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Sample records for diminished neural processing

  1. Diminished Neural Processing of Aversive and Rewarding Stimuli During Selective Serotonin Reuptake Inhibitor Treatment

    PubMed Central

    McCabe, Ciara; Mishor, Zevic; Cowen, Philip J.; Harmer, Catherine J.

    2010-01-01

    Background Selective serotonin reuptake inhibitors (SSRIs) are popular medications for anxiety and depression, but their effectiveness, particularly in patients with prominent symptoms of loss of motivation and pleasure, has been questioned. There are few studies of the effect of SSRIs on neural reward mechanisms in humans. Methods We studied 45 healthy participants who were randomly allocated to receive the SSRI citalopram, the noradrenaline reuptake inhibitor reboxetine, or placebo for 7 days in a double-blind, parallel group design. We used functional magnetic resonance imaging to measure the neural response to rewarding (sight and/or flavor of chocolate) and aversive stimuli (sight of moldy strawberries and/or an unpleasant strawberry taste) on the final day of drug treatment. Results Citalopram reduced activation to the chocolate stimuli in the ventral striatum and the ventral medial/orbitofrontal cortex. In contrast, reboxetine did not suppress ventral striatal activity and in fact increased neural responses within medial orbitofrontal cortex to reward. Citalopram also decreased neural responses to the aversive stimuli conditions in key “punishment” areas such as the lateral orbitofrontal cortex. Reboxetine produced a similar, although weaker effect. Conclusions Our findings are the first to show that treatment with SSRIs can diminish the neural processing of both rewarding and aversive stimuli. The ability of SSRIs to decrease neural responses to reward might underlie the questioned efficacy of SSRIs in depressive conditions characterized by decreased motivation and anhedonia and could also account for the experience of emotional blunting described by some patients during SSRI treatment. PMID:20034615

  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 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

  4. Patterns in neural processing

    NASA Astrophysics Data System (ADS)

    Engineer, Sunu

    2012-03-01

    In this paper we propose a model for neural processing that addresses both the evolutionary and functional aspects of neural systems that are observed in nature, from the simplest neural collections to dense large scale associations such as human brains. We propose both an architecture and a process in which these components interact to create the emergent behavior that we define as the 'mind'.

  5. 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).

  6. 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.

  7. 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

  8. Diminishing fear: Optogenetic approach toward understanding neural circuits of fear control.

    PubMed

    Luchkina, Natalia V; Bolshakov, Vadim Y

    2017-05-11

    Understanding complex behavioral processes, both learned and innate, requires detailed characterization of the principles governing signal flow in corresponding neural circuits. Previous studies were hampered by the lack of appropriate tools needed to address the complexities of behavior-driving micro- and macrocircuits. The development and implementation of optogenetic methodologies revolutionized the field of behavioral neuroscience, allowing precise spatiotemporal control of specific, genetically defined neuronal populations and their functional connectivity both in vivo and ex vivo, thus providing unprecedented insights into the cellular and network-level mechanisms contributing to behavior. Here, we review recent pioneering advances in behavioral studies with optogenetic tools, focusing on mechanisms of fear-related behavioral processes with an emphasis on approaches which could be used to suppress fear when it is pathologically expressed. We also discuss limitations of these methodologies as well as review new technological developments which could be used in future mechanistic studies of fear behavior. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. [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.

  10. [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.

  11. The neural processing of taste

    PubMed Central

    Lemon, Christian H; Katz, Donald B

    2007-01-01

    Although there have been many recent advances in the field of gustatory neurobiology, our knowledge of how the nervous system is organized to process information about taste is still far from complete. Many studies on this topic have focused on understanding how gustatory neural circuits are spatially organized to represent information about taste quality (e.g., "sweet", "salty", "bitter", etc.). Arguments pertaining to this issue have largely centered on whether taste is carried by dedicated neural channels or a pattern of activity across a neural population. But there is now mounting evidence that the timing of neural events may also importantly contribute to the representation of taste. In this review, we attempt to summarize recent findings in the field that pertain to these issues. Both space and time are variables likely related to the mechanism of the gustatory neural code: information about taste appears to reside in spatial and temporal patterns of activation in gustatory neurons. What is more, the organization of the taste network in the brain would suggest that the parameters of space and time extend to the neural processing of gustatory information on a much grander scale. PMID:17903281

  12. 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.

  13. 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

  14. Neural processing of natural sounds.

    PubMed

    Theunissen, Frédéric E; Elie, Julie E

    2014-06-01

    We might be forced to listen to a high-frequency tone at our audiologist's office or we might enjoy falling asleep with a white-noise machine, but the sounds that really matter to us are the voices of our companions or music from our favourite radio station. The auditory system has evolved to process behaviourally relevant natural sounds. Research has shown not only that our brain is optimized for natural hearing tasks but also that using natural sounds to probe the auditory system is the best way to understand the neural computations that enable us to comprehend speech or appreciate music.

  15. 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.

  16. Neural overlap in processing music and speech

    PubMed Central

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

    2015-01-01

    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. PMID:25646513

  17. 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.

  18. Ambient groundwater flow diminishes nitrate processing in the hyporheic zone of streams

    NASA Astrophysics Data System (ADS)

    Azizian, Morvarid; Boano, Fulvio; Cook, Perran L. M.; Detwiler, Russell L.; Rippy, Megan A.; Grant, Stanley B.

    2017-05-01

    Modeling and experimental studies demonstrate that ambient groundwater reduces hyporheic exchange, but the implications of this observation for stream N-cycling is not yet clear. Here we utilize a simple process-based model (the Pumping and Streamline Segregation or PASS model) to evaluate N-cycling over two scales of hyporheic exchange (fluvial ripples and riffle-pool sequences), ten ambient groundwater and stream flow scenarios (five gaining and losing conditions and two stream discharges), and three biogeochemical settings (identified based on a principal component analysis of previously published measurements in streams throughout the United States). Model-data comparisons indicate that our model provides realistic estimates for direct denitrification of stream nitrate, but overpredicts nitrification and coupled nitrification-denitrification. Riffle-pool sequences are responsible for most of the N-processing, despite the fact that fluvial ripples generate 3-11 times more hyporheic exchange flux. Across all scenarios, hyporheic exchange flux and the Damköhler Number emerge as primary controls on stream N-cycling; the former regulates trafficking of nutrients and oxygen across the sediment-water interface, while the latter quantifies the relative rates of organic carbon mineralization and advective transport in streambed sediments. Vertical groundwater flux modulates both of these master variables in ways that tend to diminish stream N-cycling. Thus, anthropogenic perturbations of ambient groundwater flows (e.g., by urbanization, agricultural activities, groundwater mining, and/or climate change) may compromise some of the key ecosystem services provided by streams.

  19. Neural inhibition enables selection during language processing.

    PubMed

    Snyder, Hannah R; Hutchison, Natalie; Nyhus, Erika; Curran, Tim; Banich, Marie T; O'Reilly, Randall C; Munakata, Yuko

    2010-09-21

    Whether grocery shopping or choosing words to express a thought, selecting between options can be challenging, especially for people with anxiety. We investigate the neural mechanisms supporting selection during language processing and its breakdown in anxiety. Our neural network simulations demonstrate a critical role for competitive, inhibitory dynamics supported by GABAergic interneurons. As predicted by our model, we find that anxiety (associated with reduced neural inhibition) impairs selection among options and associated prefrontal cortical activity, even in a simple, nonaffective verb-generation task, and the GABA agonist midazolam (which increases neural inhibition) improves selection, whereas retrieval from semantic memory is unaffected when selection demands are low. Neural inhibition is key to choosing our words.

  20. 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.

  1. The diminishing role of hubs in dynamical processes on complex networks

    PubMed Central

    Quax, Rick; Apolloni, Andrea; Sloot, Peter M. A.

    2013-01-01

    It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein–protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature. PMID:24004558

  2. 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.

  3. 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.

  4. Hafnium transistor process design for neural interfacing.

    PubMed

    Parent, David W; Basham, Eric J

    2009-01-01

    A design methodology is presented that uses 1-D process simulations of Metal Insulator Semiconductor (MIS) structures to design the threshold voltage of hafnium oxide based transistors used for neural recording. The methodology is comprised of 1-D analytical equations for threshold voltage specification, and doping profiles, and 1-D MIS Technical Computer Aided Design (TCAD) to design a process to implement a specific threshold voltage, which minimized simulation time. The process was then verified with a 2-D process/electrical TCAD simulation. Hafnium oxide films (HfO) were grown and characterized for dielectric constant and fixed oxide charge for various annealing temperatures, two important design variables in threshold voltage design.

  5. [Diminished culpability].

    PubMed

    Ohman, Luis; Fantini, Adrián P

    2016-05-01

    One of the central matters in forensic psychiatry is its culpability. Day after day we, the mental health professionals, are subpoenaed in different courts of our country to assess the mental state of a given individual in order to endorse a judge so that he can issue their view pertaining the culpability and the responsibility of accused subjects. Our current National Criminal Code, dating from 1921, in Art. 34 sub 1 holds for culpability a dichotomous model in which an individual is responsible and must be accountable for his behavior or not responsible and in such case must no be held accountable in criminal courts. This dichotomous model often does not permit the correct analysis of the psychopathology making sometimes the psychiatrist to force a conclusion according to this paradigm imposed by Justice. As we all know reality does not reflect itself under discrete categories and notwithstanding this is the written norm, people, thoughts, emotions and behaviors manifest in dimensions where boundaries are not always clear. Hence, we are considering it necessary to give effect to the impulses for the reform of the existing Criminal Code to lead to diminish culpability.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. Neural Correlates of Subliminal Language Processing

    PubMed Central

    Axelrod, Vadim; Bar, Moshe; Rees, Geraint; Yovel, Galit

    2015-01-01

    Language is a high-level cognitive function, so exploring the neural correlates of unconscious language processing is essential for understanding the limits of unconscious processing in general. The results of several functional magnetic resonance imaging studies have suggested that unconscious lexical and semantic processing is confined to the posterior temporal lobe, without involvement of the frontal lobe—the regions that are indispensable for conscious language processing. However, previous studies employed a similarly designed masked priming paradigm with briefly presented single and contextually unrelated words. It is thus possible, that the stimulation level was insufficiently strong to be detected in the high-level frontal regions. Here, in a high-resolution fMRI and multivariate pattern analysis study we explored the neural correlates of subliminal language processing using a novel paradigm, where written meaningful sentences were suppressed from awareness for extended duration using continuous flash suppression. We found that subjectively and objectively invisible meaningful sentences and unpronounceable nonwords could be discriminated not only in the left posterior superior temporal sulcus (STS), but critically, also in the left middle frontal gyrus. We conclude that frontal lobes play a role in unconscious language processing and that activation of the frontal lobes per se might not be sufficient for achieving conscious awareness. PMID:24557638

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. Probing the Neural Correlates of Number Processing.

    PubMed

    Knops, André

    2016-05-17

    The cognitive and neural mechanisms that enable humans to encode and manipulate numerical information have been subject to an increasing number of experimental studies over the past 25 years or so. Here, I highlight recent findings about how numerical information is neurally coded, focusing on the theoretical implications derived from the most influential theoretical framework in numerical cognition-the Triple Code Model. At the core of this model is the assumption that bilateral parietal cortex hosts an approximate number system that codes for the cardinal value of perceived numerals. I will review studies that ask whether or not the numerical coding within this system is invariant to varying input notation, format, or modality, and whether or not the observed parietal activity is number-specific over and above the parietal involvement in response-related processes. Extant computational models of numerosity (the number of objects in a set) perception are summarized and related to empirical data from human neuroimaging and monkey neurophysiology. © The Author(s) 2016.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Introduction to spiking neural networks: Information processing, learning and applications.

    PubMed

    Ponulak, Filip; Kasinski, Andrzej

    2011-01-01

    The concept that neural information is encoded in the firing rate of neurons has been the dominant paradigm in neurobiology for many years. This paradigm has also been adopted by the theory of artificial neural networks. Recent physiological experiments demonstrate, however, that in many parts of the nervous system, neural code is founded on the timing of individual action potentials. This finding has given rise to the emergence of a new class of neural models, called spiking neural networks. In this paper we summarize basic properties of spiking neurons and spiking networks. Our focus is, specifically, on models of spike-based information coding, synaptic plasticity and learning. We also survey real-life applications of spiking models. The paper is meant to be an introduction to spiking neural networks for scientists from various disciplines interested in spike-based neural processing.

  3. Neural correlates of abstract verb processing.

    PubMed

    Rodríguez-Ferreiro, Javier; Gennari, Silvia P; Davies, Robert; Cuetos, Fernando

    2011-01-01

    The present study investigated the neural correlates of the processing of abstract (low imageability) verbs. An extensive body of literature has investigated concrete versus abstract nouns but little is known about how abstract verbs are processed. Spanish abstract verbs including emotion verbs (e.g., amar, "to love"; molestar, "to annoy") were compared to concrete verbs (e.g., llevar, "to carry"; arrastrar, "to drag"). Results indicated that abstract verbs elicited stronger activity in regions previously associated with semantic retrieval such as inferior frontal, anterior temporal, and posterior temporal regions, and that concrete and abstract activation networks (compared to that of pseudoverbs) were partially distinct, with concrete verbs eliciting more posterior activity in these regions. In contrast to previous studies investigating nouns, verbs strongly engage both left and right inferior frontal gyri, suggesting, as previously found, that right prefrontal cortex aids difficult semantic retrieval. Together with previous evidence demonstrating nonverbal conceptual roles for the active regions as well as experiential content for abstract word meanings, our results suggest that abstract verbs impose greater demands on semantic retrieval or property integration, and are less consistent with the view that abstract words recruit left-lateralized regions because they activate verbal codes or context, as claimed by proponents of the dual-code theory. Moreover, our results are consistent with distributed accounts of semantic memory because distributed networks may coexist with varying retrieval demands.

  4. 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

  5. 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.

  6. Exploring the neural substrates of misinformation processing.

    PubMed

    Gordon, Andrew; Brooks, Jonathan C W; Quadflieg, Susanne; Ecker, Ullrich K H; Lewandowsky, Stephan

    2017-10-04

    It is well known that information that is initially thought to be correct but then revealed to be false, often continues to influence human judgement and decision making despite people being aware of the retraction. Yet little research has examined the underlying neural substrates of this phenomenon, which is known as the 'continued influence effect of misinformation' (CIEM). It remains unclear how the human brain processes critical information that retracts prior claims. To address this question in further detail, 26 healthy adults underwent functional magnetic resonance imaging (fMRI) while listening to brief narratives which either involved a retraction of prior information or not. Following each narrative, subjects' comprehension of the narrative, including their inclination to rely on retracted information, was probed. As expected, it was found that retracted information continued to affect participants' narrative-related reasoning. In addition, the fMRI data indicated that the continued influence of retracted information may be due to a breakdown of narrative-level integration and coherence-building mechanisms implemented by the precuneus and posterior cingulate gyrus. Copyright © 2017. Published by Elsevier Ltd.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Neural correlates of processing negative and sexually arousing pictures.

    PubMed

    Bailey, Kira; West, Robert; Mullaney, Kellie M

    2012-01-01

    Recent work has questioned whether the negativity bias is a distinct component of affective picture processing. The current study was designed to determine whether there are different neural correlates of processing positive and negative pictures using event-related brain potentials. The early posterior negativity and late positive potential were greatest in amplitude for erotic pictures. Partial Least Squares analysis revealed one latent variable that distinguished erotic pictures from neutral and positive pictures and another that differentiated negative pictures from neutral and positive pictures. The effects of orienting task on the neural correlates of processing negative and erotic pictures indicate that affective picture processing is sensitive to both stimulus-driven, and attentional or decision processes. The current data, together with other recent findings from our laboratory, lead to the suggestion that there are distinct neural correlates of processing negative and positive stimuli during affective picture processing.

  13. Neural Correlates of Processing Negative and Sexually Arousing Pictures

    PubMed Central

    Bailey, Kira; West, Robert; Mullaney, Kellie M.

    2012-01-01

    Recent work has questioned whether the negativity bias is a distinct component of affective picture processing. The current study was designed to determine whether there are different neural correlates of processing positive and negative pictures using event-related brain potentials. The early posterior negativity and late positive potential were greatest in amplitude for erotic pictures. Partial Least Squares analysis revealed one latent variable that distinguished erotic pictures from neutral and positive pictures and another that differentiated negative pictures from neutral and positive pictures. The effects of orienting task on the neural correlates of processing negative and erotic pictures indicate that affective picture processing is sensitive to both stimulus-driven, and attentional or decision processes. The current data, together with other recent findings from our laboratory, lead to the suggestion that there are distinct neural correlates of processing negative and positive stimuli during affective picture processing. PMID:23029071

  14. Neural Networks Applied to Signal Processing

    DTIC Science & Technology

    1989-09-01

    identify by block number) FIELD GROUP SUB-GROUP Neural network, backpropagation, conjugato grad- ient method, Fibonacci line search, nonlinear signal...of the First Layer Gradients ............ 31 e. Calculation of the Input Layer Gradient-. ........... 33 i%" 5. Fibonacci Line Search Parameters...conjugate gradient optimization method is presented and then applied to the neu- ral network model. The Fibonacci line search method used in conjunction

  15. 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.

  16. Linking Neural and Symbolic Representation and Processing of Conceptual Structures

    PubMed Central

    van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S.; Wiggins, Geraint A.

    2017-01-01

    We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures. PMID:28848460

  17. Linking Neural and Symbolic Representation and Processing of Conceptual Structures.

    PubMed

    van der Velde, Frank; Forth, Jamie; Nazareth, Deniece S; Wiggins, Geraint A

    2017-01-01

    We compare and discuss representations in two cognitive architectures aimed at representing and processing complex conceptual (sentence-like) structures. First is the Neural Blackboard Architecture (NBA), which aims to account for representation and processing of complex and combinatorial conceptual structures in the brain. Second is IDyOT (Information Dynamics of Thinking), which derives sentence-like structures by learning statistical sequential regularities over a suitable corpus. Although IDyOT is designed at a level more abstract than the neural, so it is a model of cognitive function, rather than neural processing, there are strong similarities between the composite structures developed in IDyOT and the NBA. We hypothesize that these similarities form the basis of a combined architecture in which the individual strengths of each architecture are integrated. We outline and discuss the characteristics of this combined architecture, emphasizing the representation and processing of conceptual structures.

  18. 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.

  19. Cognitive, social, and neural determinants of diminished decision-making and financial exploitation risk in aging and dementia: A review and new model.

    PubMed

    Spreng, R Nathan; Karlawish, Jason; Marson, Daniel C

    2016-01-01

    In this article we will briefly review how changes in brain and in cognitive and social functioning, across the spectrum from normal to pathological aging, can lead to decision-making impairments that increase abuse risk in many life domains (e.g., health care, social engagement, financial management). The review will specifically focus on emerging research identifying neural, cognitive, and social markers of declining financial decision-making capacity in older adults. We will highlight how these findings are opening avenues for early detection and new interventions to reduce exploitation risk.

  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 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…

  3. Simulation of dynamic processes with adaptive neural networks.

    SciTech Connect

    Tzanos, C. P.

    1998-02-03

    Many industrial processes are highly non-linear and complex. Their simulation with first-principle or conventional input-output correlation models is not satisfactory, either because the process physics is not well understood, or it is so complex that direct simulation is either not adequately accurate, or it requires excessive computation time, especially for on-line applications. Artificial intelligence techniques (neural networks, expert systems, fuzzy logic) or their combination with simple process-physics models can be effectively used for the simulation of such processes. Feedforward (static) neural networks (FNNs) can be used effectively to model steady-state processes. They have also been used to model dynamic (time-varying) processes by adding to the network input layer input nodes that represent values of input variables at previous time steps. The number of previous time steps is problem dependent and, in general, can be determined after extensive testing. This work demonstrates that for dynamic processes that do not vary fast with respect to the retraining time of the neural network, an adaptive feedforward neural network can be an effective simulator that is free of the complexities introduced by the use of input values at previous time steps.

