecture level design approach for low-power, robust and area-efficient hardware implementation. Conventional microprocessor or Digital Signal Processing (DSP) chips would dissipate too much power and are too large in size for an implantable system. In this paper, we propose a novel hardware design approach, referred to as "Preferential Design" that exploits the nature of the neural signal processing algorithm to achieve a low-voltage, robust and area-efficient implementation using nanoscale process technology. The basic idea is to isolate the critical components with respect to system performance and design them more conservatively compared to the noncritical ones. This allows aggressive voltage scaling for low power operation while ensuring robustness and area efficiency. We have applied the proposed approach to a neural signal processing algorithm using the Discrete Wavelet Transform (DWT) and observed significant improvement in power and robustness over conventional design.

  10. dNSP: a biologically inspired dynamic Neural network approach to Signal Processing.

    PubMed

    Cano-Izquierdo, José Manuel; Ibarrola, Julio; Pinzolas, Miguel; Almonacid, Miguel

    2008-09-01

    The arriving order of data is one of the intrinsic properties of a signal. Therefore, techniques dealing with this temporal relation are required for identification and signal processing tasks. To perform a classification of the signal according with its temporal characteristics, it would be useful to find a feature vector in which the temporal attributes were embedded. The correlation and power density spectrum functions are suitable tools to manage this issue. These functions are usually defined with statistical formulation. On the other hand, in biology there can be found numerous processes in which signals are processed to give a feature vector; for example, the processing of sound by the auditory system. In this work, the dNSP (dynamic Neural Signal Processing) architecture is proposed. This architecture allows representing a time-varying signal by a spatial (thus statical) vector. Inspired by the aforementioned biological processes, the dNSP performs frequency decomposition using an analogical parallel algorithm carried out by simple processing units. The architecture has been developed under the paradigm of a multilayer neural network, where the different layers are composed by units whose activation functions have been extracted from the theory of Neural Dynamic [Grossberg, S. (1988). Nonlinear neural networks principles, mechanisms and architectures. Neural Networks, 1, 17-61]. A theoretical study of the behavior of the dynamic equations of the units and their relationship with some statistical functions allows establishing a parallelism between the unit activations and correlation and power density spectrum functions. To test the capabilities of the proposed approach, several testbeds have been employed, i.e. the frequencial study of mathematical functions. As a possible application of the architecture, a highly interesting problem in the field of automatic control is addressed: the recognition of a controlled DC motor operating state.

  11. Testing Multiple Psychological Processes for Common Neural Mechanisms Using EEG and Independent Component Analysis.

    PubMed

    Wessel, Jan R

    2016-03-08

    Temporal independent component analysis (ICA) is applied to an electrophysiological signal mixture (such as an EEG recording) to disentangle the independent neural source signals-independent components-underlying said signal mixture. When applied to scalp EEG, ICA is most commonly used either as a pre-processing step (e.g., to isolate physiological processes from non-physiological artifacts), or as a data-reduction step (i.e., to focus on one specific neural process with increased signal-to-noise ratio). However, ICA can be used in an even more powerful way that fundamentally expands the inferential utility of scalp EEG. The core assumption of EEG-ICA-namely, that individual independent components represent separable neural processes-can be leveraged to derive the following inferential logic: If a specific independent component shows activity related to multiple psychological processes within the same dataset (e.g., elicited by different experimental events), it follows that those psychological processes involve a common, non-separable neural mechanism. As such, this logic allows testing a class of hypotheses that is beyond the reach of regular EEG analyses techniques, thereby crucially increasing the inferential utility of the EEG. In the current article, this logic will be referred to as the 'common independent process identification' (CIPI) approach. This article aims to provide a tutorial into the application of this powerful approach, targeted at researchers that have a basic understanding of standard EEG analysis. Furthermore, the article aims to exemplify the usage of CIPI by outlining recent studies that successfully applied this approach to test neural theories of mental functions.

  12. Neural basis of uncertain cue processing in trait anxiety

    PubMed Central

    Zhang, Meng; Ma, Chao; Luo, Yanyan; Li, Ji; Li, Qingwei; Liu, Yijun; Ding, Cody; Qiu, Jiang

    2016-01-01

    Individuals with high trait anxiety form a non-clinical group with a predisposition for an anxiety-related bias in emotional and cognitive processing that is considered by some to be a prerequisite for psychiatric disorders. Anxious individuals tend to experience more worry under uncertainty, and processing uncertain information is an important, but often overlooked factor in anxiety. So, we decided to explore the brain correlates of processing uncertain information in individuals with high trait anxiety using the learn-test paradigm. Behaviorally, the percentages on memory test and the likelihood ratios of identifying novel stimuli under uncertainty were similar to the certain fear condition, but different from the certain neutral condition. The brain results showed that the visual cortex, bilateral fusiform gyrus, and right parahippocampal gyrus were active during the processing of uncertain cues. Moreover, we found that trait anxiety was positively correlated with the BOLD signal of the right parahippocampal gyrus during the processing of uncertain cues. No significant results were found in the amygdala during uncertain cue processing. These results suggest that memory retrieval is associated with uncertain cue processing, which is underpinned by over-activation of the right parahippocampal gyrus, in individuals with high trait anxiety. PMID:26892030

  13. Cellular Neural Network for Real Time Image Processing

    SciTech Connect

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-12

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  14. Cellular Neural Network for Real Time Image Processing

    NASA Astrophysics Data System (ADS)

    Vagliasindi, G.; Arena, P.; Fortuna, L.; Mazzitelli, G.; Murari, A.

    2008-03-01

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET).

  15. An fMRI Investigation of the Neural Correlates Underlying the Processing of Novel Metaphoric Expressions

    ERIC Educational Resources Information Center

    Mashal, N.; Faust, M.; Hendler, T.; Jung-Beeman, M.

    2007-01-01

    The neural networks associated with processing related pairs of words forming literal, novel, and conventional metaphorical expressions and unrelated pairs of words were studied in a group of 15 normal adults using fMRI. Subjects read the four types of linguistic expressions and decided which relation exists between the two words (metaphoric,…

  16. The Processing of Verbs and Nouns in Neural Networks: Insights from Synthetic Brain Imaging

    ERIC Educational Resources Information Center

    Cangelosi, Angelo; Parisi, Domenico

    2004-01-01

    The paper presents a computational model of language in which linguistic abilities evolve in organisms that interact with an environment. Each individual's behavior is controlled by a neural network and we study the consequences in the network's internal functional organization of learning to process different classes of words. Agents are selected…

  17. Level of Processing Modulates the Neural Correlates of Emotional Memory Formation

    ERIC Educational Resources Information Center

    Ritchey, Maureen; LaBar, Kevin S.; Cabeza, Roberto

    2011-01-01

    Emotion is known to influence multiple aspects of memory formation, including the initial encoding of the memory trace and its consolidation over time. However, the neural mechanisms whereby emotion impacts memory encoding remain largely unexplored. The present study used a levels-of-processing manipulation to characterize the impact of emotion on…

  18. 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…

  19. The Question Shapes the Answer: The Neural Correlates of Task Differences Reveal Dynamic Semantic Processing

    ERIC Educational Resources Information Center

    Hargreaves, Ian S.; White, Michelle; Pexman, Penny M.; Pittman, Dan; Goodyear, Brad G.

    2012-01-01

    Task effects in semantic processing were investigated by contrasting the neural activation associated with two semantic categorization tasks (SCT) using event-related fMRI. The two SCTs involved different decision categories: "is it an animal?" vs. "is it a concrete thing?" Participants completed both tasks and, across participants, the same core…

  20. A Comparison of Neural Networks and Fuzzy Logic Methods for Process Modeling

    NASA Technical Reports Server (NTRS)

    Cios, Krzysztof J.; Sala, Dorel M.; Berke, Laszlo

    1996-01-01

    The goal of this work was to analyze the potential of neural networks and fuzzy logic methods to develop approximate response surfaces as process modeling, that is for mapping of input into output. Structural response was chosen as an example. Each of the many methods surveyed are explained and the results are presented. Future research directions are also discussed.

  1. Temporal Context in Speech Processing and Attentional Stream Selection: A Behavioral and Neural Perspective

    ERIC Educational Resources Information Center

    Golumbic, Elana M. Zion; Poeppel, David; Schroeder, Charles E.

    2012-01-01

    The human capacity for processing speech is remarkable, especially given that information in speech unfolds over multiple time scales concurrently. Similarly notable is our ability to filter out of extraneous sounds and focus our attention on one conversation, epitomized by the "Cocktail Party" effect. Yet, the neural mechanisms underlying on-line…

  2. Implicit emotional processing in peripheral vision: behavioral and neural evidence.

    PubMed

    Rigoulot, Simon; D'Hondt, Fabien; Honoré, Jacques; Sequeira, Henrique

    2012-10-01

    Emotional facial expressions (EFE) are efficiently processed when both attention and gaze are focused on them. However, what kind of processing persists when EFE are neither the target of attention nor of gaze remains largely unknown. Consequently, in this experiment we investigated whether the implicit processing of faces displayed in far periphery could still be modulated by their emotional expression. Happy, fearful and neutral faces appeared randomly for 300 ms at four peripheral locations of a panoramic screen (15 and 30° in the right and left visual fields). Reaction times and electrophysiological responses were recorded from 32 participants who had to categorize these faces according to their gender. A decrease of behavioral performance was specifically found for happy and fearful faces, probably because emotional content was automatically processed and interfered with information necessary to the task. A spatio-temporal principal component analysis of electrophysiological data confirmed an enhancement of early activity in occipito-temporal areas for emotional faces in comparison with neutral ones. Overall, these data show an implicit processing of EFE despite the strong decrease of visual performance with eccentricity. Therefore, the present research suggests that EFE could be automatically detected in peripheral vision, confirming the abilities of humans to process emotional saliency in very impoverished conditions of vision.

  3. Neural oscillatory evidence of the difference between emotional and conceptual processing in language comprehension.

    PubMed

    Chen, Xuhai; Yuan, Jiajin; Guo, Jingjing; You, Yuqun

    2013-10-11

    Despite ample study of conceptual and emotional information processing in language, it remains unclear whether these two types of processing rely on different neural mechanisms. In the present study, the processing of semantic and emotional information was directly compared in 24 participants undergoing electroencephalograms (EEGs). Participants read 120 scenarios ending in three ways (affectively and semantically congruent, affectively incongruent, and semantically incongruent) and were asked to judge the appropriateness of the last word within the context. The data were analyzed using both event-related potentials (ERPs) and event-related spectral perturbation (ERSP) analysis. In addition to the similar N400 effects evoked by both emotional and conceptual incongruity, conceptual incongruity elicited a larger theta power increase, while emotional incongruity induced a gamma band power increase, compared with the congruent condition. The different oscillatory patterns suggest that emotional and conceptual information in language processing may rely on different neural mechanisms, even though both types of processing produced a similar N400 effect.

  4. Sadness is unique: neural processing of emotions in speech prosody in musicians and non-musicians

    PubMed Central

    Park, Mona; Gutyrchik, Evgeny; Welker, Lorenz; Carl, Petra; Pöppel, Ernst; Zaytseva, Yuliya; Meindl, Thomas; Blautzik, Janusch; Reiser, Maximilian; Bao, Yan

    2015-01-01

    Musical training has been shown to have positive effects on several aspects of speech processing, however, the effects of musical training on the neural processing of speech prosody conveying distinct emotions are yet to be better understood. We used functional magnetic resonance imaging (fMRI) to investigate whether the neural responses to speech prosody conveying happiness, sadness, and fear differ between musicians and non-musicians. Differences in processing of emotional speech prosody between the two groups were only observed when sadness was expressed. Musicians showed increased activation in the middle frontal gyrus, the anterior medial prefrontal cortex, the posterior cingulate cortex and the retrosplenial cortex. Our results suggest an increased sensitivity of emotional processing in musicians with respect to sadness expressed in speech, possibly reflecting empathic processes. PMID:25688196

  5. Least square neural network model of the crude oil blending process.

    PubMed

    Rubio, José de Jesús

    2016-06-01

    In this paper, the recursive least square algorithm is designed for the big data learning of a feedforward neural network. The proposed method as the combination of the recursive least square and feedforward neural network obtains four advantages over the alone algorithms: it requires less number of regressors, it is fast, it has the learning ability, and it is more compact. Stability, convergence, boundedness of parameters, and local minimum avoidance of the proposed technique are guaranteed. The introduced strategy is applied for the modeling of the crude oil blending process.

  6. Hybrid Neural Network Model of an Industrial Ethanol Fermentation Process Considering the Effect of Temperature

    NASA Astrophysics Data System (ADS)

    Mantovanelli, Ivana C. C.; Rivera, Elmer Ccopa; da Costa, Aline C.; Filho, Rubens Maciel

    In this work a procedure for the development of a robust mathematical model for an industrial alcoholic fermentation process was evaluated. The proposed model is a hybrid neural model, which combines mass and energy balance equations with functional link networks to describe the kinetics. These networks have been shown to have a good nonlinear approximation capability, although the estimation of its weights is linear. The proposed model considers the effect of temperature on the kinetics and has the neural network weights reestimated always so that a change in operational conditions occurs. This allow to follow the system behavior when changes in operating conditions occur.

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

    PubMed Central

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

    2014-01-01

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

  8. Neural correlates of audiovisual speech processing in a second language.

    PubMed

    Barrós-Loscertales, Alfonso; Ventura-Campos, Noelia; Visser, Maya; Alsius, Agnès; Pallier, Christophe; Avila Rivera, César; Soto-Faraco, Salvador

    2013-09-01

    Neuroimaging studies of audiovisual speech processing have exclusively addressed listeners' native language (L1). Yet, several behavioural studies now show that AV processing plays an important role in non-native (L2) speech perception. The current fMRI study measured brain activity during auditory, visual, audiovisual congruent and audiovisual incongruent utterances in L1 and L2. BOLD responses to congruent AV speech in the pSTS were stronger than in either unimodal condition in both L1 and L2. Yet no differences in AV processing were expressed according to the language background in this area. Instead, the regions in the bilateral occipital lobe had a stronger congruency effect on the BOLD response (congruent higher than incongruent) in L2 as compared to L1. According to these results, language background differences are predominantly expressed in these unimodal regions, whereas the pSTS is similarly involved in AV integration regardless of language dominance.

  9. A New High-Resolution Direction Finding Architecture Using Photonics and Neural Network Signal Processing for Miniature Air Vehicle Applications

    DTIC Science & Technology

    2015-09-01

    RESOLUTION DIRECTION FINDING ARCHITECTURE USING PHOTONICS AND NEURAL NETWORK SIGNAL PROCESSING FOR MINIATURE AIR VEHICLE APPLICATIONS by Robert...RESOLUTION DIRECTION FINDING ARCHITECTURE USING PHOTONICS AND NEURAL NETWORK SIGNAL PROCESSING FOR MINIATURE AIR VEHICLE APPLICATIONS 5. FUNDING...unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) This paper investigates the design of an interferometric direction finding receiver

  10. Applications of neural network methods to the processing of earth observation satellite data.

    PubMed

    Loyola, Diego G

    2006-03-01

    The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

  11. Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods

    SciTech Connect

    Upadhyaya, B.R.; Yan, W.

    1993-11-01

    The primary purpose of the current research was to develop an integrated approach by combining information compression methods and artificial neural networks for the monitoring of plant components using nondestructive examination data. Specifically, data from eddy current inspection of heat exchanger tubing were utilized to evaluate this technology. The focus of the research was to develop and test various data compression methods (for eddy current data) and the performance of different neural network paradigms for defect classification and defect parameter estimation. Feedforward, fully-connected neural networks, that use the back-propagation algorithm for network training, were implemented for defect classification and defect parameter estimation using a modular network architecture. A large eddy current tube inspection database was acquired from the Metals and Ceramics Division of ORNL. These data were used to study the performance of artificial neural networks for defect type classification and for estimating defect parameters. A PC-based data preprocessing and display program was also developed as part of an expert system for data management and decision making. The results of the analysis showed that for effective (low-error) defect classification and estimation of parameters, it is necessary to identify proper feature vectors using different data representation methods. The integration of data compression and artificial neural networks for information processing was established as an effective technique for automation of diagnostics using nondestructive examination methods.

  12. 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.

  13. Some Characteristics of Neural Processing in the Child.

    ERIC Educational Resources Information Center

    Robinson, Daniel N.

    This report tells of the procedures and results of a psychophysical study of 28 3.8-year-old-boys from the Harlem Training Center. In spite of an experimental situation that was something of an ordeal, some meaningful data was generated. The main area investigated in this study was the evoked-response indices of temporal processing, that is, the…

  14. A Biologically-Inspired Neural Network Architecture for Image Processing

    DTIC Science & Technology

    1990-12-01

    findings, in accord with other research cited here, were obtained from cortical measurements or, 15 adult cats and 12 kittens , all anesthetized (9...software models on a Cray computer. Furthermore, care should be taken to avoid exceeding machine memory capacity when running intensive processes

  15. Neural Correlates of Top-Down Letter Processing

    ERIC Educational Resources Information Center

    Liu, Jiangang; Li, Jun; Zhang, Hongchuan; Rieth, Cory A.; Huber, David E.; Li, Wu; Lee, Kang; Tian, Jie

    2010-01-01

    This fMRI study investigated top-down letter processing with an illusory letter detection task. Participants responded whether one of a number of different possible letters was present in a very noisy image. After initial training that became increasingly difficult, they continued to detect letters even though the images consisted of pure noise,…

  16. Adolescents' Neural Processing of Risky Decisions: Effects of Sex and Behavioral Disinhibition

    PubMed Central

    Crowley, Thomas J.; Dalwani, Manish S.; Mikulich-Gilbertson, Susan K.; Young, Susan E.; Sakai, Joseph T.; Raymond, Kristen M.; McWilliams, Shannon K.; Roark, Melissa J.; Banich, Marie T.

    2015-01-01

    Background Accidental injury and homicide, relatively common among adolescents, often follow risky behaviors; those are done more by boys and by adolescents with greater behavioral disinhibition (BD). Hypothesis Neural processing during adolescents' risky decision-making will differ in youths with greater BD severity, and in males vs. females, both before cautious behaviors and before risky behaviors. Methodology/Principal Findings 81 adolescents (Patients with substance and conduct problems, and comparison youths (Comparisons)), assessed in a 2 x 2 design (Patients:Comparisons x Male:Female) repeatedly decided between doing a cautious behavior that earned 1 cent, or a risky one that either won 5 or lost 10 cents. Odds of winning after risky responses gradually decreased. Functional magnetic resonance imaging captured brain activity during 4-sec deliberation periods preceding responses. Most neural activation appeared in known decision-making structures. Patients, who had more severe BD scores and clinical problems than Comparisons, also had extensive neural hypoactivity. Comparisons' greater activation before cautious responses included frontal pole, medial prefrontal cortex, striatum, and other regions; and before risky responses, insula, temporal, and parietal regions. Males made more risky and fewer cautious responses than females, but before cautious responses males activated numerous regions more than females. Before risky behaviors female-greater activation was more posterior, and male-greater more anterior. Conclusions/Significance Neural processing differences during risky-cautious decision-making may underlie group differences in adolescents' substance-related and antisocial risk-taking. Patients reported harmful real-life decisions and showed extensive neural hypoactivity during risky-or-cautious decision-making. Males made more risky responses than females; apparently biased toward risky decisions, males (compared with females) utilized many more neural

  17. Attention and reality constraints on the neural processes of empathy for pain.

    PubMed

    Gu, Xiaosi; Han, Shihui

    2007-05-15

    Recent brain imaging studies have shown that the neural substrates underlying the ability to infer and share the feeling of pain of other individuals overlap with the pain matrix that mediates the process of one's own pain. While there has been evidence that the neural activity mediating pain experience is influenced by top-down attention, it remains unclear whether the neural substrates of empathy for pain are modulated by top-down controlled mechanisms. The current work investigated whether the neural correlates of empathic processes of pain are altered by task demand and prior knowledge of stimulus reality. Subjects were scanned using functional magnetic resonance imaging (fMRI) while watching pictures or cartoons of hands that were in painful or neutral situations. Subjects were asked either to evaluate pain intensity supposedly felt by the model or to count the number of hands in the stimulus displays. Relative to counting neutral stimuli, rating pain intensity of painful pictures and cartoons induced increased activation in ACC/paracingulate and the right middle frontal gyrus. Rating pain intensity also activated the inferior frontal cortex bilaterally and the right insula/putamen for pictures but activated the left parietal cortex, the postcentral gyrus, and the occipito-temporal cortex for cartoons. However, the neural activities related to pain rating were eliminated when subjects counted the number of hands in the painful stimuli. In addition, the ACC activity associated with empathy for pain was stronger for the pictures than for the cartoons. Our findings indicate that the involvement of the neural substrates underlying pain-related empathy is constrained by top-down attention and contextual reality of stimuli.

  18. 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.

  19. Unfolding the Spatial and Temporal Neural Processing of Making Dishonest Choices

    PubMed Central

    Wang, Zhaoxin; Chan, Chetwyn C. H.

    2016-01-01

    To understand the neural processing that underpins dishonest behavior in an economic exchange game task, this study employed both functional magnetic resonance imaging (fMRI) and event-related potential (ERP) methodologies to examine the neural conditions of 25 participants while they were making either dishonest or honest choices. It was discovered that dishonest choices, contrary to honest choices, elicited stronger fMRI activations in bilateral striatum and anterior insula. It also induced fluctuations in ERP amplitudes within two time windows, which are 270–30 milliseconds before and 110–290 milliseconds after the response, respectively. Importantly, when making either dishonest or honest choices, human and computer counterparts were associated with distinct fMRI activations in the left insula and different ERP amplitudes at medial and right central sites from 80 milliseconds before to 250 milliseconds after the response. These results support the hypothesis that there would be distinct neural processing during making dishonest decisions, especially when the subject considers the interests of the counterpart. Furthermore, the fMRI and ERP findings, together with ERP source reconstruction, clearly delineate the temporal sequence of the neural processes of a dishonest decision: the striatum is activated before response, then the left insula is involved around the time of response, and finally the thalamus is activated after response. PMID:27096474

  20. Long-term alterations in neural and endocrine processes induced by motherhood in mammals.

    PubMed

    Bridges, Robert S

    2016-01-01

    This article is part of a Special Issue "Parental Care". The reproductive experience of pregnancy, lactation and motherhood can significantly remodel the female's biological state, affecting endocrine, neuroendocrine, neural, and immunological processes. The brain, pituitary gland, liver, thymus, and mammary tissue are among the structures that are modified by reproductive experience. The present review that focuses on rodent research, but also includes pertinent studies in sheep and other species, identifies specific changes in these processes brought about by the biological states of pregnancy, parturition, and lactation and how the components of reproductive experience contribute to the remodeling of the maternal brain and organ systems. Findings indicate that prior parity alters key circulating hormone levels and neural receptor gene expression. Moreover, reproductive experience results in modifications in neural processes and glial support. The possible role of pregnancy-induced neurogenesis is considered in the context of neuroplasticity and behavior, and the effects of reproductive experience on maternal memory, i.e. the retention of maternal behavior, together with anxiety and learning are presented. Together, these sets of findings support the concept that the neural and biological state of the adult female is significantly and dramatically altered on a long-term basis by the experiences of parity and motherhood. Remodeling of the maternal brain and other biological systems is posited to help facilitate adaptations to environmental/ecological challenges as the female raises young and ages.

  1. Neural networks type MLP in the process of identification chosen varieties of maize

    NASA Astrophysics Data System (ADS)

    Boniecki, P.; Nowakowski, K.; Tomczak, R.

    2011-06-01

    During the adaptation process of the weights vector that occurs in the iterative presentation of the teaching vector, the the MLP type artificial neural network (MultiLayer Perceptron) attempts to learn the structure of the data. Such a network can learn to recognise aggregates of input data occurring in the input data set regardless of the assumed criteria of similarity and the quantity of the data explored. The MLP type neural network can be also used to detect regularities occurring in the obtained graphic empirical data. The neuronal image analysis is then a new field of digital processing of signals. It is possible to use it to identify chosen objects given in the form of bitmap. If at the network input, a new unknown case appears which the network is unable to recognise, it means that it is different from all the classes known previously. The MLP type artificial neural network taught in this way can serve as a detector signalling the appearance of a widely understood novelty. Such a network can also look for similarities between the known data and the noisy data. In this way, it is able to identify fragments of images presented in photographs of e.g. maze's grain. The purpose of the research was to use the MLP neural networks in the process of identification of chosen varieties of maize with the use of image analysis method. The neuronal classification shapes of grains was performed with the use of the Johan Gielis super formula.

  2. 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.

  3. Long-Term Alterations in Neural and Endocrine Processes Induced by Motherhood

    PubMed Central

    Bridges, Robert S.

    2015-01-01

    The reproductive experience of pregnancy, lactation and motherhood can significantly remodel the female’s biological state, affecting endocrine, neuroendocrine, neural, and immunological processes. The brain, pituitary gland, liver, thymus, and mammary tissue are among the structures that are modified by reproductive experience. The present review that focuses on rodent research, but also includes pertinent studies in sheep and other species, identifies specific changes in these processes brought about by the biological states of pregnancy, parturition, and lactation and how the components of reproductive experience contribute to the remodeling of the maternal brain and organ systems. Findings indicate that prior parity alters key circulating hormone levels and neural receptor gene expression. Moreover, reproductive experience results in modifications in neural processes and glial support. The possible role of pregnancy-induced neurogenesis is considered in the context of neuroplasticity and behavior, and the effects of reproductive experience on maternal memory, i.e. the retention of maternal behavior, together with anxiety and learning are presented. Together, these sets of findings support the concept that the neural and biological state of the adult female is significantly and dramatically altered on a long-term basis by the experiences of parity and motherhood. Remodeling of the maternal brain and other biological systems is posited to help facilitate adaptations to environmental/ecological challenges as the female raises young and ages. PMID:26388065

  4. Atypical neural functions underlying phonological processing and silent rehearsal in children who stutter.

    PubMed

    Weber-Fox, Christine; Spruill, John E; Spencer, Rebecca; Smith, Anne

    2008-03-01

    Phonological processing was examined in school-age children who stutter (CWS) by assessing their performance and recording event-related brain potentials (ERPs) in a visual rhyming task. CWS had lower accuracy on rhyming judgments, but the cognitive processes that mediate the comparisons of the phonological representations of words, as indexed by the rhyming effect (RE) ERP, were similar for the stuttering and normally fluent groups. Thus the lower behavioral accuracy of rhyming judgments by the CWS could not be attributed to that particular stage of processing. Instead, the neural functions for processes preceding the RE, indexed by the N400 and CNV elicited by the primes and the N400 elicited by the targets, suggest atypical processing that may have resulted in less efficient, less accurate rhyming judgment for the CWS. Based on the present results, it seems likely that the neural processes related to phonological rehearsal and target word anticipation, as indexed by the CNV, are distinctive for CWS at this age. Further, it is likely that the relative contributions of the left and right hemispheres differ in CWS in the stage of processing when linguistic integration occurs, as indexed by the N400. Taken together, these results suggest that CWS may be less able to form and retain a stable neural representation of the prime onset and rime as they anticipate the target presentation, which may lead to lower rhyming judgment accuracy.

  5. Optimization of biopharmaceutical downstream processes supported by mechanistic models and artificial neural networks.

    PubMed

    Pirrung, Silvia M; van der Wielen, Luuk A M; van Beckhoven, Ruud F W C; van de Sandt, Emile J A X; Eppink, Michel H M; Ottens, Marcel

    2017-01-05

    Downstream process development is a major area of importance within the field of bioengineering. During the design of such a downstream process, important decisions have to be made regarding the type of unit operations as well as their sequence and their operating conditions. Current computational approaches addressing these issues either show a high level of simplification or struggle with computational speed. Therefore, this article presents a new approach that combines detailed mechanistic models and speed-enhancing artificial neural networks. This approach was able to simultaneously optimize a process with three different chromatographic columns toward yield with a minimum purity of 99.9%. The addition of artificial neural networks greatly accelerated this optimization. Due to high computational speed, the approach is easily extendable to include more unit operations. Therefore, it can be of great help in the acceleration of downstream process development. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 2017.

  6. Neural measures reveal implicit learning during language processing

    PubMed Central

    Batterink, Laura J.; Cheng, Larry Y.; Paller, Ken A.

    2016-01-01

    Language input is highly variable; phonological, lexical and syntactic features vary systematically across different speakers, geographic regions, and social contexts. Previous evidence shows that language users are sensitive to these contextual changes and that they can rapidly adapt to local regularities. For example, listeners quickly adjust to accented speech, facilitating comprehension. It has been proposed that this type of adaptation is a form of implicit learning. The present study examined a similar type of adaptation, syntactic adaptation, in order to address two issues: (1) whether language comprehenders are sensitive to a subtle probabilistic contingency between an extraneous feature (font color) and syntactic structure, and (2) whether this sensitivity should be attributed to implicit learning. Participants read a large set of sentences, 40% of which were garden-path sentences containing temporary syntactic ambiguities. Critically, but unbeknownst to participants, font color probabilistically predicted the presence of a garden-path structure, with 75% of garden-path sentences (and 25% of normative sentences) appearing in a given font color. Event-related brain potentials (ERPs) were recorded during sentence processing. Almost all participants indicated no conscious awareness of the relationship between font color and sentence structure. Nonetheless, after sufficient time to learn this relationship, ERPs time-locked to the point of syntactic-ambiguity resolution in garden-path sentences differed significantly as a function of font color. End-of-sentence grammaticality judgments were also influenced by font color, suggesting that a match between font color and sentence structure increased processing fluency. Overall, these findings indicate that participants can implicitly detect subtle co-occurrences between physical features of sentences and abstract, syntactic properties, supporting the notion that implicit learning mechanisms are generally operative

  7. Anatomic evidence for peripheral neural processing in mammalian graviceptors

    NASA Technical Reports Server (NTRS)

    Ross, M. D.

    1985-01-01

    Ultrastructural study of utricular and saccular maculas demonstrates that their innervation patterns are complex. There is a clustering of type I and type II hair cells based upon a sharing of afferents, a system of efferent-type beaded fibers that is of intramacular (mostly calyceal) origin, and a plexus-like arrangement of afferents and efferents at many sites in the neuroepithelium. Results suggest that information concerning linear acceleration is processed peripherally, beginning at the hair cell level, before being sent to the central nervous system. The findings may supply a structural basis for peripheral adaptation to a constant stimulus, and for lateral inhibition to improve signal relative to noise.

  8. Neural and Behavioral Evidence for an Online Resetting Process in Visual Working Memory.

    PubMed

    Balaban, Halely; Luria, Roy

    2017-02-01

    Visual working memory (VWM) guides behavior by holding a set of active representations and modifying them according to changes in the environment. This updating process relies on a unique mapping between each VWM representation and an actual object in the environment. Here, we destroyed this mapping by either presenting a coherent object but then breaking it into independent parts or presenting an object but then abruptly replacing it with a different object. This allowed us to introduce the neural marker and behavioral consequence of an online resetting process in humans' VWM. Across seven experiments, we demonstrate that this resetting process involves abandoning the old VWM contents because they no longer correspond to the objects in the environment. Then, VWM encodes the novel information and reestablishes the correspondence between the new representations and the objects. The resetting process was marked by a unique neural signature: a sharp drop in the amplitude of the electrophysiological index of VWM contents (the contralateral delay activity), presumably indicating the loss of the existent object-to-representation mappings. This marker was missing when an updating process occurred. Moreover, when tracking moving items, VWM failed to detect salient changes in the object's shape when these changes occurred during the resetting process. This happened despite the object being fully visible, presumably because the mapping between the object and a VWM representation was lost. Importantly, we show that resetting, its neural marker, and the behavioral cost it entails, are specific to situations that involve a destruction of the objects-to-representations correspondence.

  9. Construction of point process adaptive filter algorithms for neural systems using sequential Monte Carlo methods.

    PubMed

    Ergün, Ayla; Barbieri, Riccardo; Eden, Uri T; Wilson, Matthew A; Brown, Emery N

    2007-03-01

    The stochastic state point process filter (SSPPF) and steepest descent point process filter (SDPPF) are adaptive filter algorithms for state estimation from point process observations that have been used to track neural receptive field plasticity and to decode the representations of biological signals in ensemble neural spiking activity. The SSPPF and SDPPF are constructed using, respectively, Gaussian and steepest descent approximations to the standard Bayes and Chapman-Kolmogorov (BCK) system of filter equations. To extend these approaches for constructing point process adaptive filters, we develop sequential Monte Carlo (SMC) approximations to the BCK equations in which the SSPPF and SDPPF serve as the proposal densities. We term the two new SMC point process filters SMC-PPFs and SMC-PPFD, respectively. We illustrate the new filter algorithms by decoding the wind stimulus magnitude from simulated neural spiking activity in the cricket cercal system. The SMC-PPFs and SMC-PPFD provide more accurate state estimates at low number of particles than a conventional bootstrap SMC filter algorithm in which the state transition probability density is the proposal density. We also use the SMC-PPFs algorithm to track the temporal evolution of a spatial receptive field of a rat hippocampal neuron recorded while the animal foraged in an open environment. Our results suggest an approach for constructing point process adaptive filters using SMC methods.

  10. Precedence of the eye region in neural processing of faces

    PubMed Central

    Issa, Elias; DiCarlo, James

    2012-01-01

    SUMMARY Functional magnetic resonance imaging (fMRI) has revealed multiple subregions in monkey inferior temporal cortex (IT) that are selective for images of faces over other objects. The earliest of these subregions, the posterior lateral face patch (PL), has not been studied previously at the neurophysiological level. Perhaps not surprisingly, we found that PL contains a high concentration of ‘face selective’ cells when tested with standard image sets comparable to those used previously to define the region at the level of fMRI. However, we here report that several different image sets and analytical approaches converge to show that nearly all face selective PL cells are driven by the presence of a single eye in the context of a face outline. Most strikingly, images containing only an eye, even when incorrectly positioned in an outline, drove neurons nearly as well as full face images, and face images lacking only this feature led to longer latency responses. Thus, bottom-up face processing is relatively local and linearly integrates features -- consistent with parts-based models -- grounding investigation of how the presence of a face is first inferred in the IT face processing hierarchy. PMID:23175821

  11. Disrupted neural processing of emotional faces in psychopathy.

    PubMed

    Contreras-Rodríguez, Oren; Pujol, Jesus; Batalla, Iolanda; Harrison, Ben J; Bosque, Javier; Ibern-Regàs, Immaculada; Hernández-Ribas, Rosa; Soriano-Mas, Carles; Deus, Joan; López-Solà, Marina; Pifarré, Josep; Menchón, José M; Cardoner, Narcís

    2014-04-01

    Psychopaths show a reduced ability to recognize emotion facial expressions, which may disturb the interpersonal relationship development and successful social adaptation. Behavioral hypotheses point toward an association between emotion recognition deficits in psychopathy and amygdala dysfunction. Our prediction was that amygdala dysfunction would combine deficient activation with disturbances in functional connectivity with cortical regions of the face-processing network. Twenty-two psychopaths and 22 control subjects were assessed and functional magnetic resonance maps were generated to identify both brain activation and task-induced functional connectivity using psychophysiological interaction analysis during an emotional face-matching task. Results showed significant amygdala activation in control subjects only, but differences between study groups did not reach statistical significance. In contrast, psychopaths showed significantly increased activation in visual and prefrontal areas, with this latest activation being associated with psychopaths' affective-interpersonal disturbances. Psychophysiological interaction analyses revealed a reciprocal reduction in functional connectivity between the left amygdala and visual and prefrontal cortices. Our results suggest that emotional stimulation may evoke a relevant cortical response in psychopaths, but a disruption in the processing of emotional faces exists involving the reciprocal functional interaction between the amygdala and neocortex, consistent with the notion of a failure to integrate emotion into cognition in psychopathic individuals.

  12. Neural processing of dynamic emotional facial expressions in psychopaths

    PubMed Central

    Decety, Jean; Skelly, Laurie; Yoder, Keith J.; Kiehl, Kent A.

    2014-01-01

    Facial expressions play a critical role in social interactions by eliciting rapid responses in the observer. Failure to perceive and experience a normal range and depth of emotion seriously impact interpersonal communication and relationships. As has been demonstrated across a number of domains, abnormal emotion processing in individuals with psychopathy plays a key role in their lack of empathy. However, the neuroimaging literature is unclear as to whether deficits are specific to particular emotions such as fear and perhaps sadness. Moreover, findings are inconsistent across studies. In the current experiment, eighty adult incarcerated males scoring high, medium, and low on the Hare Psychopathy Checklist-Revised (PCL-R) underwent fMRI scanning while viewing dynamic facial expressions of fear, sadness, happiness and pain. Participants who scored high on the PCL-R showed a reduction in neuro-hemodynamic response to all four categories of facial expressions in the face processing network (inferior occipital gyrus, fusiform gyrus, STS) as well as the extended network (inferior frontal gyrus and orbitofrontal cortex), which supports a pervasive deficit across emotion domains. Unexpectedly, the response in dorsal insula to fear, sadness and pain was greater in psychopaths than non-psychopaths. Importantly, the orbitofrontal cortex and ventromedial prefrontal cortex, regions critically implicated in affective and motivated behaviors, were significantly less active in individuals with psychopathy during the perception of all four emotional expressions. PMID:24359488

  13. Neural processing of dynamic emotional facial expressions in psychopaths.

    PubMed

    Decety, Jean; Skelly, Laurie; Yoder, Keith J; Kiehl, Kent A

    2014-02-01

    Facial expressions play a critical role in social interactions by eliciting rapid responses in the observer. Failure to perceive and experience a normal range and depth of emotion seriously impact interpersonal communication and relationships. As has been demonstrated across a number of domains, abnormal emotion processing in individuals with psychopathy plays a key role in their lack of empathy. However, the neuroimaging literature is unclear as to whether deficits are specific to particular emotions such as fear and perhaps sadness. Moreover, findings are inconsistent across studies. In the current experiment, 80 incarcerated adult males scoring high, medium, and low on the Hare Psychopathy Checklist-Revised (PCL-R) underwent functional magnetic resonance imaging (fMRI) scanning while viewing dynamic facial expressions of fear, sadness, happiness, and pain. Participants who scored high on the PCL-R showed a reduction in neuro-hemodynamic response to all four categories of facial expressions in the face processing network (inferior occipital gyrus, fusiform gyrus, and superior temporal sulcus (STS)) as well as the extended network (inferior frontal gyrus and orbitofrontal cortex (OFC)), which supports a pervasive deficit across emotion domains. Unexpectedly, the response in dorsal insula to fear, sadness, and pain was greater in psychopaths than non-psychopaths. Importantly, the orbitofrontal cortex and ventromedial prefrontal cortex (vmPFC), regions critically implicated in affective and motivated behaviors, were significantly less active in individuals with psychopathy during the perception of all four emotional expressions.