  4. The neural processes underlying self-agency.

    PubMed

    Nahab, Fatta B; Kundu, Prantik; Gallea, Cecile; Kakareka, John; Pursley, Randy; Pohida, Tom; Miletta, Nathaniel; Friedman, Jason; Hallett, Mark

    2011-01-01

    Self-agency (SA) is the individual's perception that an action is the consequence of his/her own intention. The neural networks underlying SA are not well understood. We carried out a novel, ecologically valid, virtual-reality experiment using blood oxygen level-dependent functional magnetic resonance imaging (fMRI) where SA could be modulated in real-time while subjects performed voluntary finger movements. Behavioral testing was also performed to assess the explicit judgment of SA. Twenty healthy volunteers completed the experiment. Results of the behavioral testing demonstrated paradigm validity along with the identification of a bias that led subjects to over- or underestimate the amount of control they had. The fMRI experiment identified 2 discrete networks. These leading and lagging networks likely represent a spatial and temporal flow of information, with the leading network serving the role of mismatch detection and the lagging network receiving this information and mediating its elevation to conscious awareness, giving rise to SA.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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).

  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. 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…

  12. 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…

  13. 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.

  14. 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…

  15. 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…

  16. 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.

  17. 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.

  18. Music Signal Processing Using Vector Product Neural Networks

    NASA Astrophysics Data System (ADS)

    Fan, Z. C.; Chan, T. S.; Yang, Y. H.; Jang, J. S. R.

    2017-05-01

    We propose a novel neural network model for music signal processing using vector product neurons and dimensionality transformations. Here, the inputs are first mapped from real values into three-dimensional vectors then fed into a three-dimensional vector product neural network where the inputs, outputs, and weights are all three-dimensional values. Next, the final outputs are mapped back to the reals. Two methods for dimensionality transformation are proposed, one via context windows and the other via spectral coloring. Experimental results on the iKala dataset for blind singing voice separation confirm the efficacy of our model.

  19. Alterations in neural Theory of Mind processing in euthymic patients with bipolar disorder and unaffected relatives.

    PubMed

    Willert, Anna; Mohnke, Sebastian; Erk, Susanne; Schnell, Knut; Romanczuk-Seiferth, Nina; Quinlivan, Esther; Schreiter, Stefanie; Spengler, Stephanie; Herold, Dorrit; Wackerhagen, Carolin; Romund, Lydia; Garbusow, Maria; Lett, Tristram; Stamm, Thomas; Adli, Mazda; Heinz, Andreas; Bermpohl, Felix; Walter, Henrik

    2015-12-01

    Behavioral deficits in the Theory of Mind (ToM) have been robustly demonstrated in bipolar disorder. These deficits may represent an intermediate phenotype of the disease. The aim of this study was: (i) to investigate alterations in neural ToM processing in euthymic patients with bipolar disorder, and (ii) to examine whether similar effects are present in unaffected relatives of patients with bipolar disorder suggesting that ToM functional activation may be, in part, due to genetic risk for the disease. A total of 24 euthymic patients with bipolar disorder, 21 unaffected first-degree relatives, and 81 healthy controls completed a ToM task while undergoing functional magnetic resonance imaging. We observed reduced bilateral activation of the temporoparietal junction (TPJ) and diminished functional fronto-temporoparietal connectivity in patients compared to controls. Relatives tended towards intermediate temporoparietal activity and functional coupling with medial prefrontal areas. There was also evidence for a potentially compensatory enhanced recruitment of the right middle temporal gyrus and stronger connectivity between this region and the medial prefrontal cortex in relatives. These findings provide further evidence of altered neural ToM processing in euthymic patients with bipolar disorder. Further, our findings in relatives lend support to the idea that altered ToM processing may act as an intermediate phenotype of the disorder. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  20. 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.

  1. 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.

  2. [Chronic pain : Perception, reward and neural processing].

    PubMed

    Becker, S; Diers, M

    2016-10-01

    Many chronic pain syndromes are characterized by enhanced perception of painful stimuli as well as alterations in cortical processing in sensory and motor regions. In this review article the alterations in muscle pain and neuropathic pain are described. Alterations in patients with fibromyalgia and chronic back pain are described as examples for musculoskeletal pain and also in patients with phantom limb pain after amputation and complex regional pain syndrome as examples for neuropathic pain. In addition to altered pain perception, cumulative evidence on alterations in the processing of reward and the underlying mechanisms in chronic pain has been described. A description is given of what is known on how pain and reward interact and affect each other. The relevance of such interactions for chronic pain is discussed. The implications of these findings for therapeutic approaches are delineated with respect to sensorimotor training and behavioral therapy, focusing on the effectiveness of these approaches, mechanisms and future developments. In particular, we discuss operant behavioral therapy in patients with chronic back pain and fibromyalgia as well as prosthesis training in patients with phantom limb pain and discrimination, mirror and imaginary training in patients with phantom limb pain and complex regional pain syndrome. With respect to the processing of reward, the focus of the discussion is on the role of reward and associated learning in pain therapy.

  3. Hemispheric asymmetries in motivation neurally dissociate self-description processes.

    PubMed

    Marsolek, Chad J; DeYoung, Colin G; Domansky, W Scott; Deason, Rebecca G

    2013-06-01

    When people describe themselves by responding to personality questionnaires, typically they endorse some items and reject others. Further, most people endorse likable traits and reject unlikeable traits. In one case, people use previously stored information about themselves to judge that a particular trait--usually likable--describes them well, and in the other, they use previously stored information to judge that a particular trait--usually unlikeable--does not describe them well. Here we report evidence that these processes are neurally dissociable, with the former benefiting from engaging left-hemisphere processes and the latter benefiting from engaging right-hemisphere processes. Hemispheric asymmetries in self-description are not unidirectional and do not differ across different personality traits, but do differ between endorsing likable items and rejecting unlikeable items. Thus, we are not dispassionate observers of ourselves. Dissociable, basic motivational processes are involved in the neural architecture underlying self-description.

  4. 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

  5. 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.

  6. 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.

  7. 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)

  8. 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)

  9. Neural image processing by dendritic networks.

    PubMed

    Cuntz, Hermann; Haag, Jürgen; Borst, Alexander

    2003-09-16

    Convolution is one of the most common operations in image processing. Based on experimental findings on motion-sensitive visual interneurons of the fly, we show by realistic compartmental modeling that a dendritic network can implement this operation. In a first step, dendritic electrical coupling between two cells spatially blurs the original motion input. The blurred motion image is then passed onto a third cell via inhibitory dendritic synapses resulting in a sharpening of the signal. This enhancement of motion contrast may be the central element of figure-ground discrimination based on relative motion in the fly.

  10. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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.

  18. Neural processes underlying cultural differences in cognitive persistence.

    PubMed

    Telzer, Eva H; Qu, Yang; Lin, Lynda C

    2017-08-01

    Self-improvement motivation, which occurs when individuals seek to improve upon their competence by gaining new knowledge and improving upon their skills, is critical for cognitive, social, and educational adjustment. While many studies have delineated the neural mechanisms supporting extrinsic motivation induced by monetary rewards, less work has examined the neural processes that support intrinsically motivated behaviors, such as self-improvement motivation. Because cultural groups traditionally vary in terms of their self-improvement motivation, we examined cultural differences in the behavioral and neural processes underlying motivated behaviors during cognitive persistence in the absence of extrinsic rewards. In Study 1, 71 American (47 females, M=19.68 years) and 68 Chinese (38 females, M=19.37 years) students completed a behavioral cognitive control task that required cognitive persistence across time. In Study 2, 14 American and 15 Chinese students completed the same cognitive persistence task during an fMRI scan. Across both studies, American students showed significant declines in cognitive performance across time, whereas Chinese participants demonstrated effective cognitive persistence. These behavioral effects were explained by cultural differences in self-improvement motivation and paralleled by increasing activation and functional coupling between the inferior frontal gyrus (IFG) and ventral striatum (VS) across the task among Chinese participants, neural activation and coupling that remained low in American participants. These findings suggest a potential neural mechanism by which the VS and IFG work in concert to promote cognitive persistence in the absence of extrinsic rewards. Thus, frontostriatal circuitry may be a neurobiological signal representing intrinsic motivation for self-improvement that serves an adaptive function, increasing Chinese students' motivation to engage in cognitive persistence. Copyright © 2017 Elsevier Inc. All rights

  19. 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.

  20. 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.

  1. Signal Processing, Pattern Formation and Adaptation in Neural Oscillators

    DTIC Science & Technology

    2016-11-29

    Hoppensteadt and Izhikevich (1996, 1997) showed that a weakly connected network of neural oscillators of identical natural frequencies can memorize...from the intrinsic dynamics of an emergent oscillation (Whittington et al., 2000), and the missing pulse rhythms used here enabled us to dissociate ...musical beat processing. The Neurosciences and Music III: Disorders and Plasticity. Annals of the New York Academy of Sciences, 1169, 89-92. Grahn

  2. 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.

  3. Neural Dynamics of Phonological Processing in the Dorsal Auditory Stream

    PubMed Central

    Sabri, Merav; Beardsley, Scott A.; Mangalathu-Arumana, Jain; Desai, Anjali

    2013-01-01

    Neuroanatomical models hypothesize a role for the dorsal auditory pathway in phonological processing as a feedforward efferent system (Davis and Johnsrude, 2007; Rauschecker and Scott, 2009; Hickok et al., 2011). But the functional organization of the pathway, in terms of time course of interactions between auditory, somatosensory, and motor regions, and the hemispheric lateralization pattern is largely unknown. Here, ambiguous duplex syllables, with elements presented dichotically at varying interaural asynchronies, were used to parametrically modulate phonological processing and associated neural activity in the human dorsal auditory stream. Subjects performed syllable and chirp identification tasks, while event-related potentials and functional magnetic resonance images were concurrently collected. Joint independent component analysis was applied to fuse the neuroimaging data and study the neural dynamics of brain regions involved in phonological processing with high spatiotemporal resolution. Results revealed a highly interactive neural network associated with phonological processing, composed of functional fields in posterior temporal gyrus (pSTG), inferior parietal lobule (IPL), and ventral central sulcus (vCS) that were engaged early and almost simultaneously (at 80–100 ms), consistent with a direct influence of articulatory somatomotor areas on phonemic perception. Left hemispheric lateralization was observed 250 ms earlier in IPL and vCS than pSTG, suggesting that functional specialization of somatomotor (and not auditory) areas determined lateralization in the dorsal auditory pathway. The temporal dynamics of the dorsal auditory pathway described here offer a new understanding of its functional organization and demonstrate that temporal information is essential to resolve neural circuits underlying complex behaviors. PMID:24068810

  4. Adaptive neural reward processing during anticipation and receipt of monetary rewards in mindfulness meditators.

    PubMed

    Kirk, Ulrich; Brown, Kirk Warren; Downar, Jonathan

    2015-05-01

    Reward seeking is ubiquitous and adaptive in humans. But excessive reward seeking behavior, such as chasing monetary rewards, may lead to diminished subjective well-being. This study examined whether individuals trained in mindfulness meditation show neural evidence of lower susceptibility to monetary rewards. Seventy-eight participants (34 meditators, 44 matched controls) completed the monetary incentive delay task while undergoing functional magnetic resonance imaging. The groups performed equally on the task, but meditators showed lower neural activations in the caudate nucleus during reward anticipation, and elevated bilateral posterior insula activation during reward anticipation. Meditators also evidenced reduced activations in the ventromedial prefrontal cortex during reward receipt compared with controls. Connectivity parameters between the right caudate and bilateral anterior insula were attenuated in meditators during incentive anticipation. In summary, brain regions involved in reward processing-both during reward anticipation and receipt of reward-responded differently in mindfulness meditators than in nonmeditators, indicating that the former are less susceptible to monetary incentives. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  5. 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

  6. 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. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  7. 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

  8. 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. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  9. Neural Language Processing in Adolescent First-Language Learners

    PubMed Central

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

    2014-01-01

    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. PMID:23696277

  10. Evaluating Functional Autocorrelation within Spatially Distributed Neural Processing Networks*

    PubMed Central

    Derado, Gordana; Bowman, F. Dubois; Ely, Timothy D.; Kilts, Clinton D.

    2010-01-01

    Data-driven statistical approaches, such as cluster analysis or independent component analysis, applied to in vivo functional neuroimaging data help to identify neural processing networks that exhibit similar task-related or restingstate patterns of activity. Ideally, the measured brain activity for voxels within such networks should exhibit high autocorrelation. An important limitation is that the algorithms do not typically quantify or statistically test the strength or nature of the within-network relatedness between voxels. To extend the results given by such data-driven analyses, we propose the use of Moran’s I statistic to measure the degree of functional autocorrelation within identified neural processing networks and to evaluate the statistical significance of the observed associations. We adapt the conventional definition of Moran’s I, for applicability to neuroimaging analyses, by defining the global autocorrelation index using network-based neighborhoods. Also, we compute network-specific contributions to the overall autocorrelation. We present results from a bootstrap analysis that provide empirical support for the use of our hypothesis testing framework. We illustrate our methodology using positron emission tomography (PET) data from a study that examines the neural representation of working memory among individuals with schizophrenia and functional magnetic resonance imaging (fMRI) data from a study of depression. PMID:21643436

  11. Evaluating Functional Autocorrelation within Spatially Distributed Neural Processing Networks.

    PubMed

    Derado, Gordana; Bowman, F Dubois; Ely, Timothy D; Kilts, Clinton D

    2010-01-01

    Data-driven statistical approaches, such as cluster analysis or independent component analysis, applied to in vivo functional neuroimaging data help to identify neural processing networks that exhibit similar task-related or restingstate patterns of activity. Ideally, the measured brain activity for voxels within such networks should exhibit high autocorrelation. An important limitation is that the algorithms do not typically quantify or statistically test the strength or nature of the within-network relatedness between voxels. To extend the results given by such data-driven analyses, we propose the use of Moran's I statistic to measure the degree of functional autocorrelation within identified neural processing networks and to evaluate the statistical significance of the observed associations. We adapt the conventional definition of Moran's I, for applicability to neuroimaging analyses, by defining the global autocorrelation index using network-based neighborhoods. Also, we compute network-specific contributions to the overall autocorrelation. We present results from a bootstrap analysis that provide empirical support for the use of our hypothesis testing framework. We illustrate our methodology using positron emission tomography (PET) data from a study that examines the neural representation of working memory among individuals with schizophrenia and functional magnetic resonance imaging (fMRI) data from a study of depression.

  12. 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.

  13. 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.

  14. Vicarious Neural Processing of Outcomes during Observational Learning

    PubMed Central

    Monfardini, Elisabetta; Gazzola, Valeria; Boussaoud, Driss

    2013-01-01

    Learning what behaviour is appropriate in a specific context by observing the actions of others and their outcomes is a key constituent of human cognition, because it saves time and energy and reduces exposure to potentially dangerous situations. Observational learning of associative rules relies on the ability to map the actions of others onto our own, process outcomes, and combine these sources of information. Here, we combined newly developed experimental tasks and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms that govern such observational learning. Results show that the neural systems involved in individual trial-and-error learning and in action observation and execution both participate in observational learning. In addition, we identified brain areas that specifically activate for others’ incorrect outcomes during learning in the posterior medial frontal cortex (pMFC), the anterior insula and the posterior superior temporal sulcus (pSTS). PMID:24040104

  15. Neural Correlates of Morphological Processing: Evidence from Chinese

    PubMed Central

    Zou, Lijuan; Packard, Jerome L.; Xia, Zhichao; Liu, Youyi; Shu, Hua

    2016-01-01

    Morphological decomposition is an important part of complex word processing. In Chinese, this requires a comprehensive consideration of phonological, orthographic and morphemic information. The left inferior frontal gyrus (L-IFG) has been implicated in this process in alphabetic languages. However, it is unclear whether the neural mechanisms underlying morphological processing in alphabetic languages would be the same in Chinese, a logographic language. To investigate the neural basis of morphological processing in Chinese compound words, an fMRI experiment was conducted using an explicit auditory morphological judgment task. Results showed the L-IFG to be a core area in Chinese morphological processing, consistent with research in alphabetic languages. Additionally, a broad network consisting of the L-MTG, the bilateral STG and the L-FG that taps phonological, orthographic, and semantic information was found to be involved. These results provide evidence that the L-IFG plays an important role in morphological processing even in languages that are typologically different. PMID:26834609

  16. Native language shapes automatic neural processing of speech.

    PubMed

    Intartaglia, Bastien; White-Schwoch, Travis; Meunier, Christine; Roman, Stéphane; Kraus, Nina; Schön, Daniele

    2016-08-01

    The development of the phoneme inventory is driven by the acoustic-phonetic properties of one's native language. Neural representation of speech is known to be shaped by language experience, as indexed by cortical responses, and recent studies suggest that subcortical processing also exhibits this attunement to native language. However, most work to date has focused on the differences between tonal and non-tonal languages that use pitch variations to convey phonemic categories. The aim of this cross-language study is to determine whether subcortical encoding of speech sounds is sensitive to language experience by comparing native speakers of two non-tonal languages (French and English). We hypothesized that neural representations would be more robust and fine-grained for speech sounds that belong to the native phonemic inventory of the listener, and especially for the dimensions that are phonetically relevant to the listener such as high frequency components. We recorded neural responses of American English and French native speakers, listening to natural syllables of both languages. Results showed that, independently of the stimulus, American participants exhibited greater neural representation of the fundamental frequency compared to French participants, consistent with the importance of the fundamental frequency to convey stress patterns in English. Furthermore, participants showed more robust encoding and more precise spectral representations of the first formant when listening to the syllable of their native language as compared to non-native language. These results align with the hypothesis that language experience shapes sensory processing of speech and that this plasticity occurs as a function of what is meaningful to a listener. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. A comparative analysis of neural taste processing in animals

    PubMed Central

    de Brito Sanchez, Gabriela; Giurfa, Martin

    2011-01-01

    Understanding taste processing in the nervous system is a fundamental challenge of modern neuroscience. Recent research on the neural bases of taste coding in invertebrates and vertebrates allows discussion of whether labelled-line or across-fibre pattern encoding applies to taste perception. While the former posits that each gustatory receptor responds to one stimulus or a very limited range of stimuli and sends a direct ‘line’ to the central nervous system to communicate taste information, the latter postulates that each gustatory receptor responds to a wider range of stimuli so that the entire population of taste-responsive neurons participates in the taste code. Tastes are represented in the brain of the fruitfly and of the rat by spatial patterns of neural activity containing both distinct and overlapping regions, which are in accord with both labelled-line and across-fibre pattern processing of taste, respectively. In both animal models, taste representations seem to relate to the hedonic value of the tastant (e.g. palatable versus non-palatable). Thus, although the labelled-line hypothesis can account for peripheral taste processing, central processing remains either unknown or differs from a pure labelled-line coding. The essential task for a neuroscience of taste is, therefore, to determine the connectivity of taste-processing circuits in central nervous systems. Such connectivity may determine coding strategies that differ significantly from both the labelled-line and the across-fibre pattern models. PMID:21690133

  18. Neural Mechanisms and Information Processing in Recognition Systems

    PubMed Central

    Ozaki, Mamiko; Hefetz, Abraham

    2014-01-01

    Nestmate recognition is a hallmark of social insects. It is based on the match/mismatch of an identity signal carried by members of the society with that of the perceiving individual. While the behavioral response, amicable or aggressive, is very clear, the neural systems underlying recognition are not fully understood. Here we contrast two alternative hypotheses for the neural mechanisms that are responsible for the perception and information processing in recognition. We focus on recognition via chemical signals, as the common modality in social insects. The first, classical, hypothesis states that upon perception of recognition cues by the sensory system the information is passed as is to the antennal lobes and to higher brain centers where the information is deciphered and compared to a neural template. Match or mismatch information is then transferred to some behavior-generating centers where the appropriate response is elicited. An alternative hypothesis, that of “pre-filter mechanism”, posits that the decision as to whether to pass on the information to the central nervous system takes place in the peripheral sensory system. We suggest that, through sensory adaptation, only alien signals are passed on to the brain, specifically to an “aggressive-behavior-switching center”, where the response is generated if the signal is above a certain threshold. PMID:26462936

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. Fairness influences early signatures of reward-related neural processing.

    PubMed

    Massi, Bart; Luhmann, Christian C

    2015-12-01

    Many humans exhibit a strong preference for fairness during decision-making. Although there is evidence that social factors influence reward-related and affective neural processing, it is unclear if this effect is mediated by compulsory outcome evaluation processes or results from slower deliberate cognition. Here we show that the feedback-related negativity (FRN) and late positive potential (LPP), two signatures of early hedonic processing, are modulated by the fairness of rewards during a passive rating task. We find that unfair payouts elicit larger FRNs than fair payouts, whereas fair payouts elicit larger LPPs than unfair payouts. This is true both in the time-domain, where the FRN and LPP are related, and in the time-frequency domain, where the two signals are largely independent. Ultimately, this work demonstrates that fairness affects the early stages of reward and affective processing, suggesting a common biological mechanism for social and personal reward evaluation.

  6. 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.

  7. 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.

  8. Neural pulse frequency modulation of an exponentially correlated Gaussian process

    NASA Technical Reports Server (NTRS)

    Hutchinson, C. E.; Chon, Y.-T.

    1976-01-01

    The effect of NPFM (Neural Pulse Frequency Modulation) on a stationary Gaussian input, namely an exponentially correlated Gaussian input, is investigated with special emphasis on the determination of the average number of pulses in unit time, known also as the average frequency of pulse occurrence. For some classes of stationary input processes where the formulation of the appropriate multidimensional Markov diffusion model of the input-plus-NPFM system is possible, the average impulse frequency may be obtained by a generalization of the approach adopted. The results are approximate and numerical, but are in close agreement with Monte Carlo computer simulation results.

  9. 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.

  10. 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.

  11. 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.

  12. Neural substrates of self-referential processing in Chinese Buddhists

    PubMed Central

    Gu, Xiaosi; Mao, Lihua; Ge, Jianqiao; Wang, Gang; Ma, Yina

    2010-01-01

    Our recent work showed that self-trait judgment is associated with increased activity in the ventral medial prefrontal cortex (VMPFC) in non-religious Chinese, but in the dorsal medial prefrontal cortex (DMPFC) in Chinese Christians. The current work further investigated neural substrates of self-referential processing in Chinese Buddhists. Using functional magnetic resonance imaging, we scanned 14 Chinese Buddhists, while they conducted trait judgments of the self, Zhu Rongji (the former Chinese premier), Sakyamuni (the Buddhist leader) and Jesus (the Christian leader). We found that, relative to Zhu Rongji judgment, self-judgment in Buddhist participants failed to generate increased activation in the VMPFC but induced increased activations in the DMPFC/rostral anterior cingulate cortex, midcingulate and the left frontal/insular cortex. Self-judgment was also associated with decreased functional connectivity between the DMPFC and posterior parietal cortex compared with Zhu Rongji judgment. The results suggest that Buddhist doctrine of No-self results in weakened neural coding of stimulus self-relatedness in the VMPFC, but enhanced evaluative processes of self-referential stimuli in the DMPFC. Moreover, self-referential processing in Buddhists is characterized by monitoring the conflict between the doctrine of No-self and self-focus thinking during self-trait judgment. PMID:19620181

  13. Reduced early visual emotion discrimination as an index of diminished emotion processing in Parkinson's disease? - Evidence from event-related brain potentials.

    PubMed

    Wieser, Matthias J; Klupp, Elisabeth; Weyers, Peter; Pauli, Paul; Weise, David; Zeller, Daniel; Classen, Joseph; Mühlberger, Andreas

    2012-10-01

    Although Parkinson's disease (PD) is defined by its motor symptoms, it is now well recognized that cognitive and affective domains, such as recognition of emotion from facial expressions, may also be impaired. To examine brain mechanisms involved in processing of emotion recognition from facial expressions, we obtained affective ratings and visual event-related potentials (ERPs) in response to facial expressions from 18 PD patients under dopamine-replacement therapy, and 17 healthy age- and sex-matched controls. In control subjects, the early posterior negativity (EPN) of the ERP, which is thought to reflect early perceptual emotion discrimination, was larger in response to emotional compared to neutral facial expressions. In contrast, this emotional modulation of the EPN was absent in PD patients indicating impaired early emotion discrimination. Behaviorally, PD patients showed no impairments in emotion recognition as measured by affective ratings. These findings suggest that facial emotion processing may be disrupted at an early stage of visual neural processing in PD. Absence of behavioral impairment may point to compensatory strategies of emotion recognition in medicated PD patients. Further research should clarify these dissociations between behavioral and neurophysiological levels of emotion processing in PD. Copyright © 2011 Elsevier Srl. All rights reserved.

  14. 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.

  15. 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.

  16. Infants' neural processing of positive emotion and eye gaze.

    PubMed

    Hoehl, Stefanie; Striano, Tricia

    2010-01-01

    Previous research demonstrated that young infants' neural processing of novel objects is enhanced by a fearful face gazing toward the object. The current event-related potential (ERP) study addresses the question of whether this effect is driven by the particular threat-value of a fearful expression or whether a positive emotion could elicit a similar response. Three-month-old infants' brain responses were measured while infants were presented with happy and neutral faces gazing toward simultaneously presented objects (Experiment 1) or happy and neutral faces gazing away from objects (Experiment 2). Then the objects were presented again without the face. While infants showed an increased neural response for happy relative to neutral faces looking towards objects, infants did not differentiate between happy and neutral faces gazing away from the objects. Furthermore, infants showed no different response to objects alone in Experiment 1. However, infants responded with an increased negative central component (Nc) indicating increased attention for objects in the neutral face condition in Experiment 2. The current results confirm previous findings showing that infants allocate increased attention to an emotional face if it directs eye gaze toward an object in the environment. However, a happy expression does not increase subsequent processing of the gaze-cued object. The findings are discussed in terms of early social cognitive development.

  17. Multisensory emotions: perception, combination and underlying neural processes.

    PubMed

    Klasen, Martin; Chen, Yu-Han; Mathiak, Klaus

    2012-01-01

    In our everyday lives, we perceive emotional information via multiple sensory channels. This is particularly evident for emotional faces and voices in a social context. Over the past years, a multitude of studies have addressed the question of how affective cues conveyed by auditory and visual channels are integrated. Behavioral studies show that hearing and seeing emotional expressions can support and influence each other, a notion which is supported by investigations on the underlying neurobiology. Numerous electrophysiological and neuroimaging studies have identified brain regions subserving the integration of multimodal emotions and have provided new insights into the neural processing steps underlying the synergistic confluence of affective information from voice and face. In this paper we provide a comprehensive review covering current behavioral, electrophysiological and functional neuroimaging findings on the combination of emotions from the auditory and visual domains. Behavioral advantages arising from multimodal redundancy are paralleled by specific integration patterns on the neural level, from encoding in early sensory cortices to late cognitive evaluation in higher association areas. In summary, these findings indicate that bimodal emotions interact at multiple stages of the audiovisual integration process.

  18. The neural correlates of emotion processing in juvenile offenders.

    PubMed

    Pincham, Hannah L; Bryce, Donna; Pasco Fearon, R M

    2015-11-01

    Individuals with severe antisocial behaviour often demonstrate abnormalities or difficulties in emotion processing. Antisocial behaviour typically onsets before adulthood and is reflected in antisocial individuals at the biological level. We therefore conducted a brain-based study of emotion processing in juvenile offenders. Male adolescent offenders and age-matched non-offenders passively viewed emotional images whilst their brain activity was recorded using electroencephalography. The early posterior negativity (EPN) and the late positive potential (LPP) components were used as indices of emotion processing. For both juvenile offenders and non-offenders, the EPN differentiated unpleasant images from other image types, suggesting that early perceptual processing was not impaired in the offender group. In line with normal emotion processing, the LPP was significantly enhanced following unpleasant images for non-offenders. However, for juvenile offenders, the LPP did not differ across image categories, indicative of deficient emotional processing. The findings indicated that this brain-based hypo-reactivity occurred during a late stage of cognitive processing and was not a consequence of atypical early visual attention or perception. This study is the first to show attenuated emotion processing in juvenile offenders at the neural level. Overall, these results have the potential to inform interventions for juvenile offending. © 2014 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

  19. Tickling expectations: neural processing in anticipation of a sensory stimulus.

    PubMed

    Carlsson, K; Petrovic, P; Skare, S; Petersson, K M; Ingvar, M

    2000-07-01

    Predictions of the near future can optimize the accuracy and speed of sensory processing as well as of behavioral responses. Previous experience and contextual cues are essential elements in the generation of a subjective prediction. Using a blocked fMRI paradigm, we investigated the pattern of neural activation in anticipation of a sensory stimulus and during the processing of the somatosensory stimulus itself. Tickling was chosen as the somatosensory stimulus rather than simple touch in order to increase the probability to get a high degree of anticipation. The location and nature of the stimulus were well defined to the subject. The state of anticipation was initiated by attributing an uncertainty regarding the time of stimulus onset. The network of activation and deactivation during anticipation of the expected stimulus was similar to that engaged during the actual sensory stimulation. The areas that were activated during both states included the contralateral primary sensory cortex, bilateral areas in the inferior parietal lobules, the putative area SII, the right anterior cingulate cortex and areas in the right prefrontal cortex. Similarly, common decreases were observed in areas of sensorimotor cortex located outside the area representing the target of stimulus, i.e., areas that process information which is irrelevant to the attended process. The overlapping pattern of change, during the somatosensory stimulation and the anticipation, furthers the idea that predictions are subserved by a neuronal network similar to that which subserves the processing of actual sensory input. Moreover, this study indicates that activation of primary somatosensory cortex can be obtained without intra-modal sensory input. These findings suggest that anticipation may invoke a tonic top-down regulation of neural activity.

  20. 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.

  1. 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.

  2. Emotional sounds modulate early neural processing of emotional pictures.

    PubMed

    Gerdes, Antje B M; Wieser, Matthias J; Bublatzky, Florian; Kusay, Anita; Plichta, Michael M; Alpers, Georg W

    2013-01-01

    In our natural environment, emotional information is conveyed by converging visual and auditory information; multimodal integration is of utmost importance. In the laboratory, however, emotion researchers have mostly focused on the examination of unimodal stimuli. Few existing studies on multimodal emotion processing have focused on human communication such as the integration of facial and vocal expressions. Extending the concept of multimodality, the current study examines how the neural processing of emotional pictures is influenced by simultaneously presented sounds. Twenty pleasant, unpleasant, and neutral pictures of complex scenes were presented to 22 healthy participants. On the critical trials these pictures were paired with pleasant, unpleasant, and neutral sounds. Sound presentation started 500 ms before picture onset and each stimulus presentation lasted for 2 s. EEG was recorded from 64 channels and ERP analyses focused on the picture onset. In addition, valence and arousal ratings were obtained. Previous findings for the neural processing of emotional pictures were replicated. Specifically, unpleasant compared to neutral pictures were associated with an increased parietal P200 and a more pronounced centroparietal late positive potential (LPP), independent of the accompanying sound valence. For audiovisual stimulation, increased parietal P100 and P200 were found in response to all pictures which were accompanied by unpleasant or pleasant sounds compared to pictures with neutral sounds. Most importantly, incongruent audiovisual pairs of unpleasant pictures and pleasant sounds enhanced parietal P100 and P200 compared to pairings with congruent sounds. Taken together, the present findings indicate that emotional sounds modulate early stages of visual processing and, therefore, provide an avenue by which multimodal experience may enhance perception.

  3. Emotional sounds modulate early neural processing of emotional pictures

    PubMed Central

    Gerdes, Antje B. M.; Wieser, Matthias J.; Bublatzky, Florian; Kusay, Anita; Plichta, Michael M.; Alpers, Georg W.

    2013-01-01

    In our natural environment, emotional information is conveyed by converging visual and auditory information; multimodal integration is of utmost importance. In the laboratory, however, emotion researchers have mostly focused on the examination of unimodal stimuli. Few existing studies on multimodal emotion processing have focused on human communication such as the integration of facial and vocal expressions. Extending the concept of multimodality, the current study examines how the neural processing of emotional pictures is influenced by simultaneously presented sounds. Twenty pleasant, unpleasant, and neutral pictures of complex scenes were presented to 22 healthy participants. On the critical trials these pictures were paired with pleasant, unpleasant, and neutral sounds. Sound presentation started 500 ms before picture onset and each stimulus presentation lasted for 2 s. EEG was recorded from 64 channels and ERP analyses focused on the picture onset. In addition, valence and arousal ratings were obtained. Previous findings for the neural processing of emotional pictures were replicated. Specifically, unpleasant compared to neutral pictures were associated with an increased parietal P200 and a more pronounced centroparietal late positive potential (LPP), independent of the accompanying sound valence. For audiovisual stimulation, increased parietal P100 and P200 were found in response to all pictures which were accompanied by unpleasant or pleasant sounds compared to pictures with neutral sounds. Most importantly, incongruent audiovisual pairs of unpleasant pictures and pleasant sounds enhanced parietal P100 and P200 compared to pairings with congruent sounds. Taken together, the present findings indicate that emotional sounds modulate early stages of visual processing and, therefore, provide an avenue by which multimodal experience may enhance perception. PMID:24151476

  4. 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

  5. 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

  6. 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

  7. 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.

  8. Adaptive neural information processing with dynamical electrical synapses.

    PubMed

    Xiao, Lei; Zhang, Dan-Ke; Li, Yuan-Qing; Liang, Pei-Ji; Wu, Si

    2013-01-01

    The present study investigates a potential computational role of dynamical electrical synapses in neural information process. Compared with chemical synapses, electrical synapses are more efficient in modulating the concerted activity of neurons. Based on the experimental data, we propose a phenomenological model for short-term facilitation of electrical synapses. The model satisfactorily reproduces the phenomenon that the neuronal correlation increases although the neuronal firing rates attenuate during the luminance adaptation. We explore how the stimulus information is encoded in parallel by firing rates and correlated activity of neurons, and find that dynamical electrical synapses mediate a transition from the firing rate code to the correlation one during the luminance adaptation. The latter encodes the stimulus information by using the concerted, but lower neuronal firing rate, and hence is economically more efficient.

  9. 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.

  10. 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.

  11. Neural correlates of sublexical processing in phonological working memory.

    PubMed

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

    2011-04-01

    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 responses to these manipulations under conditions of covert rehearsal (Experiment 1). A left-dominant network of temporal and motor cortex showed increased activity for longer items, with motor cortex only showing greater activity concomitant with adding consonant clusters. An individual-differences analysis revealed a significant positive relationship between activity in the angular gyrus and the hippocampus, and accuracy on pseudoword repetition. As models of pWM stipulate that its neural correlates should be activated during both perception and production/rehearsal [Buchsbaum, B. R., & D'Esposito, M. The search for the phonological store: From loop to convolution. Journal of Cognitive Neuroscience, 20, 762-778, 2008; Jacquemot, C., & Scott, S. K. What is the relationship between phonological short-term memory and speech processing? Trends in Cognitive Sciences, 10, 480-486, 2006; Baddeley, A. D., & Hitch, G. Working memory. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 8, pp. 47-89). New York: Academic Press, 1974], we further assessed the effects of the two factors in a separate passive listening experiment (Experiment 2). In this experiment, the effect of the number of syllables was concentrated in posterior-medial regions of the supratemporal plane bilaterally, although there was no evidence of a significant response to added clusters. Taken together, the results identify the planum temporale as a key region in pWM; within this region, representations are likely to take the form of auditory or audiomotor "templates" or "chunks" at the level of the syllable

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. Neural hyporesponsiveness and hyperresponsiveness during immediate and delayed reward processing in adult attention-deficit/hyperactivity disorder.

    PubMed

    Plichta, Michael M; Vasic, Nenad; Wolf, Robert Christian; Lesch, Klaus-Peter; Brummer, Dagmar; Jacob, Christian; Fallgatter, Andreas J; Grön, Georg

    2009-01-01

    Dysfunctional reward processing, accompanied by a limited ability to tolerate reward delays, has been proposed as an important feature in attention-deficit/hyperactivity disorder (ADHD). Using functional magnetic resonance imaging (fMRI), brain activation in adult patients with ADHD (n=14) and healthy control subjects (n=12) was examined during a series of choices between two monetary reward options that varied by delay to delivery. Compared with healthy control subjects, hyporesponsiveness of the ventral-striatal reward system was replicated in patients with ADHD and was evident for both immediate and delayed rewards. In contrast, delayed rewards evoked hyperactivation in dorsal caudate nucleus and amygdala of ADHD patients. In both structures, neural activity toward delayed rewards was significantly correlated with self-rated ADHD symptom severity. The finding of ventral-striatal hyporesponsiveness during immediate and delayed reward processing in patients with ADHD further strengthens the concept of a diminished neural processing of rewards in ADHD. Hyperactivation during delayed reward processing, gradually increasing along the ventral-to-dorsal extension of the caudate nucleus, and especially the concomitant hyperactivation of the amygdala are in accordance with predictions of the delay aversion hypothesis.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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

  4. Extraction of shoreline features by neural nets and image processing

    SciTech Connect

    Ryan, T.W.; Sementilli, P.J.; Yuen, P.; Hunt, B.R. )

    1991-07-01

    This paper demonstrates the capability of using neural networks as a tool for delineation of shorelines. The neural nets used are multilayer perceptrons, i.e., feed-forward nets with one or more layers of nodes between the input and output nodes. The back-propagation learning algorithm is used as the adaptation rule. 24 refs.

  5. 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.

  6. 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.

  7. 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.

  8. Socially anxious tendencies affect neural processing of gaze perception.

    PubMed

    Tsuji, Yuki; Shimada, Sotaro

    2017-11-01

    The gaze of others is known to be a particularly common cause of social anxiety. In the current study, we measured event-related potentials (ERPs) during gaze perception among people with or without high socially anxious tendencies (HSA). The experimental stimuli were grayscale images of the eye region of a face, showing direct or averted eye gaze (leftward gaze or rightward gaze) or closed eyes. We found that negative ERPs at a right occipito-temporal site (N170) and positive ERPs at the fronto-central region (P2) were evoked by eye gaze stimuli. While the N170 was not affected by socially anxious tendencies, the amplitude of the P2 was significantly greater in the HSA group than in the low socially anxious tendencies (LSA) group. Furthermore, P2 latency showed a significant interaction between groups and conditions: the HSA group exhibited shorter P2 latencies in response to direct gaze than averted gaze, while the LSA group did not. These results indicate that the neural processing of eye gaze is strongly influenced by socially anxious tendencies. In particular, the attentional processing of direct gaze is more prominent in individuals with HSA tendencies. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. 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

  10. 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.

  11. 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

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

    PubMed Central

    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. PMID:24367339

  13. 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.

  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. Dissociable Neural Processes Underlying Risky Decisions for Self Versus Other

    PubMed Central

    Jung, Daehyun; Sul, Sunhae; Kim, Hackjin

    2013-01-01

    Previous neuroimaging studies on decision making have mainly focused on decisions on behalf of oneself. Considering that people often make decisions on behalf of others, it is intriguing that there is little neurobiological evidence on how decisions for others differ from those for oneself. The present study directly compared risky decisions for self with those for another person using functional magnetic resonance imaging (fMRI). Participants were asked to perform a gambling task on behalf of themselves (decision-for-self condition) or another person (decision-for-other condition) while in the scanner. Their task was to choose between a low-risk option (i.e., win or lose 10 points) and a high-risk option (i.e., win or lose 90 points) with variable levels of winning probability. Compared with choices regarding others, those regarding oneself were more risk-averse at lower winning probabilities and more risk-seeking at higher winning probabilities, perhaps due to stronger affective process during risky decisions for oneself compared with those for other. The brain-activation pattern changed according to the target, such that reward-related regions were more active in the decision-for-self condition than in the decision-for-other condition, whereas brain regions related to the theory of mind (ToM) showed greater activation in the decision-for-other condition than in the decision-for-self condition. Parametric modulation analysis using individual decision models revealed that activation of the amygdala and the dorsomedial prefrontal cortex (DMPFC) were associated with value computations for oneself and for another, respectively, during risky financial decisions. The results of the present study suggest that decisions for oneself and for other may recruit fundamentally distinct neural processes, which can be mainly characterized as dominant affective/impulsive and cognitive/regulatory processes, respectively. PMID:23519016

  16. Audio Spectrogram Representations for Processing with Convolutional Neural Networks

    NASA Astrophysics Data System (ADS)

    Wyse, L.