  14. REVIEWS OF TOPICAL PROBLEMS: Models of neural dynamics in brain information processing — the developments of 'the decade'

    NASA Astrophysics Data System (ADS)

    Borisyuk, G. N.; Borisyuk, R. M.; Kazanovich, Yakov B.; Ivanitskii, Genrikh R.

    2002-10-01

    Neural network models are discussed that have been developed during the last decade with the purpose of reproducing spatio-temporal patterns of neural activity in different brain structures. The main goal of the modeling was to test hypotheses of synchronization, temporal and phase relations in brain information processing. The models being considered are those of temporal structure of spike sequences, of neural activity dynamics, and oscillatory models of attention and feature integration.

  15. Neural processing of speech in children is influenced by extent of bilingual experience.

    PubMed

    Krizman, Jennifer; Slater, Jessica; Skoe, Erika; Marian, Viorica; Kraus, Nina

    2015-01-12

    Language experience fine-tunes how the auditory system processes sound. Bilinguals, relative to monolinguals, have more robust evoked responses to speech that manifest as stronger neural encoding of the fundamental frequency (F0) and greater across-trial consistency. However, it is unknown whether such enhancements increase with increasing second language experience. We predict that F0 amplitude and neural consistency scale with dual-language experience during childhood, such that more years of bilingual experience leads to more robust F0 encoding and greater neural consistency. To test this hypothesis, we recorded auditory brainstem responses to the synthesized syllables 'ba' and 'ga' in two groups of bilingual children who were matched for age at test (8.4 ± 0.67 years) but differed in their age of second language acquisition. One group learned English and Spanish simultaneously from birth (n=13), while the second group learned the two languages sequentially (n=15), spending on average their first four years as monolingual Spanish speakers. We find that simultaneous bilinguals have a larger F0 response to 'ba' and 'ga' and a more consistent response to 'ba' compared to sequential bilinguals and we demonstrate that these neural enhancements track with years of bilingual experience. These findings support the notion that bilingualism enhances subcortical auditory processing.

  16. Modulated neural processing of Western harmony in folk musicians.

    PubMed

    Brattico, Elvira; Tupala, Tiina; Glerean, Enrico; Tervaniemi, Mari

    2013-07-01

    A chord deviating from the conventions of Western tonal music elicits an early right anterior negativity (ERAN) in inferofrontal brain regions. Here, we tested whether the ERAN is modulated by expertise in more than one music culture, as typical of folk musicians. Finnish folk musicians and nonmusicians participated in electroencephalography recordings. The cadences consisted of seven chords. In incongruous cadences, the third, fifth, or seventh chord was a Neapolitan. The ERAN to the Neapolitans was enhanced in folk musicians compared to nonmusicians. Folk musicians showed an enhanced P3a for the ending Neapolitan. The Neapolitan at the fifth position was perceived differently and elicited a late enhanced ERAN in folk musicians. Hence, expertise in more than one music culture seems to modify chord processing by enhancing the ERAN to ambivalent chords and the P3a to incongruous chords, and by altering their perceptual attributes.

  17. Process development for dry etching polydimethylsiloxane for neural electrodes.

    PubMed

    Anenden, Melissa P; Svehla, Martin; Lovell, Nigel H; Suaning, Gregg J

    2011-01-01

    In order to create high density electrode arrays, a reactive ion (dry) etching process was developed using sulphur hexafluoride (SF(6)) and oxygen (O(2)) plasma to pattern micro-structures in medical grade polydimethylsiloxane (PDMS). The surface topography and etch performance were analyzed by employing surface profilometry, scanning electron micrographs (SEM) and atomic force miscroscopy (AFM). The maximum etch rate was approximately 0.22 μm/min. The chemical modification of the PDMS structure in SF(6) and O(2) plasma was investigated through x-ray photoelectron spectroscopy (XPS). Micro-scale openings in PDMS were achieved using a dry etching method to allow charge injection at the electrode-tissue interface.

  18. Visual processing affects the neural basis of auditory discrimination.

    PubMed

    Kislyuk, Daniel S; Möttönen, Riikka; Sams, Mikko

    2008-12-01

    The interaction between auditory and visual speech streams is a seamless and surprisingly effective process. An intriguing example is the "McGurk effect": The acoustic syllable /ba/ presented simultaneously with a mouth articulating /ga/ is typically heard as /da/ [McGurk, H., & MacDonald, J. Hearing lips and seeing voices. Nature, 264, 746-748, 1976]. Previous studies have demonstrated the interaction of auditory and visual streams at the auditory cortex level, but the importance of these interactions for the qualitative perception change remained unclear because the change could result from interactions at higher processing levels as well. In our electroencephalogram experiment, we combined the McGurk effect with mismatch negativity (MMN), a response that is elicited in the auditory cortex at a latency of 100-250 msec by any above-threshold change in a sequence of repetitive sounds. An "odd-ball" sequence of acoustic stimuli consisting of frequent /va/ syllables (standards) and infrequent /ba/ syllables (deviants) was presented to 11 participants. Deviant stimuli in the unisensory acoustic stimulus sequence elicited a typical MMN, reflecting discrimination of acoustic features in the auditory cortex. When the acoustic stimuli were dubbed onto a video of a mouth constantly articulating /va/, the deviant acoustic /ba/ was heard as /va/ due to the McGurk effect and was indistinguishable from the standards. Importantly, such deviants did not elicit MMN, indicating that the auditory cortex failed to discriminate between the acoustic stimuli. Our findings show that visual stream can qualitatively change the auditory percept at the auditory cortex level, profoundly influencing the auditory cortex mechanisms underlying early sound discrimination.

  19. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex.

    PubMed

    Vanni, Simo; Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-08-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals.

  20. Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

    PubMed Central

    Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

    2015-01-01

    Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. PMID:25972586

  1. Modeling of local neural networks of the visual cortex and applications to image processing

    NASA Astrophysics Data System (ADS)

    Rybak, Ilya A.; Shevtsova, Natalia A.; Podladchikova, Lubov N.

    1991-08-01

    A model of an iso-orientation domain in the visual cortex is developed. The iso-orientation domain is represented as a neural network with retinotopically organized afferent inputs and anisotropic lateral inhibition formed by feedback connections via inhibitory interneurons. Temporal dynamics of neuron responses to oriented stimuli is studied. The results of computer simulations are compared with those of neurophysiological experiments. It is shown that the later phase of a neuron response has a more sharp orientation tuning than the initial one. It is suggested that the initial phase of a neuron response encodes intensity parameters of visual stimuli, whereas the later phase encodes its orientation. The design of the neural network preprocessor and the architecture of the system for visual information processing, based on the idea of parallel-sequential processing, are proposed. An example of a test image processing is presented.

  2. Neural processes in symmetry perception: a parallel spatio-temporal model.

    PubMed

    Zhu, Tao

    2014-04-01

    Symmetry is usually computationally expensive to detect reliably, while it is relatively easy to perceive. In spite of many attempts to understand the neurofunctional properties of symmetry processing, no symmetry-specific activation was found in earlier cortical areas. Psychophysical evidence relating to the processing mechanisms suggests that the basic processes of symmetry perception would not perform a serial, point-by-point comparison of structural features but rather operate in parallel. Here, modeling of neural processes in psychophysical detection of bilateral texture symmetry is considered. A simple fine-grained algorithm that is capable of performing symmetry estimation without explicit comparison of remote elements is introduced. A computational model of symmetry perception is then described to characterize the underlying mechanisms as one-dimensional spatio-temporal neural processes, each of which is mediated by intracellular horizontal connections in primary visual cortex and adopts the proposed algorithm for the neural computation. Simulated experiments have been performed to show the efficiency and the dynamics of the model. Model and human performances are comparable for symmetry perception of intensity images. Interestingly, the responses of V1 neurons to propagation activities reflecting higher-order perceptual computations have been reported in neurophysiologic experiments.

  3. A hybrid model for the neural representation of complex mental processing in the human brain.

    PubMed

    Fehr, Thorsten

    2013-04-01

    In the present conceptual review several theoretical and empirical sources of information were integrated, and a hybrid model of the neural representation of complex mental processing in the human brain was proposed. Based on empirical evidence for strategy-related and inter-individually different task-related brain activation networks, and further based on empirical evidence for a remarkable overlap of fronto-parietal activation networks across different complex mental processes, it was concluded by the author that there might be innate and modular organized neuro-developmental starting regions, for example, in intra-parietal, and both medial and middle frontal brain regions, from which the neural organization of different kinds of complex mental processes emerge differently during individually shaped learning histories. Thus, the here proposed model provides a hybrid of both massive modular and holistic concepts of idiosyncratic brain physiological elaboration of complex mental processing. It is further concluded that 3-D information, obtained by respective methodological approaches, are not appropriate to identify the non-linear spatio-temporal dynamics of complex mental process-related brain activity in a sufficient way. How different participating network parts communicate with each other seems to be an indispensable aspect, which has to be considered in particular to improve our understanding of the neural organization of complex cognition.

  4. A quantum theoretical approach to information processing in neural networks

    NASA Astrophysics Data System (ADS)

    Barahona da Fonseca, José; Barahona da Fonseca, Isabel; Suarez Araujo, Carmen Paz; Simões da Fonseca, José

    2000-05-01

    A reinterpretation of experimental data on learning was used to formulate a law on data acquisition similar to the Hamiltonian of a mechanical system. A matrix of costs in decision making specifies values attributable to a barrier that opposed to hypothesis formation about decision making. The interpretation of the encoding costs as frequencies of oscillatory phenomena leads to a quantum paradigm based in the models of photoelectric effect as well as of a particle against a potential barrier. Cognitive processes are envisaged as complex phenomena represented by structures linked by valence bounds. This metaphor is used to find some prerequisites to certain types of conscious experience as well as to find an explanation for some pathological distortions of cognitive operations as they are represented in the context of the isolobal model. Those quantum phenomena are understood as representing an analogue programming for specific special purpose computations. The formation of complex chemical structures within the context of isolobal theory is understood as an analog quantum paradigm for complex cognitive computations.

  5. Neural Modulation in Aversive Emotion Processing: An Independent Component Analysis Study

    PubMed Central

    Dragustinovis-Ruiz, Eduardo Antonio

    2016-01-01

    Emotional processing has an important role in social interaction. We report the findings about the Independent Component Analysis carried out on a fMRI set obtained with a paradigm of face emotional processing. The results showed that an independent component, mainly cerebellar-medial-frontal, had a positive modulation associated with fear processing. Also, another independent component, mainly parahippocampal-prefrontal, showed a negative modulation that could be associated with implicit reappraisal of emotional stimuli. Independent Component Analysis could serve as a method to understand complex cognitive processes and their underlying neural dynamics. PMID:27579051

  6. Optical Calibration Process Developed for Neural-Network-Based Optical Nondestructive Evaluation Method

    NASA Technical Reports Server (NTRS)

    Decker, Arthur J.

    2004-01-01

    A completely optical calibration process has been developed at Glenn for calibrating a neural-network-based nondestructive evaluation (NDE) method. The NDE method itself detects very small changes in the characteristic patterns or vibration mode shapes of vibrating structures as discussed in many references. The mode shapes or characteristic patterns are recorded using television or electronic holography and change when a structure experiences, for example, cracking, debonds, or variations in fastener properties. An artificial neural network can be trained to be very sensitive to changes in the mode shapes, but quantifying or calibrating that sensitivity in a consistent, meaningful, and deliverable manner has been challenging. The standard calibration approach has been difficult to implement, where the response to damage of the trained neural network is compared with the responses of vibration-measurement sensors. In particular, the vibration-measurement sensors are intrusive, insufficiently sensitive, and not numerous enough. In response to these difficulties, a completely optical alternative to the standard calibration approach was proposed and tested successfully. Specifically, the vibration mode to be monitored for structural damage was intentionally contaminated with known amounts of another mode, and the response of the trained neural network was measured as a function of the peak-to-peak amplitude of the contaminating mode. The neural network calibration technique essentially uses the vibration mode shapes of the undamaged structure as standards against which the changed mode shapes are compared. The published response of the network can be made nearly independent of the contaminating mode, if enough vibration modes are used to train the net. The sensitivity of the neural network can be adjusted for the environment in which the test is to be conducted. The response of a neural network trained with measured vibration patterns for use on a vibration isolation

  7. Altered neural reward and loss processing and prediction error signalling in depression.

    PubMed

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela; Diener, Carsten; Flor, Herta

    2015-08-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression.

  8. Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

    PubMed

    Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

    2000-03-01

    Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

  9. Neural classifier in the estimation process of maturity of selected varieties of apples

    NASA Astrophysics Data System (ADS)

    Boniecki, P.; Piekarska-Boniecka, H.; Koszela, K.; Zaborowicz, M.; Przybył, K.; Wojcieszak, D.; Zbytek, Z.; Ludwiczak, A.; Przybylak, A.; Lewicki, A.

    2015-07-01

    This paper seeks to present methods of neural image analysis aimed at estimating the maturity state of selected varieties of apples which are popular in Poland. An identification of the degree of maturity of selected varieties of apples has been conducted on the basis of information encoded in graphical form, presented in the digital photos. The above process involves the application of the BBCH scale, used to determine the maturity of apples. The aforementioned scale is widely used in the EU and has been developed for many species of monocotyledonous plants and dicotyledonous plants. It is also worth noticing that the given scale enables detailed determinations of development stage of a given plant. The purpose of this work is to identify maturity level of selected varieties of apples, which is supported by the use of image analysis methods and classification techniques represented by artificial neural networks. The analysis of graphical representative features based on image analysis method enabled the assessment of the maturity of apples. For the utilitarian purpose the "JabVis 1.1" neural IT system was created, in accordance with requirements of the software engineering dedicated to support the decision-making processes occurring in broadly understood production process and processing of apples.

  10. The neural processing of moral sensitivity to issues of justice and care.

    PubMed

    Robertson, Diana; Snarey, John; Ousley, Opal; Harenski, Keith; DuBois Bowman, F; Gilkey, Rick; Kilts, Clinton

    2007-03-02

    The empirical and theoretical consideration of ethical decision making has focused on the process of moral judgment; however, a precondition to judgment is moral sensitivity, the ability to detect and evaluate moral issues [Rest, J. R. (1984). The major components of morality. In W. Kurtines & J. Gewirtz (Eds.), Morality, moral behaviour, and moral development (pp. 24-38). New York, NY: Wiley]. Using functional magnetic resonance imaging (fMRI) and contextually standardized, real life moral issues, we demonstrate that sensitivity to moral issues is associated with activation of the polar medial prefrontal cortex, dorsal posterior cingulate cortex, and posterior superior temporal sulcus (STS). These activations suggest that moral sensitivity is related to access to knowledge unique to one's self, supported by autobiographical memory retrieval and social perspective taking. We also assessed whether sensitivity to rule-based or "justice" moral issues versus social situational or "care" moral issues is associated with dissociable neural processing events. Sensitivity to justice issues was associated with greater activation of the left intraparietal sulcus, whereas sensitivity to care issues was associated with greater activation of the ventral posterior cingulate cortex, ventromedial and dorsolateral prefrontal cortex, and thalamus. These results suggest a role for access to self histories and identities and social perspectives in sensitivity to moral issues, provide neural representations of the subcomponent process of moral sensitivity originally proposed by Rest, and support differing neural information processing for the interpretive recognition of justice and care moral issues.

  11. Altered neural reward and loss processing and prediction error signalling in depression

    PubMed Central

    Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

    2015-01-01

    Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

  12. Recognition of Roasted Coffee Bean Levels using Image Processing and Neural Network

    NASA Astrophysics Data System (ADS)

    Nasution, T. H.; Andayani, U.

    2017-03-01

    The coffee beans roast levels have some characteristics. However, some people cannot recognize the coffee beans roast level. In this research, we propose to design a method to recognize the coffee beans roast level of images digital by processing the image and classifying with backpropagation neural network. The steps consist of how to collect the images data with image acquisition, pre-processing, feature extraction using Gray Level Co-occurrence Matrix (GLCM) method and finally normalization of data extraction using decimal scaling features. The values of decimal scaling features become an input of classifying in backpropagation neural network. We use the method of backpropagation to recognize the coffee beans roast levels. The results showed that the proposed method is able to identify the coffee roasts beans level with an accuracy of 97.5%.

  13. Supramodal neural processing of abstract information conveyed by speech and gesture

    PubMed Central

    Straube, Benjamin; He, Yifei; Steines, Miriam; Gebhardt, Helge; Kircher, Tilo; Sammer, Gebhard; Nagels, Arne

    2013-01-01

    Abstractness and modality of interpersonal communication have a considerable impact on comprehension. They are relevant for determining thoughts and constituting internal models of the environment. Whereas concrete object-related information can be represented in mind irrespective of language, abstract concepts require a representation in speech. Consequently, modality-independent processing of abstract information can be expected. Here we investigated the neural correlates of abstractness (abstract vs. concrete) and modality (speech vs. gestures), to identify an abstractness-specific supramodal neural network. During fMRI data acquisition 20 participants were presented with videos of an actor either speaking sentences with an abstract-social [AS] or concrete-object-related content [CS], or performing meaningful abstract-social emblematic [AG] or concrete-object-related tool-use gestures [CG]. Gestures were accompanied by a foreign language to increase the comparability between conditions and to frame the communication context of the gesture videos. Participants performed a content judgment task referring to the person vs. object-relatedness of the utterances. The behavioral data suggest a comparable comprehension of contents communicated by speech or gesture. Furthermore, we found common neural processing for abstract information independent of modality (AS > CS ∩ AG > CG) in a left hemispheric network including the left inferior frontal gyrus (IFG), temporal pole, and medial frontal cortex. Modality specific activations were found in bilateral occipital, parietal, and temporal as well as right inferior frontal brain regions for gesture (G > S) and in left anterior temporal regions and the left angular gyrus for the processing of speech semantics (S > G). These data support the idea that abstract concepts are represented in a supramodal manner. Consequently, gestures referring to abstract concepts are processed in a predominantly left hemispheric language

  14. Social anhedonia is associated with neural abnormalities during face emotion processing.

    PubMed

    Germine, Laura T; Garrido, Lucia; Bruce, Lori; Hooker, Christine

    2011-10-01

    Human beings are social organisms with an intrinsic desire to seek and participate in social interactions. Social anhedonia is a personality trait characterized by a reduced desire for social affiliation and reduced pleasure derived from interpersonal interactions. Abnormally high levels of social anhedonia prospectively predict the development of schizophrenia and contribute to poorer outcomes for schizophrenia patients. Despite the strong association between social anhedonia and schizophrenia, the neural mechanisms that underlie individual differences in social anhedonia have not been studied and are thus poorly understood. Deficits in face emotion recognition are related to poorer social outcomes in schizophrenia, and it has been suggested that face emotion recognition deficits may be a behavioral marker for schizophrenia liability. In the current study, we used functional magnetic resonance imaging (fMRI) to see whether there are differences in the brain networks underlying basic face emotion processing in a community sample of individuals low vs. high in social anhedonia. We isolated the neural mechanisms related to face emotion processing by comparing face emotion discrimination with four other baseline conditions (identity discrimination of emotional faces, identity discrimination of neutral faces, object discrimination, and pattern discrimination). Results showed a group (high/low social anhedonia) × condition (emotion discrimination/control condition) interaction in the anterior portion of the rostral medial prefrontal cortex, right superior temporal gyrus, and left somatosensory cortex. As predicted, high (relative to low) social anhedonia participants showed less neural activity in face emotion processing regions during emotion discrimination as compared to each control condition. The findings suggest that social anhedonia is associated with abnormalities in networks responsible for basic processes associated with social cognition, and provide a

  15. Development of a Neural Network-Based Renewable Energy Forecasting Framework for Process Industries

    SciTech Connect

    Lee, Soobin; Ryu, Jun-Hyung; Hodge, Bri-Mathias; Lee, In-Beum

    2016-06-25

    This paper presents a neural network-based forecasting framework for photovoltaic power (PV) generation as a decision-supporting tool to employ renewable energies in the process industry. The applicability of the proposed framework is illustrated by comparing its performance against other methodologies such as linear and nonlinear time series modelling approaches. A case study of an actual PV power plant in South Korea is presented.

  16. Altered neural processing of the need to stop in young adults at risk for stimulant dependence.

    PubMed

    Harlé, Katia M; Shenoy, Pradeep; Stewart, Jennifer L; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

    2014-03-26

    Identification of neurocognitive predictors of substance dependence is an important step in developing approaches to prevent addiction. Given evidence of inhibitory control deficits in substance abusers (Monterosso et al., 2005; Fu et al., 2008; Lawrence et al., 2009; Tabibnia et al., 2011), we examined neural processing characteristics in human occasional stimulant users (OSU), a population at risk for dependence. A total of 158 nondependent OSU and 47 stimulant-naive control subjects (CS) were recruited and completed a stop signal task while undergoing functional magnetic resonance imaging (fMRI). A Bayesian ideal observer model was used to predict probabilistic expectations of inhibitory demand, P(stop), on a trial-to-trial basis, based on experienced trial history. Compared with CS, OSU showed attenuated neural activation related to P(stop) magnitude in several areas, including left prefrontal cortex and left caudate. OSU also showed reduced neural activation in the dorsal anterior cingulate cortex (dACC) and right insula in response to an unsigned Bayesian prediction error representing the discrepancy between stimulus outcome and the predicted probability of a stop trial. These results indicate that, despite minimal overt behavioral manifestations, OSU use fewer brain processing resources to predict and update the need for response inhibition, processes that are critical for adjusting and optimizing behavioral performance, which may provide a biomarker for the development of substance dependence.

  17. Thermomechanical processing optimization for 304 austenitic stainless steel using artificial neural network and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Feng, Wen; Yang, Sen

    2016-12-01

    Thermomechanical processing has an important effect on the grain boundary character distribution. To obtain the optimal thermomechanical processing parameters is the key of grain boundary engineering. In this study, genetic algorithm (GA) based on artificial neural network model was proposed to optimize the thermomechanical processing parameters. In this model, a back-propagation neural network (BPNN) was established to map the relationship between thermomechanical processing parameters and the fraction of low-Σ CSL boundaries, and GA integrated with BPNN (BPNN/GA) was applied to optimize the thermomechanical processing parameters. The validation of the optimal thermomechanical processing parameters was verified by an experiment. Moreover, the microstructures and the intergranular corrosion resistance of the base material (BM) and the materials produced by the optimal thermomechanical processing parameters (termed as the GBEM) were studied. Compared to the BM specimen, the fraction of low-Σ CSL boundaries was increased from 56.8 to 77.9% and the random boundary network was interrupted by the low-Σ CSL boundaries, and the intergranular corrosion resistance was improved in the GBEM specimen. The results indicated that the BPNN/GA model was an effective and reliable means for the thermomechanical processing parameters optimization, which resulted in improving the intergranular corrosion resistance in 304 austenitic stainless steel.

  18. Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing

    PubMed Central

    Lin, Amy

    2016-01-01

    Abstract Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: P(f)∝1/fβ, which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)—the low-frequency (<5 Hz) component of brain field potentials—and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects’ discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics. PMID:27822495

  19. Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing.

    PubMed

    Lin, Amy; Maniscalco, Brian; He, Biyu J

    2016-01-01

    Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: [Formula: see text], which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)-the low-frequency (<5 Hz) component of brain field potentials-and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects' discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics.

  20. The design, fabrication, and test of a new VLSI hybrid analog-digital neural processing element

    NASA Technical Reports Server (NTRS)

    Deyong, Mark R.; Findley, Randall L.; Fields, Chris

    1992-01-01

    A hybrid analog-digital neural processing element with the time-dependent behavior of biological neurons has been developed. The hybrid processing element is designed for VLSI implementation and offers the best attributes of both analog and digital computation. Custom VLSI layout reduces the layout area of the processing element, which in turn increases the expected network density. The hybrid processing element operates at the nanosecond time scale, which enables it to produce real-time solutions to complex spatiotemporal problems found in high-speed signal processing applications. VLSI prototype chips have been designed, fabricated, and tested with encouraging results. Systems utilizing the time-dependent behavior of the hybrid processing element have been simulated and are currently in the fabrication process. Future applications are also discussed.

  1. Neural Correlates of Metaphor Processing: The Roles of Figurativeness, Familiarity and Difficulty

    PubMed Central

    Schmidt, Gwenda L.; Seger, Carol A.

    2009-01-01

    There is currently much interest in investigating the neural substrates of metaphor processing. In particular, it has been suggested that the right hemisphere plays a special role in the comprehension of figurative (non-literal) language, and in particular metaphors. However, some studies find no evidence of right hemisphere involvement in metaphor comprehension (e.g. Lee & Dapretto, 2006; Rapp et al., 2004). We suggest that lateralization differences between literal and metaphorical language may be due to factors such as differences in familiarity (Schmidt et al., 2007), or difficulty (Bookheimer, 2002; Rapp et al., 2004) in addition to figurativeness. The purpose of this study was to separate the effects of figurativeness, familiarity, and difficulty on the recruitment of neural systems involved in language, in particular right hemisphere mechanisms. This was achieved by comparing neural activation using functional magnetic resonance imaging (fMRI) between four conditions: literal sentences, familiar and easy to understand metaphors, unfamiliar and easy to understand metaphors, and unfamiliar and difficult to understand metaphors. Metaphors recruited the right insula, left temporal pole and right inferior frontal gyrus in comparison with literal sentences. Familiar metaphors recruited the right middle frontal gyrus when contrasted with unfamiliar metaphors. Easy metaphors showed higher activation in the left middle frontal gyrus as compared to difficult metaphors, while difficult metaphors showed selective activation in the left inferior frontal gyrus as compared to easy metaphors. We conclude that the right hemisphere is involved in metaphor processing and that the factors of figurativeness, familiarity and difficulty are important in determining neural recruitment of semantic processing. PMID:19586700

  2. Musical intervention enhances infants’ neural processing of temporal structure in music and speech

    PubMed Central

    Zhao, T. Christina; Kuhl, Patricia K.

    2016-01-01

    Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants’ neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants’ neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants’ neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants’ ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing. PMID:27114512

  3. Musical intervention enhances infants' neural processing of temporal structure in music and speech.

    PubMed

    Zhao, T Christina; Kuhl, Patricia K

    2016-05-10

    Individuals with music training in early childhood show enhanced processing of musical sounds, an effect that generalizes to speech processing. However, the conclusions drawn from previous studies are limited due to the possible confounds of predisposition and other factors affecting musicians and nonmusicians. We used a randomized design to test the effects of a laboratory-controlled music intervention on young infants' neural processing of music and speech. Nine-month-old infants were randomly assigned to music (intervention) or play (control) activities for 12 sessions. The intervention targeted temporal structure learning using triple meter in music (e.g., waltz), which is difficult for infants, and it incorporated key characteristics of typical infant music classes to maximize learning (e.g., multimodal, social, and repetitive experiences). Controls had similar multimodal, social, repetitive play, but without music. Upon completion, infants' neural processing of temporal structure was tested in both music (tones in triple meter) and speech (foreign syllable structure). Infants' neural processing was quantified by the mismatch response (MMR) measured with a traditional oddball paradigm using magnetoencephalography (MEG). The intervention group exhibited significantly larger MMRs in response to music temporal structure violations in both auditory and prefrontal cortical regions. Identical results were obtained for temporal structure changes in speech. The intervention thus enhanced temporal structure processing not only in music, but also in speech, at 9 mo of age. We argue that the intervention enhanced infants' ability to extract temporal structure information and to predict future events in time, a skill affecting both music and speech processing.

  4. Neural dissociation of food- and money-related reward processing using an abstract incentive delay task.

    PubMed

    Simon, Joe J; Skunde, Mandy; Wu, Mudan; Schnell, Knut; Herpertz, Sabine C; Bendszus, Martin; Herzog, Wolfgang; Friederich, Hans-Christoph

    2015-08-01

    Food is an innate reward stimulus related to energy homeostasis and survival, whereas money is considered a more general reward stimulus that gains a rewarding value through learning experiences. Although the underlying neural processing for both modalities of reward has been investigated independently from one another, a more detailed investigation of neural similarities and/or differences between food and monetary reward is still missing. Here, we investigated the neural processing of food compared with monetary-related rewards in 27 healthy, normal-weight women using functional magnetic resonance imaging. We developed a task distinguishing between the anticipation and the receipt of either abstract food or monetary reward. Both tasks activated the ventral striatum during the expectation of a reward. Compared with money, greater food-related activations were observed in prefrontal, parietal and central midline structures during the anticipation and lateral orbitofrontal cortex (lOFC) during the receipt of food reward. Furthermore, during the receipt of food reward, brain activation in the secondary taste cortex was positively related to the body mass index. These results indicate that food-dependent activations encompass to a greater extent brain regions involved in self-control and self-reflection during the anticipation and phylogenetically older parts of the lOFC during the receipt of reward.

  5. The neural processing of foreign-accented speech and its relationship to listener bias

    PubMed Central

    Yi, Han-Gyol; Smiljanic, Rajka; Chandrasekaran, Bharath

    2014-01-01

    Foreign-accented speech often presents a challenging listening condition. In addition to deviations from the target speech norms related to the inexperience of the nonnative speaker, listener characteristics may play a role in determining intelligibility levels. We have previously shown that an implicit visual bias for associating East Asian faces and foreignness predicts the listeners' perceptual ability to process Korean-accented English audiovisual speech (Yi et al., 2013). Here, we examine the neural mechanism underlying the influence of listener bias to foreign faces on speech perception. In a functional magnetic resonance imaging (fMRI) study, native English speakers listened to native- and Korean-accented English sentences, with or without faces. The participants' Asian-foreign association was measured using an implicit association test (IAT), conducted outside the scanner. We found that foreign-accented speech evoked greater activity in the bilateral primary auditory cortices and the inferior frontal gyri, potentially reflecting greater computational demand. Higher IAT scores, indicating greater bias, were associated with increased BOLD response to foreign-accented speech with faces in the primary auditory cortex, the early node for spectrotemporal analysis. We conclude the following: (1) foreign-accented speech perception places greater demand on the neural systems underlying speech perception; (2) face of the talker can exaggerate the perceived foreignness of foreign-accented speech; (3) implicit Asian-foreign association is associated with decreased neural efficiency in early spectrotemporal processing. PMID:25339883

  6. Neural dissociation of food- and money-related reward processing using an abstract incentive delay task

    PubMed Central

    Skunde, Mandy; Wu, Mudan; Schnell, Knut; Herpertz, Sabine C.; Bendszus, Martin; Herzog, Wolfgang; Friederich, Hans-Christoph

    2015-01-01

    Food is an innate reward stimulus related to energy homeostasis and survival, whereas money is considered a more general reward stimulus that gains a rewarding value through learning experiences. Although the underlying neural processing for both modalities of reward has been investigated independently from one another, a more detailed investigation of neural similarities and/or differences between food and monetary reward is still missing. Here, we investigated the neural processing of food compared with monetary-related rewards in 27 healthy, normal-weight women using functional magnetic resonance imaging. We developed a task distinguishing between the anticipation and the receipt of either abstract food or monetary reward. Both tasks activated the ventral striatum during the expectation of a reward. Compared with money, greater food-related activations were observed in prefrontal, parietal and central midline structures during the anticipation and lateral orbitofrontal cortex (lOFC) during the receipt of food reward. Furthermore, during the receipt of food reward, brain activation in the secondary taste cortex was positively related to the body mass index. These results indicate that food-dependent activations encompass to a greater extent brain regions involved in self-control and self-reflection during the anticipation and phylogenetically older parts of the lOFC during the receipt of reward. PMID:25552570

  7. 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.

  8. Noninvertibility and resonance in discrete-time neural networks for time-series processing

    NASA Astrophysics Data System (ADS)

    Gicquel, N.; Anderson, J. S.; Kevrekidis, I. G.

    1998-01-01

    We present a computer-assisted study emphasizing certain elements of the dynamics of artificial neural networks (ANNs) used for discrete time-series processing and nonlinear system identification. The structure of the network gives rise to the possibility of multiple inverses of a phase point backward in time; this is not possible for the continuous-time system from which the time series are obtained. Using a two-dimensional illustrative model in an oscillatory regime, we study here the interaction of attractors predicted by the discrete-time ANN model (invariant circles and periodic points locked on them) with critical curves. These curves constitute a generalization of critical points for maps of the interval (in the sense of Julia-Fatou); their interaction with the model-predicted attractors plays a crucial role in the organization of the bifurcation structure and ultimately in determining the dynamic behavior predicted by the neural network.

  9. It's not just my fault: Neural correlates of feedback processing in solo and joint action.

    PubMed

    Loehr, Janeen D; Kourtis, Dimitrios; Brazil, Inti A

    2015-10-01

    People often coordinate their actions with others' in pursuit of shared goals, yet little research has examined the neural processes by which people monitor whether shared goals have been achieved. The current study compared event-related potentials elicited by feedback indicating joint errors (resulting from two people's coordinated actions) and individual errors (resulting from one's own or another person's observed actions). Joint errors elicited a reduced feedback-related negativity (FRN) and P3a relative to own errors, and an enhanced FRN relative to observed errors. In contrast, P3b amplitudes did not differ between joint and individual errors. These findings indicate that producing errors together with a partner influences neural activity related to outcome evaluation but has less impact on activity related to the motivation to adapt future behaviour.

  10. Recovery of noisy pyroelectric-detector signals through neural-network processing

    NASA Astrophysics Data System (ADS)

    González, Martín G.; Peuriot, Alejandro L.; Slezak, Verónica B.; Santiago, Guillermo D.

    2005-05-01

    We introduce a neural-network-based filter devised to extend the dynamic range of pyroelectric detectors which otherwise would only be useful for medium-to-high energy measurements. To accomplish this task, we trained a multilayer perceptron through the back-propagation method using the theoretical signal derived from the detector equivalent electric circuit. We tested the performance of the neural-network filter both numerically and experimentally. In the former case we recovered theoretical signals corrupted with white and impulse noise and compared the results with those obtained through the use of standard filtering methods. In the latter case, we applied the filter to measure pulses from a Nd:YAG laser whose energy was below the detector noise-equivalent energy. With this processing technique in a standard PC we have been able to accurately measure laser energy values as low as one-tenth the detector's noise-equivalent energy and at 10-20Hz repetition rate.

  11. The neural correlates of cognitive effort in anxiety: effects on processing efficiency.

    PubMed

    Ansari, Tahereh L; Derakshan, Nazanin

    2011-03-01

    We investigated the neural correlates of cognitive effort/pre-target preparation (Contingent Negative Variation activity; CNV) in anxiety using a mixed antisaccade task that manipulated the interval between offset of instructional cue and onset of target (CTI). According to attentional control theory (Eysenck et al., 2007) we predicted that anxiety should result in increased levels of compensatory effort, as indicated by greater frontal CNV, to maintain comparable levels of performance under competing task demands. Our results showed that anxiety resulted in faster antisaccade latencies during medium compared with short and long CTIs. Accordingly, high-anxious individuals compared with low-anxious individuals showed greater levels of CNV activity at frontal sites during medium CTI suggesting that they exerted greater cognitive effort and invested more attentional resources in preparation for the task goal. Our results are the first to demonstrate the neural correlates of processing efficiency and compensatory effort in anxiety and are discussed within the framework of attentional control theory.

  12. Neural Correlates of Contrast and Humor: Processing Common Features of Verbal Irony

    PubMed Central

    Obert, Alexandre; Gierski, Fabien; Calmus, Arnaud; Flucher, Aurélie; Portefaix, Christophe; Pierot, Laurent; Kaladjian, Arthur; Caillies, Stéphanie

    2016-01-01

    Irony is a kind of figurative language used by a speaker to say something that contrasts with the context and, to some extent, lends humor to a situation. However, little is known about the brain regions that specifically support the processing of these two common features of irony. The present study had two main aims: (i) investigate the neural basis of irony processing, by delivering short ironic spoken sentences (and their literal counterparts) to participants undergoing fMRI; and (ii) assess the neural effect of two irony parameters, obtained from normative studies: degree of contrast and humor appreciation. Results revealed activation of the bilateral inferior frontal gyrus (IFG), posterior part of the left superior temporal gyrus, medial frontal cortex, and left caudate during irony processing, suggesting the involvement of both semantic and theory-of-mind networks. Parametric models showed that contrast was specifically associated with the activation of bilateral frontal and subcortical areas, and that these regions were also sensitive to humor, as shown by a conjunction analysis. Activation of the bilateral IFG is consistent with the literature on humor processing, and reflects incongruity detection/resolution processes. Moreover, the activation of subcortical structures can be related to the reward processing of social events. PMID:27851821

  13. Resting state neural networks for visual Chinese word processing in Chinese adults and children.

    PubMed

    Li, Ling; Liu, Jiangang; Chen, Feiyan; Feng, Lu; Li, Hong; Tian, Jie; Lee, Kang

    2013-07-01

    This study examined the resting state neural networks for visual Chinese word processing in Chinese children and adults. Both the functional connectivity (FC) and amplitude of low frequency fluctuation (ALFF) approaches were used to analyze the fMRI data collected when Chinese participants were not engaged in any specific explicit tasks. We correlated time series extracted from the visual word form area (VWFA) with those in other regions in the brain. We also performed ALFF analysis in the resting state FC networks. The FC results revealed that, regarding the functionally connected brain regions, there exist similar intrinsically organized resting state networks for visual Chinese word processing in adults and children, suggesting that such networks may already be functional after 3-4 years of informal exposure to reading plus 3-4 years formal schooling. The ALFF results revealed that children appear to recruit more neural resources than adults in generally reading-irrelevant brain regions. Differences between child and adult ALFF results suggest that children's intrinsic word processing network during the resting state, though similar in functional connectivity, is still undergoing development. Further exposure to visual words and experience with reading are needed for children to develop a mature intrinsic network for word processing. The developmental course of the intrinsically organized word processing network may parallel that of the explicit word processing network.

  14. Evidence for sex-specific shifting of neural processes underlying learning and memory following stress.

    PubMed

    Beck, Kevin D; Luine, Victoria N

    2010-02-09

    Recent human research has been focused upon determining whether there is evidence that stress responses cause qualitative changes in neural activity such that people change their learning strategies from a spatial/contextual memory process through the hippocampus to a procedural stimulus-response process through the caudate nucleus. Moreover, interest has shifted to determining whether males and females exhibit the same type of stress-induced change in neural processing of associations. Presented is a select review of 2 different animal models that have examined how acute or chronic stressors change learning in a sex-specific manner. This is followed by a brief review of recent human studies documenting how learning and memory functions change following stressor exposure. In both cases, it is clear that ovarian hormones have a significant influence on how stress affects learning processes in females. We then examine the evidence for a role of acetylcholine, dopamine, norepinephrine, or serotonin in modulating this shifting of processing and how that may differ across sex. Conclusions drawn suggest that there may be evidence for sex-specific changes in amygdala and hippocampus neuromodulation; however, the behavioral data are still not conclusive as to whether this represents a common or sex-specific shift in how males and females process associations after stressor exposure.