    2017-05-01

    One of the decisions that arise when designing a neural network for any application is how the data should be represented in order to be presented to, and possibly generated by, a neural network. For audio, the choice is less obvious than it seems to be for visual images, and a variety of representations have been used for different applications including the raw digitized sample stream, hand-crafted features, machine discovered features, MFCCs and variants that include deltas, and a variety of spectral representations. This paper reviews some of these representations and issues that arise, focusing particularly on spectrograms for generating audio using neural networks for style transfer.

  17. 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

  18. 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

  19. 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.

  20. 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.

  1. Neural correlates of semantic ambiguity processing during context verification.

    PubMed

    Hoenig, Klaus; Scheef, Lukas

    2009-04-15

    Understanding the relevant meaning of a word with different meanings (homonym) in a given context requires activation of the neural representations of the relevant meaning and inhibition of the irrelevant meaning. The cognitive demand of such disambiguation is highest when the dominant, yet contextually irrelevant meaning of a polar homonym must be suppressed. This central process (semantic inhibition) for lexico-semantic ambiguity resolution was monitored with fMRI during semantic context verifications. Twenty-two healthy volunteers decided whether congruent or incongruent target words fitted into the contexts established by preceding sentences. Half of the sentences ended with a homonym, thereby allowing to cross the factors ambiguity and semantic congruency. BOLD increases related to the inhibitory attentional control over non-selected meanings during ambiguity processing occurred in a brain network including left dorsolateral prefrontal cortex (DLPFC), bilateral angular gyrus (AG), bilateral anterior superior temporal gyrus (aSTG) as well as right ventromedial temporal lobe. In left DLPFC (BA 46/9) and left AG (BA 39) BOLD activity to target words of the incongruent-ambiguous condition correlated with the individual amount of semantic interference experienced by the subjects. BOLD increases of incongruent versus congruent semantic verifications occurred in bilateral inferior frontal gyrus. The results of the present study suggest a specific role of left DLPFC and AG in the resolution of semantic interference from contextually inappropriate homonym meanings. These fronto-parietal areas might exert inhibitory control over temporal regions in service of attentional selection between relevant and irrelevant homonym meanings, by creating a sufficient activation difference between their respective representations.

  2. 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.

  3. 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

  4. 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…

  5. 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…

  6. 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…

  7. 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…

  8. 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

  9. 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.

  10. 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.

  11. Neural processing of biological motion in the macaque temporal cortex

    NASA Astrophysics Data System (ADS)

    Oram, Michael W.; Perrett, David I.

    1994-03-01

    Cells have been found in the superior temporal polysensory area (STPa) of the macaque temporal cortex which are selectively responsive to the sight of particular whole body movements (e.g., walking) under normal lighting. These cells typically discriminate the direction of walking and the view of the body (e.g., left profile walking left). We investigated the extent to which these cells are responsive under `biological motion' conditions where the form of the body is defined only by the movement of light patches attached to the points of limb articulation. One third of the cells (25/72) selective for the form and motion of waling bodies, showed sensitivity to the moving light displays. Seven of these cells showed only partial sensitivity to form from motion, in so far as the cells responded more to moving light displays than to moving controls but failed to discriminate body view. These seven cells exhibited directional selectivity. Eighteen cells showed statistical discrimination for both direction of movement and body view under biological motion conditions. Most of these cells showed reduced responses to the impoverished moving light stimuli compared to full light conditions. The 18 cells were thus sensitive to detailed form information (body view) from the pattern of articulating motion. Cellular processing of the global pattern of articulation was indicated by the observations that none of the cells were found sensitive to movement of individual limbs and that jumbling the pattern of moving limbs reduced response magnitude. The cell responses thus provide direct evidence for neural mechanisms computing form from non-rigid motion. The selectivity of the cells was for body view, specific direction and specific type of body motion presented by moving light displays and is not predicted by many current computational approaches to the extraction of form from motion.

  12. Learning-induced neural plasticity of speech processing before birth

    PubMed Central

    Partanen, Eino; Kujala, Teija; Näätänen, Risto; Liitola, Auli; Sambeth, Anke; Huotilainen, Minna

    2013-01-01

    Learning, the foundation of adaptive and intelligent behavior, is based on plastic changes in neural assemblies, reflected by the modulation of electric brain responses. In infancy, auditory learning implicates the formation and strengthening of neural long-term memory traces, improving discrimination skills, in particular those forming the prerequisites for speech perception and understanding. Although previous behavioral observations show that newborns react differentially to unfamiliar sounds vs. familiar sound material that they were exposed to as fetuses, the neural basis of fetal learning has not thus far been investigated. Here we demonstrate direct neural correlates of human fetal learning of speech-like auditory stimuli. We presented variants of words to fetuses; unlike infants with no exposure to these stimuli, the exposed fetuses showed enhanced brain activity (mismatch responses) in response to pitch changes for the trained variants after birth. Furthermore, a significant correlation existed between the amount of prenatal exposure and brain activity, with greater activity being associated with a higher amount of prenatal speech exposure. Moreover, the learning effect was generalized to other types of similar speech sounds not included in the training material. Consequently, our results indicate neural commitment specifically tuned to the speech features heard before birth and their memory representations. PMID:23980148

  13. 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.

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

    PubMed Central

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

    2016-01-01

    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 = 104 does not exceed 8. PMID:26778977

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. Integration Of Parallel Image Processing With Symbolic And Neural Computations For Imagery Exploitation

    NASA Astrophysics Data System (ADS)

    Roman, Evelyn

    1990-02-01

    In this paper we discuss the work being done at Itek combining parallel, symbolic, and neural methodologies at different stages of processing for imagery exploitation. We describe a prototype system we have been implementing combining real-time parallel image processing on an 8-stage parallel image-processing engine (PIPE) computer with expert system software such as our Multi-Sensor Exploitation Assistant system on the Symbolics LISP machine and with neural computations on the PIPE and on its host IBM AT for target recognition and change detection applications. We also provide a summary of basic neural concepts, and show the commonality between neural nets and related mathematics, artificial intelligence, and traditional image processing concepts. This provides us with numerous choices for the implementation of constraint satisfaction, transformational invariance, inference and representational mechanisms, and software lifecycle engineering methodologies in the different computational layers. Our future work may include optical processing as well, for a real-time capability complementing the PIPE's.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

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

    DTIC Science & Technology

    1998-06-08

    June 98 REPORT TYPE AND DATES COVERED Final \\^Q\\ Cf\\ - M DteC ^ TITLE AND SUBTITLE Neural Networks for Signal Processing VII Proceeding...C^ mm m 13, ABSTRACT (Maximum 200 words) NNSP󈨥 was held in Amelia Island Plantation, Amelia Island, Florida, September 24-26.1997. NNSP󈨥 was...1997 IEEE WORKSHOP Edited by Jose Principe Lee Gile Nelson Morgan Elizabeth Wilson l^J m NEURAL NETWORKS H»«lf FOR SIGNAL PROCESSING VII

  6. 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

  7. The 1991 Neural Information Processing Systems-natural & Synthetic

    DTIC Science & Technology

    1993-02-01

    K ! Williams, and Mich /l D. Retvow Part IX CONTROL AND PLANNING Obstacle Avoidance through Reinforcement Learning .................. 523 TonyJ Prescon...Separation of Sources that are Superimposed and Delayed . . . 730 John C. Plan and Federico Faggin Part XI IMPLEMENTATION CCD Neural Network Processors... Federico Faggin, Synaptics David A. Cohn, Univ. of Washington Hans Peter GraL AT&T Michael Littman, Bellcore Kristina Johnson, Univ. of Colorado David Plaut

  8. 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

  9. SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

    PubMed

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

    2016-03-01

    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.

  10. 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.

  11. 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

  12. Auditory processing disorders: relationship to cognitive processes and underlying auditory neural integrity.

    PubMed

    Allen, Prudence; Allan, Chris

    2014-02-01

    Auditory processing disorder (APD) in children has been reported and discussed in the clinical and research literature for many years yet there remains poor agreement on diagnostic criteria, the relationship between APD and cognitive skills, and the importance of assessing underlying neural integrity. The present study used a repeated measures design to examine the relationship between a clinical APD diagnosis achieved with behavioral tests used in many clinics, cognitive abilities measured with standardized tests of intelligence, academic achievement, language, phonology, memory and attention and measures of auditory neural integrity as measured with acoustic reflex thresholds and auditory brainstem responses. Participants were 63 children, 7-17 years of age, who reported listening difficulties in spite of normal hearing thresholds. Parents/guardians completed surveys about the child's auditory and attention behavior while children completed an audiologic examination that included 5 behavioral tests of auditory processing ability. Standardized tests that examined intelligence, academic achievement, language, phonology, memory and attention, and objective tests auditory function included crossed and uncrossed acoustic reflex thresholds and auditory brainstem responses (ABR) were also administered to each child. Forty of the children received an APD diagnosis based on the 5 behavioral tests and 23 did not. The groups of children performed similarly on intelligence measures but the children with an APD diagnosis tended to perform more poorly on other cognitive measures. Auditory brainstem responses and acoustic reflex thresholds were often abnormal in both groups of children. Results of this study suggest that a purely behavioral test battery may be insufficient to accurately identify all children with auditory processing disorders. Physiologic test measures, including acoustic reflex and auditory brainstem response tests, are important indicators of auditory

  13. 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

  14. 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.

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

    PubMed

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

    2016-01-01

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

  16. Negative symptoms in schizophrenia show association with amygdala volumes and neural activation during affective processing.

    PubMed

    Rahm, Christoffer; Liberg, Benny; Reckless, Greg; Ousdal, Olga; Melle, Ingrid; Andreassen, Ole A; Agartz, Ingrid

    2015-08-01

    Negative symptoms in schizophrenia have been associated with structural and functional alterations of the amygdala. We hypothesised that there would be between-group differences in amygdala volume and neural activation patterns during processing of affective stimuli among patients with schizophrenia and healthy controls. We further hypothesised correlations between neuroimaging metrics and clinical ratings of negative symptoms in patients with schizophrenia. We used structural and functional magnetic resonance imaging to assess volume and neural activation of the amygdala in 28 patients with schizophrenia and 28 healthy controls. We found no between-group differences in amygdala volume or neural activation. However, we found a significant negative correlation between emotional blunting and neural activation in the left amygdala during processing of positive affect. We also found a significant negative correlation between stereotyped thinking and the volume of right amygdala. Our findings implicate the amygdala in a subgroup of negative symptoms in schizophrenia that are characterised by reduced expression with blunted affect and stereotyped thinking.

  17. 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.

  18. 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

  19. 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

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

    PubMed

    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.

  1. 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.

  2. 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.

  3. Aberrant neural processing of moral violations in criminal psychopaths

    PubMed Central

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

    2010-01-01

    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, 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 vs. nonpsychopaths showed atypical activity in several regions involved in moral decision-making. This included reduced moral/non-moral 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. PMID:21090881

  4. 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.

  5. Time-dependent Neural Processing of Auditory Feedback during Voice Pitch Error Detection

    PubMed Central

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

    2012-01-01

    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. PMID:20146608

  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.

    1998-01-01

    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. 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.

  9. 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.

    1998-01-01

    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.

  10. Real-time water treatment process control with artificial neural networks

    SciTech Connect

    Zhang, Q.; Stanley, S.J.

    1999-02-01

    With more stringent requirements being placed on water treatment performance, operators need a reliable tool to optimize the process control in the treatment plant. In the present paper, one such tool is presented, which is a process control system built with the artificial neural network (ANN) modeling approach. The coagulation, flocculation, and sedimentation processes involve many complex physical and chemical phenomena and thus are difficult to model for process control with traditional methods. Proposed is the use of a neural network process control system for the coagulation, flocculation, and sedimentation processes. Presented is a review of influential control parameters and control requirements for these processes followed by the development of a feed forward neural network control scheme. A neural network process model was built based on nearly 2,000 sets of process control data. This model formed the major component of a software controller and was found to consistently predict the optimum alum and power activated carbon doses for different control actions. With minor modifications, the approach illustrated can be used for building control models for other water treatment processes.

  11. Diminishing Returns in Humanities Research

    ERIC Educational Resources Information Center

    Bauerlein, Mark

    2009-01-01

    The author discusses the shift from criticism-as-explanation to criticism-as-performance that has taken place in literary criticism over the past five decades, and the resultant surge in published offerings to what has become a diminishing audience. The question of supersaturation applies to the institutions that demand and reward humanities…

  12. 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.

  13. Neural processing of amplitude and formant rise time in dyslexia.

    PubMed

    Peter, Varghese; Kalashnikova, Marina; Burnham, Denis

    2016-06-01

    This study aimed to investigate how children with dyslexia weight amplitude rise time (ART) and formant rise time (FRT) cues in phonetic discrimination. Passive mismatch responses (MMR) were recorded for a/ba/-/wa/contrast in a multiple deviant odd-ball paradigm to identify the neural response to cue weighting in 17 children with dyslexia and 17 age-matched control children. The deviant stimuli had either partial or full ART or FRT cues. The results showed that ART did not generate an MMR in either group, whereas both partial and full FRT cues generated MMR in control children while only full FRT cues generated MMR in children with dyslexia. These findings suggest that children, both controls and those with dyslexia, discriminate speech based on FRT cues and not ART cues. However, control children have greater sensitivity to FRT cues in speech compared to children with dyslexia. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. 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.

  15. 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…

  16. 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…

  17. 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…

  18. 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.

  19. 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

  20. Neural reward processing is modulated by approach- and avoidance-related personality traits.

    PubMed

    Simon, Joe J; Walther, Stephan; Fiebach, Christian J; Friederich, Hans-Christoph; Stippich, Christoph; Weisbrod, Matthias; Kaiser, Stefan

    2010-01-15

    The neural processing of reward can be differentiated into two sub-components with different functions, "wanting" (i.e., the expectation of a reward which includes appetitive and motivational components) and "liking" (i.e., the hedonic impact experienced during the receipt of a reward), involving distinct neural systems. We hypothesize that variability in neural reward processing previously observed in healthy subjects could reflect inter-individual differences in personality. Therefore, the aim of this study was to investigate how the neural processing during expectation and reception of a reward depends on interpersonal differences in reward sensitivity, more specifically the tendency to approach vs. avoid reward-related situations. We employed event-related functional magnetic resonance imaging during a monetary incentive delay task. Subjects with a high approach motivation showed more activation of the Ventral Striatum (VS) during the receipt of a reward, and more medial orbitofrontal activity during both the receipt and omission of a reward. Subjects with a high behavioral inhibition showed less activation in the VS during the receipt of a reward. These findings indicate that the tendency to approach or avoid reward-related situations exhibits a distinct relation with neural reward processing. Specifically, subjects with high behavioral approach appear to be sensitive mainly to positive outcomes and to a lesser extent to the omissions of rewards, whereas subjects with low behavioral approach as well as those with a high inhibition tendency display a blunted response to rewards.

  1. 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.

  2. 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.

  3. 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

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

    PubMed

    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.

  5. Large-Scale Neural Network for Sentence Processing

    ERIC Educational Resources Information Center

    Cooke, Ayanna; Grossman, Murray; DeVita, Christian; Gonzalez-Atavales, Julio; Moore, Peachie; Chen, Willis; Gee, James; Detre, John

    2006-01-01

    Our model of sentence comprehension includes at least grammatical processes important for structure-building, and executive resources such as working memory that support these grammatical processes. We hypothesized that a core network of brain regions supports grammatical processes, and that additional brain regions are activated depending on the…

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

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

    PubMed Central

    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. PMID:26985989

  12. 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.

  13. Neural dissociation of number from letter recognition and its relationship to parietal numerical processing.

    PubMed

    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 numerals. We found that letters activated the left midfusiform and inferior temporal gyri more than numbers, replicating previous studies, whereas numbers activated a right lateral occipital area more than letters at the group level. Because the distinction between letters and numbers is culturally defined and relatively arbitrary, this double dissociation provides some of the strongest evidence to date that a neural dissociation can emerge as a result of experience. We then investigated a potential source of the observed neural dissociation. Specifically, we tested the hypothesis that lateralization of visual number recognition depends on lateralization of higher-order numerical processing. In Experiment 2, the same participants performed addition, subtraction, and counting on arrays of nonsymbolic stimuli varying in numerosity, which produced neural activity in and around the intraparietal sulcus, a region associated with higher-order numerical processing. We found that individual differences in the lateralization of number activity in visual cortex could be explained by individual differences in the lateralization of numerical processing in parietal cortex, suggesting a functional relationship between the two regions. Together, these results demonstrate a neural double dissociation between letter and number recognition and suggest that higher-level numerical processing in parietal cortex may influence the neural organization of number processing in visual cortex.

  14. Adaptive neural reward processing during anticipation and receipt of monetary rewards in mindfulness meditators

    PubMed Central

    Brown, Kirk Warren; Downar, Jonathan

    2015-01-01

    Reward seeking is ubiquitous and adaptive in humans. But excessive reward seeking behavior, such as chasing monetary rewards, may lead to diminished subjective well-being. This study examined whether individuals trained in mindfulness meditation show neural evidence of lower susceptibility to monetary rewards. Seventy-eight participants (34 meditators, 44 matched controls) completed the monetary incentive delay task while undergoing functional magnetic resonance imaging. The groups performed equally on the task, but meditators showed lower neural activations in the caudate nucleus during reward anticipation, and elevated bilateral posterior insula activation during reward anticipation. Meditators also evidenced reduced activations in the ventromedial prefrontal cortex during reward receipt compared with controls. Connectivity parameters between the right caudate and bilateral anterior insula were attenuated in meditators during incentive anticipation. In summary, brain regions involved in reward processing—both during reward anticipation and receipt of reward—responded differently in mindfulness meditators than in nonmeditators, indicating that the former are less susceptible to monetary incentives. PMID:25193949

  15. 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.

  16. 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.

  17. Neural Correlates of Individual Differences in Strategic Retrieval Processing

    ERIC Educational Resources Information Center

    Bridger, Emma K.; Herron, Jane E.; Elward, Rachael L.; Wilding, Edward L.

    2009-01-01

    Processes engaged when information is encoded into memory are an important determinant of whether that information will be recovered subsequently. Also influential, however, are processes engaged at the time of retrieval, and these were investigated here by using event-related potentials (ERPs) to measure a specific class of retrieval operations.…

  18. 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.

  19. Music training enhances the automatic neural processing of foreign speech sounds.

    PubMed

    Intartaglia, Bastien; White-Schwoch, Travis; Kraus, Nina; Schön, Daniele

    2017-10-03

    Growing evidence shows that music and language experience affect the neural processing of speech sounds throughout the auditory system. Recent work mainly focused on the benefits induced by musical practice on the processing of native language or tonal foreign language, which rely on pitch processing. The aim of the present study was to take this research a step further by investigating the effect of music training on processing English sounds by foreign listeners. We recorded subcortical electrophysiological responses to an English syllable in three groups of participants: native speakers, non-native nonmusicians, and non-native musicians. Native speakers had enhanced neural processing of the formant frequencies of speech, compared to non-native nonmusicians, suggesting that automatic encoding of these relevant speech cues are sensitive to language experience. Most strikingly, in non-native musicians, neural responses to the formant frequencies did not differ from those of native speakers, suggesting that musical training may compensate for the lack of language experience by strengthening the neural encoding of important acoustic information. Language and music experience seem to induce a selective sensory gain along acoustic dimensions that are functionally-relevant-here, formant frequencies that are crucial for phoneme discrimination.

  20. 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.

  1. An analysis of neural receptive field plasticity by point process adaptive filtering

    PubMed Central

    Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

    2001-01-01

    Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

  2. Processing of different types of social threat in shyness: Preliminary findings of distinct functional neural connectivity.