  15. Neural Correlates of Contrast and Humor: Processing Common Features of Verbal Irony.

    PubMed

    Obert, Alexandre; Gierski, Fabien; Calmus, Arnaud; Flucher, Aurélie; Portefaix, Christophe; Pierot, Laurent; Kaladjian, Arthur; Caillies, Stéphanie

    2016-01-01

    Irony is a kind of figurative language used by a speaker to say something that contrasts with the context and, to some extent, lends humor to a situation. However, little is known about the brain regions that specifically support the processing of these two common features of irony. The present study had two main aims: (i) investigate the neural basis of irony processing, by delivering short ironic spoken sentences (and their literal counterparts) to participants undergoing fMRI; and (ii) assess the neural effect of two irony parameters, obtained from normative studies: degree of contrast and humor appreciation. Results revealed activation of the bilateral inferior frontal gyrus (IFG), posterior part of the left superior temporal gyrus, medial frontal cortex, and left caudate during irony processing, suggesting the involvement of both semantic and theory-of-mind networks. Parametric models showed that contrast was specifically associated with the activation of bilateral frontal and subcortical areas, and that these regions were also sensitive to humor, as shown by a conjunction analysis. Activation of the bilateral IFG is consistent with the literature on humor processing, and reflects incongruity detection/resolution processes. Moreover, the activation of subcortical structures can be related to the reward processing of social events.

  16. Training of goal-directed attention regulation enhances control over neural processing for individuals with brain injury.

    PubMed

    Chen, Anthony J-W; Novakovic-Agopian, Tatjana; Nycum, Terrence J; Song, Shawn; Turner, Gary R; Hills, Nancy K; Rome, Scott; Abrams, Gary M; D'Esposito, Mark

    2011-05-01

    Deficits in attention and executive control are some of the most common, debilitating and persistent consequences of brain injuries. Understanding neural mechanisms that support clinically significant improvements, when they do occur, may help advance treatment development. Intervening via rehabilitation provides an opportunity to probe such mechanisms. Our objective was to identify neural mechanisms that underlie improvements in attention and executive control with rehabilitation training. We tested the hypothesis that intensive training enhances modulatory control of neural processing of perceptual information in patients with acquired brain injuries. Patients (n=12) participated either in standardized training designed to target goal-directed attention regulation, or a comparison condition (brief education). Training resulted in significant improvements on behavioural measures of attention and executive control. Functional magnetic resonance imaging methods adapted for testing the effects of intervention for patients with varied injury pathology were used to index modulatory control of neural processing. Pattern classification was utilized to decode individual functional magnetic resonance imaging data acquired during a visual selective attention task. Results showed that modulation of neural processing in extrastriate cortex was significantly enhanced by attention regulation training. Neural changes in prefrontal cortex, a candidate mediator for attention regulation, appeared to depend on individual baseline state. These behavioural and neural effects did not occur with the comparison condition. These results suggest that enhanced modulatory control over visual processing and a rebalancing of prefrontal functioning may underlie improvements in attention and executive control.

  17. 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.

  18. Signal processing and neural network toolbox and its application to failure diagnosis and prognosis

    NASA Astrophysics Data System (ADS)

    Tu, Fang; Wen, Fang; Willett, Peter K.; Pattipati, Krishna R.; Jordan, Eric H.

    2001-07-01

    Many systems are comprised of components equipped with self-testing capability; however, if the system is complex involving feedback and the self-testing itself may occasionally be faulty, tracing faults to a single or multiple causes is difficult. Moreover, many sensors are incapable of reliable decision-making on their own. In such cases, a signal processing front-end that can match inference needs will be very helpful. The work is concerned with providing an object-oriented simulation environment for signal processing and neural network-based fault diagnosis and prognosis. In the toolbox, we implemented a wide range of spectral and statistical manipulation methods such as filters, harmonic analyzers, transient detectors, and multi-resolution decomposition to extract features for failure events from data collected by data sensors. Then we evaluated multiple learning paradigms for general classification, diagnosis and prognosis. The network models evaluated include Restricted Coulomb Energy (RCE) Neural Network, Learning Vector Quantization (LVQ), Decision Trees (C4.5), Fuzzy Adaptive Resonance Theory (FuzzyArtmap), Linear Discriminant Rule (LDR), Quadratic Discriminant Rule (QDR), Radial Basis Functions (RBF), Multiple Layer Perceptrons (MLP) and Single Layer Perceptrons (SLP). Validation techniques, such as N-fold cross-validation and bootstrap techniques, are employed for evaluating the robustness of network models. The trained networks are evaluated for their performance using test data on the basis of percent error rates obtained via cross-validation, time efficiency, generalization ability to unseen faults. Finally, the usage of neural networks for the prediction of residual life of turbine blades with thermal barrier coatings is described and the results are shown. The neural network toolbox has also been applied to fault diagnosis in mixed-signal circuits.

  19. Neural Mechanisms of Human Perceptual Learning: Electrophysiological Evidence for a Two-Stage Process

    PubMed Central

    Hamamé, Carlos M.; Cosmelli, Diego; Henriquez, Rodrigo; Aboitiz, Francisco

    2011-01-01

    Background Humans and other animals change the way they perceive the world due to experience. This process has been labeled as perceptual learning, and implies that adult nervous systems can adaptively modify the way in which they process sensory stimulation. However, the mechanisms by which the brain modifies this capacity have not been sufficiently analyzed. Methodology/Principal Findings We studied the neural mechanisms of human perceptual learning by combining electroencephalographic (EEG) recordings of brain activity and the assessment of psychophysical performance during training in a visual search task. All participants improved their perceptual performance as reflected by an increase in sensitivity (d') and a decrease in reaction time. The EEG signal was acquired throughout the entire experiment revealing amplitude increments, specific and unspecific to the trained stimulus, in event-related potential (ERP) components N2pc and P3 respectively. P3 unspecific modification can be related to context or task-based learning, while N2pc may be reflecting a more specific attentional-related boosting of target detection. Moreover, bell and U-shaped profiles of oscillatory brain activity in gamma (30–60 Hz) and alpha (8–14 Hz) frequency bands may suggest the existence of two phases for learning acquisition, which can be understood as distinctive optimization mechanisms in stimulus processing. Conclusions/Significance We conclude that there are reorganizations in several neural processes that contribute differently to perceptual learning in a visual search task. We propose an integrative model of neural activity reorganization, whereby perceptual learning takes place as a two-stage phenomenon including perceptual, attentional and contextual processes. PMID:21541280

  20. Cognitive and Neural Aspects of Information Processing in Major Depressive Disorder: An Integrative Perspective

    PubMed Central

    Foland-Ross, Lara C.; Gotlib, Ian H.

    2012-01-01

    Researchers using experimental paradigms to examine cognitive processes have demonstrated that Major Depressive Disorder (MDD) is associated not with a general deficit in cognitive functioning, but instead with more specific anomalies in the processing of negatively valenced material. Indeed, cognitive theories of depression posit that negative biases in the processing of information play a critical role in influencing the onset, maintenance, and recurrence of depressive episodes. In this paper we review findings from behavioral studies documenting that MDD is associated with specific difficulties in attentional disengagement from negatively valenced material, with tendencies to interpret information in a negative manner, with deficits in cognitive control in the processing of negative material, and with enhanced memory for negative material. To gain a better understanding of the neurobiological basis of these abnormalities, we also examine findings from functional neuroimaging studies of depression and show that dysfunction in neural systems that subserve emotion processing, inhibition, and attention may underlie and contribute to the deficits in cognition that have been documented in depressed individuals. Finally, we briefly review evidence from studies of children who are at high familial risk for depression that indicates that abnormalities in cognition and neural function are observable before the onset of MDD and, consequently, may represent a risk factor for the development of this disorder. By integrating research from cognitive and neural investigations of depression, we can gain a more comprehensive understanding not only of how cognitive and biological factors interact to affect the onset, maintenance, and course of MDD, but also of how such research can aid in the development of targeted strategies for the prevention and treatment of this debilitating disorder. PMID:23162521

  1. Dissociated Neural Processing for Decisions in Managers and Non-Managers

    PubMed Central

    Caspers, Svenja; Heim, Stefan; Lucas, Marc G.; Stephan, Egon; Fischer, Lorenz; Amunts, Katrin; Zilles, Karl

    2012-01-01

    Functional neuroimaging studies of decision-making so far mainly focused on decisions under uncertainty or negotiation with other persons. Dual process theory assumes that, in such situations, decision making relies on either a rapid intuitive, automated or a slower rational processing system. However, it still remains elusive how personality factors or professional requirements might modulate the decision process and the underlying neural mechanisms. Since decision making is a key task of managers, we hypothesized that managers, facing higher pressure for frequent and rapid decisions than non-managers, prefer the heuristic, automated decision strategy in contrast to non-managers. Such different strategies may, in turn, rely on different neural systems. We tested managers and non-managers in a functional magnetic resonance imaging study using a forced-choice paradigm on word-pairs. Managers showed subcortical activation in the head of the caudate nucleus, and reduced hemodynamic response within the cortex. In contrast, non-managers revealed the opposite pattern. With the head of the caudate nucleus being an initiating component for process automation, these results supported the initial hypothesis, hinting at automation during decisions in managers. More generally, the findings reveal how different professional requirements might modulate cognitive decision processing. PMID:22927984

  2. Prior perceptual processing enhances the effect of emotional arousal on the neural correlates of memory retrieval.

    PubMed

    Dew, Ilana T Z; Ritchey, Maureen; LaBar, Kevin S; Cabeza, Roberto

    2014-07-01

    A fundamental idea in memory research is that items are more likely to be remembered if encoded with a semantic, rather than perceptual, processing strategy. Interestingly, this effect has been shown to reverse for emotionally arousing materials, such that perceptual processing enhances memory for emotional information or events. The current fMRI study investigated the neural mechanisms of this effect by testing how neural activations during emotional memory retrieval are influenced by the prior encoding strategy. Participants incidentally encoded emotional and neutral pictures under instructions to attend to either semantic or perceptual properties of each picture. Recognition memory was tested 2 days later. fMRI analyses yielded three main findings. First, right amygdalar activity associated with emotional memory strength was enhanced by prior perceptual processing. Second, prior perceptual processing of emotional pictures produced a stronger effect on recollection- than familiarity-related activations in the right amygdala and left hippocampus. Finally, prior perceptual processing enhanced amygdalar connectivity with regions strongly associated with retrieval success, including hippocampal/parahippocampal regions, visual cortex, and ventral parietal cortex. Taken together, the results specify how encoding orientations yield alterations in brain systems that retrieve emotional memories.

  3. Unconscious neural processing differs with method used to render stimuli invisible.

    PubMed

    Fogelson, Sergey V; Kohler, Peter J; Miller, Kevin J; Granger, Richard; Tse, Peter U

    2014-01-01

    Visual stimuli can be kept from awareness using various methods. The extent of processing that a given stimulus receives in the absence of awareness is typically used to make claims about the role of consciousness more generally. The neural processing elicited by a stimulus, however, may also depend on the method used to keep it from awareness, and not only on whether the stimulus reaches awareness. Here we report that the method used to render an image invisible has a dramatic effect on how category information about the unseen stimulus is encoded across the human brain. We collected fMRI data while subjects viewed images of faces and tools, that were rendered invisible using either continuous flash suppression (CFS) or chromatic flicker fusion (CFF). In a third condition, we presented the same images under normal fully visible viewing conditions. We found that category information about visible images could be extracted from patterns of fMRI responses throughout areas of neocortex known to be involved in face or tool processing. However, category information about stimuli kept from awareness using CFS could be recovered exclusively within occipital cortex, whereas information about stimuli kept from awareness using CFF was also decodable within temporal and frontal regions. We conclude that unconsciously presented objects are processed differently depending on how they are rendered subjectively invisible. Caution should therefore be used in making generalizations on the basis of any one method about the neural basis of consciousness or the extent of information processing without consciousness.

  4. Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

    NASA Astrophysics Data System (ADS)

    Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas

    2016-06-01

    While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization.

  5. The Neural Signatures of Processing Semantic End Values in Automatic Number Comparisons

    PubMed Central

    Pinhas, Michal; Buchman, Chananel; Lavro, Dmitri; Mesika, David; Tzelgov, Joseph; Berger, Andrea

    2015-01-01

    The brain activity associated with processing numerical end values has received limited research attention. The present study explored the neural correlates associated with processing semantic end values under conditions of automatic number processing. Event-related potentials (ERPs) were recorded while participants performed the numerical Stroop task, in which they were asked to compare the physical size of pairs of numbers, while ignoring their numerical values. The smallest end value in the set, which is a task irrelevant factor, was manipulated between participant groups. We focused on the processing of the lower end values of 0 and 1 because these numbers were found to be automatically tagged as the “smallest.” Behavioral results showed that the size congruity effect was modulated by the presence of the smallest end value in the pair. ERP data revealed a spatially extended centro-parieto-occipital P3 that was enhanced for congruent versus incongruent trials. Importantly, over centro-parietal sites, the P3 congruity effect (congruent minus incongruent) was larger for pairs containing the smallest end value than for pairs containing non-smallest values. These differences in the congruency effect were localized to the precuneus. The presence of an end value within the pair also modulated P3 latency. Our results provide the first neural evidence for the encoding of numerical end values. They further demonstrate that the use of end values as anchors is a primary aspect of processing symbolic numerical information. PMID:26640436

  6. Handedness is related to neural mechanisms underlying hemispheric lateralization of face processing

    PubMed Central

    Frässle, Stefan; Krach, Sören; Paulus, Frieder Michel; Jansen, Andreas

    2016-01-01

    While the right-hemispheric lateralization of the face perception network is well established, recent evidence suggests that handedness affects the cerebral lateralization of face processing at the hierarchical level of the fusiform face area (FFA). However, the neural mechanisms underlying differential hemispheric lateralization of face perception in right- and left-handers are largely unknown. Using dynamic causal modeling (DCM) for fMRI, we aimed to unravel the putative processes that mediate handedness-related differences by investigating the effective connectivity in the bilateral core face perception network. Our results reveal an enhanced recruitment of the left FFA in left-handers compared to right-handers, as evidenced by more pronounced face-specific modulatory influences on both intra- and interhemispheric connections. As structural and physiological correlates of handedness-related differences in face processing, right- and left-handers varied with regard to their gray matter volume in the left fusiform gyrus and their pupil responses to face stimuli. Overall, these results describe how handedness is related to the lateralization of the core face perception network, and point to different neural mechanisms underlying face processing in right- and left-handers. In a wider context, this demonstrates the entanglement of structurally and functionally remote brain networks, suggesting a broader underlying process regulating brain lateralization. PMID:27250879

  7. Measuring Process Dynamics and Nuclear Migration for Clones of Neural Progenitor Cells

    PubMed Central

    De La Hoz, Edgar Cardenas; Winter, Mark R.; Apostolopoulou, Maria; Temple, Sally

    2016-01-01

    Neural stem and progenitor cells (NPCs) generate processes that extend from the cell body in a dynamic manner. The NPC nucleus migrates along these processes with patterns believed to be tightly coupled to mechanisms of cell cycle regulation and cell fate determination. Here, we describe a new segmentation and tracking approach that allows NPC processes and nuclei to be reliably tracked across multiple rounds of cell division in phase-contrast microscopy images. Results are presented for mouse adult and embryonic NPCs from hundreds of clones, or lineage trees, containing tens of thousands of cells and millions of segmentations. New visualization approaches allow the NPC nuclear and process features to be effectively visualized for an entire clone. Significant differences in process and nuclear dynamics were found among type A and type C adult NPCs, and also between embryonic NPCs cultured from the anterior and posterior cerebral cortex. PMID:27878138

  8. Residual Neural Processing of Musical Sound Features in Adult Cochlear Implant Users

    PubMed Central

    Timm, Lydia; Vuust, Peter; Brattico, Elvira; Agrawal, Deepashri; Debener, Stefan; Büchner, Andreas; Dengler, Reinhard; Wittfoth, Matthias

    2014-01-01

    Auditory processing in general and music perception in particular are hampered in adult cochlear implant (CI) users. To examine the residual music perception skills and their underlying neural correlates in CI users implanted in adolescence or adulthood, we conducted an electrophysiological and behavioral study comparing adult CI users with normal-hearing age-matched controls (NH controls). We used a newly developed musical multi-feature paradigm, which makes it possible to test automatic auditory discrimination of six different types of sound feature changes inserted within a musical enriched setting lasting only 20 min. The presentation of stimuli did not require the participants’ attention, allowing the study of the early automatic stage of feature processing in the auditory cortex. For the CI users, we obtained mismatch negativity (MMN) brain responses to five feature changes but not to changes of rhythm, whereas we obtained MMNs for all the feature changes in the NH controls. Furthermore, the MMNs to deviants of pitch of CI users were reduced in amplitude and later than those of NH controls for changes of pitch and guitar timber. No other group differences in MMN parameters were found to changes in intensity and saxophone timber. Furthermore, the MMNs in CI users reflected the behavioral scores from a respective discrimination task and were correlated with patients’ age and speech intelligibility. Our results suggest that even though CI users are not performing at the same level as NH controls in neural discrimination of pitch-based features, they do possess potential neural abilities for music processing. However, CI users showed a disrupted ability to automatically discriminate rhythmic changes compared with controls. The current behavioral and MMN findings highlight the residual neural skills for music processing even in CI users who have been implanted in adolescence or adulthood. Highlights: -Automatic brain responses to musical feature changes

  9. Use of uniform designs in combination with neural networks for viral infection process development.

    PubMed

    Buenno, Laís Hara; Rocha, José Celso; Leme, Jaci; Caricati, Celso Pereira; Tonso, Aldo; Fernández Núñez, Eutimio Gustavo

    2015-01-01

    This work aimed to compare the predictive capacity of empirical models, based on the uniform design utilization combined to artificial neural networks with respect to classical factorial designs in bioprocess, using as example the rabies virus replication in BHK-21 cells. The viral infection process parameters under study were temperature (34°C, 37°C), multiplicity of infection (0.04, 0.07, 0.1), times of infection, and harvest (24, 48, 72 hours) and the monitored output parameter was viral production. A multilevel factorial experimental design was performed for the study of this system. Fractions of this experimental approach (18, 24, 30, 36 and 42 runs), defined according uniform designs, were used as alternative for modelling through artificial neural network and thereafter an output variable optimization was carried out by means of genetic algorithm methodology. Model prediction capacities for all uniform design approaches under study were better than that found for classical factorial design approach. It was demonstrated that uniform design in combination with artificial neural network could be an efficient experimental approach for modelling complex bioprocess like viral production. For the present study case, 67% of experimental resources were saved when compared to a classical factorial design approach. In the near future, this strategy could replace the established factorial designs used in the bioprocess development activities performed within biopharmaceutical organizations because of the improvements gained in the economics of experimentation that do not sacrifice the quality of decisions.

  10. Concepts in context: Processing mental state concepts with internal or external focus involves different neural systems

    PubMed Central

    Oosterwijk, Suzanne; Mackey, Scott; Wilson-Mendenhall, Christine; Winkielman, Piotr; Paulus, Martin P.

    2015-01-01

    According to embodied cognition theories concepts are contextually-situated and grounded in neural systems that produce experiential states. This view predicts that processing mental state concepts recruits neural regions associated with different aspects of experience depending on the context in which people understand a concept. This neuroimaging study tested this prediction using a set of sentences that described emotional (e.g., fear, joy) and non-emotional (e.g., thinking, hunger) mental states with internal focus (i.e. focusing on bodily sensations and introspection) or external focus (i.e. focusing on expression and action). Consistent with our predictions, data suggested that the inferior frontal gyrus, a region associated with action representation, was engaged more by external than internal sentences. By contrast, the ventromedial prefrontal cortex, a region associated with the generation of internal states, was engaged more by internal emotion sentences than external sentence categories. Similar patterns emerged when we examined the relationship between neural activity and independent ratings of sentence focus. Furthermore, ratings of emotion were associated with activation in the medial prefrontal cortex, whereas ratings of activity were associated with activation in the inferior frontal gyrus. These results suggest that mental state concepts are represented in a dynamic way, using context-relevant interoceptive and sensorimotor resources. PMID:25748274

  11. Artificial neural network associated to UV/Vis spectroscopy for monitoring bioreactions in biopharmaceutical processes.

    PubMed

    Takahashi, Maria Beatriz; Leme, Jaci; Caricati, Celso Pereira; Tonso, Aldo; Fernández Núñez, Eutimio Gustavo; Rocha, José Celso

    2015-06-01

    Currently, mammalian cells are the most utilized hosts for biopharmaceutical production. The culture media for these cell lines include commonly in their composition a pH indicator. Spectroscopic techniques are used for biopharmaceutical process monitoring, among them, UV-Vis spectroscopy has found scarce applications. This work aimed to define artificial neural networks architecture and fit its parameters to predict some nutrients and metabolites, as well as viable cell concentration based on UV-Vis spectral data of mammalian cell bioprocess using phenol red in culture medium. The BHK-21 cell line was used as a mammalian cell model. Off-line spectra of supernatant samples taken from batches performed at different dissolved oxygen concentrations in two bioreactor configurations and with two pH control strategies were used to define two artificial neural networks. According to absolute errors, glutamine (0.13 ± 0.14 mM), glutamate (0.02 ± 0.02 mM), glucose (1.11 ± 1.70 mM), lactate (0.84 ± 0.68 mM) and viable cell concentrations (1.89 10(5) ± 1.90 10(5) cell/mL) were suitably predicted. The prediction error averages for monitored variables were lower than those previously reported using different spectroscopic techniques in combination with partial least squares or artificial neural network. The present work allows for UV-VIS sensor development, and decreases cost related to nutrients and metabolite quantifications.

  12. Degraded neural and behavioral processing of speech sounds in a rat model of Rett syndrome.

    PubMed

    Engineer, Crystal T; Rahebi, Kimiya C; Borland, Michael S; Buell, Elizabeth P; Centanni, Tracy M; Fink, Melyssa K; Im, Kwok W; Wilson, Linda G; Kilgard, Michael P

    2015-11-01

    Individuals with Rett syndrome have greatly impaired speech and language abilities. Auditory brainstem responses to sounds are normal, but cortical responses are highly abnormal. In this study, we used the novel rat Mecp2 knockout model of Rett syndrome to document the neural and behavioral processing of speech sounds. We hypothesized that both speech discrimination ability and the neural response to speech sounds would be impaired in Mecp2 rats. We expected that extensive speech training would improve speech discrimination ability and the cortical response to speech sounds. Our results reveal that speech responses across all four auditory cortex fields of Mecp2 rats were hyperexcitable, responded slower, and were less able to follow rapidly presented sounds. While Mecp2 rats could accurately perform consonant and vowel discrimination tasks in quiet, they were significantly impaired at speech sound discrimination in background noise. Extensive speech training improved discrimination ability. Training shifted cortical responses in both Mecp2 and control rats to favor the onset of speech sounds. While training increased the response to low frequency sounds in control rats, the opposite occurred in Mecp2 rats. Although neural coding and plasticity are abnormal in the rat model of Rett syndrome, extensive therapy appears to be effective. These findings may help to explain some aspects of communication deficits in Rett syndrome and suggest that extensive rehabilitation therapy might prove beneficial.

  13. Power to Punish Norm Violations Affects the Neural Processes of Fairness-Related Decision Making

    PubMed Central

    Cheng, Xuemei; Zheng, Li; Li, Lin; Guo, Xiuyan; Wang, Qianfeng; Lord, Anton; Hu, Zengxi; Yang, Guang

    2015-01-01

    Punishing norm violations is considered an important motive during rejection of unfair offers in the ultimatum game (UG). The present study investigates the impact of the power to punish norm violations on people’s responses to unfairness and associated neural correlates. In the UG condition participants had the power to punish norm violations, while an alternate condition, the impunity game (IG), was presented where participants had no power to punish norm violations since rejection only reduced the responder’s income to zero. Results showed that unfair offers were rejected more often in UG compared to IG. At the neural level, anterior insula and dorsal anterior cingulate cortex were more active when participants received and rejected unfair offers in both UG and IG. Moreover, greater dorsolateral prefrontal cortex activity was observed when participants rejected than accepted unfair offers in UG but not in IG. Ventromedial prefrontal cortex activation was higher in UG than IG when unfair offers were accepted as well as when rejecting unfair offers in IG as opposed to UG. Taken together, our results demonstrate that the power to punish norm violations affects not only people’s behavioral responses to unfairness but also the neural correlates of the fairness-related social decision-making process. PMID:26696858

  14. Neural basis of first and second language processing of sentence-level linguistic prosody.

    PubMed

    Gandour, Jackson; Tong, Yunxia; Talavage, Thomas; Wong, Donald; Dzemidzic, Mario; Xu, Yisheng; Li, Xiaojian; Lowe, Mark

    2007-02-01

    A fundamental question in multilingualism is whether the neural substrates are shared or segregated for the two or more languages spoken by polyglots. This study employs functional MRI to investigate the neural substrates underlying the perception of two sentence-level prosodic phenomena that occur in both Mandarin Chinese (L1) and English (L2): sentence focus (sentence-initial vs. -final position of contrastive stress) and sentence type (declarative vs. interrogative modality). Late-onset, medium proficiency Chinese-English bilinguals were asked to selectively attend to either sentence focus or sentence type in paired three-word sentences in both L1 and L2 and make speeded-response discrimination judgments. L1 and L2 elicited highly overlapping activations in frontal, temporal, and parietal lobes. Furthermore, region of interest analyses revealed that for both languages the sentence focus task elicited a leftward asymmetry in the supramarginal gyrus; both tasks elicited a rightward asymmetry in the mid-portion of the middle frontal gyrus. A direct comparison between L1 and L2 did not show any difference in brain activation in the sentence type task. In the sentence focus task, however, greater activation for L2 than L1 occurred in the bilateral anterior insula and superior frontal sulcus. The sentence focus task also elicited a leftward asymmetry in the posterior middle temporal gyrus for L1 only. Differential activation patterns are attributed primarily to disparities between L1 and L2 in the phonetic manifestation of sentence focus. Such phonetic divergences lead to increased computational demands for processing L2. These findings support the view that L1 and L2 are mediated by a unitary neural system despite late age of acquisition, although additional neural resources may be required in task-specific circumstances for unequal bilinguals.

  15. Lateral information processing by spiking neurons: a theoretical model of the neural correlate of consciousness.

    PubMed

    Ebner, Marc; Hameroff, Stuart

    2011-01-01

    Cognitive brain functions, for example, sensory perception, motor control and learning, are understood as computation by axonal-dendritic chemical synapses in networks of integrate-and-fire neurons. Cognitive brain functions may occur either consciously or nonconsciously (on "autopilot"). Conscious cognition is marked by gamma synchrony EEG, mediated largely by dendritic-dendritic gap junctions, sideways connections in input/integration layers. Gap-junction-connected neurons define a sub-network within a larger neural network. A theoretical model (the "conscious pilot") suggests that as gap junctions open and close, a gamma-synchronized subnetwork, or zone moves through the brain as an executive agent, converting nonconscious "auto-pilot" cognition to consciousness, and enhancing computation by coherent processing and collective integration. In this study we implemented sideways "gap junctions" in a single-layer artificial neural network to perform figure/ground separation. The set of neurons connected through gap junctions form a reconfigurable resistive grid or sub-network zone. In the model, outgoing spikes are temporally integrated and spatially averaged using the fixed resistive grid set up by neurons of similar function which are connected through gap-junctions. This spatial average, essentially a feedback signal from the neuron's output, determines whether particular gap junctions between neurons will open or close. Neurons connected through open gap junctions synchronize their output spikes. We have tested our gap-junction-defined sub-network in a one-layer neural network on artificial retinal inputs using real-world images. Our system is able to perform figure/ground separation where the laterally connected sub-network of neurons represents a perceived object. Even though we only show results for visual stimuli, our approach should generalize to other modalities. The system demonstrates a moving sub-network zone of synchrony, within which the contents of

  16. City living and urban upbringing affect neural social stress processing in humans.

    PubMed

    Lederbogen, Florian; Kirsch, Peter; Haddad, Leila; Streit, Fabian; Tost, Heike; Schuch, Philipp; Wüst, Stefan; Pruessner, Jens C; Rietschel, Marcella; Deuschle, Michael; Meyer-Lindenberg, Andreas

    2011-06-22

    More than half of the world's population now lives in cities, making the creation of a healthy urban environment a major policy priority. Cities have both health risks and benefits, but mental health is negatively affected: mood and anxiety disorders are more prevalent in city dwellers and the incidence of schizophrenia is strongly increased in people born and raised in cities. Although these findings have been widely attributed to the urban social environment, the neural processes that could mediate such associations are unknown. Here we show, using functional magnetic resonance imaging in three independent experiments, that urban upbringing and city living have dissociable impacts on social evaluative stress processing in humans. Current city living was associated with increased amygdala activity, whereas urban upbringing affected the perigenual anterior cingulate cortex, a key region for regulation of amygdala activity, negative affect and stress. These findings were regionally and behaviourally specific, as no other brain structures were affected and no urbanicity effect was seen during control experiments invoking cognitive processing without stress. Our results identify distinct neural mechanisms for an established environmental risk factor, link the urban environment for the first time to social stress processing, suggest that brain regions differ in vulnerability to this risk factor across the lifespan, and indicate that experimental interrogation of epidemiological associations is a promising strategy in social neuroscience.

  17. Gender-specific modulation of neural mechanisms underlying social reward processing by Autism Quotient.

    PubMed

    Barman, Adriana; Richter, Sylvia; Soch, Joram; Deibele, Anna; Richter, Anni; Assmann, Anne; Wüstenberg, Torsten; Walter, Henrik; Seidenbecher, Constanze I; Schott, Björn H

    2015-11-01

    Autism spectrum disorder refers to a neurodevelopmental condition primarily characterized by deficits in social cognition and behavior. Subclinically, autistic features are supposed to be present in healthy humans and can be quantified using the Autism Quotient (AQ). Here, we investigated a potential relationship between AQ and neural correlates of social and monetary reward processing, using functional magnetic resonance imaging in young, healthy participants. In an incentive delay task with either monetary or social reward, reward anticipation elicited increased ventral striatal activation, which was more pronounced during monetary reward anticipation. Anticipation of social reward elicited activation in the default mode network (DMN), a network previously implicated in social processing. Social reward feedback was associated with bilateral amygdala and fusiform face area activation. The relationship between AQ and neural correlates of social reward processing varied in a gender-dependent manner. In women and, to a lesser extent in men, higher AQ was associated with increased posterior DMN activation during social reward anticipation. During feedback, we observed a negative correlation of AQ and right amygdala activation in men only. Our results suggest that social reward processing might constitute an endophenotype for autism-related traits in healthy humans that manifests in a gender-specific way.

  18. Improved object segmentation using Markov random fields, artificial neural networks, and parallel processing techniques

    NASA Astrophysics Data System (ADS)

    Foulkes, Stephen B.; Booth, David M.

    1997-07-01

    Object segmentation is the process by which a mask is generated which identifies the area of an image which is occupied by an object. Many object recognition techniques depend on the quality of such masks for shape and underlying brightness information, however, segmentation remains notoriously unreliable. This paper considers how the image restoration technique of Geman and Geman can be applied to the improvement of object segmentations generated by a locally adaptive background subtraction technique. Also presented is how an artificial neural network hybrid, consisting of a single layer Kohonen network with each of its nodes connected to a different multi-layer perceptron, can be used to approximate the image restoration process. It is shown that the restoration techniques are very well suited for parallel processing and in particular the artificial neural network hybrid has the potential for near real time image processing. Results are presented for the detection of ships in SPOT panchromatic imagery and the detection of vehicles in infrared linescan images, these being a fair representation of the wider class of problem.

  19. Neural Processing of Threat Cues in Young Children With Attention-Deficit/Hyperactivity Symptoms.

    PubMed

    Flegenheimer, Chaia; Lugo-Candelas, Claudia; Harvey, Elizabeth; McDermott, Jennifer M

    2017-03-03

    A growing literature indicates that attention deficit/hyperactivity disorder (ADHD) involves difficulty processing threat-related emotion faces. This deficit is especially important to understand in young children, as threat emotion processing is related to the development of social skills and related behavioral regulation. Therefore, the current study aimed to better understand the neural basis of this processing in young children with ADHD symptoms. Forty-seven children between 4 and 7 years of age were included in the analysis, 28 typical developing and 19 with clinically significant levels of ADHD hyperactive/impulsive symptoms. Participants completed a passive affective face-viewing task. Event-related potentials were assessed for each emotion, and parental report of child behavior and emotion regulation abilities was assessed. Children with ADHD symptoms showed altered N170 modulation in response to specific emotion faces, such that the N170 was less negative in response to fearful compared to neutral faces, whereas typically developing children showed the opposite pattern. Groups did not differ in reactivity to anger or non-threat-related emotion faces. The N170 difference in fearful compared to neutral faces correlated with reported behavior, such that less fear reactivity predicted fewer prosocial behaviors. Abnormalities in the underlying neural systems for fear processing in young children with ADHD symptoms may play an important role in social and behavioral deficits within this population.

  20. Event segmentation in a visual language: neural bases of processing American Sign Language predicates.

    PubMed

    Malaia, Evie; Ranaweera, Ruwan; Wilbur, Ronnie B; Talavage, Thomas M

    2012-02-15

    Motion capture studies show that American Sign Language (ASL) signers distinguish end-points in telic verb signs by means of marked hand articulator motion, which rapidly decelerates to a stop at the end of these signs, as compared to atelic signs (Malaia and Wilbur, in press). Non-signers also show sensitivity to velocity in deceleration cues for event segmentation in visual scenes (Zacks et al., 2010; Zacks et al., 2006), introducing the question of whether the neural regions used by ASL signers for sign language verb processing might be similar to those used by non-signers for event segmentation. The present study investigated the neural substrate of predicate perception and linguistic processing in ASL. Observed patterns of activation demonstrate that Deaf signers process telic verb signs as having higher phonological complexity as compared to atelic verb signs. These results, together with previous neuroimaging data on spoken and sign languages (Shetreet et al., 2010; Emmorey et al., 2009), illustrate a route for how a prominent perceptual-kinematic feature used for non-linguistic event segmentation might come to be processed as an abstract linguistic feature due to sign language exposure.

  1. Research on the neural networks used for shaping tubes by the liquid extrusion process

    SciTech Connect

    Qi, L.H.; Li, H.J.; Hou, J.J.; Cui, P.L.

    2000-02-01

    Liquid extrusion, as a new kind of metal forming process for shaping tube and bar products directly from liquid metal, can reduce the intermediate steps and production costs and make the materials doubly strengthened. But it has not been widely used since the process parameters are now selected by experience, which can easily result in a high reject rate. In order to analyze the contributing factors of the process, the artificial neural network method was used in this paper. The network architecture was determined by adopting 125 sets of experimental data of the shaping tubes of AlCuSiMg alloy as samples and, by contrast, one or two hidden layers and the numbers of nodes and other network parameters. The knowledge base for the process parameters of liquid extrusion has been established. The values predicted by the knowledge base are very consistent with the practical ones. The result shows that the introduced method is feasible and effective.

  2. Body posture and gender impact neural processing of power-related words.

    PubMed

    Bailey, April H; Kelly, Spencer D

    2016-09-29

    Judging others' power facilitates successful social interaction. Both gender and body posture have been shown to influence judgments of another's power. However, little is known about how these two cues interact when they conflict or how they influence early processing. The present study investigated this question during very early processing of power-related words using event-related potentials (ERPs). Participants viewed images of women and men in dominant and submissive postures that were quickly followed by dominant or submissive words. Gender and posture both modulated neural responses in the N2 latency range to dominant words, but for submissive words they had little impact. Thus, in the context of dual-processing theories of person perception, information extracted from both behavior (i.e., posture) and from category membership (i.e., gender) are recruited side-by-side to impact word processing.

  3. Neural correlates of audiotactile phonetic processing in early-blind readers: an fMRI study.

    PubMed

    Pishnamazi, Morteza; Nojaba, Yasaman; Ganjgahi, Habib; Amousoltani, Asie; Oghabian, Mohammad Ali

    2016-05-01

    Reading is a multisensory function that relies on arbitrary associations between auditory speech sounds and symbols from a second modality. Studies of bimodal phonetic perception have mostly investigated the integration of visual letters and speech sounds. Blind readers perform an analogous task by using tactile Braille letters instead of visual letters. The neural underpinnings of audiotactile phonetic processing have not been studied before. We used functional magnetic resonance imaging to reveal the neural correlates of audiotactile phonetic processing in 16 early-blind Braille readers. Braille letters and corresponding speech sounds were presented in unimodal, and congruent/incongruent bimodal configurations. We also used a behavioral task to measure the speed of blind readers in identifying letters presented via tactile and/or auditory modalities. Reaction times for tactile stimuli were faster. The reaction times for bimodal stimuli were equal to those for the slower auditory-only stimuli. fMRI analyses revealed the convergence of unimodal auditory and unimodal tactile responses in areas of the right precentral gyrus and bilateral crus I of the cerebellum. The left and right planum temporale fulfilled the 'max criterion' for bimodal integration, but activities of these areas were not sensitive to the phonetical congruency between sounds and Braille letters. Nevertheless, congruency effects were found in regions of frontal lobe and cerebellum. Our findings suggest that, unlike sighted readers who are assumed to have amodal phonetic representations, blind readers probably process letters and sounds separately. We discuss that this distinction might be due to mal-development of multisensory neural circuits in early blinds or it might be due to inherent differences between Braille and print reading mechanisms.

  4. Neural Correlates of Hostile Jokes: Cognitive and Motivational Processes in Humor Appreciation

    PubMed Central

    Chan, Yu-Chen; Liao, Yi-Jun; Tu, Cheng-Hao

    2016-01-01

    Hostile jokes (HJs) provide aggressive catharsis and a feeling of superiority. Behavioral research has found that HJs are perceived as funnier than non-hostile jokes (NJs). The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing HJs, NJs, and their corresponding hostile sentences (HSs) and non-hostile sentences (NSs). HJs primarily showed activation in the dorsomedial prefrontal cortex (dmPFC) and midbrain compared with the corresponding hostile baseline. Conversely, NJs primarily revealed activation in the ventromedial PFC (vmPFC), amygdala, midbrain, ventral anterior cingulate cortex, and nucleus accumbens (NAcc) compared with the corresponding non-hostile baseline. These results support the critical role of the medial PFC (mPFC) for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of HJs showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of NJs displayed increased activation in the vmPFC, which suggested social-affective engagement. HJs versus NJs primarily showed increased activation in the dmPFC and midbrain, whereas NJs versus HJs primarily displayed greater activation in the amygdala and midbrain. The psychophysiological interaction (PPI) analysis demonstrated functional coupling of the dmPFC–dlPFC and midbrain–dmPFC for HJs and functional coupling of the vmPFC–midbrain and amygdala–midbrain–NAcc for NJs. Surprisingly, HJs were not perceived as funnier than NJs. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation based on the psychoanalytic and superiority theories of humor. PMID:27840604

  5. Inside the brain of an elite athlete: the neural processes that support high achievement in sports.

    PubMed

    Yarrow, Kielan; Brown, Peter; Krakauer, John W

    2009-08-01

    Events like the World Championships in athletics and the Olympic Games raise the public profile of competitive sports. They may also leave us wondering what sets the competitors in these events apart from those of us who simply watch. Here we attempt to link neural and cognitive processes that have been found to be important for elite performance with computational and physiological theories inspired by much simpler laboratory tasks. In this way we hope to inspire neuroscientists to consider how their basic research might help to explain sporting skill at the highest levels of performance.