    PubMed

    Tang, Alva; Beaton, Elliott A; Tatham, Erica; Schulkin, Jay; Hall, Geoffrey B; Schmidt, Louis A

    2016-01-01

    Current theory suggests that the processing of different types of threat is supported by distinct neural networks. Here we tested whether there are distinct neural correlates associated with different types of threat processing in shyness. Using fMRI and multivariate techniques, we compared neural responses and functional connectivity during the processing of imminent (i.e., congruent angry/angry face pairs) and ambiguous (i.e., incongruent angry/neutral face pairs) social threat in young adults selected for high and low shyness. To both types of threat processing, non-shy adults recruited a right medial prefrontal cortex (mPFC) network encompassing nodes of the default mode network involved in automatic emotion regulation, whereas shy adults recruited a right dorsal anterior cingulate cortex (dACC) network encompassing nodes of the frontoparietal network that instantiate active attentional and cognitive control. Furthermore, in shy adults, the mPFC interacted with the dACC network for ambiguous threat, but with a distinct network encompassing nodes of the salience network for imminent threat. These preliminary results expand our understanding of right mPFC function associated with temperamental shyness. They also provide initial evidence for differential neural networks associated with shy and non-shy profiles in the context of different types of social threat processing.

  3. 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.

  4. Neural correlates of variations in event processing during learning in basolateral amygdala

    PubMed Central

    Roesch, Matthew R.; Calu, Donna J.; Esber, Guillem R.; Schoenbaum, Geoffrey

    2010-01-01

    The discovery that dopamine neurons signal errors in reward prediction has demonstrated that concepts empirically-derived from the study of animal behavior, can be used to understand the neural implementation of reward learning. Yet the learning theory models linked to phasic dopamine activity treat attention to events such as cues and rewards as static quantities; other models, such as Pearce-Hall, propose that learning might be influenced by variations in processing of these events. A key feature of these accounts is that event processing is modulated by unsigned rather than signed reward prediction errors. Here we tested whether neural activity in rat basolateral amygdala conforms to this pattern by recording single-units in a behavioral task in which rewards were unexpectedly delivered or omitted. We report that neural activity at the time of reward in provided an unsigned error signal with characteristics consistent with those postulated by these models. This neural signal increased immediately after a change in reward, and stronger firing was evident whether the value of the reward increased or decreased. Further, as predicted by these models, the change in firing developed over several trials as expectations for reward were repeatedly violated. This neural signal was correlated with faster orienting to predictive cues after changes in reward, and abolition of the signal by inactivation of basolateral amygdala disrupted this change in orienting and retarded learning in response to changes in reward. These results suggest that basolateral amygdala serves a critical function in attention for learning. PMID:20164330

  5. 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

  6. 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.

  7. 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.

  8. 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)

  9. 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).

  10. The neural bases of spatial frequency processing during scene perception

    PubMed Central

    Kauffmann, Louise; Ramanoël, Stephen; Peyrin, Carole

    2014-01-01

    Theories on visual perception agree that scenes are processed in terms of spatial frequencies. Low spatial frequencies (LSF) carry coarse information whereas high spatial frequencies (HSF) carry fine details of the scene. However, how and where spatial frequencies are processed within the brain remain unresolved questions. The present review addresses these issues and aims to identify the cerebral regions differentially involved in low and high spatial frequency processing, and to clarify their attributes during scene perception. Results from a number of behavioral and neuroimaging studies suggest that spatial frequency processing is lateralized in both hemispheres, with the right and left hemispheres predominantly involved in the categorization of LSF and HSF scenes, respectively. There is also evidence that spatial frequency processing is retinotopically mapped in the visual cortex. HSF scenes (as opposed to LSF) activate occipital areas in relation to foveal representations, while categorization of LSF scenes (as opposed to HSF) activates occipital areas in relation to more peripheral representations. Concomitantly, a number of studies have demonstrated that LSF information may reach high-order areas rapidly, allowing an initial coarse parsing of the visual scene, which could then be sent back through feedback into the occipito-temporal cortex to guide finer HSF-based analysis. Finally, the review addresses spatial frequency processing within scene-selective regions areas of the occipito-temporal cortex. PMID:24847226

  11. 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.

  12. 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,…

  13. 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…

  14. 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…

  15. 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…

  16. 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…

  17. 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.

  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. 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,…

  20. 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…

  1. Perceiving nonverbal behavior: neural correlates of processing movement fluency and contingency in dyadic interactions.

    PubMed

    Georgescu, Alexandra L; Kuzmanovic, Bojana; Santos, Natacha S; Tepest, Ralf; Bente, Gary; Tittgemeyer, Marc; Vogeley, Kai

    2014-04-01

    Despite the fact that nonverbal dyadic social interactions are abundant in the environment, the neural mechanisms underlying their processing are not yet fully understood. Research in the field of social neuroscience has suggested that two neural networks appear to be involved in social understanding: (1) the action observation network (AON) and (2) the social neural network (SNN). The aim of this study was to determine the differential contributions of the AON and the SNN to the processing of nonverbal behavior as observed in dyadic social interactions. To this end, we used short computer animation sequences displaying dyadic social interactions between two virtual characters and systematically manipulated two key features of movement activity, which are known to influence the perception of meaning in nonverbal stimuli: (1) movement fluency and (2) contingency of movement patterns. A group of 21 male participants rated the "naturalness" of the observed scenes on a four-point scale while undergoing fMRI. Behavioral results showed that both fluency and contingency significantly influenced the "naturalness" experience of the presented animations. Neurally, the AON was preferentially engaged when processing contingent movement patterns, but did not discriminate between different degrees of movement fluency. In contrast, regions of the SNN were engaged more strongly when observing dyads with disturbed movement fluency. In conclusion, while the AON is involved in the general processing of contingent social actions, irrespective of their kinematic properties, the SNN is preferentially recruited when atypical kinematic properties prompt inferences about the agents' intentions. Copyright © 2013 Wiley Periodicals, Inc.

  2. 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…

  3. Neural Processing of Eye Gaze and Threat-Related Emotional Facial Expressions in Infancy

    ERIC Educational Resources Information Center

    Hoehl, Stefanie; Striano, Tricia

    2008-01-01

    Combined with emotional expressions, eye gaze can provide essential information to indicate threat in the environment. The current study assessed the effects of eye gaze direction on infants' neural processing of fearful and angry faces. Event-related potentials were recorded from thirteen 7-month-old infants. Two face-sensitive posterior…

  4. 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…

  5. 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…

  6. 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…

  7. 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

  8. 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.

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

    PubMed

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

    2014-01-01

    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.

  10. The neural correlates of intentional and incidental self processing.

    PubMed

    Kircher, Tilo T J; Brammer, M; Bullmore, Edward; Simmons, A; Bartels, M; David, Anthony S

    2002-01-01

    The neuroscientific study of the 'Self' is just beginning to emerge. We used functional Magnetic Resonance Imaging (fMRI) to investigate cerebral activation while subjects processed words describing personality traits and physical features, in two experiments with contrasting designs: incidental and intentional. In the first experiment (intentional self processing), subjects were presented with personality trait adjectives and made judgements as to their self descriptiveness (versus non self descriptiveness). In the second experiment (incidental self processing), subjects categorised words according to whether they described physical versus psychological attributes, while unaware that the words had been arranged in blocks according to self descriptiveness. The subjects had previously rated all words for self descriptiveness 6 weeks prior to the scanning session. A reaction time advantage was present in both experiments for self descriptive trait words, suggesting a facilitation effect. Common areas of activation for the two experiments included the left superior parietal lobe, with adjacent regions of the lateral prefrontal cortex also active in both experiments. Differential signal changes were present in the left precuneus for the intentional and the right middle temporal gyrus for the incidental experiment. The results suggest that self processing involves distinct processes and can occur on more than one cognitive level with corresponding functional neuroanatomic correlates in areas previously implicated in the awareness of one's own state.

  11. 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.

  12. 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.

  13. 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.

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

    PubMed

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

    2015-01-15

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

  15. 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

  16. 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,…

  17. Neural correlates of the healthiness evaluation processes of food labels.

    PubMed

    Prevost, M; Hot, P; Muller, L; Ruffieux, B; Cousin, E; Pichat, C; Baciu, M

    2017-04-11

    This fMRI study evaluated the cognitive mechanisms and the cerebral substrates when evaluating the healthiness of food products from nutritional information displayed either with a traffic light (TL) system, a colored nutritional label, or with a guideline daily amount (GDA) system, a numeric label. We postulated that TL label would recruit emotional processes and activation of subjacent cerebral regions (e.g. insula and amygdala). On the contrary, the nutritional information presented in a GDA label, would recruit, due to its numeric format and higher complexity, supplementary cognitive processes and activation of related brain regions (e.g. middle and superior frontal as well as parietal cortices). We examined 50 healthy participants during an evaluation task on the healthiness of real food products from nutritional information only. Per total, 60 food products nutritional labels have been presented, with either colored (TL) or numeric (GDA) nutritional information and three levels of complexity of nutritional information. In line with our predictions, evaluations based on GDA recruited prefrontal and parietal regions reported for analytic processes. Contrary to our predictions, the same network has been recruited when evaluations were based on TL. Finally, we found significant correlation between response time and the superior parietal lobule in the GDA condition. Our results suggested that TL did not have an effect on the used strategy compared to GDA, based on calculation and arithmetic processes. Correlations between response time and brain activations suggested a significant involvement of the arithmetic mechanisms in the evaluation of food healthiness.

  18. 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…

  19. 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,…

  20. 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.

  1. Neural correlates of three types of negative life events during angry face processing in adolescents.

    PubMed

    Gollier-Briant, Fanny; Paillère-Martinot, Marie-Laure; Lemaitre, Hervé; Miranda, Ruben; Vulser, Hélène; Goodman, Robert; Penttilä, Jani; Struve, Maren; Fadai, Tahmine; Kappel, Viola; Poustka, Luise; Grimmer, Yvonne; Bromberg, Uli; Conrod, Patricia; Banaschewski, Tobias; Barker, Gareth J; Bokde, Arun L W; Büchel, Christian; Flor, Herta; Gallinat, Juergen; Garavan, Hugh; Heinz, Andreas; Lawrence, Claire; Mann, Karl; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Frouin, Vincent; Rietschel, Marcella; Robbins, Trevor W; Smolka, Michael N; Schumann, Gunter; Martinot, Jean-Luc; Artiges, Eric

    2016-12-01

    Negative life events (NLE) contribute to anxiety and depression disorders, but their relationship with brain functioning in adolescence has rarely been studied. We hypothesized that neural response to social threat would relate to NLE in the frontal-limbic emotional regions. Participants (N = 685) were drawn from the Imagen database of 14-year-old community adolescents recruited in schools. They underwent functional MRI while viewing angry and neutral faces, as a probe to neural response to social threat. Lifetime NLEs were assessed using the 'distress', 'family' and 'accident' subscales from a life event dimensional questionnaire. Relationships between NLE subscale scores and neural response were investigated. Links of NLE subscales scores with anxiety or depression outcomes at the age of 16 years were also investigated. Lifetime 'distress' positively correlated with ventral-lateral orbitofrontal and temporal cortex activations during angry face processing. 'Distress' scores correlated with the probabilities of meeting criteria for Generalized Anxiety Disorder or Major Depressive Disorder at the age of 16 years. Lifetime 'family' and 'accident' scores did not relate with neural response or follow-up conditions, however. Thus, different types of NLEs differentially predicted neural responses to threat during adolescence, and differentially predicted a de novo internalizing condition 2 years later. The deleterious effect of self-referential NLEs is suggested. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  2. Neural correlates of three types of negative life events during angry face processing in adolescents

    PubMed Central

    Gollier-Briant, Fanny; Paillère-Martinot, Marie-Laure; Lemaitre, Hervé; Miranda, Ruben; Vulser, Hélène; Goodman, Robert; Penttilä, Jani; Struve, Maren; Fadai, Tahmine; Kappel, Viola; Poustka, Luise; Grimmer, Yvonne; Bromberg, Uli; Conrod, Patricia; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun L. W.; Büchel, Christian; Flor, Herta; Gallinat, Juergen; Garavan, Hugh; Heinz, Andreas; Lawrence, Claire; Mann, Karl; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Frouin, Vincent; Rietschel, Marcella; Robbins, Trevor W.; Smolka, Michael N.; Schumann, Gunter; Artiges, Eric

    2016-01-01

    Negative life events (NLE) contribute to anxiety and depression disorders, but their relationship with brain functioning in adolescence has rarely been studied. We hypothesized that neural response to social threat would relate to NLE in the frontal–limbic emotional regions. Participants (N = 685) were drawn from the Imagen database of 14-year-old community adolescents recruited in schools. They underwent functional MRI while viewing angry and neutral faces, as a probe to neural response to social threat. Lifetime NLEs were assessed using the ‘distress’, ‘family’ and ‘accident’ subscales from a life event dimensional questionnaire. Relationships between NLE subscale scores and neural response were investigated. Links of NLE subscales scores with anxiety or depression outcomes at the age of 16 years were also investigated. Lifetime ‘distress’ positively correlated with ventral-lateral orbitofrontal and temporal cortex activations during angry face processing. ‘Distress’ scores correlated with the probabilities of meeting criteria for Generalized Anxiety Disorder or Major Depressive Disorder at the age of 16 years. Lifetime ‘family’ and ‘accident’ scores did not relate with neural response or follow-up conditions, however. Thus, different types of NLEs differentially predicted neural responses to threat during adolescence, and differentially predicted a de novo internalizing condition 2 years later. The deleterious effect of self-referential NLEs is suggested. PMID:27697987

  3. 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.

  4. Neural Signatures of Controlled and Automatic Retrieval Processes in Memory-based Decision-making.

    PubMed

    Khader, Patrick H; Pachur, Thorsten; Weber, Lilian A E; Jost, Kerstin

    2016-01-01

    Decision-making often requires retrieval from memory. Drawing on the neural ACT-R theory [Anderson, J. R., Fincham, J. M., Qin, Y., & Stocco, A. A central circuit of the mind. Trends in Cognitive Sciences, 12, 136-143, 2008] and other neural models of memory, we delineated the neural signatures of two fundamental retrieval aspects during decision-making: automatic and controlled activation of memory representations. To disentangle these processes, we combined a paradigm developed to examine neural correlates of selective and sequential memory retrieval in decision-making with a manipulation of associative fan (i.e., the decision options were associated with one, two, or three attributes). The results show that both the automatic activation of all attributes associated with a decision option and the controlled sequential retrieval of specific attributes can be traced in material-specific brain areas. Moreover, the two facets of memory retrieval were associated with distinct activation patterns within the frontoparietal network: The dorsolateral prefrontal cortex was found to reflect increasing retrieval effort during both automatic and controlled activation of attributes. In contrast, the superior parietal cortex only responded to controlled retrieval, arguably reflecting the sequential updating of attribute information in working memory. This dissociation in activation pattern is consistent with ACT-R and constitutes an important step toward a neural model of the retrieval dynamics involved in memory-based decision-making.

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. The neural substrates of inferential and referential semantic processing.

    PubMed

    Marconi, Diego; Manenti, Rosa; Catricalà, Eleonora; Della Rosa, Pasquale A; Siri, Simona; Cappa, Stefano F

    2013-09-01

    A distinction has been proposed, on theoretical grounds, between referential and inferential semantic abilities. The former account for the relationship of words to the world, the latter for the relationship of words among themselves. The hypothesis of, at least partially, different neurological underpinnings for this distinction has been supported by the presence of double dissociations in neurological patients between tasks that can be considered to tap the cognitive processes involving these two different classes of semantic knowledge, such as, for example, picture naming (referential) and naming to a verbal definition (inferential). We report here the results of a functional magnetic resonance experiment, contrasting the pattern of brain activity associated with, respectively, "referential" (picture naming, word-to-picture matching) and "inferential" (naming to definition, word-to-word matching) tasks. All tasks activate an extensive set of brain areas involving both hemispheres, corresponding to the "common semantic network". In addition, left hemispheric temporal areas are selectively engaged by the inferential tasks. Conversely, a specific activation of the right fusiform gyrus is associated with the referential tasks. These findings suggest that while inferential tasks, as compared with referential tasks, engage additional processing resources subserved by left hemispheric language areas involved in lexical retrieval, referential tasks (as compared with inferential tasks) recruit right hemispheric areas generally associated with nonverbal conceptual and structural object processing. These findings are compatible with the double dissociations reported in neurological patients. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. 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.

  17. Neural Processing of Musical Meter in Musicians and Non-musicians.

    PubMed

    Zhao, T Christina; Gloria Lam, H T; Sohi, Harkirat; Kuhl, Patricia K

    2017-10-04

    Musical sounds, along with speech, are the most prominent sounds in our daily lives. They are highly dynamic, yet well structured in the temporal domain in a hierarchical manner. The temporal structures enhance the predictability of musical sounds. Western music provides an excellent example: while time intervals between musical notes are highly variable, underlying beats can be realized. The beat-level temporal structure provides a sense of regular pulses. Beats can be further organized into units, giving the percept of alternating strong and weak beats (i.e. metrical structure or meter). Examining neural processing at the meter level offers a unique opportunity to understand how the human brain extracts temporal patterns, predicts future stimuli and optimizes neural resources for processing. The present study addresses two important questions regarding meter processing, using the mismatch negativity (MMN) obtained with electroencephalography (EEG): 1) how tempo (fast vs. slow) and type of metrical structure (duple: two beats per unit vs. triple: three beats per unit) affect the neural processing of metrical structure in non-musically trained individuals, and 2) how early music training modulates the neural processing of metrical structure. Metrical structures were established by patterns of consecutive strong and weak tones (Standard) with occasional violations that disrupted and reset the structure (Deviant). Twenty non-musicians listened passively to these tones while their neural activities were recorded. MMN indexed the neural sensitivity to the meter violations. Results suggested that MMNs were larger for fast tempo and for triple meter conditions. Further, 20 musically trained individuals were tested using the same methods and the results were compared to the non-musicians. While tempo and meter type similarly influenced MMNs in both groups, musicians overall exhibited significantly reduced MMNs, compared to their non-musician counterparts. Further analyses

  18. 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

  19. Neural correlates of negative emotion processing in bipolar disorder.

    PubMed

    Sepede, Gianna; De Berardis, Domenico; Campanella, Daniela; Perrucci, Mauro Gianni; Ferretti, Antonio; Salerno, Rosa Maria; Di Giannantonio, Massimo; Romani, Gian Luca; Gambi, Francesco

    2015-07-03

    Bipolar disorder type I (BD-I) is characterized by a severe impairment in emotional processing during both acute and euthymic phases of the illness. The aim of the present study was to investigate negative emotion processing in both euthymic patients and non-affected first-degree relatives, looking for state and trait markers of BD-I. 22 healthy relatives of BD-I patients (mean age 31.5±7.3 years; 15 females), 23 euthymic BD-I patients (mean age 35.2±7.9 years; 14 females), and 24 matched controls (mean age 32.5±6.2 years; 16 females) performed an IAPS-based emotional task during 1.5T fMRI. They were required to identify vegetable items (targets) inside neutral or negative pictures. Euthymic BD-I patients showed a significant reduced accuracy in target detection during both neutral and negative images presentation, whereas first-degree relatives performed similarly to normal comparisons. We found a reduced activation of Left precuneus during negative images condition in the patients only. By contrast, both patients and relatives hyperactivated the Left insula and hypoactivated the Right supramarginal gyrus with respect to controls. Moreover, relatives showed an increased activation of Right lingual gyrus and lower activation of pre-supplementary motor area and Right superior frontal gyrus. During a negative emotion task, euthymic BD-I patients and non-affected first-degree relatives shared an abnormal activation of a limbic area (Left insula) coupled with a reduced activation of a parietal region (Right supramarginal gyrus), thus suggesting a trait-like anomalous processing of affective contents. On the other hand, functional abnormalities found only in unaffected relatives and not in patients and controls may correspond to resilience factors. Copyright © 2015 Elsevier Inc. All rights reserved.