  6. A novel process monitoring and control system based on a neural manufacturing concept

    SciTech Connect

    Fu, Chi Yung; Petrich, L.; Law, B.

    1993-09-14

    This paper describes our work to produce ``smart`` equipment using a neural network to provide intelligence for process monitoring, adaptive control, metrology, and equipment diagnostics. This novel system will improve both quality and yield for critical thin films used in semiconductors, superconductors, high-density magnetic and optical storage, and advanced displays, all of which are critical to maintaining our leadership in the multibillion-dollar electronic and computer industries. The equipment will have on-line, real-time diagnostics capabilities to detect component problems early in order to minimize maintenance and downtime.

  7. Neural Decoding Reveals Impaired Face Configural Processing in the Right Fusiform Face Area of Individuals with Developmental Prosopagnosia

    PubMed Central

    Zhang, Jiedong; Liu, Jia

    2015-01-01

    Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ∼2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit normal face selectivity in the right fusiform face area (FFA), a key brain region involved in face configural processing. This finding, together with evidence showing impairments downstream from the right FFA in DP individuals, has led some to argue that perhaps the right FFA is largely intact in DP individuals. Using fMRI multivoxel pattern analysis, here we report the discovery of a neural impairment in the right FFA of DP individuals that may play a critical role in mediating their face-processing deficits. In seven individuals with DP, we discovered that, despite the right FFA's preference for faces and it showing decoding for the different face parts, it exhibited impaired face configural decoding and did not contain distinct neural response patterns for the intact and the scrambled face configurations. This abnormality was not present throughout the ventral visual cortex, as normal neural decoding was found in an adjacent object-processing region. To our knowledge, this is the first direct neural evidence showing impaired face configural processing in the right FFA in individuals with DP. The discovery of this neural impairment provides a new clue to our understanding of the neural basis of DP. PMID:25632131

  8. Neural decoding reveals impaired face configural processing in the right fusiform face area of individuals with developmental prosopagnosia.

    PubMed

    Zhang, Jiedong; Liu, Jia; Xu, Yaoda

    2015-01-28

    Most of human daily social interactions rely on the ability to successfully recognize faces. Yet ∼2% of the human population suffers from face blindness without any acquired brain damage [this is also known as developmental prosopagnosia (DP) or congenital prosopagnosia]). Despite the presence of severe behavioral face recognition deficits, surprisingly, a majority of DP individuals exhibit normal face selectivity in the right fusiform face area (FFA), a key brain region involved in face configural processing. This finding, together with evidence showing impairments downstream from the right FFA in DP individuals, has led some to argue that perhaps the right FFA is largely intact in DP individuals. Using fMRI multivoxel pattern analysis, here we report the discovery of a neural impairment in the right FFA of DP individuals that may play a critical role in mediating their face-processing deficits. In seven individuals with DP, we discovered that, despite the right FFA's preference for faces and it showing decoding for the different face parts, it exhibited impaired face configural decoding and did not contain distinct neural response patterns for the intact and the scrambled face configurations. This abnormality was not present throughout the ventral visual cortex, as normal neural decoding was found in an adjacent object-processing region. To our knowledge, this is the first direct neural evidence showing impaired face configural processing in the right FFA in individuals with DP. The discovery of this neural impairment provides a new clue to our understanding of the neural basis of DP.

  9. Neural correlates of anticipation and processing of performance feedback in social anxiety.

    PubMed

    Heitmann, Carina Y; Peterburs, Jutta; Mothes-Lasch, Martin; Hallfarth, Marlit C; Böhme, Stephanie; Miltner, Wolfgang H R; Straube, Thomas

    2014-12-01

    Fear of negative evaluation, such as negative social performance feedback, is the core symptom of social anxiety. The present study investigated the neural correlates of anticipation and perception of social performance feedback in social anxiety. High (HSA) and low (LSA) socially anxious individuals were asked to give a speech on a personally relevant topic and received standardized but appropriate expert performance feedback in a succeeding experimental session in which neural activity was measured during anticipation and presentation of negative and positive performance feedback concerning the speech performance, or a neutral feedback-unrelated control condition. HSA compared to LSA subjects reported greater anxiety during anticipation of negative feedback. Functional magnetic resonance imaging results showed deactivation of medial prefrontal brain areas during anticipation of negative feedback relative to the control and the positive condition, and medial prefrontal and insular hyperactivation during presentation of negative as well as positive feedback in HSA compared to LSA subjects. The results indicate distinct processes underlying feedback processing during anticipation and presentation of feedback in HSA as compared to LSA individuals. In line with the role of the medial prefrontal cortex in self-referential information processing and the insula in interoception, social anxiety seems to be associated with lower self-monitoring during feedback anticipation, and an increased self-focus and interoception during feedback presentation, regardless of feedback valence.

  10. Transcranial direct current stimulation effects on neural processing in post-stroke aphasia.

    PubMed

    Darkow, Robert; Martin, Andrew; Würtz, Anna; Flöel, Agnes; Meinzer, Marcus

    2017-03-01

    Non-invasive transcranial direct current stimulation (tDCS) can enhance recovery after stroke. However, fundamental knowledge about how tDCS impacts neural processing in the lesioned human brain is currently lacking. In the present study, it was investigated how tDCS modulates brain function in patients with post-stroke language impairment (aphasia). In a cross-over, randomized trial, patients named pictures of common objects during functional magnetic resonance imaging (fMRI). Concurrently, excitatory (anodal-) or sham-tDCS (1 mA, 20 min, or 30 s, respectively) was administered to the left primary motor cortex, a montage with demonstrated potential to improve aphasic language. By choosing stimuli that could reliable be named by the patients, the authors aimed to derive a pure measure of stimulation effects that was independent of treatment or performance effects and to assess how tDCS interacts with the patients' residual language network. Univariate fMRI data analysis revealed reduced activity in domain-general regions mediating high-level cognitive control during anodal-tDCS. Independent component functional network analysis demonstrated selectively increased language network activity and an inter-correlated shift from higher to lower frequency bands, indicative of increased within-network communication. Compared with healthy controls, anodal-tDCS resulted in overall "normalization" of brain function in the patients. These results demonstrate for the first time how tDCS modulates neural processing in stroke patients. Such information is crucial to assure that behavioral treatments targeting specific neural circuits overlap with regions that are modulated by tDCS, thereby maximizing stimulation effects during therapy. Hum Brain Mapp 38:1518-1531, 2017. © 2016 Wiley Periodicals, Inc.

  11. The neural processes underlying perceptual decision making in humans: recent progress and future directions.

    PubMed

    Kelly, Simon P; O'Connell, Redmond G

    2015-01-01

    In the last two decades, animal neurophysiology research has made great strides towards explaining how the brain can enable adaptive action in the face of noisy sensory information. In particular, this work has identified neural signals that perform the role of a 'decision variable' which integrates sensory information in favor of a particular outcome up to an action-triggering threshold, consistent with long-standing predictions from mathematical psychology. This has provoked an intensive search for similar neural processes at work in the human brain. In this paper we review the progress that has been made in tracing the dynamics of perceptual decision formation in humans using functional imaging and electrophysiology. We highlight some of the limitations that non-invasive recording techniques place on our ability to make definitive judgments regarding the role that specific signals play in decision making. Finally, we provide an overview of our own work in this area which has focussed on two perceptual tasks - intensity change detection and motion discrimination - performed under continuous-monitoring conditions, and highlight the insights gained thus far. We show that through simple paradigm design features such as avoiding sudden intensity transients at evidence onset, a neural instantiation of the theoretical decision variable can be directly traced in the form of a centro-parietal positivity (CPP) in the standard event-related potential (ERP). We recapitulate evidence for the domain-general nature of the CPP process, being divorced from the sensory and motor requirements of the task, and re-plot data of both tasks highlighting this aspect as well as its relationship to decision outcome and reaction time. We discuss the implications of these findings for mechanistically principled research on normal and abnormal decision making in humans.

  12. Common and dissociable neural correlates associated with component processes of inductive reasoning.

    PubMed

    Jia, Xiuqin; Liang, Peipeng; Lu, Jie; Yang, Yanhui; Zhong, Ning; Li, Kuncheng

    2011-06-15

    The ability to draw numerical inductive reasoning requires two key cognitive processes, identification and extrapolation. This study aimed to identify the neural correlates of both component processes of numerical inductive reasoning using event-related fMRI. Three kinds of tasks: rule induction (RI), rule induction and application (RIA), and perceptual judgment (Jud) were solved by twenty right-handed adults. Our results found that the left superior parietal lobule (SPL) extending into the precuneus and left dorsolateral prefrontal cortex (DLPFC) were commonly recruited in the two components. It was also observed that the fronto-parietal network was more specific to identification, whereas the striatal-thalamic network was more specific to extrapolation. The findings suggest that numerical inductive reasoning is mediated by the coordination of multiple brain areas including the prefrontal, parietal, and subcortical regions, of which some are more specific to demands on only one of these two component processes, whereas others are sensitive to both.

  13. Neural Dynamics of Emotional Salience Processing in Response to Voices during the Stages of Sleep.

    PubMed

    Chen, Chenyi; Sung, Jia-Ying; Cheng, Yawei

    2016-01-01

    Sleep has been related to emotional functioning. However, the extent to which emotional salience is processed during sleep is unknown. To address this concern, we investigated night sleep in healthy adults regarding brain reactivity to the emotionally (happily, fearfully) spoken meaningless syllables dada, along with correspondingly synthesized nonvocal sounds. Electroencephalogram (EEG) signals were continuously acquired during an entire night of sleep while we applied a passive auditory oddball paradigm. During all stages of sleep, mismatch negativity (MMN) in response to emotional syllables, which is an index for emotional salience processing of voices, was detected. In contrast, MMN to acoustically matching nonvocal sounds was undetected during Sleep Stage 2 and 3 as well as rapid eye movement (REM) sleep. Post-MMN positivity (PMP) was identified with larger amplitudes during Stage 3, and at earlier latencies during REM sleep, relative to wakefulness. These findings clearly demonstrated the neural dynamics of emotional salience processing during the stages of sleep.

  14. Neural Dynamics of Emotional Salience Processing in Response to Voices during the Stages of Sleep

    PubMed Central

    Chen, Chenyi; Sung, Jia-Ying; Cheng, Yawei

    2016-01-01

    Sleep has been related to emotional functioning. However, the extent to which emotional salience is processed during sleep is unknown. To address this concern, we investigated night sleep in healthy adults regarding brain reactivity to the emotionally (happily, fearfully) spoken meaningless syllables dada, along with correspondingly synthesized nonvocal sounds. Electroencephalogram (EEG) signals were continuously acquired during an entire night of sleep while we applied a passive auditory oddball paradigm. During all stages of sleep, mismatch negativity (MMN) in response to emotional syllables, which is an index for emotional salience processing of voices, was detected. In contrast, MMN to acoustically matching nonvocal sounds was undetected during Sleep Stage 2 and 3 as well as rapid eye movement (REM) sleep. Post-MMN positivity (PMP) was identified with larger amplitudes during Stage 3, and at earlier latencies during REM sleep, relative to wakefulness. These findings clearly demonstrated the neural dynamics of emotional salience processing during the stages of sleep. PMID:27378870

  15. Neural changes associated with semantic processing in healthy aging despite intact behavioral performance.

    PubMed

    Lacombe, Jacinthe; Jolicoeur, Pierre; Grimault, Stephan; Pineault, Jessica; Joubert, Sven

    2015-10-01

    Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level.

  16. Neural Correlates of Sex/Gender Differences in Humor Processing for Different Joke Types

    PubMed Central

    Chan, Yu-Chen

    2016-01-01

    Humor operates through a variety of techniques, which first generate surprise and then amusement and laughter once the unexpected incongruity is resolved. As different types of jokes use different techniques, the corresponding humor processes also differ. The present study builds on the framework of the ‘tri-component theory of humor,’ which details the mechanisms involved in cognition (comprehension), affect (appreciation), and laughter (expression). This study seeks to identify differences among joke types and between sexes/genders in the neural mechanisms underlying humor processing. Three types of verbal jokes, bridging-inference jokes (BJs), exaggeration jokes (EJs), and ambiguity jokes (AJs), were used as stimuli. The findings revealed differences in brain activity for an interaction between sex/gender and joke type. For BJs, women displayed greater activation in the temporoparietal–mesocortical-motor network than men, demonstrating the importance of the temporoparietal junction (TPJ) presumably for ‘theory of mind’ processing, the orbitofrontal cortex for motivational functions and reward coding, and the supplementary motor area for laughter. Women also showed greater activation than men in the frontal-mesolimbic network associated with EJs, including the anterior (frontopolar) prefrontal cortex (aPFC, BA 10) for executive control processes, and the amygdala and midbrain for reward anticipation and salience processes. Conversely, AJs elicited greater activation in men than women in the frontal-paralimbic network, including the dorsal prefrontal cortex (dPFC) and parahippocampal gyrus. All joke types elicited greater activation in the aPFC of women than of men, whereas men showed greater activation than women in the dPFC. To confirm the findings related to sex/gender differences, random group analysis and within group variance analysis were also performed. These findings help further establish the mechanisms underlying the processing of different

  17. Neural Correlates of Sex/Gender Differences in Humor Processing for Different Joke Types.

    PubMed

    Chan, Yu-Chen

    2016-01-01

    Humor operates through a variety of techniques, which first generate surprise and then amusement and laughter once the unexpected incongruity is resolved. As different types of jokes use different techniques, the corresponding humor processes also differ. The present study builds on the framework of the 'tri-component theory of humor,' which details the mechanisms involved in cognition (comprehension), affect (appreciation), and laughter (expression). This study seeks to identify differences among joke types and between sexes/genders in the neural mechanisms underlying humor processing. Three types of verbal jokes, bridging-inference jokes (BJs), exaggeration jokes (EJs), and ambiguity jokes (AJs), were used as stimuli. The findings revealed differences in brain activity for an interaction between sex/gender and joke type. For BJs, women displayed greater activation in the temporoparietal-mesocortical-motor network than men, demonstrating the importance of the temporoparietal junction (TPJ) presumably for 'theory of mind' processing, the orbitofrontal cortex for motivational functions and reward coding, and the supplementary motor area for laughter. Women also showed greater activation than men in the frontal-mesolimbic network associated with EJs, including the anterior (frontopolar) prefrontal cortex (aPFC, BA 10) for executive control processes, and the amygdala and midbrain for reward anticipation and salience processes. Conversely, AJs elicited greater activation in men than women in the frontal-paralimbic network, including the dorsal prefrontal cortex (dPFC) and parahippocampal gyrus. All joke types elicited greater activation in the aPFC of women than of men, whereas men showed greater activation than women in the dPFC. To confirm the findings related to sex/gender differences, random group analysis and within group variance analysis were also performed. These findings help further establish the mechanisms underlying the processing of different joke types

  18. Using historical data for bioprocess optimization: modeling wine characteristics using artificial neural networks and archived process information.

    PubMed

    Vlassides, S; Ferrier, J G; Block, D E

    2001-04-05

    Optimization of fermentation processes is a difficult task that relies on an understanding of the complex effects of processing inputs on productivity and quality outputs. Because of the complexity of these biological systems, traditional optimization methods utilizing mathematical models and statistically designed experiments are less effective, especially on a production scale. At the same time, information is being collected on a regular basis during the course of normal manufacturing and process development that is rarely fully utilized. We are developing an optimization method in which historical process data is used to train an artificial neural network for correlation of processing inputs and outputs. Subsequently, an optimization routine is used in conjunction with the trained neural network to find optimal processing conditions given the desired product characteristics and any constraints on inputs. Wine processing is being used as a case study for this work. Using data from wine produced in our pilot winery over the past 3 years, we have demonstrated that trained neural networks can be used successfully to predict the yeast-fermentation kinetics, as well as chemical and sensory properties of the finished wine, based solely on the properties of the grapes and the intended processing. To accomplish this, a hybrid neural network training method, Stop Training with Validation (STV), has been developed to find the most desirable neural network architecture and training level. As industrial historical data will not be evenly spaced over the entire possible search space, we have also investigated the ability of the trained neural networks to interpolate and extrapolate with data not used during training. Because a company will utilize its own existing process data for this method, the result of this work will be a general fermentation optimization method that can be applied to fermentation processes to improve quality and productivity.

  19. From image processing to computational neuroscience: a neural model based on histogram equalization

    PubMed Central

    Bertalmío, Marcelo

    2014-01-01

    There are many ways in which the human visual system works to reduce the inherent redundancy of the visual information in natural scenes, coding it in an efficient way. The non-linear response curves of photoreceptors and the spatial organization of the receptive fields of visual neurons both work toward this goal of efficient coding. A related, very important aspect is that of the existence of post-retinal mechanisms for contrast enhancement that compensate for the blurring produced in early stages of the visual process. And alongside mechanisms for coding and wiring efficiency, there is neural activity in the human visual cortex that correlates with the perceptual phenomenon of lightness induction. In this paper we propose a neural model that is derived from an image processing technique for histogram equalization, and that is able to deal with all the aspects just mentioned: this new model is able to predict lightness induction phenomena, and improves the efficiency of the representation by flattening both the histogram and the power spectrum of the image signal. PMID:25100983

  20. Altered Neural Processing to Social Exclusion in Young Adult Marijuana Users

    PubMed Central

    Gilman, Jodi M.; Curran, Max T.; Calderon, Vanessa; Schuster, Randi M.; Evins, A. Eden

    2015-01-01

    Previous studies have reported that peer groups are one of the most important predictors of adolescent and young adult marijuana use, and yet the neural correlates of social processing in marijuana users have not yet been studied. In the current study, marijuana-using young adults (n = 20) and non-using controls (n = 22) participated in a neuroimaging social exclusion task called Cyberball, a computerized ball-tossing game in which the participant is excluded from the game after a pre-determined number of ball tosses. Controls, but not marijuana users, demonstrated significant activation in the insula, a region associated with negative emotion, when being excluded from the game. Both groups demonstrated activation of the ventral anterior cingulate cortex (vACC), a region associated with affective monitoring, during peer exclusion. Only the marijuana group showed a correlation between vACC activation and scores on a self-report measure of peer conformity. This study indicates that marijuana users show atypical neural processing of social exclusion, which may be either caused by, or the result of, regular marijuana use. PMID:26977454

  1. Neural-network-based image processing of human corneal endothelial micrograms

    NASA Astrophysics Data System (ADS)

    Hasegawa, Akira; Zhang, Wei; Itoh, Kazuyoshi; Ichioka, Yoshiki

    1991-11-01

    This report presents an application of a learning network to the detection of cell membranes in human corneal endothelial micrograms. Our neural network model is a multilayered feed- forward network, and units in any single layer are divided into clusters. Every unit in the higher layer is connected with some of the units in each cluster of the lower layer. Units in the same layer have the same size of receptive field. In order to perform space-invariant processing in the same cluster, units in the same cluster have the same pattern of connectivity, but units in the different clusters have a different one. Such a network has been shown to be robust against distortions of input patterns and to match well with optical implementations. The neural network is trained by small parts of a microgram to extract the boundaries of the endothelial cells using the supervised learning algorithm. Desired output images are their cell membrane images that are traced by hand. After training, the network showed good performance with the whole microgram, which contained non-experienced parts. The final membrane image was obtained with the help of additional processing by a conventional digital filter based on mathematical morphology and linear filtering. The approach for shortcut learning and the internal representations of the network are studied.

  2. Altered neural basis of the reality processing and its relation to cognitive insight in schizophrenia.

    PubMed

    Lee, Jung Suk; Chun, Ji Won; Lee, Sang-Hoon; Kim, Eosu; Lee, Seung-Koo; Kim, Jae-Jin

    2015-01-01

    It has been reported that reality evaluation and recognition are impaired in patients with schizophrenia and these impairments are related to the severity of psychotic symptoms. The current study aimed to investigate the neural basis of impairments in reality evaluation and recognition and their relationships with cognitive insight in schizophrenia. During functional magnetic resonance imaging, 20 patients with schizophrenia and 20 healthy controls performed a set of reality evaluation and recognition tasks, in which subjects judged whether scenes in a series of drawings were real or unreal and whether they were familiar or novel. During reality evaluation, patients showed decreased activity in various regions including the inferior parietal lobule, retrosplenial cortex and parahippocampal gyrus, compared with controls. Particularly, parahippocampal gyrus activity was correlated with the severity of positive symptoms in patients. During recognition, patients also exhibited decreased activity in various regions, including the dorsolateral prefrontal cortex, inferior parietal lobule and posterior cingulate cortex. Particularly, inferior parietal lobule activity and posterior cingulate cortex activity were correlated with cognitive insight in patients. These findings provide evidence that neural impairments in reality evaluation and recognition are related to psychotic symptoms. Anomalous appraisal of context by dysfunctions in the context network may contribute to impairments in the reality processing in schizophrenia, and abnormal declarative memory processes may be involved in cognitive insight in patients with schizophrenia.

  3. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    NASA Astrophysics Data System (ADS)

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model.

  4. Bottom-up and top-down processes in emotion generation: common and distinct neural mechanisms.

    PubMed

    Ochsner, Kevin N; Ray, Rebecca R; Hughes, Brent; McRae, Kateri; Cooper, Jeffrey C; Weber, Jochen; Gabrieli, John D E; Gross, James J

    2009-11-01

    Emotions are generally thought to arise through the interaction of bottom-up and top-down processes. However, prior work has not delineated their relative contributions. In a sample of 20 females, we used functional magnetic resonance imaging to compare the neural correlates of negative emotions generated by the bottom-up perception of aversive images and by the top-down interpretation of neutral images as aversive. We found that (a) both types of responses activated the amygdala, although bottom-up responses did so more strongly; (b) bottom-up responses activated systems for attending to and encoding perceptual and affective stimulus properties, whereas top-down responses activated prefrontal regions that represent high-level cognitive interpretations; and (c) self-reported affect correlated with activity in the amygdala during bottom-up responding and with activity in the medial prefrontal cortex during top-down responding. These findings provide a neural foundation for emotion theories that posit multiple kinds of appraisal processes and help to clarify mechanisms underlying clinically relevant forms of emotion dysregulation.

  5. Textural identification of carbonate rocks by image processing and neural network: Methodology proposal and examples

    NASA Astrophysics Data System (ADS)

    Marmo, Roberto; Amodio, Sabrina; Tagliaferri, Roberto; Ferreri, Vittoria; Longo, Giuseppe

    2005-06-01

    Using more than 1000 thin section photos of ancient (Phanerozoic) carbonates from different marine environments (pelagic to shallow-water) a new numerical methodology, based on digitized images of thin sections, is proposed here. In accordance with the Dunham classification, it allows the user to automatically identify carbonate textures unaffected by post-depositional modifications (recrystallization, dolomitization, meteoric dissolution and so on). The methodology uses, as input, 256 grey-tone digital image and by image processing gives, as output, a set of 23 values of numerical features measured on the whole image including the "white areas" (calcite cement). A multi-layer perceptron neural network takes as input this features and gives, as output, the estimated class. We used 532 images of thin sections to train the neural network, whereas to test the methodology we used 268 images taken from the same photo collection and 215 images from San Lorenzello carbonate sequence (Matese Mountains, southern Italy), Early Cretaceous in age. This technique has shown 93.3% and 93.5% of accuracy to classify automatically textures of carbonate rocks using digitized images on the 268 and 215 test sets, respectively. Therefore, the proposed methodology is a further promising application to the geosciences allowing carbonate textures of many thin sections to be identified in a rapid and accurate way. A MATLAB-based computer code has been developed for the processing and display of images.

  6. Linear-phase delay filters for ultra-low-power signal processing in neural recording implants.

    PubMed

    Gosselin, Benoit; Sawan, Mohamad; Kerherve, Eric

    2010-06-01

    We present the design and implementation of linear-phase delay filters for ultra-low-power signal processing in neural recording implants. We use these filters as low-distortion delay elements along with an automatic biopotential detector to perform integral waveform extraction and efficient power management. The presented delay elements are realized employing continuous-time OTA-C filters featuring 9th-order equiripple transfer functions with constant group delay. Such analog delay enables processing neural waveforms with reduced overhead compared to a digital delay since it does not requires sampling and digitization. It uses an allpass transfer function for achieving wider constant-delay bandwidth than all-pole does. Two filters realizations are compared for implementing the delay element: the Cascaded structure and the Inverse follow-the-leader feedback filter. Their respective strengths and drawbacks are assessed by modeling parasitics and non-idealities of OTAs, and by transistor-level simulations. A budget of 200 nA is used in both filters. Experimental measurements with the chosen filter topology are presented and discussed.

  7. A New Efficient Hybrid Intelligent Model for Biodegradation Process of DMP with Fuzzy Wavelet Neural Networks

    PubMed Central

    Huang, Mingzhi; Zhang, Tao; Ruan, Jujun; Chen, Xiaohong

    2017-01-01

    A new efficient hybrid intelligent approach based on fuzzy wavelet neural network (FWNN) was proposed for effectively modeling and simulating biodegradation process of Dimethyl phthalate (DMP) in an anaerobic/anoxic/oxic (AAO) wastewater treatment process. With the self learning and memory abilities of neural networks (NN), handling uncertainty capacity of fuzzy logic (FL), analyzing local details superiority of wavelet transform (WT) and global search of genetic algorithm (GA), the proposed hybrid intelligent model can extract the dynamic behavior and complex interrelationships from various water quality variables. For finding the optimal values for parameters of the proposed FWNN, a hybrid learning algorithm integrating an improved genetic optimization and gradient descent algorithm is employed. The results show, compared with NN model (optimized by GA) and kinetic model, the proposed FWNN model have the quicker convergence speed, the higher prediction performance, and smaller RMSE (0.080), MSE (0.0064), MAPE (1.8158) and higher R2 (0.9851) values. which illustrates FWNN model simulates effluent DMP more accurately than the mechanism model. PMID:28120889

  8. Second language processing shows increased native-like neural responses after months of no exposure.

    PubMed

    Morgan-Short, Kara; Finger, Ingrid; Grey, Sarah; Ullman, Michael T

    2012-01-01

    Although learning a second language (L2) as an adult is notoriously difficult, research has shown that adults can indeed attain native language-like brain processing and high proficiency levels. However, it is important to then retain what has been attained, even in the absence of continued exposure to the L2--particularly since periods of minimal or no L2 exposure are common. This event-related potential (ERP) study of an artificial language tested performance and neural processing following a substantial period of no exposure. Adults learned to speak and comprehend the artificial language to high proficiency with either explicit, classroom-like, or implicit, immersion-like training, and then underwent several months of no exposure to the language. Surprisingly, proficiency did not decrease during this delay. Instead, it remained unchanged, and there was an increase in native-like neural processing of syntax, as evidenced by several ERP changes--including earlier, more reliable, and more left-lateralized anterior negativities, and more robust P600s, in response to word-order violations. Moreover, both the explicitly and implicitly trained groups showed increased native-like ERP patterns over the delay, indicating that such changes can hold independently of L2 training type. The results demonstrate that substantial periods with no L2 exposure are not necessarily detrimental. Rather, benefits may ensue from such periods of time even when there is no L2 exposure. Interestingly, both before and after the delay the implicitly trained group showed more native-like processing than the explicitly trained group, indicating that type of training also affects the attainment of native-like processing in the brain. Overall, the findings may be largely explained by a combination of forgetting and consolidation in declarative and procedural memory, on which L2 grammar learning appears to depend. The study has a range of implications, and suggests a research program with

  9. Gene-environment interaction on neural mechanisms of orthographic processing in Chinese children

    PubMed Central

    Su, Mengmeng; Wang, Jiuju; Maurer, Urs; Zhang, Yuping; Li, Jun; McBride-Chang, Catherine; Tardif, Twila; Liu, Youyi; Shu, Hua

    2015-01-01

    The ability to process and identify visual words requires efficient orthographic processing of print, consisting of letters in alphabetic languages or characters in Chinese. The N170 is a robust neural marker for orthographic processes. Both genetic and environmental factors, such as home literacy, have been shown to influence orthographic processing at the behavioral level, but their relative contributions and interactions are not well understood. The present study aimed to reveal possible gene-by-environment interactions on orthographic processing at the behavioral and neural level in a normal children sample. Sixty 12 year old Chinese children from a 10-year longitudinal sample underwent an implicit visual-word color decision task on real words and stroke combinations. The ERP analysis focused on the increase of the occipito-temporal N170 to words compared to stroke combinations. The genetic analysis focused on two SNPs (rs1419228, rs1091047) in the gene DCDC2 based on previous findings linking these 2 SNPs to orthographic coding. Home literacy was measured previously as the number of children's books at home, when the children were at the age of 3. Relative to stroke combinations, real words evoked greater N170 in bilateral posterior brain regions. A significant interaction between rs1091047 and home literacy was observed on the changes of N170 comparing real words to stroke combinations in the left hemisphere. Particularly, children carrying the major allele “G” showed a similar N170 effect irrespective of their environment, while children carrying the minor allele “C” showed a smaller N170 effect in low home-literacy environment than those in good environment. PMID:26294811

  10. Using artificial neural networks to model extrusion processes for the manufacturing of polymeric micro-tubes

    NASA Astrophysics Data System (ADS)

    Mekras, N.; Artemakis, I.

    2012-09-01

    In this paper a methodology and an application example are presented aiming to show how Artificial Neural Networks (ANNs) can be used to model manufacturing processes when mathematical models are missing or are not applicable e.g. due to the micro- & nano-scaling, due to non-conventional processes, etc. Besides the ANNs methodology, the results of a Software System developed will be presented, which was used to create ANNs models for micro & nano manufacturing processes. More specifically results of a specific application example will be presented, concerning the modeling of extrusion processes for polymeric micro-tubes. ANNs models are capable for modeling manufacturing processes as far as adequate experimental and/or historical data of processes' inputs & outputs are available for their training. The POLYTUBES ANNs models have been trained and tested with experimental data records of process' inputs and outputs concerning a micro-extrusion process of polymeric micro-tubes for several materials such as: COC, PC, PET, PETG, PP and PVDF. The main ANN model of the extrusion application example has 3 inputs and 9 outputs. The inputs are: tube's inner & outer diameters, and the material density. The model outputs are 9 process parameters, which correspond to the specific inputs e.g. process temperature, die inner & outer diameters, extrusion pressure, draw speed etc. The training of the ANN model was completed, when the errors for the model's outputs, which expressed the difference between the training target values and the ANNs outputs, were minimized to acceptable levels. After the training, the micro-extrusion ANN is capable to simulate the process and can be used to calculate model's outputs, which are the process parameters for any new set of inputs. By this way a satisfactory functional approximation of the whole process is achieved. This research work has been supported by the EU FP7 NMP project POLYTUBES.

  11. Risky Decisions and Their Consequences: Neural Processing by Boys with Antisocial Substance Disorder

    PubMed Central

    Crowley, Thomas J.; Dalwani, Manish S.; Mikulich-Gilbertson, Susan K.; Du, Yiping P.; Lejuez, Carl W.; Raymond, Kristen M.; Banich, Marie T.

    2010-01-01

    Background Adolescents with conduct and substance problems (“Antisocial Substance Disorder” (ASD)) repeatedly engage in risky antisocial and drug-using behaviors. We hypothesized that, during processing of risky decisions and resulting rewards and punishments, brain activation would differ between abstinent ASD boys and comparison boys. Methodology/Principal Findings We compared 20 abstinent adolescent male patients in treatment for ASD with 20 community controls, examining rapid event-related blood-oxygen-level-dependent (BOLD) responses during functional magnetic resonance imaging. In 90 decision trials participants chose to make either a cautious response that earned one cent, or a risky response that would either gain 5 cents or lose 10 cents; odds of losing increased as the game progressed. We also examined those times when subjects experienced wins, or separately losses, from their risky choices. We contrasted decision trials against very similar comparison trials requiring no decisions, using whole-brain BOLD-response analyses of group differences, corrected for multiple comparisons. During decision-making ASD boys showed hypoactivation in numerous brain regions robustly activated by controls, including orbitofrontal and dorsolateral prefrontal cortices, anterior cingulate, basal ganglia, insula, amygdala, hippocampus, and cerebellum. While experiencing wins, ASD boys had significantly less activity than controls in anterior cingulate, temporal regions, and cerebellum, with more activity nowhere. During losses ASD boys had significantly more activity than controls in orbitofrontal cortex, dorsolateral prefrontal cortex, brain stem, and cerebellum, with less activity nowhere. Conclusions/Significance Adolescent boys with ASD had extensive neural hypoactivity during risky decision-making, coupled with decreased activity during reward and increased activity during loss. These neural patterns may underlie the dangerous, excessive, sustained risk-taking of

  12. Decision Making Under Uncertainty: A Neural Model Based on Partially Observable Markov Decision Processes

    PubMed Central

    Rao, Rajesh P. N.

    2010-01-01

    A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs). Actions are selected based not on a single “optimal” estimate of state but on the posterior distribution over states (the “belief” state). We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD) learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

  13. Motor learning and cross-limb transfer rely upon distinct neural adaptation processes.

    PubMed

    Stöckel, Tino; Carroll, Timothy J; Summers, Jeffery J; Hinder, Mark R

    2016-08-01

    Performance benefits conferred in the untrained limb after unilateral motor practice are termed cross-limb transfer. Although the effect is robust, the neural mechanisms remain incompletely understood. In this study we used noninvasive brain stimulation to reveal that the neural adaptations that mediate motor learning in the trained limb are distinct from those that underlie cross-limb transfer to the opposite limb. Thirty-six participants practiced a ballistic motor task with their right index finger (150 trials), followed by intermittent theta-burst stimulation (iTBS) applied to the trained (contralateral) primary motor cortex (cM1 group), the untrained (ipsilateral) M1 (iM1 group), or the vertex (sham group). After stimulation, another 150 training trials were undertaken. Motor performance and corticospinal excitability were assessed before motor training, pre- and post-iTBS, and after the second training bout. For all groups, training significantly increased performance and excitability of the trained hand, and performance, but not excitability, of the untrained hand, indicating transfer at the level of task performance. The typical facilitatory effect of iTBS on MEPs was reversed for cM1, suggesting homeostatic metaplasticity, and prior performance gains in the trained hand were degraded, suggesting that iTBS interfered with learning. In stark contrast, iM1 iTBS facilitated both performance and excitability for the untrained hand. Importantly, the effects of cM1 and iM1 iTBS on behavior were exclusive to the hand contralateral to stimulation, suggesting that adaptations within the untrained M1 contribute to cross-limb transfer. However, the neural processes that mediate learning in the trained hemisphere vs. transfer in the untrained hemisphere appear distinct.

  14. Holographic image processing, coherent optical computing, and neural computer architecture for pattern recognition

    NASA Astrophysics Data System (ADS)

    Schempp, Walter

    Metaplectic harmonic analysis is well matched with high resolution image processing. The metaplectic representation of the symplectic group and its twofold cover arises when the symplectic group is considered as a group of outer automorphisms of the irreducible linear representations of the Heisenberg two-step nilpotent Lie group. Starting with the Paley-Wiener theorem which forms the classical result for information-preserving sequential bandwidth compression, and its Stone-von Neumann-Segal analogue for the Heisenberg group which is at the basis of holographic reciprocity and coupling, the paper points out a unified metaplectic approach to signal geometry such as holographic image processing, coherent optical computing, and neural computer architecture for pattern recognition. Brief descriptions of hardware implementations are also included.

  15. Subcellular Imaging of Voltage and Calcium Signals Reveals Neural Processing In Vivo.

    PubMed

    Yang, Helen H; St-Pierre, François; Sun, Xulu; Ding, Xiaozhe; Lin, Michael Z; Clandinin, Thomas R

    2016-06-30

    A mechanistic understanding of neural computation requires determining how information is processed as it passes through neurons and across synapses. However, it has been challenging to measure membrane potential changes in axons and dendrites in vivo. We use in vivo, two-photon imaging of novel genetically encoded voltage indicators, as well as calcium imaging, to measure sensory stimulus-evoked signals in the Drosophila visual system with subcellular resolution. Across synapses, we find major transformations in the kinetics, amplitude, and sign of voltage responses to light. We also describe distinct relationships between voltage and calcium signals in different neuronal compartments, a substrate for local computation. Finally, we demonstrate that ON and OFF selectivity, a key feature of visual processing across species, emerges through the transformation of membrane potential into intracellular calcium concentration. By imaging voltage and calcium signals to map information flow with subcellular resolution, we illuminate where and how critical computations arise.

  16. Roles of neural precursor cell expressed, developmentally downregulated 9 in tumor-associated cellular processes (Review).

    PubMed

    Zhang, Sisen; Wu, Lihua

    2015-11-01

    Neural precursor cell expressed, developmentally downregulated 9 (NEDD9), a gene exclusively expressed in the brain during embryonic stages but not in brains of adult mice, is an important cytoskeletal protein and regarded as a 'router/hub' in cellular signal transduction processes connecting external stimulation signals with downstream target proteins that can directly promote tumor metastasis. Numerous studies showed that NEDD9 has an essential role in cell proliferation, apoptosis, adhesion, migration and invasion. The roles of NEDD9, including the underlying mechanisms of its regulation of cell migration, its distinctive functions in various tumor stages and its association with other diseases, are required to be elucidated at large. Future studies of NEDD9 may provide a more profound understanding of the development of tumor invasiveness and NEDD9 may serve as a potential novel target for tumor therapy. The present review examined the significant roles of NEDD9 in the abovementioned processes.

  17. A probablistic neural network classification system for signal and image processing

    SciTech Connect

    Bowman, B.

    1994-11-15

    The Acoustical Heart Valve Analysis Package is a system for signal and image processing and classification. It is being developed in both Matlab and C, to provide an interactive, interpreted environment, and has been optimized for large scale matrix operations. It has been used successfully to classify acoustic signals from implanted prosthetic heart valves in human patients, and will be integrated into a commercial Heart Valve Screening Center. The system uses several standard signal processing algorithms, as well as supervised learning techniques using the probabilistic neural network (PNN). Although currently used for the acoustic heart valve application, the algorithms and modular design allow it to be used for other applications, as well. We will describe the signal classification system, and show results from a set of test valves.

  18. Dynamical Behavior of Delayed Reaction-Diffusion Hopfield Neural Networks Driven by Infinite Dimensional Wiener Processes.

    PubMed

    Liang, Xiao; Wang, Linshan; Wang, Yangfan; Wang, Ruili

    2016-09-01

    In this paper, we focus on the long time behavior of the mild solution to delayed reaction-diffusion Hopfield neural networks (DRDHNNs) driven by infinite dimensional Wiener processes. We analyze the existence, uniqueness, and stability of this system under the local Lipschitz function by constructing an appropriate Lyapunov-Krasovskii function and utilizing the semigroup theory. Some easy-to-test criteria affecting the well-posedness and stability of the networks, such as infinite dimensional noise and diffusion effect, are obtained. The criteria can be used as theoretic guidance to stabilize DRDHNNs in practical applications when infinite dimensional noise is taken into consideration. Meanwhile, considering the fact that the standard Brownian motion is a special case of infinite dimensional Wiener process, we undertake an analysis of the local Lipschitz condition, which has a wider range than the global Lipschitz condition. Two samples are given to examine the availability of the results in this paper. Simulations are also given using the MATLAB.

  19. Representation and Processing of Acoustic Information in a Biomimetic Neural Network

    DTIC Science & Technology

    1992-01-01

    The effectiveness of artificial neural network models depends strongly on the way in which the information to be learned is presented to the network...We developed a model of the dolphin cochlea and used this model to produce the representations used by a neural network to model the delayed...from the dolphin.... Artificial neural networks (AN-N), Echolocation Gateway- integrator neural network (GIN)

  20. Neural responses to ambiguity involve domain-general and domain-specific emotion processing systems.

    PubMed

    Neta, Maital; Kelley, William M; Whalen, Paul J

    2013-04-01

    Extant research has examined the process of decision making under uncertainty, specifically in situations of ambiguity. However, much of this work has been conducted in the context of semantic and low-level visual processing. An open question is whether ambiguity in social signals (e.g., emotional facial expressions) is processed similarly or whether a unique set of processors come on-line to resolve ambiguity in a social context. Our work has examined ambiguity using surprised facial expressions, as they have predicted both positive and negative outcomes in the past. Specifically, whereas some people tended to interpret surprise as negatively valenced, others tended toward a more positive interpretation. Here, we examined neural responses to social ambiguity using faces (surprise) and nonface emotional scenes (International Affective Picture System). Moreover, we examined whether these effects are specific to ambiguity resolution (i.e., judgments about the ambiguity) or whether similar effects would be demonstrated for incidental judgments (e.g., nonvalence judgments about ambiguously valenced stimuli). We found that a distinct task control (i.e., cingulo-opercular) network was more active when resolving ambiguity. We also found that activity in the ventral amygdala was greater to faces and scenes that were rated explicitly along the dimension of valence, consistent with findings that the ventral amygdala tracks valence. Taken together, there is a complex neural architecture that supports decision making in the presence of ambiguity: (a) a core set of cortical structures engaged for explicit ambiguity processing across stimulus boundaries and (b) other dedicated circuits for biologically relevant learning situations involving faces.

  1. Early neural disruption and auditory processing outcomes in rodent models: implications for developmental language disability.

    PubMed

    Fitch, R Holy; Alexander, Michelle L; Threlkeld, Steven W

    2013-10-21

    Most researchers in the field of neural plasticity are familiar with the "Kennard Principle," which purports a positive relationship between age at brain injury and severity of subsequent deficits (plateauing in adulthood). As an example, a child with left hemispherectomy can recover seemingly normal language, while an adult with focal injury to sub-regions of left temporal and/or frontal cortex can suffer dramatic and permanent language loss. Here we present data regarding the impact of early brain injury in rat models as a function of type and timing, measuring long-term behavioral outcomes via auditory discrimination tasks varying in temporal demand. These tasks were created to model (in rodents) aspects of human sensory processing that may correlate-both developmentally and functionally-with typical and atypical language. We found that bilateral focal lesions to the cortical plate in rats during active neuronal migration led to worse auditory outcomes than comparable lesions induced after cortical migration was complete. Conversely, unilateral hypoxic-ischemic (HI) injuries (similar to those seen in premature infants and term infants with birth complications) led to permanent auditory processing deficits when induced at a neurodevelopmental point comparable to human "term," but only transient deficits (undetectable in adulthood) when induced in a "preterm" window. Convergent evidence suggests that regardless of when or how disruption of early neural development occurs, the consequences may be particularly deleterious to rapid auditory processing (RAP) outcomes when they trigger developmental alterations that extend into subcortical structures (i.e., lower sensory processing stations). Collective findings hold implications for the study of behavioral outcomes following early brain injury as well as genetic/environmental disruption, and are relevant to our understanding of the neurologic risk factors underlying developmental language disability in human

  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. Two distinct neural mechanisms in early visual cortex determine subsequent visual processing.

    PubMed

    Jacobs, Christianne; de Graaf, Tom A; Sack, Alexander T

    2014-10-01

    Neuroscience research has conventionally focused on how the brain processes sensory information, after the information has been received. Recently, increased interest focuses on how the state of the brain upon receiving inputs determines and biases their subsequent processing and interpretation. Here, we investigated such 'pre-stimulus' brain mechanisms and their relevance for objective and subjective visual processing. Using non-invasive focal brain stimulation [transcranial magnetic stimulation (TMS)] we disrupted spontaneous brain state activity within early visual cortex (EVC) before onset of visual stimulation, at two different pre-stimulus-onset-asynchronies (pSOAs). We found that TMS pulses applied to EVC at either 20 msec or 50 msec before onset of a simple orientation stimulus both prevented this stimulus from reaching visual awareness. Interestingly, only the TMS-induced visual suppression following TMS at a pSOA of ?20 msec was retinotopically specific, while TMS at a pSOA of ?50 msec was not. In a second experiment, we used more complex symbolic arrow stimuli, and found TMS-induced suppression only when disrupting EVC at a pSOA of ? ?60 msec, which, in line with Experiment 1, was not retinotopically specific. Despite this topographic unspecificity of the ?50 msec effect, the additional control measurements as well as tracking and removal of eye blinks, suggested that also this effect was not the result of an unspecific artifact, and thus neural in origin. We therefore obtained evidence of two distinct neural mechanisms taking place in EVC, both determining whether or not subsequent visual inputs are successfully processed by the human visual system.

  4. Parallel processing in an identified neural circuit: the Aplysia californica gill-withdrawal response model system.

    PubMed

    Leonard, Janet L; Edstrom, John P

    2004-02-01

    /or 'Back-propagation' type. Such models may offer a more biologically realistic representation of nervous system organisation than has been thought. In this model, the six parallel GMNs of the CNS correspond to a hidden layer within one module of the gill-control system. That is, the gill-control system appears to be organised as a distributed system with several parallel modules, some of which are neural networks in their own right. A new model is presented here which predicts that the six GMNs serve as components of a 'push-pull' gain control system, along with known but largely unidentified inhibitory motor neurons from the PVG. This 'push-pull' gain control system sets the responsiveness of the peripheral gill motor system. Neither causal nor correlational links between specific forms of neural plasticity and behavioural plasticity have been demonstrated in the GWR model system. However, the GWR model system does provide an opportunity to observe and describe directly the physiological and biochemical mechanisms of distributed representation and parallel processing in a largely identifiable 'wetware' neural network.

  5. Intermodal auditory, visual, and tactile attention modulates early stages of neural processing

    PubMed Central

    Karns, Christina M.; Knight, Robert T.

    2011-01-01

    We used event-related potentials (ERPs) and gamma band oscillatory responses (GBRs) to examine whether intermodal attention operates early in the auditory, visual, and tactile modalities. To control for the effects of spatial attention, we spatially coregistered all stimuli and varied the attended modality across counterbalanced blocks in an intermodal selection task. In each block participants selectively responded to either auditory, visual, or vibrotactile stimuli from the stream of intermodal events. Auditory and visual ERPs were modulated at the latencies of early cortical processing, but attention manifested later for tactile ERPs. For ERPs, auditory processing was modulated at the latency of the Na (29 ms) which indexes early cortical or thalamocortical processing and the subsequent P1 (90 ms) ERP components. Visual processing was modulated at the latency of the early phase of the C1 (62-72 ms) thought to be generated in primary visual cortex and the subsequent P1 and N1 (176 ms). Tactile processing was modulated at the latency of the N160 (165 ms) likely generated in secondary association cortex. Intermodal attention enhanced early sensory GBRs for all three modalities: auditory (onset 57 ms), visual (onset 47 ms) and tactile (onset 27 ms). Together, these results suggest that intermodal attention enhances neural processing relatively early in the sensory stream independent from differential effects of spatial and intramodal selective attention. PMID:18564047

  6. Neural processing of facial expressions of emotion in first onset psychosis.

    PubMed

    Brennan, Annie M; Harris, Anthony W F; Williams, Leanne M

    2014-11-30

    Schizophrenia is characterized by deficits in face and facial emotion processing. This is the first study using event-related potentials (ERPs) to investigate the corresponding neural activation in first onset psychosis. ERPs for 108 first onset psychosis participants and 108 matched healthy controls were recorded while they viewed facial expressions. Group differences on general (neutral) face processing and emotional valence were examined under both unmasked (conscious) and backward-masked (nonconscious implicit) conditions over frontal and temporo-occipital regions. Clinical significance was assessed by comparing diagnoses and correlating ERPs with symptoms. During general face processing, patients showed reduced activation within 70 ms and exaggerated later processing from 160 ms over the frontal region, with a negative shift in voltage over left temporal and occipital regions across the time course. In addition, from 70 ms onwards, patients showed a positive shift in voltage for disgust whereas controls showed a negative shift in voltage for fear and anger (both compared to happy) over temporo-occipital regions. Effects were related to disorganization and depression symptoms and (preliminarily) were apparent across psychotic diagnoses. These results suggest that first onset psychosis is characterized by general as well as emotion-specific face processing impairments from the earliest, automatic processing period.

  7. DNA methylation mediates neural processing after odor learning in the honeybee

    PubMed Central

    Biergans, Stephanie D.; Claudianos, Charles; Reinhard, Judith; Galizia, C. Giovanni

    2017-01-01

    DNA methyltransferases (Dnmts) - epigenetic writers catalyzing the transfer of methyl-groups to cytosine (DNA methylation) – regulate different aspects of memory formation in many animal species. In honeybees, Dnmt activity is required to adjust the specificity of olfactory reward memories and bees’ relearning capability. The physiological relevance of Dnmt-mediated DNA methylation in neural networks, however, remains unknown. Here, we investigated how Dnmt activity impacts neuroplasticity in the bees’ primary olfactory center, the antennal lobe (AL) an equivalent of the vertebrate olfactory bulb. The AL is crucial for odor discrimination, an indispensable process in forming specific odor memories. Using pharmacological inhibition, we demonstrate that Dnmt activity influences neural network properties during memory formation in vivo. We show that Dnmt activity promotes fast odor pattern separation in trained bees. Furthermore, Dnmt activity during memory formation increases both the number of responding glomeruli and the response magnitude to a novel odor. These data suggest that Dnmt activity is necessary for a form of homoeostatic network control which might involve inhibitory interneurons in the AL network. PMID:28240742

  8. Beyond emotions: A meta-analysis of neural response within face processing system in social anxiety

    PubMed Central

    Gentili, Claudio; Cristea, Ioana Alina; Angstadt, Mike; Klumpp, Heide; Tozzi, Leonardo; Phan, K Luan

    2015-01-01

    Patients with social anxiety disorder (SAD) experience anxiety and avoidance in face-to-face interactions. We performed a meta-analysis of functional magnetic resonance imaging (fMRI) studies in SAD to provide a comprehensive understanding of the neural underpinnings of face perception in this disorder. To this purpose, we adopted an innovative approach, asking authors for unpublished data. This is a common procedure for behavioral meta-analyses, which, however has never been used in neuroimaging studies. We searched Pubmed with the key words “Social Anxiety AND faces” and “Social Phobia AND faces.” Then, we selected those fMRI studies for which we were able to obtain data for the comparison between SAD and healthy controls (HC) in a face perception task, either from the published papers or from the authors themselves. In this way, we obtained 23 studies (totaling 449 SAD and 424 HC individuals). We identified significant clusters in which faces evoked a higher response in SAD in bilateral amygdala, globus pallidus, superior temporal sulcus, visual cortex, and prefrontal cortex. We also found a higher activity for HC in the lingual gyrus and in the posterior cingulate. Our findings show that altered neural response to face in SAD is not limited to emotional structures but involves a complex network. These results may have implications for the understanding of SAD pathophysiology, as they suggest that a dysfunctional face perception process may bias patient person-to-person interactions. PMID:26341469

  9. Age associations with neural processing of reward anticipation in adolescents with bipolar disorders

    PubMed Central

    Urošević, Snežana; Luciana, Monica; Jensen, Jonathan B.; Youngstrom, Eric A.; Thomas, Kathleen M.

    2016-01-01

    Reward/behavioral approach system hypersensitivity is implicated in bipolar disorders (BD) and in normative development during adolescence. Pediatric onset of BD is associated with a more severe illness course. However, little is known about neural processing of rewards in adolescents with BD or developmental (i.e., age) associations with activation of these neural systems. The present study aims to address this knowledge gap. The present sample included 21 adolescents with BD and 26 healthy adolescents, ages 13 to 19. Participants completed a functional magnetic resonance imaging (fMRI) protocol using the Monetary Incentive Delay (MID) task. Behavioral performance was similar between groups. Group differences in BOLD activation during target anticipation and feedback anticipation periods of the task were examined using whole-brain analyses, as were group differences in age effects. During both target anticipation and feedback anticipation, adolescents with BD, compared to adolescents without psychopathology, exhibited decreased engagement of frontal regions involved in cognitive control (i.e., dorsolateral prefrontal cortex). Healthy adolescents exhibited age-related decreases, while adolescents with BD exhibited age-related increases, in activity of other cognitive control frontal areas (i.e., right inferior frontal gyrus), suggesting altered development in the BD group. Longitudinal research is needed to examine potentially abnormal development of cognitive control during reward pursuit in adolescent BD and whether early therapeutic interventions can prevent these potential deviations from normative development. PMID:27114896

  10. DNA methylation mediates neural processing after odor learning in the honeybee.

    PubMed

    Biergans, Stephanie D; Claudianos, Charles; Reinhard, Judith; Galizia, C Giovanni

    2017-02-27

    DNA methyltransferases (Dnmts) - epigenetic writers catalyzing the transfer of methyl-groups to cytosine (DNA methylation) - regulate different aspects of memory formation in many animal species. In honeybees, Dnmt activity is required to adjust the specificity of olfactory reward memories and bees' relearning capability. The physiological relevance of Dnmt-mediated DNA methylation in neural networks, however, remains unknown. Here, we investigated how Dnmt activity impacts neuroplasticity in the bees' primary olfactory center, the antennal lobe (AL) an equivalent of the vertebrate olfactory bulb. The AL is crucial for odor discrimination, an indispensable process in forming specific odor memories. Using pharmacological inhibition, we demonstrate that Dnmt activity influences neural network properties during memory formation in vivo. We show that Dnmt activity promotes fast odor pattern separation in trained bees. Furthermore, Dnmt activity during memory formation increases both the number of responding glomeruli and the response magnitude to a novel odor. These data suggest that Dnmt activity is necessary for a form of homoeostatic network control which might involve inhibitory interneurons in the AL network.

  11. Neural Networks

    DTIC Science & Technology

    1990-01-01

    FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT ELEMENT NO. NO. NO. ACCESSION NO 11 TITLE (Include Security Classification) NEURAL NETWORKS 12. PERSONAL...SUB-GROUP Neural Networks Optical Architectures Nonlinear Optics Adaptation 19. ABSTRACT (Continue on reverse if necessary and identify by block number...341i Y C-odes , lo iii/(iv blank) 1. INTRODUCTION Neural networks are a type of distributed processing system [1

  12. Classification of biological and non-biological fluvial particles using image processing and artificial neural network

    NASA Astrophysics Data System (ADS)

    Shrestha, Bim Prasad; Shrestha, Nabin Kumar; Poudel, Laxman

    2009-04-01

    Particles flowing along with water largely affect safe drinking water, irrigation, aquatic life preservation and hydropower generation. This research describes activities that lead to development of fluvial particle characterization that includes detection of biological and non-biological particles and shape characterization using Image Processing and Artificial Neural Network (ANN). Fluvial particles are characterized based on multi spectral images processing using ANN. Images of wavelength of 630nm and 670nm are taken as most distinctive characterizing properties of biological and non-biological particles found in Bagmati River of Nepal. The samples were collected at pre-monsoon, monsoon and post-monsoon seasons. Random samples were selected and multi spectral images are processed using MATLAB 6.5. Thirty matrices were built from each sample. The obtained data of 42 rows and 60columns were taken as input training with an output matrix of 42 rows and 2 columns. Neural Network of Perceptron model was created using a transfer function. The system was first validated and later on tested at 18 different strategic locations of Bagmati River of Kathmandu Valley, Nepal. This network classified biological and non biological particles. Development of new non-destructive technique to characterize biological and non-biological particles from fluvial sample in a real time has a significance breakthrough. This applied research method and outcome is an attractive model for real time monitoring of particles and has many applications that can throw a significant outlet to many researches and for effective utilization of water resources. It opened a new horizon of opportunities for basic and applied research at Kathmandu University in Nepal.

  13. Interaction matters: A perceived social partner alters the neural processing of human speech.

    PubMed

    Rice, Katherine; Redcay, Elizabeth

    2016-04-01

    Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing-thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional "offline" (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes--which contained no reference to people or mental states--believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant's own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction.

  14. Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception: An Event-Related Potential Study

    PubMed Central

    Liu, Tongran; Xiao, Tong; Li, Xiaoyan; Shi, Jiannong

    2015-01-01

    The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two experimental conditions: a happy condition, in which neutral expressions were standard stimuli (p = 0.8) and happy expressions were deviant stimuli (p = 0.2), and a fearful condition, in which neutral expressions were standard stimuli (p = 0.8) and fearful expressions were deviant stimuli (p = 0.2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were analyzed to index the automatic neural processing of facial expressions. For the early vMMN (50–130 ms), the high IQ group showed more negative vMMN amplitudes than the average IQ group in the happy condition. For the late vMMN (320–450 ms), the high IQ group had greater vMMN responses than the average IQ group over frontal and occipito-temporal areas in the fearful condition, and the average IQ group evoked larger vMMN amplitudes than the high IQ group over occipito-temporal areas in the happy condition. The present study elucidated the close relationships between fluid intelligence and pre-attentive change detection on social-emotional information. PMID:26375031

  15. Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception: An Event-Related Potential Study.

    PubMed

    Liu, Tongran; Xiao, Tong; Li, Xiaoyan; Shi, Jiannong

    2015-01-01

    The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two experimental conditions: a happy condition, in which neutral expressions were standard stimuli (p = 0.8) and happy expressions were deviant stimuli (p = 0.2), and a fearful condition, in which neutral expressions were standard stimuli (p = 0.8) and fearful expressions were deviant stimuli (p = 0.2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were analyzed to index the automatic neural processing of facial expressions. For the early vMMN (50-130 ms), the high IQ group showed more negative vMMN amplitudes than the average IQ group in the happy condition. For the late vMMN (320-450 ms), the high IQ group had greater vMMN responses than the average IQ group over frontal and occipito-temporal areas in the fearful condition, and the average IQ group evoked larger vMMN amplitudes than the high IQ group over occipito-temporal areas in the happy condition. The present study elucidated the close relationships between fluid intelligence and pre-attentive change detection on social-emotional information.

  16. Neural correlates of masked and unmasked face emotion processing in youth with severe mood dysregulation

    PubMed Central

    Thomas, Laura A.; Harkins, Elizabeth; Pine, Daniel S.; Leibenluft, Ellen; Brotman, Melissa A.

    2016-01-01

    Reproducibility of results is important in improving the robustness of conclusions drawn from research, particularly in functional magnetic resonance imaging (fMRI). In this study, we aim to replicate a previous study on the neural correlates of face emotion processing above and below awareness level using an independent sample of youth with severe mood dysregulation (SMD) and healthy volunteers (HV). We collected fMRI data in 17 SMD and 20 HV, using an affective priming paradigm with masked (17 ms) and unmasked (187 ms) faces (angry, happy, neutral, blank oval). When processing masked and unmasked angry faces, SMD patients exhibited increased activation in the parahippocampal gyrus (PHG) and superior temporal gyrus relative to HV. When processing masked and unmasked happy faces, SMD patients showed decreased activation in the insula, PHG and thalamus compared with HV. During masked face processing in general across emotions, youth with SMD showed greater ventromedial prefrontal cortex (vmPFC) activation relative to HV. Perturbed activation in emotion processing areas (e.g. insula, PHG, superior temporal gyrus and thalamus) manifests as hyper-sensitivity toward negative emotions and hypo-sensitivity toward positive emotions may be important in the etiology and maintenance of irritability, aggression and depressive symptoms in SMD. vmPFC dysfunction may mediate over-reactivity to face emotions associated with irritability. PMID:26137973

  17. A transfer process to fabricate ultra-compliant neural probes in dissolvable needles

    NASA Astrophysics Data System (ADS)

    Ong, Xiao Chuan; Khilwani, Rakesh; Forssell, Mats; Burak Ozdoganlar, O.; Fedder, Gary K.

    2017-03-01

    A fabrication approach for ultra-miniature ultra-compliant neural probes with parylene-C insulation that are embedded in biodissolvable insertion needles was previously established by the authors. However, that approach required application of a peeling process to release the probe-needle assembly from its handle wafer. The use of thermal annealing in vacuum to improve encapsulation properties of parylene-C results in increased adhesion to the substrate that undermines the peeling process. In this paper, we introduce a transfer process step that eliminates the peeling process and allows the potential use of a wide range of sacrificial release materials. The transfer step increases the versatility of the overall fabrication approach since it allows the integration of insertion needle and sacrificial release materials that otherwise would not have been compatible with the high-temperature annealing. Several sacrificial release materials, including photoresist, polydimethylsiloxane, mounting adhesive, and liquid wax, are investigated and characterized for suitability in the transfer process. Considering compatibility with the biodissolvable needle attachment, a liquid wax is identified to be an effective material because of its strong adhesion to relevant surfaces, its ability to be spin coated, and its dissolvability in isopropyl alcohol.

  18. Adults with high social anhedonia have altered neural connectivity with ventral lateral prefrontal cortex when processing positive social signals

    PubMed Central

    Yin, Hong; Tully, Laura M.; Lincoln, Sarah Hope; Hooker, Christine I.

    2015-01-01

    Social anhedonia (SA) is a debilitating characteristic of schizophrenia, a common feature in individuals at psychosis-risk, and a vulnerability for developing schizophrenia-spectrum disorders. Prior work (Hooker et al., 2014) revealed neural deficits in the ventral lateral prefrontal cortex (VLPFC) when processing positive social cues in a community sample of people with high SA. Lower VLPFC neural activity was related to more severe self-reported schizophrenia-spectrum symptoms as well as the exacerbation of symptoms after social stress. In the current study, psycho-physiological interaction (PPI) analysis was applied to further investigate the neural mechanisms mediated by the VLPFC during emotion processing. PPI analysis revealed that, compared to low SA controls, participants with high SA exhibited reduced connectivity between the VLPFC and the motor cortex, the inferior parietal and the posterior temporal regions when viewing socially positive (relative to neutral) emotions. Across all participants, VLPFC connectivity correlated with behavioral and self-reported measures of attentional control, emotion management, and reward processing. Our results suggest that impairments to the VLPFC mediated neural circuitry underlie the cognitive and emotional deficits associated with social anhedonia, and may serve as neural targets for prevention and treatment of schizophrenia-spectrum disorders. PMID:26379532

  19. Temporal context in speech processing and attentional stream selection: a behavioral and neural perspective.

    PubMed

    Zion Golumbic, Elana M; Poeppel, David; Schroeder, Charles E

    2012-09-01

    The human capacity for processing speech is remarkable, especially given that information in speech unfolds over multiple time scales concurrently. Similarly notable is our ability to filter out of extraneous sounds and focus our attention on one conversation, epitomized by the 'Cocktail Party' effect. Yet, the neural mechanisms underlying on-line speech decoding and attentional stream selection are not well understood. We review findings from behavioral and neurophysiological investigations that underscore the importance of the temporal structure of speech for achieving these perceptual feats. We discuss the hypothesis that entrainment of ambient neuronal oscillations to speech's temporal structure, across multiple time-scales, serves to facilitate its decoding and underlies the selection of an attended speech stream over other competing input. In this regard, speech decoding and attentional stream selection are examples of 'Active Sensing', emphasizing an interaction between proactive and predictive top-down modulation of neuronal dynamics and bottom-up sensory input.

  20. A neurally plausible parallel distributed processing model of event-related potential word reading data.

    PubMed

    Laszlo, Sarah; Plaut, David C

    2012-03-01

    The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between explicit, computational models and physiological data collected during the performance of cognitive tasks, we developed a PDP model of visual word recognition which simulates key results from the ERP reading literature, while simultaneously being able to successfully perform lexical decision-a benchmark task for reading models. Simulations reveal that the model's success depends on the implementation of several neurally plausible features in its architecture which are sufficiently domain-general to be relevant to cognitive modeling more generally.

  1. Gender effects and sexual-orientation impact on androstadienone-evoked behavior and neural processing.

    PubMed

    Krajnik, Jacqueline; Kollndorfer, Kathrin; Nenning, Karl-Heinz; Lundström, Johan N; Schöpf, Veronika

    2014-01-01

    In humans, the most established and investigated substance acting as a chemosignal, i.e., a substance that is excreted from the body, is 4,16-androstadien-3-one (AND). AND, which is found in sweat and saliva, is known to be responsible for influencing several variables, such as psychophysiological status, behavior, as well as cortical processing. The aim of the present review is to give insight into the variety of AND effects, with special regard to specific cross-sexual characteristics of this putative human chemosignal, emphasizing the neural activation patterns and factors such as contextual conditions. This review highlights the importance of including those contributing factors into the analysis of behavioral as well as brain-related studies.

  2. Neural image analysis in the process of quality assessment: domestic pig oocytes

    NASA Astrophysics Data System (ADS)

    Boniecki, P.; Przybył, J.; Kuzimska, T.; Mueller, W.; Raba, B.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.

    2014-04-01

    The questions related to quality classification of animal oocytes are explored by numerous scientific and research centres. This research is important, particularly in the context of improving the breeding value of farm animals. The methods leading to the stimulation of normal development of a larger number of fertilised animal oocytes in extracorporeal conditions are of special importance. Growing interest in the techniques of supported reproduction resulted in searching for new, increasingly effective methods for quality assessment of mammalian gametes and embryos. Progress in the production of in vitro animal embryos in fact depends on proper classification of obtained oocytes. The aim of this paper was the development of an original method for quality assessment of oocytes, performed on the basis of their graphical presentation in the form of microscopic digital images. The classification process was implemented on the basis of the information coded in the form of microphotographic pictures of the oocytes of domestic pig, using the modern methods of neural image analysis.

  3. Preserved Discrimination Performance and Neural Processing during Crossmodal Attention in Aging

    PubMed Central

    Mishra, Jyoti; Gazzaley, Adam

    2013-01-01

    In a recent study in younger adults (19-29 year olds) we showed evidence that distributed audiovisual attention resulted in improved discrimination performance for audiovisual stimuli compared to focused visual attention. Here, we extend our findings to healthy older adults (60-90 year olds), showing that performance benefits of distributed audiovisual attention in this population match those of younger adults. Specifically, improved performance was revealed in faster response times for semantically congruent audiovisual stimuli during distributed relative to focused visual attention, without any differences in accuracy. For semantically incongruent stimuli, discrimination accuracy was significantly improved during distributed relative to focused attention. Furthermore, event-related neural processing showed intact crossmodal integration in higher performing older adults similar to younger adults. Thus, there was insufficient evidence to support an age-related deficit in crossmodal attention. PMID:24278464

  4. Neural networks related to dysfunctional face processing in autism spectrum disorder

    PubMed Central

    Nickl-Jockschat, Thomas; Rottschy, Claudia; Thommes, Johanna; Schneider, Frank; Laird, Angela R.; Fox, Peter T.; Eickhoff, Simon B.

    2016-01-01

    One of the most consistent neuropsychological findings in autism spectrum disorders (ASD) is a reduced interest in and impaired processing of human faces. We conducted an activation likelihood estimation meta-analysis on 14 functional imaging studies on neural correlates of face processing enrolling a total of 164 ASD patients. Subsequently, normative whole-brain functional connectivity maps for the identified regions of significant convergence were computed for the task-independent (resting-state) and task-dependent (co-activations) state in healthy subjects. Quantitative functional decoding was performed by reference to the BrainMap database. Finally, we examined the overlap of the delineated network with the results of a previous meta-analysis on structural abnormalities in ASD as well as with brain regions involved in human action observation/imitation. We found a single cluster in the left fusiform gyrus showing significantly reduced activation during face processing in ASD across all studies. Both task-dependent and task-independent analyses indicated significant functional connectivity of this region with the temporo-occipital and lateral occipital cortex, the inferior frontal and parietal cortices, the thalamus and the amygdala. Quantitative reverse inference then indicated an association of these regions mainly with face processing, affective processing, and language-related tasks. Moreover, we found that the cortex in the region of right area V5 displaying structural changes in ASD patients showed consistent connectivity with the region showing aberrant responses in the context of face processing. Finally, this network was also implicated in the human action observation/imitation network. In summary, our findings thus suggest a functionally and structurally disturbed network of occipital regions related primarily to face (but potentially also language) processing, which interact with inferior frontal as well as limbic regions and may be the core of

  5. Emotionally anesthetized: media violence induces neural changes during emotional face processing

    PubMed Central

    Stockdale, Laura A.; Morrison, Robert G.; Kmiecik, Matthew J.; Garbarino, James

    2015-01-01

    Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others’ emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five participants were shown a violent or nonviolent film clip and then completed a gender discrimination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was observed in the N170 and P200 event-related potentials following the violent film, indicating that exposure to film violence leads to suppression of holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300 amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive resources to inhibit behavior. PMID:25759472

  6. Emotionally anesthetized: media violence induces neural changes during emotional face processing.

    PubMed

    Stockdale, Laura A; Morrison, Robert G; Kmiecik, Matthew J; Garbarino, James; Silton, Rebecca L

    2015-10-01

    Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others' emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five participants were shown a violent or nonviolent film clip and then completed a gender discrimination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was observed in the N170 and P200 event-related potentials following the violent film, indicating that exposure to film violence leads to suppression of holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300 amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive resources to inhibit behavior.

  7. Neural predictors and mechanisms of cognitive behavioral therapy on threat processing in social anxiety disorder.

    PubMed

    Klumpp, Heide; Fitzgerald, Daniel A; Phan, K Luan

    2013-08-01

    Cognitive behavioral therapy (CBT) is "gold standard" psychotherapy for social anxiety disorder (SAD). Cognitive models posit that preferential processing of threat mediates excessive forms of anxiety, which is supported by exaggerated amygdala, insula, and cortical reactivity to threatening socio-emotional signals in SAD. However, little is known about neural predictors of CBT success or the mechanisms by which CBT exerts its therapeutic effects. Functional magnetic resonance imaging (fMRI) was conducted during responses to social signals of threat (fearful/angry faces) against positive signals (happy faces) in 14 patients with SAD before and after 12 weeks of CBT. For comparison, 14 healthy control (HC) participants also underwent two fMRI scans, 12 weeks apart. Whole-brain voxel-wise analyses showed therapeutic success was predicted by enhanced pre-treatment activation to threatening faces in higher-order visual (superior and middle temporal gyrus), cognitive, and emotion processing areas (dorsal anterior cingulate cortex, dorsomedial prefrontal cortex). Moreover, a group by time interaction was revealed in prefrontal regions (dorsomedial, medial gyrus) and insula. The interaction was driven by relatively greater activity during threat processing in SAD, which significantly reduced after CBT but did not significantly predict response to CBT. Therefore, pre-treatment cortical hyperactivity to social threat signals may serve as a prognostic indicator of CBT success in SAD. Collectively, CBT-related brain changes involved a reduction in activity in insula, prefrontal, and extrastriate regions. Results are consistent with cognitive models, which associate decreases in threat processing bias with recovery.

  8. Molecular and neural mechanisms of sex pheromone reception and processing in the silkmoth Bombyx mori

    PubMed Central

    Sakurai, Takeshi; Namiki, Shigehiro; Kanzaki, Ryohei

    2014-01-01

    Male moths locate their mates using species-specific sex pheromones emitted by conspecific females. One striking feature of sex pheromone recognition in males is the high degree of specificity and sensitivity at all levels, from the primary sensory processes to behavior. The silkmoth Bombyx mori is an excellent model insect in which to decipher the underlying mechanisms of sex pheromone recognition due to its simple sex pheromone communication system, where a single pheromone component, bombykol, elicits the full sexual behavior of male moths. Various technical advancements that cover all levels of analysis from molecular to behavioral also allow the systematic analysis of pheromone recognition mechanisms. Sex pheromone signals are detected by pheromone receptors expressed in olfactory receptor neurons in the pheromone-sensitive sensilla trichodea on male antennae. The signals are transmitted to the first olfactory processing center, the antennal lobe (AL), and then are processed further in the higher centers (mushroom body and lateral protocerebrum) to elicit orientation behavior toward females. In recent years, significant progress has been made elucidating the molecular mechanisms underlying the detection of sex pheromones. In addition, extensive studies of the AL and higher centers have provided insights into the neural basis of pheromone processing in the silkmoth brain. This review describes these latest advances, and discusses what these advances have revealed about the mechanisms underlying the specific and sensitive recognition of sex pheromones in the silkmoth. PMID:24744736

  9. Neural processing during older adults' comprehension of spoken sentences: age differences in resource allocation and connectivity.

    PubMed

    Peelle, Jonathan E; Troiani, Vanessa; Wingfield, Arthur; Grossman, Murray

    2010-04-01

    Speech comprehension remains largely preserved in older adults despite significant age-related neurophysiological change. However, older adults' performance declines more rapidly than that of young adults when listening conditions are challenging. We investigated the cortical network underlying speech comprehension in healthy aging using short sentences differing in syntactic complexity, with processing demands further manipulated through speech rate. Neural activity was monitored using blood oxygen level-dependent functional magnetic resonance imaging. Comprehension of syntactically complex sentences activated components of a core sentence-processing network in both young and older adults, including the left inferior and middle frontal gyri, left inferior parietal cortex, and left middle temporal gyrus. However, older adults showed reduced recruitment of inferior frontal regions relative to young adults; the individual degree of recruitment predicted accuracy at the more difficult fast speech rate. Older adults also showed increased activity in frontal regions outside the core sentence-processing network, which may have played a compensatory role. Finally, a functional connectivity analysis demonstrated reduced coherence between activated regions in older adults. We conclude that decreased activation of specialized processing regions, and limited ability to coordinate activity between regions, contribute to older adults' difficulty with sentence comprehension under difficult listening conditions.

  10. The effect of early visual deprivation on the neural bases of multisensory processing.

    PubMed

    Guerreiro, Maria J S; Putzar, Lisa; Röder, Brigitte

    2015-06-01

    Developmental vision is deemed to be necessary for the maturation of multisensory cortical circuits. Thus far, this has only been investigated in animal studies, which have shown that congenital visual deprivation markedly reduces the capability of neurons to integrate cross-modal inputs. The present study investigated the effect of transient congenital visual deprivation on the neural mechanisms of multisensory processing in humans. We used functional magnetic resonance imaging to compare responses of visual and auditory cortical areas to visual, auditory and audio-visual stimulation in cataract-reversal patients and normally sighted controls. The results showed that cataract-reversal patients, unlike normally sighted controls, did not exhibit multisensory integration in auditory areas. Furthermore, cataract-reversal patients, but not normally sighted controls, exhibited lower visual cortical processing within visual cortex during audio-visual stimulation than during visual stimulation. These results indicate that congenital visual deprivation affects the capability of cortical areas to integrate cross-modal inputs in humans, possibly because visual processing is suppressed during cross-modal stimulation. Arguably, the lack of vision in the first months after birth may result in a reorganization of visual cortex, including the suppression of noisy visual input from the deprived retina in order to reduce interference during auditory processing.

  11. Brain Functional Effects of Psychopharmacological Treatment in Major Depression: a Focus on Neural Circuitry of Affective Processing.

    PubMed

    Wessa, Michèle; Lois, Giannis

    2015-01-01

    In the last two decades, neuroimaging research has reached a much deeper understanding of the neurobiological underpinnings of major depression (MD) and has converged on functional alterations in limbic and prefrontal neural networks, which are mainly linked to altered emotional processing observed in MD patients. To date, a considerable number of studies have sought to investigate how these neural networks change with pharmacological antidepressant treatment. In the current review, we therefore discuss results from a) pharmacological functional magnetic resonance imaging (fMRI) studies investigating the effects of selective serotonin or noradrenalin reuptake inhibitors on neural activation patterns in relation to emotional processing in healthy individuals, b) treatment studies in patients with unipolar depression assessing changes in neural activation patterns before and after antidepressant pharmacotherapy, and c) predictive neural biomarkers of clinical response in depression. Comparing results from pharmacological fMRI studies in healthy individuals and treatment studies in depressed patients nicely showed parallel findings, mainly for a reduction of limbic activation in response to negative stimuli. A thorough investigation of the empirical findings highlights the importance of the specific paradigm employed in every study which may account for some of the discrepant findings reported in treatment studies in depressed patients.

  12. Specific aspects of cognitive and language proficiency account for variability in neural indices of semantic and syntactic processing in children

    PubMed Central

    Wray, Amanda Hampton; Weber-Fox, Christine

    2013-01-01

    The neural activity mediating language processing in young children is characterized by large individual variability that is likely related in part to individual strengths and weakness across various cognitive abilities. The current study addresses the following question: How does proficiency in specific cognitive and language functions impact neural indices mediating language processing in children? Thirty typically developing seven- and eight-year-olds were divided into high-normal and low-normal proficiency groups based on performance on nonverbal IQ, auditory word recall, and grammatical morphology tests. Event-related brain potentials (ERPs) were elicited by semantic anomalies and phrase structure violations in naturally spoken sentences. The proficiency for each of the specific cognitive and language tasks uniquely contributed to specific aspects (e.g., timing and/or resource allocation) of neural indices underlying semantic (N400) and syntactic (P600) processing. These results suggest that distinct aptitudes within broader domains of cognition and language, even within the normal range, influence the neural signatures of semantic and syntactic processing. Furthermore, the current findings have important implications for the design and interpretation of developmental studies of ERPs indexing language processing, and they highlight the need to take into account cognitive abilities both within and outside the classic language domain. PMID:23557881

  13. Neural Correlates of Indicators of Sound Change in Cantonese: Evidence from Cortical and Subcortical Processes

    PubMed Central

    Maggu, Akshay R.; Liu, Fang; Antoniou, Mark; Wong, Patrick C. M.