  20. Altered neural processing of emotional faces in remitted Cushing's disease.

    PubMed

    Bas-Hoogendam, Janna Marie; Andela, Cornelie D; van der Werff, Steven J A; Pannekoek, J Nienke; van Steenbergen, Henk; Meijer, Onno C; van Buchem, Mark A; Rombouts, Serge A R B; van der Mast, Roos C; Biermasz, Nienke R; van der Wee, Nic J A; Pereira, Alberto M

    2015-09-01

    Patients with long-term remission of Cushing's disease (CD) demonstrate residual psychological complaints. At present, it is not known how previous exposure to hypercortisolism affects psychological functioning in the long-term. Earlier magnetic resonance imaging (MRI) studies demonstrated abnormalities of brain structure and resting-state connectivity in patients with long-term remission of CD, but no data are available on functional alterations in the brain during the performance of emotional or cognitive tasks in these patients. We performed a cross-sectional functional MRI study, investigating brain activation during emotion processing in patients with long-term remission of CD. Processing of emotional faces versus a non-emotional control condition was examined in 21 patients and 21 matched healthy controls. Analyses focused on activation and connectivity of two a priori determined regions of interest: the amygdala and the medial prefrontal-orbitofrontal cortex (mPFC-OFC). We also assessed psychological functioning, cognitive failure, and clinical disease severity. Patients showed less mPFC activation during processing of emotional faces compared to controls, whereas no differences were found in amygdala activation. An exploratory psychophysiological interaction analysis demonstrated decreased functional coupling between the ventromedial PFC and posterior cingulate cortex (a region structurally connected to the PFC) in CD-patients. The present study is the first to show alterations in brain function and task-related functional coupling in patients with long-term remission of CD relative to matched healthy controls. These alterations may, together with abnormalities in brain structure, be related to the persisting psychological morbidity in patients with CD after long-term remission. Copyright © 2015 Elsevier Ltd. All rights reserved.

  1. 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.

  2. Neural differences in the processing of semantic relationships across cultures

    PubMed Central

    Hedden, Trey; Ketay, Sarah; Aron, Arthur; Gabrieli, John D.E.

    2010-01-01

    The current study employed functional MRI to investigate the contribution of domain-general (e.g. executive functions) and domain-specific (e.g. semantic knowledge) processes to differences in semantic judgments across cultures. Previous behavioral experiments have identified cross-cultural differences in categorization, with East Asians preferring strategies involving thematic or functional relationships (e.g. cow-grass) and Americans preferring categorical relationships (e.g. cow-chicken). East Asians and American participants underwent functional imaging while alternating between categorical or thematic strategies to sort triads of words, as well as matching words on control trials. Many similarities were observed. However, across both category and relationship trials compared to match (control) trials, East Asians activated a frontal-parietal network implicated in controlled executive processes, whereas Americans engaged regions of the temporal lobes and the cingulate, possibly in response to conflict in the semantic content of information. The results suggest that cultures differ in the strategies employed to resolve conflict between competing semantic judgments. PMID:20139116

  3. 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

  4. 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.

  5. Neural differences in the processing of semantic relationships across cultures.

    PubMed

    Gutchess, Angela H; Hedden, Trey; Ketay, Sarah; Aron, Arthur; Gabrieli, John D E

    2010-06-01

    The current study employed functional MRI to investigate the contribution of domain-general (e.g. executive functions) and domain-specific (e.g. semantic knowledge) processes to differences in semantic judgments across cultures. Previous behavioral experiments have identified cross-cultural differences in categorization, with East Asians preferring strategies involving thematic or functional relationships (e.g. cow-grass) and Americans preferring categorical relationships (e.g. cow-chicken). East Asians and American participants underwent functional imaging while alternating between categorical or thematic strategies to sort triads of words, as well as matching words on control trials. Many similarities were observed. However, across both category and relationship trials compared to match (control) trials, East Asians activated a frontal-parietal network implicated in controlled executive processes, whereas Americans engaged regions of the temporal lobes and the cingulate, possibly in response to conflict in the semantic content of information. The results suggest that cultures differ in the strategies employed to resolve conflict between competing semantic judgments.

  6. 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

  7. 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.

  8. 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.

  9. 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.

  10. Neural Correlates of Semantic Prediction and Resolution in Sentence Processing.

    PubMed

    Grisoni, Luigi; Miller, Tally McCormick; Pulvermüller, Friedemann

    2017-05-03

    Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding.SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they

  11. PIMS Data Storage, Access, and Neural Network Processing

    NASA Technical Reports Server (NTRS)

    McPherson, Kevin M.; Moskowitz, Milton E.

    1998-01-01

    The Principal Investigator Microgravity Services (PIMS) project at NASA's Lewis Research Center has supported microgravity science Principal Investigator's (PIs) by processing, analyzing, and storing the acceleration environment data recorded on the NASA Space Shuttles and the Russian Mir space station. The acceleration data recorded in support of the microgravity science investigated on these platforms has been generated in discrete blocks totaling approximately 48 gigabytes for the Orbiter missions and 50 gigabytes for the Mir increments. Based on the anticipated volume of acceleration data resulting from continuous or nearly continuous operations, the International Space Station (ISS) presents a unique set of challenges regarding the storage of and access to microgravity acceleration environment data. This paper presents potential microgravity environment data storage, access, and analysis concepts for the ISS era.

  12. 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.

  13. 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.

  14. 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.

  15. Neural correlates of affect processing and aggression in methamphetamine dependence.

    PubMed

    Payer, Doris E; Lieberman, Matthew D; London, Edythe D

    2011-03-01

    Methamphetamine abuse is associated with high rates of aggression but few studies have addressed the contributing neurobiological factors. To quantify aggression, investigate function in the amygdala and prefrontal cortex, and assess relationships between brain function and behavior in methamphetamine-dependent individuals. In a case-control study, aggression and brain activation were compared between methamphetamine-dependent and control participants. Participants were recruited from the general community to an academic research center. Thirty-nine methamphetamine-dependent volunteers (16 women) who were abstinent for 7 to 10 days and 37 drug-free control volunteers (18 women) participated in the study; subsets completed self-report and behavioral measures. Functional magnetic resonance imaging (fMRI) was performed on 25 methamphetamine-dependent and 23 control participants. We measured self-reported and perpetrated aggression and self-reported alexithymia. Brain activation was assessed using fMRI during visual processing of facial affect (affect matching) and symbolic processing (affect labeling), the latter representing an incidental form of emotion regulation. Methamphetamine-dependent participants self-reported more aggression and alexithymia than control participants and escalated perpetrated aggression more following provocation. Alexithymia scores correlated with measures of aggression. During affect matching, fMRI showed no differences between groups in amygdala activation but found lower activation in methamphetamine-dependent than control participants in the bilateral ventral inferior frontal gyrus. During affect labeling, participants recruited the dorsal inferior frontal gyrus and exhibited decreased amygdala activity, consistent with successful emotion regulation; there was no group difference in this effect. The magnitude of decrease in amygdala activity during affect labeling correlated inversely with self-reported aggression in control participants

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

    PubMed Central

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

    2014-01-01

    Language experience fine-tunes how the auditory system processes sound. For example, 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. We also demonstrate that these neural enhancements positively relate with years of bilingual experience. These findings support the notion that bilingualism enhances subcortical auditory processing. PMID:25445377

  17. 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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  18. Neural Correlates of Affect Processing and Aggression in Methamphetamine Dependence

    PubMed Central

    Payer, Doris E.; Lieberman, Matthew D.; London, Edythe D.

    2012-01-01

    Context Methamphetamine abuse is associated with high rates of aggression, but few studies have addressed the contributing neurobiological factors. Objective To quantify aggression, investigate function of the amygdala and prefrontal cortex, and assess relationships between brain function and behavior in methamphetamine-dependent individuals. Design In a case-control study, aggression and brain activation were compared between methamphetamine-dependent and control participants. Setting Participants were recruited from the general community to an academic research center. Participants Thirty-nine methamphetamine-dependent volunteers (16 women) who were abstinent for 7 to 10 days and 37 drug-free control volunteers (18 women) participated in the study; subsets completed self-report and behavioral measures. Functional magnetic resonance imaging (fMRI) was performed on 25 methamphetamine-dependent and 23 control participants. Main outcome measures We measured self-reported and perpetrated aggression, and self-reported alexithymia. Brain activation was assessed using fMRI during visual processing of facial affect (affect matching), and symbolic processing (affect labeling), the latter representing an incidental form of emotion regulation. Results Methamphetamine-dependent participants self-reported more aggression and alexithymia than control participants and escalated perpetrated aggression more following provocation. Alexithymia scores correlated with measures of aggression. During affect matching, fMRI showed no differences between groups in amygdala activation, but found lower activation in methamphetamine-dependent than control participants in bilateral ventral inferior frontal gyrus. During affect labeling, participants recruited dorsal inferior frontal gyrus and exhibited decreased amygdala activity, consistent with successful emotion regulation; there was no group difference in this effect. The magnitude of decrease in amygdala activity during affect labeling

  19. 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

  20. 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.

  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. Suprathreshold stochastic resonance in neural processing tuned by correlation.

    PubMed

    Durrant, Simon; Kang, Yanmei; Stocks, Nigel; Feng, Jianfeng

    2011-07-01

    Suprathreshold stochastic resonance (SSR) is examined in the context of integrate-and-fire neurons, with an emphasis on the role of correlation in the neuronal firing. We employed a model based on a network of spiking neurons which received synaptic inputs modeled by Poisson processes stimulated by a stepped input signal. The smoothed ensemble firing rate provided an output signal, and the mutual information between this signal and the input was calculated for networks with different noise levels and different numbers of neurons. It was found that an SSR effect was present in this context. We then examined a more biophysically plausible scenario where the noise was not controlled directly, but instead was tuned by the correlation between the inputs. The SSR effect remained present in this scenario with nonzero noise providing improved information transmission, and it was found that negative correlation between the inputs was optimal. Finally, an examination of SSR in the context of this model revealed its connection with more traditional stochastic resonance and showed a trade-off between supratheshold and subthreshold components. We discuss these results in the context of existing empirical evidence concerning correlations in neuronal firing.

  3. Linking major depression and the neural substrates of associative processing.

    PubMed

    Harel, Eiran Vadim; Tennyson, Robert Langley; Fava, Maurizio; Bar, Moshe

    2016-12-01

    It has been proposed that mood correlates with the breadth of associative thinking. Here we set this hypothesis to the test in healthy and depressed individuals. Generating contextual associations engages a network of cortical regions including the parahippocampal cortex (PHC), retrosplenial complex, and medial prefrontal cortex. The link between mood, associative processing, and its underlying cortical infrastructure provides a promising avenue for elucidating the mechanisms underlying the cognitive impairments in major depressive disorder (MDD). The participants included 15 nonmedicated individuals with acute major depressive episodes and 15 healthy matched controls. In an fMRI experiment, participants viewed images of objects that were either strongly or weakly associated with a specific context (e.g., a beach chair vs. a water bottle) while rating the commonality of each object. Analyses were performed to examine the brain activation and structural differences between the groups. Consistent with our hypothesis, controls showed greater activation of the contextual associations network than did depressed participants. In addition, PHC structural volume was correlated with ruminative tendencies, and the volumes of the hippocampal subfields were significantly smaller in depressed participants. Surprisingly, depressed participants showed increased activity in the entorhinal cortex (ERC), as compared with controls. We integrated these findings within a mechanistic account linking mood and associative thinking and suggest directions for the future.

  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. 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.

  6. 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.

  7. Automatic Neural Processing of Disorder-Related Stimuli in Social Anxiety Disorder: Faces and More

    PubMed Central

    Schulz, Claudia; Mothes-Lasch, Martin; Straube, Thomas

    2013-01-01

    It has been proposed that social anxiety disorder (SAD) is associated with automatic information processing biases resulting in hypersensitivity to signals of social threat such as negative facial expressions. However, the nature and extent of automatic processes in SAD on the behavioral and neural level is not entirely clear yet. The present review summarizes neuroscientific findings on automatic processing of facial threat but also other disorder-related stimuli such as emotional prosody or negative words in SAD. We review initial evidence for automatic activation of the amygdala, insula, and sensory cortices as well as for automatic early electrophysiological components. However, findings vary depending on tasks, stimuli, and neuroscientific methods. Only few studies set out to examine automatic neural processes directly and systematic attempts are as yet lacking. We suggest that future studies should: (1) use different stimulus modalities, (2) examine different emotional expressions, (3) compare findings in SAD with other anxiety disorders, (4) use more sophisticated experimental designs to investigate features of automaticity systematically, and (5) combine different neuroscientific methods (such as functional neuroimaging and electrophysiology). Finally, the understanding of neural automatic processes could also provide hints for therapeutic approaches. PMID:23745116

  8. 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

  9. Fetal alcohol spectrum disorder: can diminished responsibility diminish criminal behaviour?

    PubMed

    Mela, Mansfield; Luther, Glen

    2013-01-01

    This text examines how current scientific knowledge has the potential of fulfilling one of the major functions of the criminal justice system. Scientific knowledge should be used to ensure that the criminal justice system's functioning results in maximizing societal protection and crime reduction. Abnormal states of the mind contribute to criminal behaviour and are considered in exculpatory defences. The failure of the long standing insanity defence and its utility among cognitively impaired offenders, provided impetus to this work. In estimating the success rates (or lack thereof) of raised defences for the cases of the 'invisible disorder', fetal alcohol spectrum disorder (FASD), coming before the Canadian Courts, we sought to expound on the reasons, from knowledge and pragmatic perspectives. We propose that a diminished responsibility defence and verdict that recognizes the 'grey zone' between 'knowing' and 'not knowing' based on neurocognitive disparities in FASD serves the individual, legal system and the society better than the current practice. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. 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

  11. 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

  12. Neural systems mediating processing of sound units of language distinguish recovery versus persistence in stuttering.

    PubMed

    Mohan, Ranjini; Weber, Christine

    2015-01-01

    Developmental stuttering is a multi-factorial disorder. Measures of neural activity while children processed the phonological (language sound unit) properties of words have revealed neurodevelopmental differences between fluent children and those who stutter. However, there is limited evidence to show whether the neural bases of phonological processing can be used to identify stuttering recovery status. As an initial step, we aimed to determine if differences in neural activity during phonological processing could aid in distinguishing children who had recovered from stuttering and those whose stuttering persisted. We examined neural activity mediating phonological processing in forty-three 7-8 year old children. Groups included children who had recovered from stuttering (CWS-Rec), those whose stuttering persisted (CWS-Per), and children who did not stutter (CWNS). All children demonstrated normal non-verbal intelligence and language skills. Electroencephalograms were recorded as the children listened to pairs of pseudo-words (primes-targets) that either rhymed or did not. Behavioral rhyme judgments along with peak latency and mean amplitude of the N400s elicited by prime and target stimuli were examined. All the groups were very accurate in their rhyme judgments and displayed a typical ERP rhyme effect, characterized by increased N400 amplitudes over central parietal sites for nonrhyming targets compared to rhyming targets. However, over anterior electrode sites, an earlier onset of the N400 for rhyming compared to non-rhyming targets, indexing phonological segmentation and rehearsal, was observed in the CWNS and CWS-Rec groups. This effect occurred bilaterally for the CWNS, was greater over the right hemisphere in the CWS-Rec, and was absent in the CWS-Per. These results are the first to show that differences in ERPs reflecting phonological processing are marked by atypical lateralization in childhood even after stuttering recovery and more pronounced atypical

  13. Energy-efficient neural information processing in individual neurons and neuronal networks.

    PubMed

    Yu, Lianchun; Yu, Yuguo

    2017-11-01

    Brains are composed of networks of an enormous number of neurons interconnected with synapses. Neural information is carried by the electrical signals within neurons and the chemical signals among neurons. Generating these electrical and chemical signals is metabolically expensive. The fundamental issue raised here is whether brains have evolved efficient ways of developing an energy-efficient neural code from the molecular level to the circuit level. Here, we summarize the factors and biophysical mechanisms that could contribute to the energy-efficient neural code for processing input signals. The factors range from ion channel kinetics, body temperature, axonal propagation of action potentials, low-probability release of synaptic neurotransmitters, optimal input and noise, the size of neurons and neuronal clusters, excitation/inhibition balance, coding strategy, cortical wiring, and the organization of functional connectivity. Both experimental and computational evidence suggests that neural systems may use these factors to maximize the efficiency of energy consumption in processing neural signals. Studies indicate that efficient energy utilization may be universal in neuronal systems as an evolutionary consequence of the pressure of limited energy. As a result, neuronal connections may be wired in a highly economical manner to lower energy costs and space. Individual neurons within a network may encode independent stimulus components to allow a minimal number of neurons to represent whole stimulus characteristics efficiently. This basic principle may fundamentally change our view of how billions of neurons organize themselves into complex circuits to operate and generate the most powerful intelligent cognition in nature. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  14. 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.

  15. The effects of ongoing distraction on the neural processes underlying signal detection

    PubMed Central

    Demeter, Elise; De Alburquerque, Daniela; Woldorff, Marty G.

    2016-01-01

    Distraction can impede our ability to detect and effectively process task-relevant stimuli in our environment. Here we leveraged the high temporal resolution of event-related potentials (ERPs) to study the neural consequences of a global, continuous distractor on signal-detection processes. Healthy, young adults performed the dSAT task, a translational sustained-attention task that has been used across different species and in clinical groups, in the presence and absence of ongoing distracting stimulation. We found the presence of distracting stimuli impaired participants’ ability to behaviorally detect task-relevant signal stimuli and greatly affected the neural cascade of processes underlying signal detection. Specifically, we found distraction reduced an anterior and a posterior early-latency N2 ERP component (~140–220 ms) and modulated long-latency, detection-related P3 subcomponents (P3a: ~200–330 ms, P3b: 300–700 ms), even to correctly detected targets. These data provide evidence that distraction can induce powerful alterations in the neural processes related to signal detection, even when stimuli are behaviorally detected. PMID:27378439

  16. Bottom-up and top-down attention: different processes and overlapping neural systems.

    PubMed

    Katsuki, Fumi; Constantinidis, Christos

    2014-10-01

    The brain is limited in its capacity to process all sensory stimuli present in the physical world at any point in time and relies instead on the cognitive process of attention to focus neural resources according to the contingencies of the moment. Attention can be categorized into two distinct functions: bottom-up attention, referring to attentional guidance purely by externally driven factors to stimuli that are salient because of their inherent properties relative to the background; and top-down attention, referring to internal guidance of attention based on prior knowledge, willful plans, and current goals. Over the past few years, insights on the neural circuits and mechanisms of bottom-up and top-down attention have been gained through neurophysiological experiments. Attention affects the mean neuronal firing rate as well as its variability and correlation across neurons. Although distinct processes mediate the guidance of attention based on bottom-up and top-down factors, a common neural apparatus, the frontoparietal network, is essential in both types of attentional processes. © The Author(s) 2013.

  17. 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.