    2016-01-01

    Across time, languages undergo changes in phonetic, syntactic, and semantic dimensions. Social, cognitive, and cultural factors contribute to sound change, a phenomenon in which the phonetics of a language undergo changes over time. Individuals who misperceive and produce speech in a slightly divergent manner (called innovators) contribute to variability in the society, eventually leading to sound change. However, the cause of variability in these individuals is still unknown. In this study, we examined whether such misperceptions are represented in neural processes of the auditory system. We investigated behavioral, subcortical (via FFR), and cortical (via P300) manifestations of sound change processing in Cantonese, a Chinese language in which several lexical tones are merging. Across the merging categories, we observed a similar gradation of speech perception abilities in both behavior and the brain (subcortical and cortical processes). Further, we also found that behavioral evidence of tone merging correlated with subjects' encoding at the subcortical and cortical levels. These findings indicate that tone-merger categories, that are indicators of sound change in Cantonese, are represented neurophysiologically with high fidelity. Using our results, we speculate that innovators encode speech in a slightly deviant neurophysiological manner, and thus produce speech divergently that eventually spreads across the community and contributes to sound change. PMID:28066218

  14. Cultural influences on the neural correlate of moral decision making processes.

    PubMed

    Han, Hyemin; Glover, Gary H; Jeong, Changwoo

    2014-02-01

    This study compares the neural substrate of moral decision making processes between Korean and American participants. By comparison with Americans, Korean participants showed increased activity in the right putamen associated with socio-intuitive processes and right superior frontal gyrus associated with cognitive control processes under a moral-personal condition, and in the right postcentral sulcus associated with mental calculation in familiar contexts under a moral-impersonal condition. On the other hand, American participants showed a significantly higher degree of activity in the bilateral anterior cingulate cortex (ACC) associated with conflict resolution under the moral-personal condition, and in the right medial frontal gyrus (MFG) associated with simple cognitive branching in non-familiar contexts under the moral-impersonal condition when a more lenient threshold was applied, than Korean participants. These findings support the ideas of the interactions between the cultural background, education, and brain development, proposed in the field of cultural psychology and educational psychology. The study introduces educational implications relevant to moral psychologists and educators.

  15. Training of Working Memory Impacts Neural Processing of Vocal Pitch Regulation

    PubMed Central

    Li, Weifeng; Guo, Zhiqiang; Jones, Jeffery A.; Huang, Xiyan; Chen, Xi; Liu, Peng; Chen, Shaozhen; Liu, Hanjun

    2015-01-01

    Working memory training can improve the performance of tasks that were not trained. Whether auditory-motor integration for voice control can benefit from working memory training, however, remains unclear. The present event-related potential (ERP) study examined the impact of working memory training on the auditory-motor processing of vocal pitch. Trained participants underwent adaptive working memory training using a digit span backwards paradigm, while control participants did not receive any training. Before and after training, both trained and control participants were exposed to frequency-altered auditory feedback while producing vocalizations. After training, trained participants exhibited significantly decreased N1 amplitudes and increased P2 amplitudes in response to pitch errors in voice auditory feedback. In addition, there was a significant positive correlation between the degree of improvement in working memory capacity and the post-pre difference in P2 amplitudes. Training-related changes in the vocal compensation, however, were not observed. There was no systematic change in either vocal or cortical responses for control participants. These findings provide evidence that working memory training impacts the cortical processing of feedback errors in vocal pitch regulation. This enhanced cortical processing may be the result of increased neural efficiency in the detection of pitch errors between the intended and actual feedback. PMID:26553373

  16. Neural processes underlying memory attribution on a reality-monitoring task.

    PubMed

    Kensinger, Elizabeth A; Schacter, Daniel L

    2006-08-01

    A relatively common form of memory distortion arises when individuals must discriminate items they have seen from those they have imagined (reality monitoring). The present fMRI investigation (at 1.5 T) focused on the processes that relate to memory assignment regardless of accuracy (e.g. that correspond with the belief that an item was presented as a picture, regardless of whether that belief is correct). Prior to the scan, participants (n = 16) viewed concrete nouns and formed mental images of the object named. Half of the names were followed by the object's photo. During the scan, participants saw the object names and indicated whether the corresponding photo had been studied. Activity in visual-processing regions (including the precuneus and fusiform gyrus) corresponded with the attribution of an item to a pictorial presentation. In contrast, activity in regions thought to be important for self-referential processing (including the ventromedial prefrontal cortex and posterior cingulate gyrus) was associated with attribution to a nonpresented source. These neural findings converge with behavioral evidence indicating that individuals use the amount of different types of information retrieved (e.g. perceptual detail, information about cognitive operations) to determine whether an item was imagined or perceived.

  17. Abnormal Neural Oscillations in Schizophrenia Assessed by Spectral Power Ratio of MEG During Word Processing.

    PubMed

    Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

    2016-11-01

    This study investigated spectral power of neural oscillations associated with word processing in schizophrenia. Magnetoencephalography (MEG) data were acquired from 12 schizophrenia patients and 10 healthy controls during a visual word processing task. Two spectral power ratio (SPR) feature sets: the band power ratio (BPR) and the window power ratio (WPR) were extracted from MEG data in five frequency bands, four time windows of word processing, and at locations covering whole head. Cluster-based nonparametric permutation tests were employed to identify SPRs that show significant between-group difference. Machine learning based feature selection and classification techniques were then employed to select optimal combinations of the significant SPR features, and distinguish schizophrenia patients from healthy controls. We identified three BPR clusters and three WPR clusters that show significant oscillation power difference between groups. These include the theta/delta, alpha/delta and beta/delta BPRs during base-to-encode and encode time windows, and the beta band WPR from base to encode and from encode to post-encode windows. Based on two WPR and one BPR features combined, over 95% cross-validation classification accuracy was achieved using three different linear classifiers separately. These features may have potential as quantitative markers that discriminate schizophrenia patients and healthy controls; however, this needs further validation on larger samples.

  18. Corticofugal Modulation of Initial Neural Processing of Sound Information from the Ipsilateral Ear in the Mouse

    PubMed Central

    Liu, Xiuping; Yan, Yuchu; Wang, Yalong; Yan, Jun

    2010-01-01

    Background Cortical neurons implement a high frequency-specific modulation of subcortical nuclei that includes the cochlear nucleus. Anatomical studies show that corticofugal fibers terminating in the auditory thalamus and midbrain are mostly ipsilateral. Differently, corticofugal fibers terminating in the cochlear nucleus are bilateral, which fits to the needs of binaural hearing that improves hearing quality. This leads to our hypothesis that corticofugal modulation of initial neural processing of sound information from the contralateral and ipsilateral ears could be equivalent or coordinated at the first sound processing level. Methodology/Principal Findings With the focal electrical stimulation of the auditory cortex and single unit recording, this study examined corticofugal modulation of the ipsilateral cochlear nucleus. The same methods and procedures as described in our previous study of corticofugal modulation of contralateral cochlear nucleus were employed simply for comparison. We found that focal electrical stimulation of cortical neurons induced substantial changes in the response magnitude, response latency and receptive field of ipsilateral cochlear nucleus neurons. Cortical stimulation facilitated auditory response and shortened the response latency of physiologically matched neurons whereas it inhibited auditory response and lengthened the response latency of unmatched neurons. Finally, cortical stimulation shifted the best frequencies of cochlear neurons towards those of stimulated cortical neurons. Conclusion Our data suggest that cortical neurons enable a high frequency-specific remodelling of sound information processing in the ipsilateral cochlear nucleus in the same manner as that in the contralateral cochlear nucleus. PMID:21124980

  19. Combined expert system/neural networks method for process fault diagnosis

    DOEpatents

    Reifman, J.; Wei, T.Y.C.

    1995-08-15

    A two-level hierarchical approach for process fault diagnosis of an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach. 9 figs.

  20. Combined expert system/neural networks method for process fault diagnosis

    DOEpatents

    Reifman, Jaques; Wei, Thomas Y. C.

    1995-01-01

    A two-level hierarchical approach for process fault diagnosis is an operating system employs a function-oriented approach at a first level and a component characteristic-oriented approach at a second level, where the decision-making procedure is structured in order of decreasing intelligence with increasing precision. At the first level, the diagnostic method is general and has knowledge of the overall process including a wide variety of plant transients and the functional behavior of the process components. An expert system classifies malfunctions by function to narrow the diagnostic focus to a particular set of possible faulty components that could be responsible for the detected functional misbehavior of the operating system. At the second level, the diagnostic method limits its scope to component malfunctions, using more detailed knowledge of component characteristics. Trained artificial neural networks are used to further narrow the diagnosis and to uniquely identify the faulty component by classifying the abnormal condition data as a failure of one of the hypothesized components through component characteristics. Once an anomaly is detected, the hierarchical structure is used to successively narrow the diagnostic focus from a function misbehavior, i.e., a function oriented approach, until the fault can be determined, i.e., a component characteristic-oriented approach.

  1. Segmentation and classification of shallow subbottom acoustic data, using image processing and neural networks

    NASA Astrophysics Data System (ADS)

    Yegireddi, Satyanarayana; Thomas, Nitheesh

    2014-06-01

    Subbottom acoustic profiler provides acoustic imaging of the subbottom structure constituting the upper sediment layers of the seabed, which is essential for geological and offshore geo-engineering studies. Delineation of the subbottom structure from a noisy acoustic data and classification of the sediment strata is a challenging task with the conventional signal processing techniques. Image processing techniques utilise the spatial variability of the image characteristics, known for their potential in medical imaging and pattern recognition applications. In the present study, they are found to be good in demarcating the boundaries of the sediment layers associated with weak acoustic reflectivity, masked by noisy background. The study deals with application of image processing techniques, like segmentation in identification of subbottom features and extraction of textural feature vectors using grey level co-occurrence matrix statistics. And also attempted classification using Self Organised Map, an unsupervised neural network model utilising these feature vectors. The methodology was successfully demonstrated in demarcating the different sediment layers from the subbottom images and established the sediments constituting the inferred four subsurface sediment layers differ from each other. The network model was also tested for its consistency, with repeated runs of different configuration of the network. Also the ability of simulated network was tested using a few untrained test images representing the similar environment and the classification results show a good agreement with the anticipated.

  2. Temperament trait of sensory processing sensitivity moderates cultural differences in neural response

    PubMed Central

    Ketay, Sarah; Hedden, Trey; Aron, Elaine N.; Rose Markus, Hazel; Gabrieli, John D. E.

    2010-01-01

    This study focused on a possible temperament-by-culture interaction. Specifically, it explored whether a basic temperament/personality trait (sensory processing sensitivity; SPS), perhaps having a genetic component, might moderate a previously established cultural difference in neural responses when making context-dependent vs context-independent judgments of simple visual stimuli. SPS has been hypothesized to underlie what has been called inhibitedness or reactivity in infants, introversion in adults, and reactivity or responsivness in diverse animal species. Some biologists view the trait as one of two innate strategies—observing carefully before acting vs being first to act. Thus the central characteristic of SPS is hypothesized to be a deep processing of information. Here, 10 European-Americans and 10 East Asians underwent functional magnetic resonance imaging while performing simple visuospatial tasks emphasizing judgments that were either context independent (typically easier for Americans) or context dependent (typically easier for Asians). As reported elsewhere, each group exhibited greater activation for the culturally non-preferred task in frontal and parietal regions associated with greater effort in attention and working memory. However, further analyses, reported here for the first time, provided preliminary support for moderation by SPS. Consistent with the careful-processing theory, high-SPS individuals showed little cultural difference; low-SPS, strong culture differences. PMID:20388694

  3. Neural organization and visual processing in the anterior optic tubercle of the honeybee brain.

    PubMed

    Mota, Theo; Yamagata, Nobuhiro; Giurfa, Martin; Gronenberg, Wulfila; Sandoz, Jean-Christophe

    2011-08-10

    The honeybee Apis mellifera represents a valuable model for studying the neural segregation and integration of visual information. Vision in honeybees has been extensively studied at the behavioral level and, to a lesser degree, at the physiological level using intracellular electrophysiological recordings of single neurons. However, our knowledge of visual processing in honeybees is still limited by the lack of functional studies of visual processing at the circuit level. Here we contribute to filling this gap by providing a neuroanatomical and neurophysiological characterization at the circuit level of a practically unstudied visual area of the bee brain, the anterior optic tubercle (AOTu). First, we analyzed the internal organization and neuronal connections of the AOTu. Second, we established a novel protocol for performing optophysiological recordings of visual circuit activity in the honeybee brain and studied the responses of AOTu interneurons during stimulation of distinct eye regions. Our neuroanatomical data show an intricate compartmentalization and connectivity of the AOTu, revealing a dorsoventral segregation of the visual input to the AOTu. Light stimuli presented in different parts of the visual field (dorsal, lateral, or ventral) induce distinct patterns of activation in AOTu output interneurons, retaining to some extent the dorsoventral input segregation revealed by our neuroanatomical data. In particular, activity patterns evoked by dorsal and ventral eye stimulation are clearly segregated into distinct AOTu subunits. Our results therefore suggest an involvement of the AOTu in the processing of dorsoventrally segregated visual information in the honeybee brain.

  4. Neural, psychophysiological, and behavioral markers of fear processing in PTSD: a review of the literature.

    PubMed

    Shvil, Erel; Rusch, Heather L; Sullivan, Gregory M; Neria, Yuval

    2013-05-01

    As presently defined, post-traumatic stress disorder (PTSD) is an amalgam of symptoms falling into: re-experiencing of the trauma, avoidance of reminders of it, emotional numbing and hyperarousal. PTSD has a well-known proximate cause, commonly occurring after a life-threatening event that induces a response of intense fear, horror, and helplessness. Much of the advancement in understanding of the neurobiology of PTSD has emerged from conceptualizing the disorder as one that involves substantial dysfunction in fear processing. This article reviews recent knowledge of fear processing markers in PTSD. A systematic search was performed of reports within the specific three-year publication time period of January 2010 to December 2012. We identified a total of 31 studies reporting fear processing markers in PTSD. We further categorized them according to the following classification: (1) neural-activation markers (n=10), (2) psychophysiological markers (n=14), and (3) behavioral markers (n=7). Across most studies reviewed here, significant differences between individuals with PTSD and healthy controls were shown. Methodological, theoretical and clinical implications were discussed.

  5. Neural bases for basic processes in heuristic problem solving: Take solving Sudoku puzzles as an example.

    PubMed

    Qin, Yulin; Xiang, Jie; Wang, Rifeng; Zhou, Haiyan; Li, Kuncheng; Zhong, Ning

    2012-12-01

    Newell and Simon postulated that the basic steps in human problem-solving involve iteratively applying operators to transform the state of the problem to eventually achieve a goal. To check the neural basis of this framework, the present study focused on the basic processes in human heuristic problem-solving that the participants identified the current problem state and then recalled and applied the corresponding heuristic rules to change the problem state. A new paradigm, solving simplified Sudoku puzzles, was developed for an event-related functional magnetic resonance imaging (fMRI) study in problem solving. Regions of interest (ROIs), including the left prefrontal cortex, the bilateral posterior parietal cortex, the anterior cingulated cortex, the bilateral caudate nuclei, the bilateral fusiform, as well as the bilateral frontal eye fields, were found to be involved in the task. To obtain convergent evidence, in addition to traditional statistical analysis, we used the multivariate voxel classification method to check the accuracy of the predictions for the condition of the task from the blood oxygen level dependent (BOLD) response of the ROIs, using a new classifier developed in this study for fMRI data. To reveal the roles that the ROIs play in problem solving, we developed an ACT-R computational model of the information-processing processes in human problem solving, and tried to predict the BOLD response of the ROIs from the task. Advances in human problem-solving research after Newell and Simon are then briefly discussed.

  6. Classification of RF transients in space using digital signal processing and neural network techniques

    SciTech Connect

    Moore, K.R.; Blain, P.C.; Briles, S.D.; Jones, R.G.

    1995-02-01

    The FORTE{prime} (Fast On-Orbit Recording of Transient Events) small satellite experiment scheduled for launch in October, 1995 will attempt to measure and classify electromagnetic transients as sensed from space. The FORTE{prime} payload will employ an Event Classifier to perform onboard classification of radio frequency transients from terrestrial sources such as lightning. These transients are often dominated by a constantly changing assortment of man-made ``clutter`` such as TV, FM, and radar signals. The FORTE{prime} Event Classifier, or EC, uses specialized hardware to implement various signal processing and neural network algorithms. The resulting system can process and classify digitized records of several thousand samples onboard the spacecraft at rates of about a second per record. In addition to reducing dowlink rates, the EC minimizes command uplink data by normally using uploaded algorithm sequences rather than full code modules (although it is possible for full code modules to be uploaded from the ground). The FORTE{prime} Event Classifier experiment combines science and engineering in an evolutionary step toward useful and robust adaptive processing systems in space.

  7. Temperament trait of sensory processing sensitivity moderates cultural differences in neural response.

    PubMed

    Aron, Arthur; Ketay, Sarah; Hedden, Trey; Aron, Elaine N; Rose Markus, Hazel; Gabrieli, John D E

    2010-06-01

    This study focused on a possible temperament-by-culture interaction. Specifically, it explored whether a basic temperament/personality trait (sensory processing sensitivity; SPS), perhaps having a genetic component, might moderate a previously established cultural difference in neural responses when making context-dependent vs context-independent judgments of simple visual stimuli. SPS has been hypothesized to underlie what has been called inhibitedness or reactivity in infants, introversion in adults, and reactivity or responsivness in diverse animal species. Some biologists view the trait as one of two innate strategies-observing carefully before acting vs being first to act. Thus the central characteristic of SPS is hypothesized to be a deep processing of information. Here, 10 European-Americans and 10 East Asians underwent functional magnetic resonance imaging while performing simple visuospatial tasks emphasizing judgments that were either context independent (typically easier for Americans) or context dependent (typically easier for Asians). As reported elsewhere, each group exhibited greater activation for the culturally non-preferred task in frontal and parietal regions associated with greater effort in attention and working memory. However, further analyses, reported here for the first time, provided preliminary support for moderation by SPS. Consistent with the careful-processing theory, high-SPS individuals showed little cultural difference; low-SPS, strong culture differences.

  8. Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

    NASA Astrophysics Data System (ADS)

    Deng, Xinyi

    A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in

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

    NASA Astrophysics Data System (ADS)

    Luongo, Francisco

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

  10. 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.

  11. Hardware Implementation of a Desktop Supercomputer for High Performance Image Processing. Color Image Processing Using Cellular Neural Networks

    DTIC Science & Technology

    1994-11-01

    This report addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of...The report discusses the new fault model, presents the algorithmic procedures and shows simulated testing results. Cellular neural Networks , Testing.

  12. Level of processing modulates the neural correlates of emotional memory formation.

    PubMed

    Ritchey, Maureen; LaBar, Kevin S; Cabeza, Roberto

    2011-04-01

    Emotion is known to influence multiple aspects of memory formation, including the initial encoding of the memory trace and its consolidation over time. However, the neural mechanisms whereby emotion impacts memory encoding remain largely unexplored. The present study used a levels-of-processing manipulation to characterize the impact of emotion on encoding with and without the influence of elaborative processes. Participants viewed emotionally negative, neutral, and positive scenes under two conditions: a shallow condition focused on the perceptual features of the scenes and a deep condition that queried their semantic meaning. Recognition memory was tested 2 days later. Results showed that emotional memory enhancements were greatest in the shallow condition. fMRI analyses revealed that the right amygdala predicted subsequent emotional memory in the shallow more than deep condition, whereas the right ventrolateral PFC demonstrated the reverse pattern. Furthermore, the association of these regions with the hippocampus was modulated by valence: the amygdala-hippocampal link was strongest for negative stimuli, whereas the prefrontal-hippocampal link was strongest for positive stimuli. Taken together, these results suggest two distinct activation patterns underlying emotional memory formation: an amygdala component that promotes memory during shallow encoding, especially for negative information, and a prefrontal component that provides extra benefits during deep encoding, especially for positive information.

  13. Temperature and relative humidity estimation and prediction in the tobacco drying process using Artificial Neural Networks.

    PubMed

    Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén

    2012-10-17

    This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.

  14. Incipient fault detection and identification in process systems using accelerating neural network learning

    SciTech Connect

    Parlos, A.G.; Muthusami, J.; Atiya, A.F. . Dept. of Nuclear Engineering)

    1994-02-01

    The objective of this paper is to present the development and numerical testing of a robust fault detection and identification (FDI) system using artificial neural networks (ANNs), for incipient (slowly developing) faults occurring in process systems. The challenge in using ANNs in FDI systems arises because of one's desire to detect faults of varying severity, faults from noisy sensors, and multiple simultaneous faults. To address these issues, it becomes essential to have a learning algorithm that ensures quick convergence to a high level of accuracy. A recently developed accelerated learning algorithm, namely a form of an adaptive back propagation (ABP) algorithm, is used for this purpose. The ABP algorithm is used for the development of an FDI system for a process composed of a direct current motor, a centrifugal pump, and the associated piping system. Simulation studies indicate that the FDI system has significantly high sensitivity to incipient fault severity, while exhibiting insensitivity to sensor noise. For multiple simultaneous faults, the FDI system detects the fault with the predominant signature. The major limitation of the developed FDI system is encountered when it is subjected to simultaneous faults with similar signatures. During such faults, the inherent limitation of pattern-recognition-based FDI methods becomes apparent. Thus, alternate, more sophisticated FDI methods become necessary to address such problems. Even though the effectiveness of pattern-recognition-based FDI methods using ANNs has been demonstrated, further testing using real-world data is necessary.

  15. Processing Narratives Concerning Protected Values: A Cross-Cultural Investigation of Neural Correlates.

    PubMed

    Kaplan, Jonas T; Gimbel, Sarah I; Dehghani, Morteza; Immordino-Yang, Mary Helen; Sagae, Kenji; Wong, Jennifer D; Tipper, Christine M; Damasio, Hanna; Gordon, Andrew S; Damasio, Antonio

    2017-02-01

    Narratives are an important component of culture and play a central role in transmitting social values. Little is known, however, about how the brain of a listener/reader processes narratives. A receiver's response to narration is influenced by the narrator's framing and appeal to values. Narratives that appeal to "protected values," including core personal, national, or religious values, may be particularly effective at influencing receivers. Protected values resist compromise and are tied with identity, affective value, moral decision-making, and other aspects of social cognition. Here, we investigated the neural mechanisms underlying reactions to protected values in narratives. During fMRI scanning, we presented 78 American, Chinese, and Iranian participants with real-life stories distilled from a corpus of over 20 million weblogs. Reading these stories engaged the posterior medial, medial prefrontal, and temporo-parietal cortices. When participants believed that the protagonist was appealing to a protected value, signal in these regions was increased compared with when no protected value was perceived, possibly reflecting the intensive and iterative search required to process this material. The effect strength also varied across groups, potentially reflecting cultural differences in the degree of concern for protected values.

  16. Temperature and Relative Humidity Estimation and Prediction in the Tobacco Drying Process Using Artificial Neural Networks

    PubMed Central

    Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M.; Aguiar, Javier M.; Carro, Belén

    2012-01-01

    This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed. PMID:23202032

  17. 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

  18. Choosing our words: Retrieval and selection processes recruit shared neural substrates in left ventrolateral prefrontal cortex

    PubMed Central

    Snyder, Hannah R.; Banich, Marie T.; Munakata, Yuko

    2011-01-01

    When we speak, we constantly retrieve and select words for production in the face of multiple possible alternatives. Our ability to respond in such underdetermined situations is supported by left ventrolateral prefrontal cortical (VLPFC) regions, but there is active debate about whether these regions support: (1) selection between competing alternatives, (2) controlled retrieval from semantic memory, or (3) selection and controlled retrieval in distinct subregions of VLPFC (selection in mid-VLPFC and controlled retrieval in anterior-VLPFC). Each of these theories has been supported by some prior evidence, but challenged by other findings, leaving the debate unresolved. We propose that these discrepancies in the previous literature reflect problems in the way that selection and controlled retrieval processes have been operationalized and measured. Using improved measures, we find that shared neural substrates in left VLPFC support both selection and controlled retrieval, with no dissociation between mid and anterior regions. Moreover, selection and retrieval demands interact in left VLPFC, such that selection effects are greatest when retrieval demands are low, consistent with prior behavioral findings. These findings enable a synthesis and reinterpretation of prior evidence, and suggest that the ability to respond in underdetermined situations is affected by both selection and retrieval mechanisms for verbal material subserved by left VLPFC, and these processes interact in meaningful ways. PMID:21452939

  19. Design Process for High Speed Civil Transport Aircraft Improved by Neural Network and Regression Methods

    NASA Technical Reports Server (NTRS)

    Hopkins, Dale A.

    1998-01-01

    A key challenge in designing the new High Speed Civil Transport (HSCT) aircraft is determining a good match between the airframe and engine. Multidisciplinary design optimization can be used to solve the problem by adjusting parameters of both the engine and the airframe. Earlier, an example problem was presented of an HSCT aircraft with four mixed-flow turbofan engines and a baseline mission to carry 305 passengers 5000 nautical miles at a cruise speed of Mach 2.4. The problem was solved by coupling NASA Lewis Research Center's design optimization testbed (COMETBOARDS) with NASA Langley Research Center's Flight Optimization System (FLOPS). The computing time expended in solving the problem was substantial, and the instability of the FLOPS analyzer at certain design points caused difficulties. In an attempt to alleviate both of these limitations, we explored the use of two approximation concepts in the design optimization process. The two concepts, which are based on neural network and linear regression approximation, provide the reanalysis capability and design sensitivity analysis information required for the optimization process. The HSCT aircraft optimization problem was solved by using three alternate approaches; that is, the original FLOPS analyzer and two approximate (derived) analyzers. The approximate analyzers were calibrated and used in three different ranges of the design variables; narrow (interpolated), standard, and wide (extrapolated).

  20. Using The Finite Element Method And Artificial Neural Networks To Predict Ductile Fracture In Cold Forming Processes

    NASA Astrophysics Data System (ADS)

    Klocke, F.; Breuer, D.

    2004-06-01

    Apart from the calculation of the plastic formability of metals the prediction of ductile cracks in cold forming processes is very important in order to design these processes efficiently. Therefore, many crack criteria have been developed and implemented in several FEM Programs. These criteria scale the crack prediction down to one value and they are qualified to detect the most endangered areas occurring cracks during the forming process quite well. All these criteria have two significant disadvantages: on one hand none of these criteria consider the whole forming history and on the other hand the detected critical value is not applicable to other forming processes. Therefore a new method to predict ductile fracture in cold forming processes has been developed. Various upsetting, bending and extrusion tests were designed in order to provoke a failure during the forming process. All these processes were modelled by means of the Finite Element Method to acquire the whole forming history (including the first principle stress, the equivalent stress and the equivalent strain starting with the first deformation to the first crack occurrence) for the area where the first fracture occurs. Basal in the results way a database with forming histories which all will lead to an failure during a forming process was built up. This database is used to train an artificial neural network. The artificial neural network will be able to predict a failure for new forming histories. The paper gives an overview over the use of the artificial neural network, the calculation of the forming histories and the used forming processes as well as the interaction between the Finite Element Method and the artificial neural network.

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

    PubMed

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

    2016-02-10

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

  2. Neural Processes in the Human Temporoparietal Cortex Separated by Localized Independent Component Analysis.

    PubMed

    Igelström, Kajsa M; Webb, Taylor W; Graziano, Michael S A

    2015-06-24

    The human temporoparietal junction (TPJ) is a topic of intense research. Imaging studies have identified TPJ activation in association with many higher-order functions such as theory-of-mind, episodic memory, and attention, causing debate about the distribution of different processes. One major challenge is the lack of consensus about the anatomical location and extent of the TPJ. Here, we address this problem using data-driven analysis to test the hypothesis that the bilateral TPJ can be parcellated into subregions. We applied independent component analysis (ICA) to task-free fMRI data within a local region around the bilateral TPJ, iterating the ICA at multiple model orders and in several datasets. The localized analysis allowed finer separation of processes and the use of multiple dimensionalities provided qualitative information about lateralization. We identified four subdivisions that were bilaterally symmetrical and one that was right biased. To test whether the independent components (ICs) reflected true subdivisions, we performed functional connectivity analysis using the IC coordinates as seeds. This confirmed that the subdivisions belonged to distinct networks. The right-biased IC was connected with a network often associated with attentional processing. One bilateral subdivision was connected to sensorimotor regions and another was connected to auditory regions. One subdivision that presented as distinct left- and right-biased ICs was connected to frontoparietal regions. Another subdivision that also had left- and right-biased ICs was connected to social or default mode networks. Our results show that the TPJ in both hemispheres hosts multiple neural processes with connectivity patterns consistent with well developed specialization and lateralization.

  3. Dissociated emergent-response system and fine-processing system in human neural network and a heuristic neural architecture for autonomous humanoid robots.

    PubMed

    Yan, Xiaodan

    2010-01-01

    The current study investigated the functional connectivity of the primary sensory system with resting state fMRI and applied such knowledge into the design of the neural architecture of autonomous humanoid robots. Correlation and Granger causality analyses were utilized to reveal the functional connectivity patterns. Dissociation was within the primary sensory system, in that the olfactory cortex and the somatosensory cortex were strongly connected to the amygdala whereas the visual cortex and the auditory cortex were strongly connected with the frontal cortex. The posterior cingulate cortex (PCC) and the anterior cingulate cortex (ACC) were found to maintain constant communication with the primary sensory system, the frontal cortex, and the amygdala. Such neural architecture inspired the design of dissociated emergent-response system and fine-processing system in autonomous humanoid robots, with separate processing units and another consolidation center to coordinate the two systems. Such design can help autonomous robots to detect and respond quickly to danger, so as to maintain their sustainability and independence.

  4. Dissociated Emergent-Response System and Fine-Processing System in Human Neural Network and a Heuristic Neural Architecture for Autonomous Humanoid Robots

    PubMed Central

    Yan, Xiaodan

    2010-01-01

    The current study investigated the functional connectivity of the primary sensory system with resting state fMRI and applied such knowledge into the design of the neural architecture of autonomous humanoid robots. Correlation and Granger causality analyses were utilized to reveal the functional connectivity patterns. Dissociation was within the primary sensory system, in that the olfactory cortex and the somatosensory cortex were strongly connected to the amygdala whereas the visual cortex and the auditory cortex were strongly connected with the frontal cortex. The posterior cingulate cortex (PCC) and the anterior cingulate cortex (ACC) were found to maintain constant communication with the primary sensory system, the frontal cortex, and the amygdala. Such neural architecture inspired the design of dissociated emergent-response system and fine-processing system in autonomous humanoid robots, with separate processing units and another consolidation center to coordinate the two systems. Such design can help autonomous robots to detect and respond quickly to danger, so as to maintain their sustainability and independence. PMID:21331371

  5. Implicit and explicit second language training recruit common neural mechanisms for syntactic processing.

    PubMed

    Batterink, Laura; Neville, Helen

    2013-06-01

    In contrast to native language acquisition, adult second-language (L2) acquisition occurs under highly variable learning conditions. Although most adults acquire their L2 at least partially through explicit instruction, as in a classroom setting, many others acquire their L2 primarily through implicit exposure, as is typical of an immersion environment. Whether these differences in acquisition environment play a role in determining the neural mechanisms that are ultimately recruited to process L2 grammar has not been well characterized. This study investigated this issue by comparing the ERP response to novel L2 syntactic rules acquired under conditions of implicit exposure and explicit instruction, using a novel laboratory language-learning paradigm. Native speakers tested on these stimuli showed a biphasic response to syntactic violations, consisting of an earlier negativity followed by a later P600 effect. After merely an hour of training, both implicitly and explicitly trained learners who were capable of detecting grammatical violations also elicited P600 effects. In contrast, learners who were unable to discriminate between grammatically correct and incorrect sentences did not show significant P600 effects. The magnitude of the P600 effect was found to correlate with learners' behavioral proficiency. Behavioral measures revealed that successful learners from both the implicit and explicit groups gained explicit, verbalizable knowledge about the L2 grammar rules. Taken together, these results indicate that late, controlled mechanisms indexed by the P600 play a crucial role in processing a late-learned L2 grammar, regardless of training condition. These findings underscore the remarkable plasticity of later, attention-dependent processes and their importance in lifelong learning.

  6. Implicit and Explicit Second Language Training Recruit Common Neural Mechanisms for Syntactic Processing

    PubMed Central

    Batterink, Laura; Neville, Helen

    2015-01-01

    In contrast to native language acquisition, adult second language (L2) acquisition occurs under highly variable learning conditions. While most adults acquire their L2 at least partially through explicit instruction, as in a classroom setting, many others acquire their L2 primarily through implicit exposure, as is typical of an immersion environment. Whether these differences in acquisition environment play a role in determining the neural mechanisms that are ultimately recruited to process L2 grammar has not been well characterized. The present study investigated this issue by comparing the event-related potential response to novel L2 syntactic rules acquired under conditions of implicit exposure and explicit instruction, using a novel laboratory language-learning paradigm. Native speakers tested on these stimuli showed a biphasic response to syntactic violations, consisting of an earlier negativity followed by a later P600 effect. After merely an hour of training, both implicitly- and explicitly-trained learners who were capable of detecting grammatical violations also elicited P600 effects. In contrast, learners who were unable to discriminate between grammatically correct and incorrect sentences did not show significant P600 effects. The magnitude of the P600 effect was found to correlate with learners’ behavioral proficiency. Behavioral measures revealed that successful learners from both the implicit and explicit groups gained explicit, verbalizable knowledge about the L2 grammar rules. Taken together, these results indicate that late, controlled mechanisms indexed by the P600 play a crucial role in processing a late-learned L2 grammar, regardless of training condition. These findings underscore the remarkable plasticity of later, attention-dependent processes and their importance in lifelong learning. PMID:23631551

  7. Atypical Neural Processing of Ironic and Sincere Remarks in Children and Adolescents with Autism Spectrum Disorders

    PubMed Central

    Colich, Natalie L.; Wang, Audrey-Ting; Rudie, Jeffrey D.; Hernandez, Leanna M.; Bookheimer, Susan Y.; Dapretto, Mirella

    2013-01-01

    Individuals with ASD show consistent impairment in processing pragmatic language when attention to multiple social cues (e.g., facial expression, tone of voice) is often needed to navigate social interactions. Building upon prior fMRI work examining how facial affect and prosodic cues are used to infer a speaker's communicative intent, the authors examined whether children and adolescents with ASD differ from typically developing (TD) controls in their processing of sincere versus ironic remarks. At the behavioral level, children and adolescents with ASD and matched TD controls were able to determine whether a speaker's remark was sincere or ironic equally well, with both groups showing longer response times for ironic remarks. At the neural level, for both sincere and ironic scenarios, an extended cortical network—including canonical language areas in the left hemisphere and their right hemisphere counterparts—was activated in both groups, albeit to a lesser degree in the ASD sample. Despite overall similar patterns of activity observed for the two conditions in both groups, significant modulation of activity was detected when directly comparing sincere and ironic scenarios within and between groups. While both TD and ASD groups showed significantly greater activity in several nodes of this extended network when processing ironic versus sincere remarks, increased activity was largely confined to left language areas in TD controls, whereas the ASD sample showed a more bilateral activation profile which included both language and “theory of mind” areas (i.e., ventromedial prefrontal cortex). These findings suggest that, for high-functioning individuals with ASD, increased activity in right hemisphere homologues of language areas in the left hemisphere, as well as regions involved in social cognition, may reflect compensatory mechanisms supporting normative behavioral task performance. PMID:24497750

  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. Onshore rig surplus diminishes as demand rises

    SciTech Connect

    Isenberg, E.M.

    1997-09-22

    US and international onshore surplus rig supply is diminishing rapidly as rig demand in many regions continues to increase. Consequently, capital costs associated with reactivating, constructing, and refurbishing new and existing rigs are on the rise. In addition, rising operating costs are putting upward pressure on operating costs. In order to justify replacement of existing rigs, US rig day rates will need to more than double. Current rig-market indicators show that rig demand should continue to rise at current levels, or even accelerate. Day rates will have to rise to a level that justifies investments in new capacity, and with continuing rig attrition, even more rigs will have to be built to offset deletions. It is not a matter of whether this will occur, but only when. This will not necessarily threaten the operators` returns over the long-term because technological advances will continue, resulting in lower exploration and production costs. The paper discusses the drivers of increasing demand, faster recovery rates, increasing rig demand, diminishing rig supply, and escalating component costs.

  10. The use of artificial neural network (ANN) for modeling of COD removal from antibiotic aqueous solution by the Fenton process.

    PubMed

    Elmolla, Emad S; Chaudhuri, Malay; Eltoukhy, Mohamed Meselhy

    2010-07-15

    The study examined the implementation of artificial neural network (ANN) for the prediction and simulation of antibiotic degradation in aqueous solution by the Fenton process. A three-layer backpropagation neural network was optimized to predict and simulate the degradation of amoxicillin, ampicillin and cloxacillin in aqueous solution in terms of COD removal. The configuration of the backpropagation neural network giving the smallest mean square error (MSE) was three-layer ANN with tangent sigmoid transfer function (tansig) at hidden layer with 14 neurons, linear transfer function (purelin) at output layer and Levenberg-Marquardt backpropagation training algorithm (LMA). ANN predicted results are very close to the experimental results with correlation coefficient (R(2)) of 0.997 and MSE 0.000376. The sensitivity analysis showed that all studied variables (reaction time, H(2)O(2)/COD molar ratio, H(2)O(2)/Fe(2+) molar ratio, pH and antibiotics concentration) have strong effect on antibiotic degradation in terms of COD removal. In addition, H(2)O(2)/Fe(2+) molar ratio is the most influential parameter with relative importance of 25.8%. The results showed that neural network modeling could effectively predict and simulate the behavior of the Fenton process.

  11. Implementing spiking neural networks for real-time signal-processing and control applications: a model-validated FPGA approach.

    PubMed

    Pearson, Martin J; Pipe, A G; Mitchinson, B; Gurney, K; Melhuish, C; Gilhespy, I; Nibouche, M

    2007-09-01

    In this paper, we present two versions of a hardware processing architecture for modeling large networks of leaky-integrate-and-fire (LIF) neurons; the second version provides performance enhancing features relative to the first. Both versions of the architecture use fixed-point arithmetic and have been implemented using a single field-programmable gate array (FPGA). They have successfully simulated networks of over 1000 neurons configured using biologically plausible models of mammalian neural systems. The neuroprocessor has been designed to be employed primarily for use on mobile robotic vehicles, allowing bio-inspired neural processing models to be integrated directly into real-world control environments. When a neuroprocessor has been designed to act as part of the closed-loop system of a feedback controller, it is imperative to maintain strict real-time performance at all times, in order to maintain integrity of the control system. This resulted in the reevaluation of some of the architectural features of existing hardware for biologically plausible neural networks (NNs). In addition, we describe a development system for rapidly porting an underlying model (based on floating-point arithmetic) to the fixed-point representation of the FPGA-based neuroprocessor, thereby allowing validation of the hardware architecture. The developmental system environment facilitates the cooperation of computational neuroscientists and engineers working on embodied (robotic) systems with neural controllers, as demonstrated by our own experience on the Whiskerbot project, in which we developed models of the rodent whisker sensory system.

  12. Dimethylsulfoniopropionate Promotes Process Outgrowth in Neural Cells and Exerts Protective Effects against Tropodithietic Acid

    PubMed Central

    Wichmann, Heidi; Brinkhoff, Thorsten; Simon, Meinhard; Richter-Landsberg, Christiane

    2016-01-01

    The marine environment harbors a plethora of bioactive substances, including drug candidates of potential value in the field of neuroscience. The present study was undertaken to investigate the effects of dimethylsulfoniopropionate (DMSP), produced by several algae, corals and higher plants, on cells of the mammalian nervous system, i.e., neuronal N2a and OLN-93 cells as model system for nerve cells and glia, respectively. Additionally, the protective capabilities of DMSP were assessed in cells treated with tropodithietic acid (TDA), a marine metabolite produced by several Roseobacter clade bacteria. Both cell lines, N2a and OLN-93, have previously been shown to be a sensitive target for the action of TDA, and cytotoxic effects of TDA have been connected to the induction of oxidative stress. Our data shows that DMSP promotes process outgrowth and microtubule reorganization and bundling, accompanied by an increase in alpha-tubulin acetylation. Furthermore, DMSP was able to prevent the cytotoxic effects exerted by TDA, including the breakdown of the mitochondrial membrane potential, upregulation of heat shock protein Hsp32 and activation of the extracellular signal-regulated kinases 1/2 (ERK1/2). Our study points to the conclusion that DMSP provides an antioxidant defense, not only in algae but also in mammalian neural cells. PMID:27164116

  13. Experimental and Computational Studies of Cortical Neural Network Properties Through Signal Processing

    NASA Astrophysics Data System (ADS)

    Clawson, Wesley Patrick

    Previous studies, both theoretical and experimental, of network level dynamics in the cerebral cortex show evidence for a statistical phenomenon called criticality; a phenomenon originally studied in the context of phase transitions in physical systems and that is associated with favorable information processing in the context of the brain. The focus of this thesis is to expand upon past results with new experimentation and modeling to show a relationship between criticality and the ability to detect and discriminate sensory input. A line of theoretical work predicts maximal sensory discrimination as a functional benefit of criticality, which can then be characterized using mutual information between sensory input, visual stimulus, and neural response,. The primary finding of our experiments in the visual cortex in turtles and neuronal network modeling confirms this theoretical prediction. We show that sensory discrimination is maximized when visual cortex operates near criticality. In addition to presenting this primary finding in detail, this thesis will also address our preliminary results on change-point-detection in experimentally measured cortical dynamics.

  14. Estimation of snow covered area for an urban catchment using image processing and neural networks.

    PubMed

    Matheussen, B V; Thorolfsson, S T

    2003-01-01

    This paper presents a method to estimate the snow covered area (SCA) for small urban catchments. The method uses images taken with a digital camera positioned on top of a tall building. The camera is stationary and takes overview images of the same area every fifteen minutes throughout the winter season. The images were read into an image-processing program and a three-layered feed-forward perceptron artificial neural network (ANN) was used to calculate fractional snow cover within three different land cover types (road, park and roofs). The SCA was estimated from the number of pixels with snow cover relative to the total number of pixels. The method was tested for a small urban catchment, Risvollan in Trondheim, Norway. A time series of images taken during spring of 2001 and the 2001-2002 winter season was used to generate a time series of SCA. Snow covered area was also estimated from aerial photos. The results showed a strong correlation between SCA estimated from the digital camera and the aerial photos. The time series of SCA can be used for verification of urban snowmelt models.

  15. Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

    PubMed Central

    Sato, Wataru; Kochiyama, Takanori; Uono, Shota

    2015-01-01

    The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

  16. Neural correlates in the processing of phoneme-level complexity in vowel production.

    PubMed

    Park, Haeil; Iverson, Gregory K; Park, Hae-Jeong

    2011-12-01

    We investigated how articulatory complexity at the phoneme level is manifested neurobiologically in an overt production task. fMRI images were acquired from young Korean-speaking adults as they pronounced bisyllabic pseudowords in which we manipulated phonological complexity defined in terms of vowel duration and instability (viz., COMPLEX: /tiɯi/ > MID-COMPLEX: /tiye/ > SIMPLE: /tii/). Increased activity in the left inferior frontal gyrus (Brodmann Areas (BA) 44 and 47), supplementary motor area and anterior insula was observed for the articulation of COMPLEX sequences relative to MID-COMPLEX; this was the case with the articulation of MID-COMPLEX relative to SIMPLE, except that the pars orbitalis (BA 47) was dominantly identified in the Broca's area. The differentiation indicates that phonological complexity is reflected in the neural processing of distinct phonemic representations, both by recruiting brain regions associated with retrieval of phonological information from memory and via articulatory rehearsal for the production of COMPLEX vowels. In addition, the finding that increased complexity engages greater areas of the brain suggests that brain activation can be a neurobiological measure of articulo-phonological complexity, complementing, if not substituting for, biomechanical measurements of speech motor activity.

  17. The Effect of Opioid Receptor Blockade on the Neural Processing of Thermal Stimuli

    PubMed Central

    Schoell, Eszter D.; Bingel, Ulrike; Eippert, Falk; Yacubian, Juliana; Christiansen, Kerrin; Andresen, Hilke; May, Arne; Buechel, Christian

    2010-01-01

    The endogenous opioid system represents one of the principal systems in the modulation of pain. This has been demonstrated in studies of placebo analgesia and stress-induced analgesia, where anti-nociceptive activity triggered by pain itself or by cognitive states is blocked by opioid antagonists. The aim of this study was to characterize the effect of opioid receptor blockade on the physiological processing of painful thermal stimulation in the absence of cognitive manipulation. We therefore measured BOLD (blood oxygen level dependent) signal responses and intensity ratings to non-painful and painful thermal stimuli in a double-blind, cross-over design using the opioid receptor antagonist naloxone. On the behavioral level, we observed an increase in intensity ratings under naloxone due mainly to a difference in the non-painful stimuli. On the neural level, painful thermal stimulation was associated with a negative BOLD signal within the pregenual anterior cingulate cortex, and this deactivation was abolished by naloxone. PMID:20811582

  18. Learning from experience: Event-related potential correlates of reward processing, neural adaptation, and behavioral choice

    PubMed Central

    Walsh, Matthew M.; Anderson, John R.

    2012-01-01

    To behave adaptively, we must learn from the consequences of our actions. Studies using event-related potentials (ERPs) have been informative with respect to the question of how such learning occurs. These studies have revealed a frontocentral negativity termed the feedback-related negativity (FRN) that appears after negative feedback. According to one prominent theory, the FRN tracks the difference between the values of actual and expected outcomes, or reward prediction errors. As such, the FRN provides a tool for studying reward valuation and decision making. We begin this review by examining the neural significance of the FRN. We then examine its functional significance. To understand the cognitive processes that occur when the FRN is generated, we explore variables that influence its appearance and amplitude. Specifically, we evaluate four hypotheses: (1) the FRN encodes a quantitative reward prediction error; (2) the FRN is evoked by outcomes and by stimuli that predict outcomes; (3) the FRN and behavior change with experience; and (4) the system that produces the FRN is maximally engaged by volitional actions. PMID:22683741

  19. The neural correlates of priming emotion and reward systems for conflict processing in alcoholics.

    PubMed

    Schulte, T; Jung, Y-C; Sullivan, E V; Pfefferbaum, A; Serventi, M; Müller-Oehring, E M

    2016-11-04

    Emotional dysregulation in alcoholism (ALC) may result from disturbed inhibitory mechanisms. We therefore tested emotion and alcohol cue reactivity and inhibitory processes using negative priming. To test the neural correlates of cue reactivity and negative priming, 26 ALC and 26 age-matched controls underwent functional MRI performing a Stroop color match-to-sample task. In cue reactivity trials, task-irrelevant emotion and alcohol-related pictures were interspersed between color samples and color words. In negative priming trials, pictures primed the semantic content of an alcohol or emotion Stroop word. Behaviorally, both groups showed response facilitation to picture cue trials and response inhibition to primed trials. For cue reactivity to emotion and alcohol pictures, ALC showed midbrain-limbic activation. By contrast, controls activated frontoparietal executive control regions. Greater midbrain-hippocampal activation in ALC correlated with higher amounts of lifetime alcohol consumption and higher anxiety. With negative priming, ALC exhibited frontal cortical but not midbrain-hippocampal activation, similar to the pattern observed in controls. Higher frontal activation to alcohol-priming correlated with less craving and to emotion-priming with fewer depressive symptoms. The findings suggest that neurofunctional systems in ALC can be primed to deal with upcoming emotion- and alcohol-related conflict and can overcome the prepotent midbrain-limbic cue reactivity response.

  20. Neural processing around 200 ms after stimulus-onset correlates with subjective visual awareness.

    PubMed

    Koivisto, Mika; Grassini, Simone

    2016-04-01

    Does visual awareness correlate with early activity in visual cortex or with later wide-spread neural activation? This question was studied by presenting liminal targets in one of the four quadrants of the screen and asking the participants to make forced-choice localization responses and to rate their subjective visual awareness of each target, while electroencephalography was measured. In the analyses of event-related potential (ERP) correlates of awareness, response accuracy was kept constant so that only the subjectively rated awareness varied between high-awareness ('seen' rating) and low-awareness ('unseen' rating) targets. High-awareness-correct trials were associated with enhanced contralateral N200 at 180-280 ms as compared with low-awareness-correct trials. This effect (visual awareness negativity, VAN) also correlated with aware sensitivity to the presence vs. absence of the stimulus (d'). In addition, high-awareness-correct trials were associated with later enhanced P3 amplitudes (after 350 ms), but this effect correlated only with the response bias (c). ERPs to low-awareness-correct trials elicited larger contralateral N200 than ERPs to low-awareness-incorrect trials, and this effect correlated with conservative response bias, suggesting that it reflected weak awareness rather than unconscious processing. The results suggest that the enhanced N200 correlates with graded awareness. The results support theories of visual awareness in which early activity in visual cortex gives rise to subjective visual experiences.

  1. dFasArt: dynamic neural processing in FasArt model.

    PubMed

    Cano-Izquierdo, Jose-Manuel; Almonacid, Miguel; Pinzolas, Miguel; Ibarrola, Julio

    2009-05-01

    The temporal character of the input is, generally, not taken into account in the neural models. This paper presents an extension of the FasArt model focused on the treatment of temporal signals. FasArt model is proposed as an integration of the characteristic elements of the Fuzzy System Theory in an ART architecture. A duality between the activation concept and membership function is established. FasArt maintains the structure of the Fuzzy ARTMAP architecture, implying a static character since the dynamic response of the input is not considered. The proposed novel model, dynamic FasArt (dFasArt), uses dynamic equations for the processing stages of FasArt: activation, matching and learning. The new formulation of dFasArt includes time as another characteristic of the input. This allows the activation of the units to have a history-dependent character instead of being only a function of the last input value. Therefore, dFasArt model is robust to spurious values and noisy inputs. As experimental work, some cases have been used to check the robustness of dFasArt. A possible application has been proposed for the detection of variations in the system dynamics.

  2. Improving nitrogen removal using a fuzzy neural network-based control system in the anoxic/oxic process.

    PubMed

    Huang, Mingzhi; Ma, Yongwen; Wan, Jinquan; Wang, Yan; Chen, Yangmei; Yoo, Changkyoo

    2014-10-01

    Due to the inherent complexity, uncertainty, and posterity in operating a biological wastewater treatment process, it is difficult to control nitrogen removal in the biological wastewater treatment process. In order to cope with this problem and perform a cost-effective operation, an integrated neural-fuzzy control system including a fuzzy neural network (FNN) predicted model for forecasting the nitrate concentration of the last anoxic zone and a FNN controller were developed to control the nitrate recirculation flow and realize nitrogen removal in an anoxic/oxic (A/O) process. In order to improve the network performance, a self-learning ability embedded in the FNN model was emphasized for improving the rule extraction performance. The results indicate that reasonable forecasting and control performances had been achieved through the developed control system. The effluent COD, TN, and the operation cost were reduced by about 14, 10.5, and 17 %, respectively.

  3. Searching for optimal setting conditions in technological processes using parametric estimation models and neural network mapping approach: a tutorial.

    PubMed

    Fjodorova, Natalja; Novič, Marjana

    2015-09-03

    Engineering optimization is an actual goal in manufacturing and service industries. In the tutorial we represented the concept of traditional parametric estimation models (Factorial Design (FD) and Central Composite Design (CCD)) for searching optimal setting parameters of technological processes. Then the 2D mapping method based on Auto Associative Neural Networks (ANN) (particularly, the Feed Forward Bottle Neck Neural Network (FFBN NN)) was described in comparison with traditional methods. The FFBN NN mapping technique enables visualization of all optimal solutions in considered processes due to the projection of input as well as output parameters in the same coordinates of 2D map. This phenomenon supports the more efficient way of improving the performance of existing systems. Comparison of two methods was performed on the bases of optimization of solder paste printing processes as well as optimization of properties of cheese. Application of both methods enables the double check. This increases the reliability of selected optima or specification limits.

  4. Neural pathways link social support to attenuated neuroendocrine stress responses.

    PubMed

    Eisenberger, Naomi I; Taylor, Shelley E; Gable, Shelly L; Hilmert, Clayton J; Lieberman, Matthew D

    2007-05-01

    It is well established that a lack of social support constitutes a major risk factor for morbidity and mortality, comparable to risk factors such as smoking, obesity, and high blood pressure. Although it has been hypothesized that social support may benefit health by reducing physiological reactivity to stressors, the mechanisms underlying this process remain unclear. Moreover, to date, no studies have investigated the neurocognitive mechanisms that translate experiences of social support into the health outcomes that follow. To investigate these processes, thirty participants completed three tasks in which daily social support, neurocognitive reactivity to a social stressor, and neuroendocrine responses to a social stressor were assessed. Individuals who interacted regularly with supportive individuals across a 10-day period showed diminished cortisol reactivity to a social stressor. Moreover, greater social support and diminished cortisol responses were associated with diminished activity in the dorsal anterior cingulate cortex (dACC) and Brodmann's area (BA) 8, regions previously associated with the distress of social separation. Lastly, individual differences in dACC and BA 8 reactivity mediated the relationship between high daily social support and low cortisol reactivity, such that supported individuals showed reduced neurocognitive reactivity to social stressors, which in turn was associated with reduced neuroendocrine stress responses. This study is the first to investigate the neural underpinnings of the social support-health relationship and provides evidence that social support may ultimately benefit health by diminishing neural and physiological reactivity to social stressors.

  5. Differential neural network approach in information process for prediction of roadside air pollution by peat fire

    NASA Astrophysics Data System (ADS)

    Lozhkin, V.; Tarkhov, D.; Timofeev, V.; Lozhkina, O.; Vasilyev, A.

    2016-11-01

    The paper presents a novel differential neural network model estimating the dispersion of CO emissions from a peat fire near a highway. We have developed approaches for the optimization of the model on the base of simulated and experimental measurements of CO concentrations in the area of dispersion of the smoke cloud. The numerical solutions of the problem are presented in the form of neural network approximations by the Gaussian model and in the form of neural network approximate solutions of partial differential equations. The trained neural network model can be used for the prediction of emergency when wind speed and direction and other fire parameters are changing. The method is also recommended for the development of air quality monitoring and predicting information systems.

  6. Artificial neural networks for processing fluorescence spectroscopy data in skin cancer diagnostics

    NASA Astrophysics Data System (ADS)

    Lenhardt, L.; Zeković, I.; Dramićanin, T.; Dramićanin, M. D.

    2013-11-01

    Over the years various optical spectroscopic techniques have been widely used as diagnostic tools in the discrimination of many types of malignant diseases. Recently, synchronous fluorescent spectroscopy (SFS) coupled with chemometrics has been applied in cancer diagnostics. The SFS method involves simultaneous scanning of both emission and excitation wavelengths while keeping the interval of wavelengths (constant-wavelength mode) or frequencies (constant-energy mode) between them constant. This method is fast, relatively inexpensive, sensitive and non-invasive. Total synchronous fluorescence spectra of normal skin, nevus and melanoma samples were used as input for training of artificial neural networks. Two different types of artificial neural networks were trained, the self-organizing map and the feed-forward neural network. Histopathology results of investigated skin samples were used as the gold standard for network output. Based on the obtained classification success rate of neural networks, we concluded that both networks provided high sensitivity with classification errors between 2 and 4%.

  7. Functionally integrated neural processing of linguistic and talker information: An event-related fMRI and ERP study

    PubMed Central

    Zhang, Caicai; Pugh, Kenneth R.; Mencl, W. Einar; Molfese, Peter J.; Frost, Stephen J.; Magnuson, James S.; Peng, Gang; Wang, William S-Y

    2016-01-01

    Speech signals contain information of both linguistic content and a talker’s voice. Conventionally, linguistic and talker processing are thought to be mediated by distinct neural systems in the left and right hemispheres respectively, but there is growing evidence that linguistic and talker processing interact in many ways. Previous studies suggest that talker-related vocal tract changes are processed integrally with phonetic changes in the bilateral posterior superior temporal gyrus/superior temporal sulcus (STG/STS), because the vocal tract parameter influences the perception of phonetic information. It is yet unclear whether the bilateral STG are also activated by the integral processing of another parameter – pitch, which influences the perception of lexical tone information and are related to talker differences in tone languages. In this study, we conducted separate functional magnetic resonance imaging (fMRI) and event-related potential (ERP) experiments to examine the spatial and temporal loci of interactions of lexical tone and talker-related pitch processing in Cantonese. We found that the STG was activated bilaterally during the processing of talker changes when listeners attended to lexical tone changes in the stimuli and during the processing of lexical tone changes when listeners attended to talker changes, suggesting that lexical tone and talker processing are functionally integrated in the bilateral STG. It extends the previous study, providing evidence for a general neural mechanism of integral phonetic and talker processing in the bilateral STG. The ERP results show interactions of lexical tone and talker processing 500–800 ms after auditory word onset (a simultaneous posterior P3b and a frontal negativity). Moreover, there is some asymmetry in the interaction, such that unattended talker changes affect linguistic processing more than vice versa, which may be related to the ambiguity that talker changes cause in speech perception and

  8. Automated identification of copepods using digital image processing and artificial neural network

    PubMed Central

    2015-01-01

    Background Copepods are planktonic organisms that play a major role in the marine food chain. Studying the community structure and abundance of copepods in relation to the environment is essential to evaluate their contribution to mangrove trophodynamics and coastal fisheries. The routine identification of copepods can be very technical, requiring taxonomic expertise, experience and much effort which can be very time-consuming. Hence, there is an urgent need to introduce novel methods and approaches to automate identification and classification of copepod specimens. This study aims to apply digital image processing and machine learning methods to build an automated identification and classification technique. Results We developed an automated technique to extract morphological features of copepods' specimen from captured images using digital image processing techniques. An Artificial Neural Network (ANN) was used to classify the copepod specimens from species Acartia spinicauda, Bestiolina similis, Oithona aruensis, Oithona dissimilis, Oithona simplex, Parvocalanus crassirostris, Tortanus barbatus and Tortanus forcipatus based on the extracted features. 60% of the dataset was used for a two-layer feed-forward network training and the remaining 40% was used as testing dataset for system evaluation. Our approach demonstrated an overall classification accuracy of 93.13% (100% for A. spinicauda, B. similis and O. aruensis, 95% for T. barbatus, 90% for O. dissimilis and P. crassirostris, 85% for O. similis and T. forcipatus). Conclusions The methods presented in this study enable fast classification of copepods to the species level. Future studies should include more classes in the model, improving the selection of features, and reducing the time to capture the copepod images. PMID:26678287

  9. Neural plasticity and treatment-induced recovery of sentence processing in agrammatism

    PubMed Central

    Thompson, Cynthia K.; Ouden, Dirk-Bart den; Bonakdarpour, Borna; Garibaldi, Kyla; Parrish, Todd B.

    2010-01-01

    This study examined patterns of neural activation associated with treatment-induced improvement of complex sentence production (and comprehension) in six individuals with stroke-induced agrammatic aphasia, taking into account possible alterations in blood flow often associated with stroke, including delayed time-to-peak of the hemodynamic response function (HRF) and hypoperfused tissue. Aphasic participants performed an auditory verification fMRI task, processing object cleft, subject cleft, and simple active sentences, prior to and following a course of Treatment of Underlying Forms (TUF; Thompson et al., 2003), a linguistically based approach for treating aphasic sentence deficits, which targeted object relative clause constructions. The patients also were scanned in a long-trials task to examine HRFs, to account for any local deviations resulting from stroke, and perfusion images were obtained to evaluate regions of hypoperfused tissue. Region-of-interest (ROI) analyses were conducted (bilaterally), modeling participant-specific local HRFs in left hemisphere areas activated by 12 healthy age-matched volunteers performing the same task, including the middle and inferior frontal gyri, precentral gyrus, middle and superior temporal gyri, and insula, and additional regions associated with complex syntactic processing, including the posterior perisylvian and superior parietal cortices. Results showed that, despite individual variation in activation differences from pre- to post-treatment scans in the aphasic participants, main-effects analyses revealed a general shift from left superior temporal activation to more posterior temporoparietal areas, bilaterally. Time-to-peak of these responses correlated negatively with blood flow, as measured with perfusion imaging. PMID:20603138

  10. Fluvial particle characterization using artificial neural network and spectral image processing

    NASA Astrophysics Data System (ADS)

    Shrestha, Bim Prasad; Gautam, Bijaya; Nagata, Masateru

    2008-03-01

    Sand, chemical waste, microbes and other solid materials flowing with the water bodies are of great significance to us as they cause substantial impact to different sectors including drinking water management, hydropower generation, irrigation, aquatic life preservation and various other socio-ecological factors. Such particles can't completely be avoided due to the high cost of construction and maintenance of the waste-treatment methods. A detailed understanding of solid particles in surface water system can have benefit in effective, economic, environmental and social management of water resources. This paper describes an automated system of fluvial particle characterization based on spectral image processing that lead to the development of devices for monitoring flowing particles in river. Previous research in coherent field has shown that it is possible to automatically classify shapes and sizes of solid particles ranging from 300-400 μm using artificial neural networks (ANN) and image processing. Computer facilitated with hyper spectral and multi spectral images using ANN can further classify fluvial materials into organic, inorganic, biodegradable, bio non degradable and microbes. This makes the method attractive for real time monitoring of particles, sand and microorganism in water bodies at strategic locations. Continuous monitoring can be used to determine the effect of socio-economic activities in upstream rivers, or to monitor solid waste disposal from treatment plants and industries or to monitor erosive characteristic of sand and its contribution to degradation of efficiency of hydropower plant or to identify microorganism, calculate their population and study the impact of their presence. Such system can also be used to characterize fluvial particles for planning effective utilization of water resources in micro-mega hydropower plant, irrigation, aquatic life preservation etc.

  11. A novel hybrid-maximum neural network in stereo-matching process.

    PubMed

    Laskowski, Lukasz

    2013-01-01

    In the present paper, the completely innovative architecture of artificial neural network based on Hopfield structure for solving a stereo-matching problem-hybrid neural network, consisting of the classical analog Hopfield neural network and the Maximum Neural Network-is described. The application of this kind of structure as a part of assistive device for visually impaired individuals is considered. The role of the analog Hopfield network is to find the attraction area of the global minimum, whereas Maximum Neural Network is finding accurate location of this minimum. The network presented here is characterized by an extremely high rate of work performance with the same accuracy as a classical Hopfield-like network, which makes it possible to use this kind of structure as a part of systems working in real time. The network considered here underwent experimental tests with the use of real stereo pictures as well as simulated stereo images. This enables error calculation and direct comparison with the classic analog Hopfield neural network as well as other networks proposed in the literature.

  12. Spatial Frequency Training Modulates Neural Face Processing: Learning Transfers from Low- to High-Level Visual Features

    PubMed Central

    Peters, Judith C.; van den Boomen, Carlijn; Kemner, Chantal

    2017-01-01

    Perception of visual stimuli improves with training, but improvements are specific for trained stimuli rendering the development of generic training programs challenging. It remains unknown to which extent training of low-level visual features transfers to high-level visual perception, and whether this is accompanied by neuroplastic changes. The current event-related potential (ERP) study showed that training-induced increased sensitivity to a low-level feature, namely low spatial frequency (LSF), alters neural processing of this feature in high-level visual stimuli. Specifically, neural activity related to face processing (N170), was decreased for low (trained) but not high (untrained) SF content in faces following LSF training. These novel results suggest that: (1) SF discrimination learning transfers from simple stimuli to complex objects; and that (2) training the use of specific SF information affects neural processing of facial information. These findings may open up a new avenue to improve face recognition skills in individuals with atypical SF processing, such as in cataract or Autism Spectrum Disorder (ASD). PMID:28149275

  13. Electronic Neural Networks

    NASA Technical Reports Server (NTRS)

    Thakoor, Anil

    1990-01-01

    Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

  14. Improved Neural Processing Efficiency in a Chronic Aphasia Patient Following Melodic Intonation Therapy: A Neuropsychological and Functional MRI Study

    PubMed Central

    Tabei, Ken-ichi; Satoh, Masayuki; Nakano, Chizuru; Ito, Ai; Shimoji, Yasuo; Kida, Hirotaka; Sakuma, Hajime; Tomimoto, Hidekazu

    2016-01-01

    Melodic intonation therapy (MIT) is a treatment program for the rehabilitation of aphasic patients with speech production disorders. We report a case of severe chronic non-fluent aphasia unresponsive to several years of conventional therapy that showed a marked improvement following intensive 9-day training on the Japanese version of MIT (MIT-J). The purpose of this study was to verify the efficacy of MIT-J by functional assessment and examine associated changes in neural processing by functional magnetic resonance imaging. MIT improved language output and auditory comprehension, and decreased the response time for picture naming. Following MIT-J, an area of the right hemisphere was less activated on correct naming trials than compared with before training but similarly activated on incorrect trials. These results suggest that the aphasic symptoms of our patient were improved by increased neural processing efficiency and a concomitant decrease in cognitive load. PMID:27698650

  15. Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

    PubMed Central

    Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

    2014-01-01

    The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved. PMID:24516363

  16. Introspective minds: using ALE meta-analyses to study commonalities in the neural correlates of emotional processing, social & unconstrained cognition.

    PubMed

    Schilbach, Leonhard; Bzdok, Danilo; Timmermans, Bert; Fox, Peter T; Laird, Angela R; Vogeley, Kai; Eickhoff, Simon B

    2012-01-01

    Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states.

  17. A novel spatter detection algorithm based on typical cellular neural network operations for laser beam welding processes

    NASA Astrophysics Data System (ADS)

    Nicolosi, L.; Abt, F.; Blug, A.; Heider, A.; Tetzlaff, R.; Höfler, H.

    2012-01-01

    Real-time monitoring of laser beam welding (LBW) has increasingly gained importance in several manufacturing processes ranging from automobile production to precision mechanics. In the latter, a novel algorithm for the real-time detection of spatters was implemented in a camera based on cellular neural networks. The latter can be connected to the optics of commercially available laser machines leading to real-time monitoring of LBW processes at rates up to 15 kHz. Such high monitoring rates allow the integration of other image evaluation tasks such as the detection of the full penetration hole for real-time control of process parameters.

  18. Neural dynamics of feedforward and feedback processing in figure-ground segregation.

    PubMed

    Layton, Oliver W; Mingolla, Ennio; Yazdanbakhsh, Arash

    2014-01-01

    Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

  19. At What Stage of Neural Processing Does Cocaine Act to Boost Pursuit of Rewards?

    PubMed Central

    Hernandez, Giovanni; Breton, Yannick-André; Conover, Kent; Shizgal, Peter

    2010-01-01

    Dopamine-containing neurons have been implicated in reward and decision making. One element of the supporting evidence is that cocaine, like other drugs that increase dopaminergic neurotransmission, powerfully potentiates reward seeking. We analyze this phenomenon from a novel perspective, introducing a new conceptual framework and new methodology for determining the stage(s) of neural processing at which drugs, lesions and physiological manipulations act to influence reward-seeking behavior. Cocaine strongly boosts the proclivity of rats to work for rewarding electrical brain stimulation. We show that the conventional conceptual framework and methods do not distinguish between three conflicting accounts of how the drug produces this effect: increased sensitivity of brain reward circuitry, increased gain, or decreased subjective reward costs. Sensitivity determines the stimulation strength required to produce a reward of a given intensity (a measure analogous to the KM of an enzyme) whereas gain determines the maximum intensity attainable (a measure analogous to the vmax of an enzyme-catalyzed reaction). To distinguish sensitivity changes from the other determinants, we measured and modeled reward seeking as a function of both stimulation strength and opportunity cost. The principal effect of cocaine was a two-fourfold increase in willingness to pay for the electrical reward, an effect consistent with increased gain or decreased subjective cost. This finding challenges the long-standing view that cocaine increases the sensitivity of brain reward circuitry. We discuss the implications of the results and the analytic approach for theories of how dopaminergic neurons and other diffuse modulatory brain systems contribute to reward pursuit, and we explore the implications of the conceptual framework for the study of natural rewards, drug reward, and mood. PMID:21152097

  20. Biological neural networks as model systems for designing future parallel processing computers

    NASA Technical Reports Server (NTRS)

    Ross, Muriel D.

    1991-01-01

    One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

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

    PubMed Central

    Crabtree, Gregg W.; Gogos, Joseph A.

    2014-01-01

    Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations. PMID:25505409

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

    PubMed

    Crabtree, Gregg W; Gogos, Joseph A

    2014-01-01

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

  3. Dissociating the Neural Basis of Conceptual Self-Awareness from Perceptual Awareness and Unaware Self-Processing.

    PubMed

    Tacikowski, Pawel; Berger, Christopher C; Ehrsson, H Henrik

    2017-01-23

    Conceptual self-awareness is a mental state in which the content of one's consciousness refers to a particular aspect of semantic knowledge about oneself. This form of consciousness plays a crucial role in shaping human behavior; however, little is known about its neural basis. Here, we use functional magnetic resonance imaging (fMRI) and a visual masked priming paradigm to dissociate the neural responses related to the awareness of semantic autobiographical information (one's own name, surname, etc.) from the awareness of information related to any visual stimulus (perceptual awareness), as well as from the unaware processing of self-relevant stimuli. To detect brain activity that is highly selective for self-relevant information, we used the blood-oxygen-level-dependent (BOLD) adaptation approach, which goes beyond the spatial limitations of conventional fMRI. We found that self-awareness was associated with BOLD adaptation in the medial frontopolar-retrosplenial areas, whereas perceptual awareness and unaware self-processing were associated with BOLD adaptation in the lateral fronto-parietal areas and the inferior temporal cortex, respectively. Thus, using a direct manipulation of conscious awareness we demonstrate for the first time that the neural basis of conceptual self-awareness is neuroanatomically distinct from the network mediating perceptual awareness of the sensory environment or unaware processing of self-related stimuli.

  4. 32 CFR 776.33 - Client with diminished capacity.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 32 National Defense 5 2012-07-01 2012-07-01 false Client with diminished capacity. 776.33 Section... Rules of Professional Conduct § 776.33 Client with diminished capacity. (a) Client with diminished capacity: (1) When a client's ability to make adequately considered decisions in connection with...

  5. 32 CFR 776.33 - Client with diminished capacity.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 32 National Defense 5 2013-07-01 2013-07-01 false Client with diminished capacity. 776.33 Section... Rules of Professional Conduct § 776.33 Client with diminished capacity. (a) Client with diminished capacity: (1) When a client's ability to make adequately considered decisions in connection with...

  6. 32 CFR 776.33 - Client with diminished capacity.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 32 National Defense 5 2011-07-01 2011-07-01 false Client with diminished capacity. 776.33 Section... Rules of Professional Conduct § 776.33 Client with diminished capacity. (a) Client with diminished capacity: (1) When a client's ability to make adequately considered decisions in connection with...

  7. 32 CFR 776.33 - Client with diminished capacity.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 32 National Defense 5 2014-07-01 2014-07-01 false Client with diminished capacity. 776.33 Section... Rules of Professional Conduct § 776.33 Client with diminished capacity. (a) Client with diminished capacity: (1) When a client's ability to make adequately considered decisions in connection with...

  8. Neural Networks

    SciTech Connect

    Smith, Patrick I.

    2003-09-23

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  9. A Decade of Diminishing Sunspot Vigor

    NASA Astrophysics Data System (ADS)

    Livingston, W. C.; Penn, M.; Svalgard, L.

    2011-05-01

    1A Decade of Diminishing Sunspot Vigor William Livingston1 Matt Penn1 Leif Svalgard2 Sunspots are small dark areas on the solar disk where internal magnetism, 1500 to 3500 Gauss, has been buoyed to the surface. (Spot life times are the order of one day to a couple of weeks or more. They are thought to be dark because convection inhibits the outward transport of energy there). Their "vigor” can be described by spot area, spot brightness intensity, and magnetic field. From 2001 to 2011 we have measured field strength and brightness at the darkest position in umbrae of 1750 spots using the Zeeman splitting of the Fe 1564.8 nm line. Only one observation per spot per day is carried out during our monthly telescope time of 3-4 days average. Over this interval the temporal mean magnetic field has declined about 500 Gauss and mean spot intensity has risen about 20%. We do not understand the physical mechanism behind these changes or the effect, if any, it will have on the Earth environment. 1. wcl@noao.edu mpenn@noao.edu 2. leif@leif.org

  10. EEG frequency tagging dissociates between neural processing of motion synchrony and human quality of multiple point-light dancers

    PubMed Central

    Alp, Nihan; Nikolaev, Andrey R.; Wagemans, Johan; Kogo, Naoki

    2017-01-01

    Do we perceive a group of dancers moving in synchrony differently from a group of drones flying in-sync? The brain has dedicated networks for perception of coherent motion and interacting human bodies. However, it is unclear to what extent the underlying neural mechanisms overlap. Here we delineate these mechanisms by independently manipulating the degree of motion synchrony and the humanoid quality of multiple point-light displays (PLDs). Four PLDs moving within a group were changing contrast in cycles of fixed frequencies, which permits the identification of the neural processes that are tagged by these frequencies. In the frequency spectrum of the steady-state EEG we found two emergent frequency components, which signified distinct levels of interactions between PLDs. The first component was associated with motion synchrony, the second with the human quality of the moving items. These findings indicate that visual processing of synchronously moving dancers involves two distinct neural mechanisms: one for the perception of a group of items moving in synchrony and one for the perception of a group of moving items with human quality. We propose that these mechanisms underlie high-level perception of social interactions. PMID:28272421

  11. The use of artificial neural network for modeling the decolourization of acid orange 7 solution of industrial by ozonation process

    NASA Astrophysics Data System (ADS)

    Fatimah, S.; Wiharto, W.

    2017-02-01

    Acid Orange 7 (AO7) is one of the synthetic dye in the dyeing process in the textile industry. The use of this dye can produce wastewater which will be endangered if not treated well. Ozonation method is one technique to solve this problem. Ozonation is a waste processing techniques using ozone as an oxidizing agent. Variables used in this research is the ozone concentration, the initial concentration of AO7, temperature, and pH. Based on the experimental result that the optimum value decolourization percentage is 80% when the ozone concentration is 560 mg/L, the initial concentration AO7 is 14 mg/L, the temperature is 390 °C, and pH is 7,6. Decolourization efficiency of experimental results and predictions successfully modelled by the neural network architecture. The data used to construct a neural network architecture quasi newton one step secant as many as 31 data. A comparison between the predicted results of the designed ANN models and experiment was conducted. From the modeling results obtained MAPE value of 0.7763%. From the results of this artificial neural network architecture obtained the optimum value decolourization percentage in 80,64% when the concentration of ozone is 550 mg/L, the initial concentration AO7 is 11 mg/L, the temperature is 41 °C, and the pH is 7.9.

  12. The potato chip really does look like Elvis! Neural hallmarks of conceptual processing associated with finding novel shapes subjectively meaningful.

    PubMed

    Voss, Joel L; Federmeier, Kara D; Paller, Ken A

    2012-10-01

    Clouds and inkblots often compellingly resemble something else--faces, animals, or other identifiable objects. Here, we investigated illusions of meaning produced by novel visual shapes. Individuals found some shapes meaningful and others meaningless, with considerable variability among individuals in these subjective categorizations. Repetition for shapes endorsed as meaningful produced conceptual priming in a priming test along with concurrent activity reductions in cortical regions associated with conceptual processing of real objects. Subjectively meaningless shapes elicited robust activity in the same brain areas, but activity was not influenced by repetition. Thus, all shapes were conceptually evaluated, but stable conceptual representations supported neural priming for meaningful shapes only. During a recognition memory test, performance was associated with increased frontoparietal activity, regardless of meaningfulness. In contrast, neural conceptual priming effects for meaningful shapes occurred during both priming and recognition testing. These different patterns of brain activation as a function of stimulus repetition, type of memory test, and subjective meaningfulness underscore the distinctive neural bases of conceptual fluency versus episodic memory retrieval. Finding meaning in ambiguous stimuli appears to depend on conceptual evaluation and cortical processing events similar to those typically observed for known objects. To the brain, the vaguely Elvis-like potato chip truly can provide a substitute for the King himself.