  18. Hidden sources of joy, fear, and sadness: Explicit versus implicit neural processing of musical emotions.

    PubMed

    Bogert, Brigitte; Numminen-Kontti, Taru; Gold, Benjamin; Sams, Mikko; Numminen, Jussi; Burunat, Iballa; Lampinen, Jouko; Brattico, Elvira

    2016-08-01

    Music is often used to regulate emotions and mood. Typically, music conveys and induces emotions even when one does not attend to them. Studies on the neural substrates of musical emotions have, however, only examined brain activity when subjects have focused on the emotional content of the music. Here we address with functional magnetic resonance imaging (fMRI) the neural processing of happy, sad, and fearful music with a paradigm in which 56 subjects were instructed to either classify the emotions (explicit condition) or pay attention to the number of instruments playing (implicit condition) in 4-s music clips. In the implicit vs. explicit condition, stimuli activated bilaterally the inferior parietal lobule, premotor cortex, caudate, and ventromedial frontal areas. The cortical dorsomedial prefrontal and occipital areas activated during explicit processing were those previously shown to be associated with the cognitive processing of music and emotion recognition and regulation. Moreover, happiness in music was associated with activity in the bilateral auditory cortex, left parahippocampal gyrus, and supplementary motor area, whereas the negative emotions of sadness and fear corresponded with activation of the left anterior cingulate and middle frontal gyrus and down-regulation of the orbitofrontal cortex. Our study demonstrates for the first time in healthy subjects the neural underpinnings of the implicit processing of brief musical emotions, particularly in frontoparietal, dorsolateral prefrontal, and striatal areas of the brain. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. 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. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  20. 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

  1. Unfolding the spatial and temporal neural processing of lying about face familiarity.

    PubMed

    Sun, Delin; Lee, Tatia M C; Chan, Chetwyn C H

    2015-04-01

    To understand the neural processing underpinnings of deception, this study employed both neuroimaging (functional magnetic resonance imaging, fMRI) and neurophysiological (event-related potential, ERP) methodologies to examine the temporal and spatial coupling of the neural correlates and processes that occur when one lies about face familiarity. This was performed using simple directed lying tasks. According to cues provided by the researchers, the 17 participants were required to respond truthfully or with lies to a series of faces. The findings confirmed that lie and truth conditions are associated with different fMRI activations in the ventrolateral, dorsolateral, and dorsal medial-frontal cortices; premotor cortex, and inferior parietal gyrus. They are also associated with different amplitudes within the time interval between 300 and 1000 ms post face stimulus, after the initiation (270 ms) of face familiarity processing. These results support the cognitive model that suggests representations of truthful information are first aroused and then manipulated during deception. Stronger fMRI activations at the left inferior frontal gyrus and more positive-going ERP amplitudes within [1765, 1800] ms were observed in the contrast between lie and truth for familiar than for unfamiliar faces. The fMRI and ERP findings, together with ERP source reconstruction, clearly delineate the neural processing of face familiarity deception. © The Author 2013. Published by Oxford University Press.

  2. 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.

  3. Contextual Processing of Abstract Concepts Reveals Neural Representations of Non-Linguistic Semantic Content

    PubMed Central

    Wilson-Mendenhall, Christine D.; Simmons, W. Kyle; Martin, Alex; Barsalou, Lawrence W.

    2014-01-01

    Concepts develop for many aspects of experience, including abstract internal states and abstract social activities that do not refer to concrete entities in the world. The current study assessed the hypothesis that, like concrete concepts, distributed neural patterns of relevant, non-linguistic semantic content represent the meanings of abstract concepts. In a novel neuroimaging paradigm, participants processed two abstract concepts (convince, arithmetic) and two concrete concepts (rolling, red) deeply and repeatedly during a concept-scene matching task that grounded each concept in typical contexts. Using a catch trial design, neural activity associated with each concept word was separated from neural activity associated with subsequent visual scenes to assess activations underlying the detailed semantics of each concept. We predicted that brain regions underlying mentalizing and social cognition (e.g., medial prefrontal cortex, superior temporal sulcus) would become active to represent semantic content central to convince, whereas brain regions underlying numerical cognition (e.g., bilateral intraparietal sulcus) would become active to represent semantic content central to arithmetic. The results supported these predictions, suggesting that the meanings of abstract concepts arise from distributed neural systems that represent concept-specific content. PMID:23363408

  4. 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%.

  5. Opponent appetitive-aversive neural processes underlie predictive learning of pain relief.

    PubMed

    Seymour, Ben; O'Doherty, John P; Koltzenburg, Martin; Wiech, Katja; Frackowiak, Richard; Friston, Karl; Dolan, Raymond

    2005-09-01

    Termination of a painful or unpleasant event can be rewarding. However, whether the brain treats relief in a similar way as it treats natural reward is unclear, and the neural processes that underlie its representation as a motivational goal remain poorly understood. We used fMRI (functional magnetic resonance imaging) to investigate how humans learn to generate expectations of pain relief. Using a pavlovian conditioning procedure, we show that subjects experiencing prolonged experimentally induced pain can be conditioned to predict pain relief. This proceeds in a manner consistent with contemporary reward-learning theory (average reward/loss reinforcement learning), reflected by neural activity in the amygdala and midbrain. Furthermore, these reward-like learning signals are mirrored by opposite aversion-like signals in lateral orbitofrontal cortex and anterior cingulate cortex. This dual coding has parallels to 'opponent process' theories in psychology and promotes a formal account of prediction and expectation during pain.

  6. Optimization of magnetically driven directional solidification of silicon using artificial neural networks and Gaussian process models

    NASA Astrophysics Data System (ADS)

    Dropka, Natasha; Holena, Martin

    2017-08-01

    In directional solidification of silicon, the solid-liquid interface shape plays a crucial role for the quality of crystals. The interface shape can be influenced by forced convection using travelling magnetic fields. Up to now, there is no general and explicit methodology to identify the relation and the optimum combination of magnetic and growth parameters e.g., frequency, phase shift, current magnitude and interface deflection in a buoyancy regime. In the present study, 2D CFD modeling was used to generate data for the design and training of artificial neural networks and for Gaussian process modeling. The aim was to quickly assess the complex nonlinear dependences among the parameters and to optimize them for the interface flattening. The first encouraging results are presented and the pros and cons of artificial neural networks and Gaussian process modeling discussed.

  7. Musical experience and neural efficiency: effects of training on subcortical processing of vocal expressions of emotion.

    PubMed

    Strait, Dana L; Kraus, Nina; Skoe, Erika; Ashley, Richard

    2009-02-01

    Musicians exhibit enhanced perception of emotion in speech, although the biological foundations for this advantage remain unconfirmed. In order to gain a better understanding for the influences of musical experience on neural processing of emotionally salient sounds, we recorded brainstem potentials to affective human vocal sounds. Musicians showed enhanced time-domain response magnitude to the most spectrally complex portion of the stimulus and decreased magnitude to the more periodic, less complex portion. Enhanced phase-locking to stimulus periodicity was likewise seen in musicians' responses to the complex portion. These results suggest that auditory expertise engenders both enhancement and efficiency of subcortical neural responses that are intricately connected with acoustic features important for the communication of emotional states. Our findings provide the first biological evidence for behavioral observations indicating that musical training enhances the perception of vocally expressed emotion in addition to establishing a subcortical role in the auditory processing of emotional cues.

  8. Choice modulates the neural dynamics of prediction error processing during rewarded learning.

    PubMed

    Peterson, David A; Lotz, Daniel T; Halgren, Eric; Sejnowski, Terrence J; Poizner, Howard

    2011-01-15

    Our ability to selectively engage with our environment enables us to guide our learning and to take advantage of its benefits. When facing multiple possible actions, our choices are a critical aspect of learning. In the case of learning from rewarding feedback, there has been substantial theoretical and empirical progress in elucidating the associated behavioral and neural processes, predominantly in terms of a reward prediction error, a measure of the discrepancy between actual versus expected reward. Nevertheless, the distinct influence of choice on prediction error processing and its neural dynamics remains relatively unexplored. In this study we used a novel paradigm to determine how choice influences prediction error processing and to examine whether there are correspondingly distinct neural dynamics. We recorded scalp electroencephalogram while healthy adults were administered a rewarded learning task in which choice trials were intermingled with control trials involving the same stimuli, motor responses, and probabilistic rewards. We used a temporal difference learning model of subjects' trial-by-trial choices to infer subjects' image valuations and corresponding prediction errors. As expected, choices were associated with lower overall prediction error magnitudes, most notably over the course of learning the stimulus-reward contingencies. Choices also induced a higher-amplitude relative positivity in the frontocentral event-related potential about 200 ms after reward signal onset that was negatively correlated with the differential effect of choice on the prediction error. Thus choice influences the neural dynamics associated with how reward signals are processed during learning. Behavioral, computational, and neurobiological models of rewarded learning should therefore accommodate a distinct influence for choice during rewarded learning. Copyright © 2010 Elsevier Inc. All rights reserved.

  9. 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.

  10. 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

  11. 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

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

    PubMed

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

    2013-01-01

    ness 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 related neural

  13. Neural Reward Processing Mediates the Relationship between Insomnia Symptoms and Depression in Adolescence

    PubMed Central

    Casement, Melynda D.; Keenan, Kate E.; Hipwell, Alison E.; Guyer, Amanda E.; Forbes, Erika E.

    2016-01-01

    Study Objectives: Emerging evidence suggests that insomnia may disrupt reward-related brain function—a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms—including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)—contribute to depressive symptoms in adolescent girls. Method: Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). Results: NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. Conclusions: These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. Citation: Casement MD, Keenan KE, Hipwell AE, Guyer AE, Forbes EE. Neural reward processing mediates the relationship between insomnia symptoms and depression in adolescence. SLEEP 2016;39(2):439–447

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. Neural processing associated with cognitive and affective Theory of Mind in adolescents and adults

    PubMed Central

    Fontaine, Nathalie M. G.; Bird, Geoffrey; Blakemore, Sarah-Jayne; De Brito, Stephane A.; McCrory, Eamon J. P.; Viding, Essi

    2012-01-01

    Theory of Mind (ToM) is the ability to attribute thoughts, intentions and beliefs to others. This involves component processes, including cognitive perspective taking (cognitive ToM) and understanding emotions (affective ToM). This study assessed the distinction and overlap of neural processes involved in these respective components, and also investigated their development between adolescence and adulthood. While data suggest that ToM develops between adolescence and adulthood, these populations have not been compared on cognitive and affective ToM domains. Using fMRI with 15 adolescent (aged 11–16 years) and 15 adult (aged 24–40 years) males, we assessed neural responses during cartoon vignettes requiring cognitive ToM, affective ToM or physical causality comprehension (control). An additional aim was to explore relationships between fMRI data and self-reported empathy. Both cognitive and affective ToM conditions were associated with neural responses in the classic ToM network across both groups, although only affective ToM recruited medial/ventromedial PFC (mPFC/vmPFC). Adolescents additionally activated vmPFC more than did adults during affective ToM. The specificity of the mPFC/vmPFC response during affective ToM supports evidence from lesion studies suggesting that vmPFC may integrate affective information during ToM. Furthermore, the differential neural response in vmPFC between adult and adolescent groups indicates developmental changes in affective ToM processing. PMID:21467048

  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. 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

  5. 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

  6. 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.

  7. Detection, location, and quantification of structural damage by neural-net-processed moiré profilometry

    NASA Astrophysics Data System (ADS)

    Grossman, Barry G.; Gonzalez, Frank S.; Blatt, Joel H.; Hooker, Jeffery A.

    1992-03-01

    The development of efficient high speed techniques to recognize, locate, and quantify damage is vitally important for successful automated inspection systems such as ones used for the inspection of undersea pipelines. Two critical problems must be solved to achieve these goals: the reduction of nonuseful information present in the video image and automatic recognition and quantification of extent and location of damage. Artificial neural network processed moire profilometry appears to be a promising technique to accomplish this. Real time video moire techniques have been developed which clearly distinguish damaged and undamaged areas on structures, thus reducing the amount of extraneous information input into an inspection system. Artificial neural networks have demonstrated advantages for image processing, since they can learn the desired response to a given input and are inherently fast when implemented in hardware due to their parallel computing architecture. Video moire images of pipes with dents of different depths were used to train a neural network, with the desired output being the location and severity of the damage. The system was then successfully tested with a second series of moire images. The techniques employed and the results obtained are discussed.

  8. Neural Substrates of Processing Anger in Language: Contributions of Prosody and Semantics.

    PubMed

    Castelluccio, Brian C; Myers, Emily B; Schuh, Jillian M; Eigsti, Inge-Marie

    2016-12-01

    Emotions are conveyed primarily through two channels in language: semantics and prosody. While many studies confirm the role of a left hemisphere network in processing semantic emotion, there has been debate over the role of the right hemisphere in processing prosodic emotion. Some evidence suggests a preferential role for the right hemisphere, and other evidence supports a bilateral model. The relative contributions of semantics and prosody to the overall processing of affect in language are largely unexplored. The present work used functional magnetic resonance imaging to elucidate the neural bases of processing anger conveyed by prosody or semantic content. Results showed a robust, distributed, bilateral network for processing angry prosody and a more modest left hemisphere network for processing angry semantics when compared to emotionally neutral stimuli. Findings suggest the nervous system may be more responsive to prosodic cues in speech than to the semantic content of speech.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. Forecasting sea cliff retreat in Southern California using process-based models and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Limber, P. W.; Barnard, P.; Erikson, L. H.

    2016-02-01

    Modeling coastal geomorphic change over multi-decadal time and regional spatial scales (i.e. >20 km alongshore) is in high demand due to rising global sea levels and heavily populated coastal zones, but is challenging for several reasons: adequate geomorphic and oceanographic data often does not exist over the entire study area or time period; models can be too computationally expensive; and model uncertainty is high. In the absence of rich datasets and unlimited computer processing power, researchers are forced to leverage existing data, however sparse, and find analytical methods that minimize computation time without sacrificing (too much) model reliability. Machine learning techniques, such as artificial neural networks, can assimilate and efficiently extrapolate geomorphic model behavior over large areas. They can also facilitate ensemble model forecasts over a broad range of parameter space, which is useful when a paucity of observational data inhibits the constraint of model parameters. Here, we assimilate the behavior of two established process-based sea cliff erosion and retreat models into a neural network to forecast the impacts of sea level rise on sea cliff retreat in Southern California ( 400 km) through the 21st century. Using inputs such as historical cliff retreat rates, mean wave power, and whether or not a beach is present, the neural network independently reproduces modeled sea cliff retreat as a function of sea level rise with a high degree of confidence (R2 > 0.9, mean squared error < 0.1 m yr-1). Results will continuously improve as more model scenarios are assimilated into the neural network, and more field data (i.e., cliff composition and rock hardness) becomes available to tune the cliff retreat models. Preliminary results suggest that sea level rise rates of 2 to 20 mm yr-1 during the next century could accelerate historical cliff retreat rates in Southern California by an average of 0.10 - 0.56 m yr-1.

  19. 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.

  20. 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.

  1. 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

  2. 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

  3. Neural mechanisms of human perceptual learning: electrophysiological evidence for a two-stage process.

    PubMed

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

    2011-04-26

    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. 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. 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.

  4. 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.

  5. 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.

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

    PubMed

    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.

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

    PubMed Central

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

    2014-01-01

    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 two 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. PMID:24380867

  8. 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.

  9. Identifying temporal and causal contributions of neural processes underlying the Implicit Association Test (IAT)

    PubMed Central

    Forbes, Chad E.; Cameron, Katherine A.; Grafman, Jordan; Barbey, Aron; Solomon, Jeffrey; Ritter, Walter; Ruchkin, Daniel S.

    2012-01-01

    The Implicit Association Test (IAT) is a popular behavioral measure that assesses the associative strength between outgroup members and stereotypical and counterstereotypical traits. Less is known, however, about the degree to which the IAT reflects automatic processing. Two studies examined automatic processing contributions to a gender-IAT using a data driven, social neuroscience approach. Performance on congruent (e.g., categorizing male names with synonyms of strength) and incongruent (e.g., categorizing female names with synonyms of strength) IAT blocks were separately analyzed using EEG (event-related potentials, or ERPs, and coherence; Study 1) and lesion (Study 2) methodologies. Compared to incongruent blocks, performance on congruent IAT blocks was associated with more positive ERPs that manifested in frontal and occipital regions at automatic processing speeds, occipital regions at more controlled processing speeds and was compromised by volume loss in the anterior temporal lobe (ATL), insula and medial PFC. Performance on incongruent blocks was associated with volume loss in supplementary motor areas, cingulate gyrus and a region in medial PFC similar to that found for congruent blocks. Greater coherence was found between frontal and occipital regions to the extent individuals exhibited more bias. This suggests there are separable neural contributions to congruent and incongruent blocks of the IAT but there is also a surprising amount of overlap. Given the temporal and regional neural distinctions, these results provide converging evidence that stereotypic associative strength assessed by the IAT indexes automatic processing to a degree. PMID:23226123

  10. 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

  11. 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

  12. 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

  13. 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

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

    PubMed

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

    2016-10-01

    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.

  15. 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

  16. Residual neural processing of musical sound features in adult cochlear implant users.

    PubMed

    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. -Automatic brain responses to musical feature changes reflect the

  17. 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.

  18. 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

  19. Developmental trajectory of neural specialization for letter and number visual processing.

    PubMed

    Park, Joonkoo; van den Berg, Berry; Chiang, Crystal; Woldorff, Marty G; Brannon, Elizabeth M

    2017-07-05

    Adult neuroimaging studies have demonstrated dissociable neural activation patterns in the visual cortex in response to letters (Latin alphabet) and numbers (Arabic numerals), which suggest a strong experiential influence of reading and mathematics on the human visual system. Here, developmental trajectories in the event-related potential (ERP) patterns evoked by visual processing of letters, numbers, and false fonts were examined in four different age groups (7-, 10-, 15-year-olds, and young adults). The 15-year-olds and adults showed greater neural sensitivity to letters over numbers in the left visual cortex and the reverse pattern in the right visual cortex, extending previous findings in adults to teenagers. In marked contrast, 7- and 10-year-olds did not show this dissociable neural pattern. Furthermore, the contrast of familiar stimuli (letters or numbers) versus unfamiliar ones (false fonts) showed stark ERP differences between the younger (7- and 10-year-olds) and the older (15-year-olds and adults) participants. These results suggest that both coarse (familiar versus unfamiliar) and fine (letters versus numbers) tuning for letters and numbers continue throughout childhood and early adolescence, demonstrating a profound impact of uniquely human cultural inventions on visual cognition and its development. © 2017 John Wiley & Sons Ltd.

  20. 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.

  1. 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

  2. Banknote recognition: investigating processing and cognition framework using competitive neural network.

    PubMed

    Oyedotun, Oyebade K; Khashman, Adnan

    2017-02-01

    Humans are apt at recognizing patterns and discovering even abstract features which are sometimes embedded therein. Our ability to use the banknotes in circulation for business transactions lies in the effortlessness with which we can recognize the different banknote denominations after seeing them over a period of time. More significant is that we can usually recognize these banknote denominations irrespective of what parts of the banknotes are exposed to us visually. Furthermore, our recognition ability is largely unaffected even when these banknotes are partially occluded. In a similar analogy, the robustness of intelligent systems to perform the task of banknote recognition should not collapse under some minimum level of partial occlusion. Artificial neural networks are intelligent systems which from inception have taken many important cues related to structure and learning rules from the human nervous/cognition processing system. Likewise, it has been shown that advances in artificial neural network simulations can help us understand the human nervous/cognition system even furthermore. In this paper, we investigate three cognition hypothetical frameworks to vision-based recognition of banknote denominations using competitive neural networks. In order to make the task more challenging and stress-test the investigated hypotheses, we also consider the recognition of occluded banknotes. The implemented hypothetical systems are tasked to perform fast recognition of banknotes with up to 75 % occlusion. The investigated hypothetical systems are trained on Nigeria's Naira banknotes and several experiments are performed to demonstrate the findings presented within this work.

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

    PubMed

    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.

  4. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    PubMed Central

    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.

    2015-01-01

    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. PMID:26321676

  6. Differences in Neural Activity when Processing Emotional Arousal and Valence in Autism Spectrum Disorders

    PubMed Central

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

    2016-01-01

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

  7. 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

  8. 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.