  13. Neural responses to witnessing peer rejection after being socially excluded: fMRI as a window into adolescents’ emotional processing

    PubMed Central

    Masten, Carrie L.; Eisenberger, Naomi I.; Pfeifer, Jennifer H.; Dapretto, Mirella

    2013-01-01

    During adolescence, concerns about peer rejection and acceptance become increasingly common. Adolescents regularly experience peer rejection firsthand and witness these behaviors among their peers. In the current study, neuroimaging techniques were employed to conduct a preliminary investigation of the affective and cognitive processes involved in witnessing peer acceptance and rejection—specifically when these witnessed events occur in the immediate aftermath of a firsthand experience with rejection. During an fMRI scan, twenty-three adolescents underwent a simulated experience of firsthand peer rejection. Then, immediately following this experience they watched as another adolescent was ostensibly first accepted and then rejected. Findings indicated that in the immediate aftermath of being rejected by peers, adolescents displayed neural activity consistent with distress when they saw another peer being accepted, and neural activity consistent with emotion regulation and mentalizing (e.g., perspective-taking) processes when they saw another peer being rejected. Furthermore, individuals displaying a heightened sensitivity to firsthand rejection were more likely to show neural activity consistent with distress when observing a peer being accepted. Findings are discussed in terms of how witnessing others being accepted or rejected relates to adolescents’ interpretations of both firsthand and observed experiences with peers. Additionally, the potential impact that witnessed events might have on the broader perpetuation of bullying at this age is also considered. PMID:24033579

  14. Neural Systems Underlying Emotional and Non-emotional Interference Processing: An ALE Meta-Analysis of Functional Neuroimaging Studies

    PubMed Central

    Xu, Min; Xu, Guiping; Yang, Yang

    2016-01-01

    Understanding how the nature of interference might influence the recruitments of the neural systems is considered as the key to understanding cognitive control. Although, interference processing in the emotional domain has recently attracted great interest, the question of whether there are separable neural patterns for emotional and non-emotional interference processing remains open. Here, we performed an activation likelihood estimation meta-analysis of 78 neuroimaging experiments, and examined common and distinct neural systems for emotional and non-emotional interference processing. We examined brain activation in three domains of interference processing: emotional verbal interference in the face-word conflict task, non-emotional verbal interference in the color-word Stroop task, and non-emotional spatial interference in the Simon, SRC and Flanker tasks. Our results show that the dorsal anterior cingulate cortex (ACC) was recruited for both emotional and non-emotional interference. In addition, the right anterior insula, presupplementary motor area (pre-SMA), and right inferior frontal gyrus (IFG) were activated by interference processing across both emotional and non-emotional domains. In light of these results, we propose that the anterior insular cortex may serve to integrate information from different dimensions and work together with the dorsal ACC to detect and monitor conflicts, whereas pre-SMA and right IFG may be recruited to inhibit inappropriate responses. In contrast, the dorsolateral prefrontal cortex (DLPFC) and posterior parietal cortex (PPC) showed different degrees of activation and distinct lateralization patterns for different processing domains, which suggests that these regions may implement cognitive control based on the specific task requirements. PMID:27895564

  15. Neural Responses to Meaningless Pseudosigns: Evidence for Sign-Based Phonetic Processing in Superior Temporal Cortex

    ERIC Educational Resources Information Center

    Emmorey, Karen; Xu, Jiang; Braun, Allen

    2011-01-01

    To identify neural regions that automatically respond to linguistically structured, but meaningless manual gestures, 14 deaf native users of American Sign Language (ASL) and 14 hearing non-signers passively viewed pseudosigns (possible but non-existent ASL signs) and non-iconic ASL signs, in addition to a fixation baseline. For the contrast…

  16. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control

    DTIC Science & Technology

    1992-12-29

    Transactions on Robotics and Automation 8(3):293-303. Nye, S.W. and Ritzmann, R.E. (1992). Motion analysis of leg joints associated with escape turns...122. Chiel, H.J., Beer, R.D., Quinn, R.D. and Espenschied, K. (1992). Robustness of a distributed neural network controller for a hexapod robot. IEEE

  17. Artificial neural network modeling of DDGS flowability with varying process and storage parameters

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Neural Network (NN) modeling techniques were used to predict flowability behavior in distillers dried grains with solubles (DDGS) prepared with varying CDS (10, 15, and 20%, wb), drying temperature (100, 200, and 300°C), cooling temperature (-12, 0, and 35°C) and cooling time (0 and 1 month) levels....

  18. Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

    PubMed

    Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

    2012-01-11

    Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

  19. Neural and Behavioral Responses during Self-Evaluative Processes Differ in Youth with and without Autism

    ERIC Educational Resources Information Center

    Pfeifer, Jennifer H.; Merchant, Junaid S.; Colich, Natalie L.; Hernandez, Leanna M.; Rudie, Jeff D.; Dapretto, Mirella

    2013-01-01

    This fMRI study investigated neural responses while making appraisals of self and other, across the social and academic domains, in children and adolescents with and without autism spectrum disorders (ASD). Compared to neurotypical youth, those with ASD exhibited hypoactivation of ventromedial prefrontal cortex during self-appraisals. Responses in…

  20. Neural networks-based modeling applied to a process of heavy metals removal from wastewaters.

    PubMed

    Suditu, Gabriel D; Curteanu, Silvia; Bulgariu, Laura

    2013-01-01

    This article approaches the problem of environment pollution with heavy metals from disposal of industrial wastewaters, namely removal of these metals by means of biosorbents, particularly with Romanian peat (from Poiana Stampei). The study is carried out by simulation using feed-forward and modular neural networks with one or two hidden layers, pursuing the influence of certain operating parameters (metal nature, sorbent dose, pH, temperature, initial concentration of metal ion, contact time) on the amount of metal ions retained on the unit mass of sorbent. In neural network modeling, a consistent data set was used, including five metals: lead, mercury, cadmium, nickel and cobalt, the quantification of the metal nature being done by its electronegativity. Even if based on successive trials, the method of designing neural models was systematically conducted, recording and comparing the errors obtained with different types of neural networks, having various numbers of hidden layers and neurons, number of training epochs, or using various learning methods. The errors with values under 5% make clear the efficiency of the applied method.

  1. The Sustained Effect of Emotional Signals on Neural Processing in 12-Month-Olds

    ERIC Educational Resources Information Center

    Leventon, Jacqueline S.; Bauer, Patricia J.

    2013-01-01

    Around the end of the first year of life, infants develop a social referencing ability -- using emotional information from others to guide their own behavior. Much research on social referencing has focused on changes in behavior in response to emotional information. The present study was an investigation of the changes in neural responses that…

  2. Neural Dissociation of Number from Letter Recognition and Its Relationship to Parietal Numerical Processing

    ERIC Educational Resources Information Center

    Park, Joonkoo; Hebrank, Andrew; Polk, Thad A.; Park, Denise C.

    2012-01-01

    The visual recognition of letters dissociates from the recognition of numbers at both the behavioral and neural level. In this article, using fMRI, we investigate whether the visual recognition of numbers dissociates from letters, thereby establishing a double dissociation. In Experiment 1, participants viewed strings of consonants and Arabic…

  3. Neural Correlates of Facial Affect Processing in Children and Adolescents with Autism Spectrum Disorder.

    ERIC Educational Resources Information Center

    Wang, A. Ting; Dapretto, Mirella; Hariri, Ahmad R.; Sigman, Marian; Bookheimer, Susan Y.

    2004-01-01

    Objective: To examine the neural basis of impairments in interpreting facial emotions in children and adolescents with autism spectrum disorders (ASD). Method: Twelve children and adolescents with ASD and 12 typically developing (TD) controls matched faces by emotion and assigned a label to facial expressions while undergoing functional magnetic…

  4. Neural Differences in Bilingual Children's Arithmetic Processing Depending on Language of Instruction

    ERIC Educational Resources Information Center

    Mondt, Katrien; Struys, Esli; Van den Noort, Maurits; Baleriaux, Danielle; Metens, Thierry; Paquier, Philippe; Van de Craen, Piet; Bosch, Peggy; Denolin, Vincent

    2011-01-01

    Many children in bilingual regions follow lessons in a language at school (school-language) that they hardly ever speak at home or in other informal settings. What are the neural effects of this phenomenon? This functional magnetic resonance imaging (fMRI) study investigates the effects of using school-language on brain activity during a high…

  5. Spintronic characteristics of self-assembled neurotransmitter acetylcholine molecular complexes enable quantum information processing in neural networks and brain

    NASA Astrophysics Data System (ADS)

    Tamulis, Arvydas; Majauskaite, Kristina; Kairys, Visvaldas; Zborowski, Krzysztof; Adhikari, Kapil; Krisciukaitis, Sarunas

    2016-09-01

    Implementation of liquid state quantum information processing based on spatially localized electronic spin in the neurotransmitter stable acetylcholine (ACh) neutral molecular radical is discussed. Using DFT quantum calculations we proved that this molecule possesses stable localized electron spin, which may represent a qubit in quantum information processing. The necessary operating conditions for ACh molecule are formulated in self-assembled dimer and more complex systems. The main quantum mechanical research result of this paper is that the neurotransmitter ACh systems, which were proposed, include the use of quantum molecular spintronics arrays to control the neurotransmission in neural networks.

  6. Applications of neural networks to real-time data processing at the Environmental and Molecular Sciences Laboratory (EMSL)

    SciTech Connect

    Keller, P.E.; Kouzes, R.T.; Kangas, L.J.

    1993-06-01

    Detailed design of the Environmental and Molecular Sciences Laboratory (EMSL) at the Pacific Northwest Laboratory (PNL) is nearing completion and construction is scheduled to begin later this year. This facility will assist in the environmental restoration and waste management mission at the Hanford Site. This paper identifies several real-time data processing applications within the EMSL where neural networks can potentially be beneficial. These applications include real-time sensor data acquisition and analysis, spectral analysis, process control, theoretical modeling, and data compression.

  7. 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.

  8. Group Interaction Sustains Positive Moods and Diminishes Negative Moods.

    PubMed

    Park, Ernest S; Hinsz, Verlin B

    2015-12-01

    The social interactions of task groups were investigated for their influences on member moods. Initially, participants' received an induction of positive, negative, or neutral moods via listening to music that continued throughout the experimental session. Moods were measured after the induction. Students then made decisions on four choice dilemmas alone or as members of a four-person group. Subsequently, positive and negative moods were again measured. Positive moods of participants who worked with other group members on the task were sustained, but diminished for those working alone. Negative moods of participants working in groups diminished over time, but were sustained for those working individually. These results were interpreted in the context of motivational systems theory of group involvement (Park & Hinsz, 2006). Additionally, although there was a tendency for member moods to homogenize over assessments, this did not reach significance. Results document the affective benefits that often accompany task group interaction suggesting that group interaction has features of positive mood induction. This report highlights the need to consider social influences on affect in task settings so that group dynamics, processes, and behaviors can be better understood.

  9. Low aggregation state diminishes ferrihydrite reactivity

    NASA Astrophysics Data System (ADS)

    Braunschweig, Juliane; Heister, Katja; Meckenstock, Rainer U.

    2013-04-01

    Ferrihydrite is an abundant iron(oxy)hydroxide in soils and sediments and plays an important role in microbial iron cycling due to its high reactivity. Therefore, it is often synthesized and used in geomicrobiological and mineralogical studies. The reactivities of synthetic ferrihydrites vary between different studies and synthesis protocols. Hence, we synthesized five different ferrihydrites and characterized them with XRD, FTIR, XPS, and BET specific surface area. The reactivity of the ferrihydrite samples towards ascorbic acid was examined and compared with microbial reduction rates by Geobacter sulfurreducens. FTIR and XRD results show the presence of secondary, higher crystalline iron oxide phases like goethite and akaganeite for two samples. Consequently, those samples revealed lower biotic and abiotic reduction rates compared to pure ferrihydrite. Comparison of reduction rates with the specific surface area of all ferrihydrites showed neither correlation with abiotic reductive dissolution nor with microbial reduction. Especially one sample, characterized by a very low aggregation state and presence of secondary minerals, revealed a poor reactivity. We speculate that apart from the occurring secondary minerals also the low aggregation state played an important role. Decreasing aggregation diminishes the amount of kinks and edges on the surfaces, which are produced at contact sites in aggregates. According to dissolution theories, dissolution mainly starts at those surface defects and slows down with decreasing amount of defects. Furthermore, the non-aggregated ferrihydrite is free of micropores, a further stimulant for dissolution. Independent repetitions of experiments and syntheses according to the same protocol but without formation of secondary minerals, confirmed the low reactivity of the non-aggregated ferrihydrite. In summary, our results indicate that a decreasing aggregation state of ferrihydrite to a certain size does increase the reactivity

  10. Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach.

    PubMed

    Cichy, Radoslaw Martin; Teng, Santani

    2017-02-19

    In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research.This article is part of the themed issue 'Auditory and visual scene analysis'.

  11. Resolving the neural dynamics of visual and auditory scene processing in the human brain: a methodological approach

    PubMed Central

    Teng, Santani

    2017-01-01

    In natural environments, visual and auditory stimulation elicit responses across a large set of brain regions in a fraction of a second, yielding representations of the multimodal scene and its properties. The rapid and complex neural dynamics underlying visual and auditory information processing pose major challenges to human cognitive neuroscience. Brain signals measured non-invasively are inherently noisy, the format of neural representations is unknown, and transformations between representations are complex and often nonlinear. Further, no single non-invasive brain measurement technique provides a spatio-temporally integrated view. In this opinion piece, we argue that progress can be made by a concerted effort based on three pillars of recent methodological development: (i) sensitive analysis techniques such as decoding and cross-classification, (ii) complex computational modelling using models such as deep neural networks, and (iii) integration across imaging methods (magnetoencephalography/electroencephalography, functional magnetic resonance imaging) and models, e.g. using representational similarity analysis. We showcase two recent efforts that have been undertaken in this spirit and provide novel results about visual and auditory scene analysis. Finally, we discuss the limits of this perspective and sketch a concrete roadmap for future research. This article is part of the themed issue ‘Auditory and visual scene analysis’. PMID:28044019

  12. In our own image? Emotional and neural processing differences when observing human–human vs human–robot interactions

    PubMed Central

    Wang, Yin

    2015-01-01

    Notwithstanding the significant role that human–robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human–human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal–parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. PMID:25911418

  13. In our own image? Emotional and neural processing differences when observing human-human vs human-robot interactions.

    PubMed

    Wang, Yin; Quadflieg, Susanne

    2015-11-01

    Notwithstanding the significant role that human-robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human-human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal-parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots.

  14. A phase transition in the first passage of a Brownian process through a fluctuating boundary with implications for neural coding.

    PubMed

    Taillefumier, Thibaud; Magnasco, Marcelo O

    2013-04-16

    Finding the first time a fluctuating quantity reaches a given boundary is a deceptively simple-looking problem of vast practical importance in physics, biology, chemistry, neuroscience, economics, and industrial engineering. Problems in which the bound to be traversed is itself a fluctuating function of time include widely studied problems in neural coding, such as neuronal integrators with irregular inputs and internal noise. We show that the probability p(t) that a Gauss-Markov process will first exceed the boundary at time t suffers a phase transition as a function of the roughness of the boundary, as measured by its Hölder exponent H. The critical value occurs when the roughness of the boundary equals the roughness of the process, so for diffusive processes the critical value is Hc = 1/2. For smoother boundaries, H > 1/2, the probability density is a continuous function of time. For rougher boundaries, H < 1/2, the probability is concentrated on a Cantor-like set of zero measure: the probability density becomes divergent, almost everywhere either zero or infinity. The critical point Hc = 1/2 corresponds to a widely studied case in the theory of neural coding, in which the external input integrated by a model neuron is a white-noise process, as in the case of uncorrelated but precisely balanced excitatory and inhibitory inputs. We argue that this transition corresponds to a sharp boundary between rate codes, in which the neural firing probability varies smoothly, and temporal codes, in which the neuron fires at sharply defined times regardless of the intensity of internal noise.

  15. Recurrent fractal neural networks: a strategy for the exchange of local and global information processing in the brain.

    PubMed

    Bieberich, Erhard

    2002-01-01

    The regulation of biological networks relies significantly on convergent feedback signaling loops that render a global output locally accessible. Ideally, the recurrent connectivity within these systems is self-organized by a time-dependent phase-locking mechanism. This study analyzes recurrent fractal neural networks (RFNNs), which utilize a self-similar or fractal branching structure of dendrites and downstream networks for phase-locking of reciprocal feedback loops: output from outer branch nodes of the network tree enters inner branch nodes of the dendritic tree in single neurons. This structural organization enables RFNNs to amplify re-entrant input by over-the-threshold signal summation from feedback loops with equivalent signal traveling times. The columnar organization of pyramidal neurons in the neocortical layers V and III is discussed as the structural substrate for this network architecture. RFNNs self-organize spike trains and render the entire neural network output accessible to the dendritic tree of each neuron within this network. As the result of a contraction mapping operation, the local dendritic input pattern contains a downscaled version of the network output coding structure. RFNNs perform robust, fractal data compression, thus coping with a limited number of feedback loops for signal transport in convergent neural networks. This property is discussed as a significant step toward the solution of a fundamental problem in neuroscience: how is neuronal computation in separate neurons and remote brain areas unified as an instance of experience in consciousness? RFNNs are promising candidates for engaging neural networks into a coherent activity and provide a strategy for the exchange of global and local information processing in the human brain, thereby ensuring the completeness of a transformation from neuronal computation into conscious experience.

  16. The diminishing criterion model for metacognitive regulation of time investment.

    PubMed

    Ackerman, Rakefet

    2014-06-01

    According to the Discrepancy Reduction Model for metacognitive regulation, people invest time in cognitive tasks in a goal-driven manner until their metacognitive judgment, either judgment of learning (JOL) or confidence, meets their preset goal. This stopping rule should lead to judgments above the goal, regardless of invested time. However, in many tasks, time is negatively correlated with JOL and confidence, with low judgments after effortful processing. This pattern has often been explained as stemming from bottom-up fluency effects on the judgments. While accepting this explanation for simple tasks, like memorizing pairs of familiar words, the proposed Diminishing Criterion Model (DCM) challenges this explanation for complex tasks, like problem solving. Under the DCM, people indeed invest effort in a goal-driven manner. However, investing more time leads to increasing compromise on the goal, resulting in negative time-judgment correlations. Experiment 1 exposed that with word-pair memorization, negative correlations are found only with minimal fluency and difficulty variability, whereas in problem solving, they are found consistently. As predicted, manipulations of low incentives (Experiment 2) and time pressure (Experiment 3) in problem solving revealed greater compromise as more time was invested in a problem. Although intermediate confidence ratings rose during the solving process, the result was negative time-confidence correlations (Experiments 3, 4, and 5), and this was not eliminated by the opportunity to respond "don't know" (Experiments 4 and 5). The results suggest that negative time-judgment correlations in complex tasks stem from top-down regulatory processes with a criterion that diminishes with invested time.

  17. Beat synchronization predicts neural speech encoding and reading readiness in preschoolers.

    PubMed

    Woodruff Carr, Kali; White-Schwoch, Travis; Tierney, Adam T; Strait, Dana L; Kraus, Nina

    2014-10-07

    Temporal cues are important for discerning word boundaries and syllable segments in speech; their perception facilitates language acquisition and development. Beat synchronization and neural encoding of speech reflect precision in processing temporal cues and have been linked to reading skills. In poor readers, diminished neural precision may contribute to rhythmic and phonological deficits. Here we establish links between beat synchronization and speech processing in children who have not yet begun to read: preschoolers who can entrain to an external beat have more faithful neural encoding of temporal modulations in speech and score higher on tests of early language skills. In summary, we propose precise neural encoding of temporal modulations as a key mechanism underlying reading acquisition. Because beat synchronization abilities emerge at an early age, these findings may inform strategies for early detection of and intervention for language-based learning disabilities.

  18. Comparison of Computational, Model and Experimental, Example Trained Neural Networks for Processing Speckled Fringe Patterns

    NASA Technical Reports Server (NTRS)

    Decker, A. J.; Fite, E. B.; Thorp, S. A.; Mehmed, O.

    1998-01-01

    The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model- generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models.

  19. Behavioral and Neuroeconomics of Drug Addiction: Competing Neural Systems and Temporal Discounting Processes

    PubMed Central

    Bickel, Warren K.; Miller, Michelle L.; Yi, Richard; Kowal, Benjamin P.; Lindquist, Diana M.; Pitcock, Jeffery A.

    2007-01-01

    We review behavioral- and neuroeconomic research that identifies temporal discounting as an important component in the development and maintenance of drug addiction. First we review behavioral economic research that explains and documents the contribution of temporal discounting to addiction. This is followed with recent insights from neuroeconomics that may provide an explanation of why drug dependent individuals discount the future. Specifically, neuroeconomics has identified two competing neural systems that are related to temporal discounting using brain-imaging techniques that examine the relative activation of different brain regions for temporal discounting. According to the competing neural systems account, choices for delayed outcomes are related to the prefrontal cortex (i.e., the “executive system”) and choices for immediate outcomes are related to the limbic brain regions (i.e., the “impulsive system”). Temporal discounting provides a useful framework for future imaging research, and suggests a novel approach to designing effective drug dependence prevention and treatment programs. PMID:17101239

  20. The effects of parental behavior on infants' neural processing of emotion expressions.

    PubMed

    Taylor-Colls, Samantha; Pasco Fearon, R M

    2015-01-01

    Infants become sensitive to emotion expressions early in the 1st year and such sensitivity is likely crucial for social development and adaptation. Social interactions with primary caregivers may play a key role in the development of this complex ability. This study aimed to investigate how variations in parenting behavior affect infants' neural responses to emotional faces. Event-related potentials (ERPs) to emotional faces were recorded from 40 healthy 7-month-old infants (24 males). Parental behavior was assessed and coded using the Emotional Availability Scales during free-play interaction. Sensitive parenting was associated with increased amplitudes to positive facial expressions on the face-sensitive ERP component, the negative central. Findings are discussed in relation to the interactive mechanisms influencing how infants neurally encode positive emotions.

  1. Neural Features of Processing the Enforcement Phrases Used during Occupational Health and Safety Inspections: An ERP Study.

    PubMed

    Ma, Qingguo; Shi, Liping; Hu, Linfeng; Liu, Qiang; Yang, Zheng; Wang, Qiuzhen

    2016-01-01

    The appropriate enforcement phrases used during occupational health and safety (OHS) inspection activities is a crucial factor to guarantee the compliance with OHS regulations in enterprises. However, few researchers have empirically investigated the issue of how enforcement phrases are processed. The present study explored the neural features of processing two types of enforcement phrases (severe-and-deterrent vs. mild-and-polite phrases) used during OHS inspections by applying event-related potentials (ERP) method. Electroencephalogram data were recorded while the participants distinguished between severe-and-deterrent phrases and mild-and-polite phrases depicted in written Chinese words. The ERP results showed that severe-and-deterrent phrases elicited significantly augmented P300 amplitude with a central-parietal scalp distribution compared with mild-and-polite phrases, indicating the allocation of more attention resources to and elaborate processing of the severe-and-deterrent phrases. It reveals that humans may consider the severe-and-deterrent phrases as more motivationally significant and elaborately process the severity and deterrence information contained in the enforcement phrases for the adaptive protection. The current study provides an objective and supplementary way to measure the efficiency of different enforcement phrases at neural level, which may help generate appropriate enforcement phrases and improve the performance of OHS inspections.

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

    PubMed Central

    2007-01-01

    The neural regulation of emotional perception, learning, and memory is essential for normal behavioral and cognitive functioning. Many of the symptoms displayed by individuals with schizophrenia may arise from fundamental disturbances in the ability to accurately process emotionally salient sensory information. The neurotransmitter dopamine (DA) and its ability to modulate neural regions involved in emotional learning, perception, and memory formation has received considerable research attention as a potential final common pathway to account for the aberrant emotional regulation and psychosis present in the schizophrenic syndrome. Evidence from both human neuroimaging studies and animal-based research using neurodevelopmental, behavioral, and electrophysiological techniques have implicated the mesocorticolimbic DA circuit as a crucial system for the encoding and expression of emotionally salient learning and memory formation. While many theories have examined the cortical-subcortical interactions between prefrontal cortical regions and subcortical DA substrates, many questions remain as to how DA may control emotional perception and learning and how disturbances linked to DA abnormalities may underlie the disturbed emotional processing in schizophrenia. Beyond the mesolimbic DA system, increasing evidence points to the amygdala-prefrontal cortical circuit as an important processor of emotionally salient information and how neurodevelopmental perturbances within this circuitry may lead to dysregulation of DAergic modulation of emotional processing and learning along this cortical-subcortical emotional processing circuit. PMID:17519393

  3. Neural Features of Processing the Enforcement Phrases Used during Occupational Health and Safety Inspections: An ERP Study

    PubMed Central

    Ma, Qingguo; Shi, Liping; Hu, Linfeng; Liu, Qiang; Yang, Zheng; Wang, Qiuzhen

    2016-01-01

    The appropriate enforcement phrases used during occupational health and safety (OHS) inspection activities is a crucial factor to guarantee the compliance with OHS regulations in enterprises. However, few researchers have empirically investigated the issue of how enforcement phrases are processed. The present study explored the neural features of processing two types of enforcement phrases (severe-and-deterrent vs. mild-and-polite phrases) used during OHS inspections by applying event-related potentials (ERP) method. Electroencephalogram data were recorded while the participants distinguished between severe-and-deterrent phrases and mild-and-polite phrases depicted in written Chinese words. The ERP results showed that severe-and-deterrent phrases elicited significantly augmented P300 amplitude with a central-parietal scalp distribution compared with mild-and-polite phrases, indicating the allocation of more attention resources to and elaborate processing of the severe-and-deterrent phrases. It reveals that humans may consider the severe-and-deterrent phrases as more motivationally significant and elaborately process the severity and deterrence information contained in the enforcement phrases for the adaptive protection. The current study provides an objective and supplementary way to measure the efficiency of different enforcement phrases at neural level, which may help generate appropriate enforcement phrases and improve the performance of OHS inspections. PMID:27807404

  4. The effect of age of acquisition, socioeducational status, and proficiency on the neural processing of second language speech sounds.

    PubMed

    Archila-Suerte, Pilar; Zevin, Jason; Hernandez, Arturo E

    2015-02-01

    This study investigates the role of age of acquisition (AoA), socioeducational status (SES), and second language (L2) proficiency on the neural processing of L2 speech sounds. In a task of pre-attentive listening and passive viewing, Spanish-English bilinguals and a control group of English monolinguals listened to English syllables while watching a film of natural scenery. Eight regions of interest were selected from brain areas involved in speech perception and executive processes. The regions of interest were examined in 2 separate two-way ANOVA (AoA×SES; AoA×L2 proficiency). The results showed that AoA was the main variable affecting the neural response in L2 speech processing. Direct comparisons between AoA groups of equivalent SES and proficiency level enhanced the intensity and magnitude of the results. These results suggest that AoA, more than SES and proficiency level, determines which brain regions are recruited for the processing of second language speech sounds.

  5. The neural time course of art perception: an ERP study on the processing of style versus content in art.

    PubMed

    Augustin, M Dorothee; Defranceschi, Birgit; Fuchs, Helene K; Carbon, Claus-Christian; Hutzler, Florian

    2011-06-01

    A central prerequisite to understand the phenomenon of art in psychological terms is to investigate the nature of the underlying perceptual and cognitive processes. Building on a study by Augustin, Leder, Hutzler, and Carbon (2008) the current ERP study examined the neural time course of two central aspects of representational art, one of which is closely related to object- and scene perception, the other of which is art-specific: content and style. We adapted a paradigm that has repeatedly been employed in psycholinguistics and that allows one to examine the neural time course of two processes in terms of when sufficient information is available to allow successful classification. Twenty-two participants viewed pictures that systematically varied in style and content and conducted a combined go/nogo dual choice task. The dependent variables of interest were the Lateralised Readiness Potential (LRP) and the N200 effect. Analyses of both measures support the notion that in the processing of art style follows content, with style-related information being available at around 224 ms or between 40 and 94 ms later than content-related information. The paradigm used here offers a promising approach to further explore the time course of art perception, thus helping to unravel the perceptual and cognitive processes that underlie the phenomenon of art and the fascination it exerts.

  6. Neural Networks for Real-Time Sensory Data Processing and Sensorimotor Control

    DTIC Science & Technology

    1991-12-13

    modal sensory signals at thoracic interneurons of the escape system of the cockroach, Periplaneta americana . Brain Research 563:175-183. Beer, R.D...Transactions on Robotics and Automation. Nye, S.W. and Ritzmann, R.E. Motion analysis of leg joints associated with escape turns of the cockroach, Periplaneta ... americana . Submitted to J. Comp. Physiol. A. Beer, R.D. and Gallagher, J.C. Evolving dynamical neural networks for adaptive behavior. Submitted to

  7. Individual differences in attentional bias associated with cocaine dependence are related to varying engagement of neural processing networks.

    PubMed

    Kilts, Clint D; Kennedy, Ashley; Elton, Amanda L; Tripathi, Shanti Prakash; Young, Jonathan; Cisler, Josh M; James, G Andrew

    2014-04-01

    Cocaine and other drug dependencies are associated with significant attentional bias for drug use stimuli that represents a candidate cognitive marker of drug dependence and treatment outcomes. We explored, using fMRI, the role of discrete neural processing networks in the representation of individual differences in the drug attentional bias effect associated with cocaine dependence (AB-coc) using a word counting Stroop task with personalized cocaine use stimuli (cocStroop). The cocStroop behavioral and neural responses were further compared with those associated with a negative emotional word Stroop task (eStroop) and a neutral word counting Stroop task (cStroop). Brain-behavior correlations were explored using both network-level correlation analysis following independent component analysis (ICA) and voxel-level, brain-wide univariate correlation analysis. Variation in the attentional bias effect for cocaine use stimuli among cocaine-dependent men and women was related to the recruitment of two separate neural processing networks related to stimulus attention and salience attribution (inferior frontal-parietal-ventral insula), and the processing of the negative affective properties of cocaine stimuli (frontal-temporal-cingulate). Recruitment of a sensory-motor-dorsal insula network was negatively correlated with AB-coc and suggested a regulatory role related to the sensorimotor processing of cocaine stimuli. The attentional bias effect for cocaine stimuli and for negative affective word stimuli were significantly correlated across individuals, and both were correlated with the activity of the frontal-temporal-cingulate network. Functional connectivity for a single prefrontal-striatal-occipital network correlated with variation in general cognitive control (cStroop) that was unrelated to behavioral or neural network correlates of cocStroop- or eStroop-related attentional bias. A brain-wide mass univariate analysis demonstrated the significant correlation of

  8. Neural processing of high and low spatial frequency information in faces changes across development: qualitative changes in face processing during adolescence.

    PubMed

    Peters, Judith C; Vlamings, Petra; Kemner, Chantal

    2013-05-01

    Face perception in adults depends on skilled processing of interattribute distances ('configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying immaturity to use facial information in low spatial frequency (SF) ranges, which capture the coarse information needed for configural processing. We hypothesized that during adolescence a shift from use of high to low SF information takes place. Therefore, we studied the influence of SF content on neural face processing in groups of children (9-10 years), adolescents (14-15 years) and young adults (21-29 years) by measuring event-related potentials (ERPs) to upright and inverted faces which varied in SF content. Results revealed that children show a neural FIE in early processing stages (i.e. P1; generated in early visual areas), suggesting a superficial, global facial analysis. In contrast, ERPs of adults revealed an FIE at later processing stages (i.e. N170; generated in face-selective, higher visual areas). Interestingly, adolescents showed FIEs in both processing stages, suggesting a hybrid developmental stage. Furthermore, adolescents and adults showed FIEs for stimuli containing low SF information, whereas such effects were driven by both low and high SF information in children. These results indicate that face processing has a protracted maturational course into adolescence, and is dependent on changes in SF processing. During adolescence, sensitivity to configural cues is developed, which aids the fast and holistic processing that is so special for faces.

  9. Inactivation of Phospholipase D Diminishes Acinetobacter baumannii Pathogenesis▿ †

    PubMed Central

    Jacobs, Anna C.; Hood, Indriati; Boyd, Kelli L.; Olson, Patrick D.; Morrison, John M.; Carson, Steven; Sayood, Khalid; Iwen, Peter C.; Skaar, Eric P.; Dunman, Paul M.

    2010-01-01

    Acinetobacter baumannii is an emerging bacterial pathogen of considerable health care concern. Nonetheless, relatively little is known about the organism's virulence factors or their regulatory networks. Septicemia and ventilator-associated pneumonia are two of the more severe forms of A. baumannii disease. To identify virulence factors that may contribute to these disease processes, genetically diverse A. baumannii clinical isolates were evaluated for the ability to proliferate in human serum. A transposon mutant library was created in a strain background that propagated well in serum and screened for members with decreased serum growth. The results revealed that disruption of A. baumannii phospholipase D (PLD) caused a reduction in the organism's ability to thrive in serum, a deficiency in epithelial cell invasion, and diminished pathogenesis in a murine model of pneumonia. Collectively, these results suggest that PLD is an A. baumannii virulence factor. PMID:20194595

  10. Polymorphism in the µ-opioid receptor gene (OPRM1) modulates neural processing of physical pain, social rejection and error processing.

    PubMed

    Bonenberger, M; Plener, P L; Groschwitz, R C; Grön, G; Abler, B

    2015-09-01

    Variations of the µ-opioid receptor gene OPRM1 have been shown to modulate pain perception with some evidence pointing towards a modulation of not only physical but also "psychological pain". In line with suggestions of a common neural network involved in the processing of physical pain and negative and distressing stimuli, like social rejection as a psychologically harmful event, we examined the influence of the A118G polymorphism on the neural processing of physical and non-physical pain. Using fMRI, we investigated a sample of 23 females with the more frequent AA genotype, and eight females with the relatively rare but more pain-sensitive AG genotype during electrical stimulation to the dorsum of the non-dominant hand. Non-physical pain was investigated using Cyberball, a virtual ball-tossing game, to induce experiences of non-self-dependent social rejection. A Go/NoGo task with an increased risk of self-dependent erroneous performance was used as a control task to investigate the effects of negative feedback as a more cognitive form of distress. Relative to A118G homozygous A-allele carriers, G-allele carriers showed significantly increased activation of the supplementary motor area/superior frontal gyrus and the precentral gyrus during electrical stimulation. Increased activation of the secondary sensorimotor cortex (SII) was found during social exclusion and during negative feedback. We demonstrate that brain regions particularly related to the somatosensory component of pain processing are modulated by variations in OPRM1. Influences were evident for both physical and psychological pain processing supporting the assumption of shared neural pathways.

  11. A point process approach to identifying and tracking transitions in neural spiking dynamics in the subthalamic nucleus of Parkinson's patients

    NASA Astrophysics Data System (ADS)

    Deng, Xinyi; Eskandar, Emad N.; Eden, Uri T.

    2013-12-01

    Understanding the role of rhythmic dynamics in normal and diseased brain function is an important area of research in neural electrophysiology. Identifying and tracking changes in rhythms associated with spike trains present an additional challenge, because standard approaches for continuous-valued neural recordings—such as local field potential, magnetoencephalography, and electroencephalography data—require assumptions that do not typically hold for point process data. Additionally, subtle changes in the history dependent structure of a spike train have been shown to lead to robust changes in rhythmic firing patterns. Here, we propose a point process modeling framework to characterize the rhythmic spiking dynamics in spike trains, test for statistically significant changes to those dynamics, and track the temporal evolution of such changes. We first construct a two-state point process model incorporating spiking history and develop a likelihood ratio test to detect changes in the firing structure. We then apply adaptive state-space filters and smoothers to track these changes through time. We illustrate our approach with a simulation study as well as with experimental data recorded in the subthalamic nucleus of Parkinson's patients performing an arm movement task. Our analyses show that during the arm movement task, neurons underwent a complex pattern of modulation of spiking intensity characterized initially by a release of inhibitory control at 20-40 ms after a spike, followed by a decrease in excitatory influence at 40-60 ms after a spike.

  12. Investigations of the polar atmosphere with use of dynamical characteristics of the processes and self -organizing neural networks on ground-based multi-position optical observations

    NASA Astrophysics Data System (ADS)

    Alpatov, V. V.; Matveev, A. A.; Enel, F.; Brandstrom, U.; Gustavsson, B.; Steen, A.

    This article discusses questions connected with investigations of the polar atmosphere via ground-based multi-position optical observations. For this investigation a specially developed method is applied. It use the calculated dynamical parameters of the processes and self-organizing artificial neural networks. With self-organizing neural networks 5-7 classes have been extracted which can be associated with the regions having different physical properties. In particular, have been extracted regions intuitively coincident with polar stratospheric clouds and aurora.

  13. Satellite image processing for precision agriculture and agroindustry using convolutional neural network and genetic algorithm

    NASA Astrophysics Data System (ADS)

    Firdaus; Arkeman, Y.; Buono, A.; Hermadi, I.

    2017-01-01

    Translating satellite imagery to a useful data for decision making during this time are usually done manually by human. In this research, we are going to translate satellite imagery by using artificial intelligence method specifically using convolutional neural network and genetic algorithm to become a useful data for decision making, especially for precision agriculture and agroindustry. In this research, we are focused on how to made a sustainable land use planning with 3 objectives. The first is maximizing economic factor. Second is minimizing CO2 emission and the last is minimizing land degradation. Results show that by using artificial intelligence method, can produced a good pareto optimum solutions in a short time.

  14. Decision net, directed graph, and neural net processing of imaging spectrometer data

    NASA Technical Reports Server (NTRS)

    Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki; Barnard, Etienne

    1989-01-01

    A decision-net solution involving a novel hierarchical classifier and a set of multiple directed graphs, as well as a neural-net solution, are respectively presented for large-class problem and mixture problem treatments of imaging spectrometer data. The clustering method for hierarchical classifier design, when used with multiple directed graphs, yields an efficient decision net. New directed-graph rules for reducing local maxima as well as the number of perturbations required, and the new starting-node rules for extending the reachability and reducing the search time of the graphs, are noted to yield superior results, as indicated by an illustrative 500-class imaging spectrometer problem.

  15. Hybrid artificial neural network genetic algorithm technique for modeling chemical oxygen demand removal in anoxic/oxic process.

    PubMed

    Ma, Yongwen; Huang, Mingzhi; Wan, Jinquan; Hu, Kang; Wang, Yan; Zhang, Huiping

    2011-01-01

    In this paper, a hybrid artificial neural network (ANN) - genetic algorithm (GA) numerical technique was successfully developed to deal with complicated problems that cannot be solved by conventional solutions. ANNs and Gas were used to model and simulate the process of removing chemical oxygen demand (COD) in an anoxic/oxic system. The minimization of the error function with respect to the network parameters (weights and biases) has been considered as training of the network. Real-coded genetic algorithm was used to train the network in an unsupervised manner. Meanwhile the important process parameters, such as the influent COD (COD(in)), reflux ratio (R(r)), carbon-nitrogen ratio (C/N) and the effluent COD (COD(out)) were considered. The result shows that compared with the performance of ANN model, the performance of the GA-ANN (genetic algorithm - artificial neural network) network was found to be more impressive. Using ANN, the mean absolute percentage error (MAPE), mean squared error (MSE) and correlation coefficient (R) were 9.33×10(-4), 2.82 and 0.98596, respectively; while for the GA-ANN, they were converged to be 4.18×10(-4), 1.12 and 0.99476, respectively.

  16. Disentangling neural processes of egocentric and allocentric mental spatial transformations using whole-body photos of self and other.

    PubMed

    Ganesh, Shanti; van Schie, Hein T; Cross, Emily S; de Lange, Floris P; Wigboldus, Daniël H J

    2015-08-01