  9. Neural processing of visual information under interocular suppression: a critical review

    PubMed Central

    Sterzer, Philipp; Stein, Timo; Ludwig, Karin; Rothkirch, Marcus; Hesselmann, Guido

    2014-01-01

    When dissimilar stimuli are presented to the two eyes, only one stimulus dominates at a time while the other stimulus is invisible due to interocular suppression. When both stimuli are equally potent in competing for awareness, perception alternates spontaneously between the two stimuli, a phenomenon called binocular rivalry. However, when one stimulus is much stronger, e.g., due to higher contrast, the weaker stimulus can be suppressed for prolonged periods of time. A technique that has recently become very popular for the investigation of unconscious visual processing is continuous flash suppression (CFS): High-contrast dynamic patterns shown to one eye can render a low-contrast stimulus shown to the other eye invisible for up to minutes. Studies using CFS have produced new insights but also controversies regarding the types of visual information that can be processed unconsciously as well as the neural sites and the relevance of such unconscious processing. Here, we review the current state of knowledge in regard to neural processing of interocularly suppressed information. Focusing on recent neuroimaging findings, we discuss whether and to what degree such suppressed visual information is processed at early and more advanced levels of the visual processing hierarchy. We review controversial findings related to the influence of attention on early visual processing under interocular suppression, the putative differential roles of dorsal and ventral areas in unconscious object processing, and evidence suggesting privileged unconscious processing of emotional and other socially relevant information. On a more general note, we discuss methodological and conceptual issues, from practical issues of how unawareness of a stimulus is assessed to the overarching question of what constitutes an adequate operational definition of unawareness. Finally, we propose approaches for future research to resolve current controversies in this exciting research area. PMID:24904469

  10. Neural processing of visual information under interocular suppression: a critical review.

    PubMed

    Sterzer, Philipp; Stein, Timo; Ludwig, Karin; Rothkirch, Marcus; Hesselmann, Guido

    2014-01-01

    When dissimilar stimuli are presented to the two eyes, only one stimulus dominates at a time while the other stimulus is invisible due to interocular suppression. When both stimuli are equally potent in competing for awareness, perception alternates spontaneously between the two stimuli, a phenomenon called binocular rivalry. However, when one stimulus is much stronger, e.g., due to higher contrast, the weaker stimulus can be suppressed for prolonged periods of time. A technique that has recently become very popular for the investigation of unconscious visual processing is continuous flash suppression (CFS): High-contrast dynamic patterns shown to one eye can render a low-contrast stimulus shown to the other eye invisible for up to minutes. Studies using CFS have produced new insights but also controversies regarding the types of visual information that can be processed unconsciously as well as the neural sites and the relevance of such unconscious processing. Here, we review the current state of knowledge in regard to neural processing of interocularly suppressed information. Focusing on recent neuroimaging findings, we discuss whether and to what degree such suppressed visual information is processed at early and more advanced levels of the visual processing hierarchy. We review controversial findings related to the influence of attention on early visual processing under interocular suppression, the putative differential roles of dorsal and ventral areas in unconscious object processing, and evidence suggesting privileged unconscious processing of emotional and other socially relevant information. On a more general note, we discuss methodological and conceptual issues, from practical issues of how unawareness of a stimulus is assessed to the overarching question of what constitutes an adequate operational definition of unawareness. Finally, we propose approaches for future research to resolve current controversies in this exciting research area.

  11. Imaging first impressions: distinct neural processing of verbal and nonverbal social information.

    PubMed

    Kuzmanovic, Bojana; Bente, Gary; von Cramon, D Yves; Schilbach, Leonhard; Tittgemeyer, Marc; Vogeley, Kai

    2012-03-01

    First impressions profoundly influence our attitudes and behavior toward others. However, little is known about whether and to what degree the cognitive processes that underlie impression formation depend on the domain of the available information about the target person. To investigate the neural bases of the influence of verbal as compared to nonverbal information on interpersonal judgments, we identified brain regions where the BOLD signal parametrically increased with increasing strength of evaluation based on either short text vignettes or mimic and gestural behavior. While for verbal stimuli the increasing strength of subjective evaluation was correlated with increased neural activation of precuneus and posterior cingulate cortex (PC/PCC), a similar effect was observed for nonverbal stimuli in the amygdala. These findings support the assumption that qualitatively different cognitive operations underlie person evaluation depending upon the stimulus domain: while the processing of nonverbal person information may be more strongly associated with affective processing as indexed by recruitment of the amygdala, verbal person information engaged the PC/PCC that has been related to social inferential processing. Copyright © 2011 Elsevier Inc. All rights reserved.

  12. 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.

  13. Neural Correlates of Intersensory Processing in Five-Month-Old Infants

    PubMed Central

    Reynolds, Greg D.; Bahrick, Lorraine E.; Lickliter, Robert; Guy, Maggie W.

    2014-01-01

    Two experiments assessing event-related potentials in 5-month-old infants were conducted to examine neural correlates of attentional salience and efficiency of processing of a visual event (woman speaking) paired with redundant (synchronous) speech, nonredundant (asynchronous) speech, or no speech. In Experiment 1, the Nc component associated with attentional salience was greater in amplitude following synchronous audiovisual as compared with asynchronous audiovisual and unimodal visual presentations. A block design was utilized in Experiment 2 to examine efficiency of processing of a visual event. Only infants exposed to synchronous audiovisual speech demonstrated a significant reduction in amplitude of the late slow wave associated with successful stimulus processing and recognition memory from early to late blocks of trials. These findings indicate that events that provide intersensory redundancy are associated with enhanced neural responsiveness indicative of greater attentional salience and more efficient stimulus processing as compared with the same events when they provide no intersensory redundancy in 5-month-old infants. PMID:23423948

  14. 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.

  15. 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.

  16. Differential neural activity and connectivity for processing one's own face: A preliminary report

    PubMed Central

    Ramasubbu, Rajamannar; Masalovich, Svetlana; Gaxiola, Ismael; Peltier, Scott; Holtzheimer, Paul E.; Heim, Christine; Goodyear, Bradley; MacQueen, Glenda; Mayberg, Helen S.

    2015-01-01

    The experience of self is unique and pivotal to clinically relevant cognitive and emotional functions. However, well-controlled data on specialized brain regions and functional networks underlying the experience of self remain limited. This functional magnetic resonance imaging study investigated neural activity and connectivity specific to processing one's own face in healthy women by examining neural responses to the pictures of the subjects' own faces in contrast to faces of their own mothers, female friends and strangers during passive viewing, emotional and self-relevance evaluations. The processing of one's own face in comparison to processing of familiar faces revealed significant activity in right anterior insula (AI) and left inferior parietal lobule (IPL), and less activity in right posterior cingulate/precuneus (PCC/PCu) across all tasks. Further, the seed-based correlation analysis of right AI, and left IPL, showed differential functional networks in self and familiar faces contrasts. There were no differences in valence and saliency ratings between self and familiar others. Our preliminary results suggest that the self-experience cued by self-face is processed predominantly by brain regions and related networks that link interoceptive feelings and sense of body ownership to self-awareness and less by regions of higher order functioning such as autobiographical memories. PMID:21962775

  17. 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.

  18. 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.

  19. 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.

  20. How aging and bilingualism influence language processing: theoretical and neural models

    PubMed Central

    Rossi, Eleonora; Diaz, Michele T.

    2016-01-01

    Healthy non-pathological aging is characterized by cognitive and neural decline, and although language is one of the more stable areas of cognition, older adults often show deficits in language production, showing word finding failures, increased slips of the tongue, and increased pauses in speech. Overall, research on language comprehension in older healthy adults show that it is more preserved than language production. Bilingualism has been shown to confer a great deal of neuroplasticity across the life span, including a number of cognitive benefits especially in executive functions such as cognitive control. Many models of bilingual language processing have been proposed to explain bilingual language processing. However, the question remains open of how such models might be modulated by age-related changes in language. Here, we discuss how current models of language processing in non-pathological aging, and models of bilingual language processing can be integrated to provide new research directions. PMID:28919933

  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. Neural Reward Processing Mediates the Relationship between Insomnia Symptoms and Depression in Adolescence.

    PubMed

    Casement, Melynda D; Keenan, Kate E; Hipwell, Alison E; Guyer, Amanda E; Forbes, Erika E

    2016-02-01

    Emerging evidence suggests that insomnia may disrupt reward-related brain function-a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms-including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)-contribute to depressive symptoms in adolescent girls. Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. © 2016 Associated Professional Sleep Societies, LLC.

  3. Statistics of the Vestibular Input Experienced during Natural Self-Motion: Implications for Neural Processing

    PubMed Central

    Carriot, Jérome; Jamali, Mohsen; Chacron, Maurice J.

    2014-01-01

    It is widely believed that sensory systems are optimized for processing stimuli occurring in the natural environment. However, it remains unknown whether this principle applies to the vestibular system, which contributes to essential brain functions ranging from the most automatic reflexes to spatial perception and motor coordination. Here we quantified, for the first time, the statistics of natural vestibular inputs experienced by freely moving human subjects during typical everyday activities. Although previous studies have found that the power spectra of natural signals across sensory modalities decay as a power law (i.e., as 1/fα), we found that this did not apply to natural vestibular stimuli. Instead, power decreased slowly at lower and more rapidly at higher frequencies for all motion dimensions. We further establish that this unique stimulus structure is the result of active motion as well as passive biomechanical filtering occurring before any neural processing. Notably, the transition frequency (i.e., frequency at which power starts to decrease rapidly) was lower when subjects passively experienced sensory stimulation than when they actively controlled stimulation through their own movement. In contrast to signals measured at the head, the spectral content of externally generated (i.e., passive) environmental motion did follow a power law. Specifically, transformations caused by both motor control and biomechanics shape the statistics of natural vestibular stimuli before neural processing. We suggest that the unique structure of natural vestibular stimuli will have important consequences on the neural coding strategies used by this essential sensory system to represent self-motion in everyday life. PMID:24920638

  4. Sensitive periods for the functional specialization of the neural system for human face processing.

    PubMed

    Röder, Brigitte; Ley, Pia; Shenoy, Bhamy H; Kekunnaya, Ramesh; Bottari, Davide

    2013-10-15

    The aim of the study was to identify possible sensitive phases in the development of the processing system for human faces. We tested the neural processing of faces in 11 humans who had been blind from birth and had undergone cataract surgery between 2 mo and 14 y of age. Pictures of faces and houses, scrambled versions of these pictures, and pictures of butterflies were presented while event-related potentials were recorded. Participants had to respond to the pictures of butterflies (targets) only. All participants, even those who had been blind from birth for several years, were able to categorize the pictures and to detect the targets. In healthy controls and in a group of visually impaired individuals with a history of developmental or incomplete congenital cataracts, the well-known enhancement of the N170 (negative peak around 170 ms) event-related potential to faces emerged, but a face-sensitive response was not observed in humans with a history of congenital dense cataracts. By contrast, this group showed a similar N170 response to all visual stimuli, which was indistinguishable from the N170 response to faces in the controls. The face-sensitive N170 response has been associated with the structural encoding of faces. Therefore, these data provide evidence for the hypothesis that the functional differentiation of category-specific neural representations in humans, presumably involving the elaboration of inhibitory circuits, is dependent on experience and linked to a sensitive period. Such functional specialization of neural systems seems necessary to archive high processing proficiency.

  5. 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.

  6. Social cues, mentalizing and the neural processing of speech accompanied by gestures.

    PubMed

    Straube, Benjamin; Green, Antonia; Jansen, Andreas; Chatterjee, Anjan; Kircher, Tilo

    2010-01-01

    Body orientation and eye gaze influence how information is conveyed during face-to-face communication. However, the neural pathways underpinning the comprehension of social cues in everyday interaction are not known. In this study we investigated the influence of addressing vs. non-addressing body orientation on the neural processing of speech accompanied by gestures. While in an fMRI scanner, participants viewed short video clips of an actor speaking sentences with object- (O; e.g., shape) or person-related content (P; e.g., saying goodbye) accompanied by iconic (e.g., circle) or emblematic gestures (e.g., waving), respectively. The actor's body was oriented either toward the participant (frontal, F) or toward a third person (lateral, L) not visible. For frontal vs. lateral actor orientation (F>L), we observed activation of bilateral occipital, inferior frontal, medial frontal, right anterior temporal and left parietal brain regions. Additionally, we observed activity in the occipital and anterior temporal lobes due to an interaction effect between actor orientation and content of the communication (PF>PL)>(OF>OL). Our findings indicate that social cues influence the neural processing of speech-gesture utterances. Mentalizing (the process of inferring the mental state of another individual) could be responsible for these effects. In particular, socially relevant cues seem to activate regions of the anterior temporal lobes if abstract person-related content is communicated by speech and gesture. These new findings illustrate the complexity of interpersonal communication, as our data demonstrate that multisensory information pathways interact at both perceptual and semantic levels. 2009 Elsevier Ltd. All rights reserved.

  7. 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

  8. Statistics of the vestibular input experienced during natural self-motion: implications for neural processing.

    PubMed

    Carriot, Jérome; Jamali, Mohsen; Chacron, Maurice J; Cullen, Kathleen E

    2014-06-11

    It is widely believed that sensory systems are optimized for processing stimuli occurring in the natural environment. However, it remains unknown whether this principle applies to the vestibular system, which contributes to essential brain functions ranging from the most automatic reflexes to spatial perception and motor coordination. Here we quantified, for the first time, the statistics of natural vestibular inputs experienced by freely moving human subjects during typical everyday activities. Although previous studies have found that the power spectra of natural signals across sensory modalities decay as a power law (i.e., as 1/f(α)), we found that this did not apply to natural vestibular stimuli. Instead, power decreased slowly at lower and more rapidly at higher frequencies for all motion dimensions. We further establish that this unique stimulus structure is the result of active motion as well as passive biomechanical filtering occurring before any neural processing. Notably, the transition frequency (i.e., frequency at which power starts to decrease rapidly) was lower when subjects passively experienced sensory stimulation than when they actively controlled stimulation through their own movement. In contrast to signals measured at the head, the spectral content of externally generated (i.e., passive) environmental motion did follow a power law. Specifically, transformations caused by both motor control and biomechanics shape the statistics of natural vestibular stimuli before neural processing. We suggest that the unique structure of natural vestibular stimuli will have important consequences on the neural coding strategies used by this essential sensory system to represent self-motion in everyday life. Copyright © 2014 the authors 0270-6474/14/348347-11$15.00/0.

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

    PubMed

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

    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.

  10. 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.

  11. Pattern reconstruction and sequence processing in feed-forward layered neural networks near saturation.

    PubMed

    Metz, F L; Theumann, W K

    2005-08-01

    The dynamics and the stationary states for the competition between pattern reconstruction and asymmetric sequence processing are studied here in an exactly solvable feed-forward layered neural network model of binary units and patterns near saturation. Earlier work by Coolen and Sherrington on a parallel dynamics far from saturation is extended here to account for finite stochastic noise due to a Hebbian and a sequential learning rule. Phase diagrams are obtained with stationary states and quasiperiodic nonstationary solutions. The relevant dependence of these diagrams and of the quasiperiodic solutions on the stochastic noise and on initial inputs for the overlaps is explicitly discussed.

  12. 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.

  13. Effects of task demands on the early neural processing of fearful and happy facial expressions.

    PubMed

    Itier, Roxane J; Neath-Tavares, Karly N

    2017-05-15

    Task demands shape how we process environmental stimuli but their impact on the early neural processing of facial expressions remains unclear. In a within-subject design, ERPs were recorded to the same fearful, happy and neutral facial expressions presented during a gender discrimination, an explicit emotion discrimination and an oddball detection tasks, the most studied tasks in the field. Using an eye tracker, fixation on the face nose was enforced using a gaze-contingent presentation. Task demands modulated amplitudes from 200 to 350ms at occipito-temporal sites spanning the EPN component. Amplitudes were more negative for fearful than neutral expressions starting on N170 from 150 to 350ms, with a temporo-occipital distribution, whereas no clear effect of happy expressions was seen. Task and emotion effects never interacted in any time window or for the ERP components analyzed (P1, N170, EPN). Thus, whether emotion is explicitly discriminated or irrelevant for the task at hand, neural correlates of fearful and happy facial expressions seem immune to these task demands during the first 350ms of visual processing. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. The trait of sensory processing sensitivity and neural responses to changes in visual scenes.

    PubMed

    Jagiellowicz, Jadzia; Xu, Xiaomeng; Aron, Arthur; Aron, Elaine; Cao, Guikang; Feng, Tingyong; Weng, Xuchu

    2011-01-01

    This exploratory study examined the extent to which individual differences in sensory processing sensitivity (SPS), a temperament/personality trait characterized by social, emotional and physical sensitivity, are associated with neural response in visual areas in response to subtle changes in visual scenes. Sixteen participants completed the Highly Sensitive Person questionnaire, a standard measure of SPS. Subsequently, they were tested on a change detection task while undergoing functional magnetic resonance imaging (fMRI). SPS was associated with significantly greater activation in brain areas involved in high-order visual processing (i.e. right claustrum, left occipitotemporal, bilateral temporal and medial and posterior parietal regions) as well as in the right cerebellum, when detecting minor (vs major) changes in stimuli. These findings remained strong and significant after controlling for neuroticism and introversion, traits that are often correlated with SPS. These results provide the first evidence of neural differences associated with SPS, the first direct support for the sensory aspect of this trait that has been studied primarily for its social and affective implications, and preliminary evidence for heightened sensory processing in individuals high in SPS.

  15. The trait of sensory processing sensitivity and neural responses to changes in visual scenes

    PubMed Central

    Xu, Xiaomeng; Aron, Arthur; Aron, Elaine; Cao, Guikang; Feng, Tingyong; Weng, Xuchu

    2011-01-01

    This exploratory study examined the extent to which individual differences in sensory processing sensitivity (SPS), a temperament/personality trait characterized by social, emotional and physical sensitivity, are associated with neural response in visual areas in response to subtle changes in visual scenes. Sixteen participants completed the Highly Sensitive Person questionnaire, a standard measure of SPS. Subsequently, they were tested on a change detection task while undergoing functional magnetic resonance imaging (fMRI). SPS was associated with significantly greater activation in brain areas involved in high-order visual processing (i.e. right claustrum, left occipitotemporal, bilateral temporal and medial and posterior parietal regions) as well as in the right cerebellum, when detecting minor (vs major) changes in stimuli. These findings remained strong and significant after controlling for neuroticism and introversion, traits that are often correlated with SPS. These results provide the first evidence of neural differences associated with SPS, the first direct support for the sensory aspect of this trait that has been studied primarily for its social and affective implications, and preliminary evidence for heightened sensory processing in individuals high in SPS. PMID:20203139

  16. 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.

  17. Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

    PubMed

    Seok, J-W; Park, M-S; Sohn, J-H

    2016-09-01

    Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. Fast maximum likelihood estimation using continuous-time neural point process models.

    PubMed

    Lepage, Kyle Q; MacDonald, Christopher J

    2015-06-01

    A recent report estimates that the number of simultaneously recorded neurons is growing exponentially. A commonly employed statistical paradigm using discrete-time point process models of neural activity involves the computation of a maximum-likelihood estimate. The time to computate this estimate, per neuron, is proportional to the number of bins in a finely spaced discretization of time. By using continuous-time models of neural activity and the optimally efficient Gaussian quadrature, memory requirements and computation times are dramatically decreased in the commonly encountered situation where the number of parameters p is much less than the number of time-bins n. In this regime, with q equal to the quadrature order, memory requirements are decreased from O(np) to O(qp), and the number of floating-point operations are decreased from O(np(2)) to O(qp(2)). Accuracy of the proposed estimates is assessed based upon physiological consideration, error bounds, and mathematical results describing the relation between numerical integration error and numerical error affecting both parameter estimates and the observed Fisher information. A check is provided which is used to adapt the order of numerical integration. The procedure is verified in simulation and for hippocampal recordings. It is found that in 95 % of hippocampal recordings a q of 60 yields numerical error negligible with respect to parameter estimate standard error. Statistical inference using the proposed methodology is a fast and convenient alternative to statistical inference performed using a discrete-time point process model of neural activity. It enables the employment of the statistical methodology available with discrete-time inference, but is faster, uses less memory, and avoids any error due to discretization.

  6. 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

  7. 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

  8. Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

    PubMed

    McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

    2016-12-01

    Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

  9. Altered Neural Basis of the Reality Processing and Its Relation to Cognitive Insight in Schizophrenia

    PubMed Central

    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. PMID:25793291

  10. 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.

  11. 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.

  12. Attentional processes in posttraumatic stress disorder and the associated changes in neural functioning.

    PubMed

    Block, Stefanie R; Liberzon, Israel

    2016-10-01

    Posttraumatic Stress Disorder (PTSD) is associated with alterations in attention at the behavioral and neural levels. However, there are conflicting findings regarding the specific type of attention impairments present in PTSD, as the commonly used tests of attention do not isolate the mechanisms behind attention abnormalities, and the constructs measured do not map onto the neurocircuits governing attention. Here, we review the literature on attention processing in PTSD and offer directions for future research to clarify these unanswered questions. First, using instruments that allow assessment of behavioral and neurophysiological attention components will be necessary to understand attention deficits in PTSD. Second, focus on intra-individual variability in addition to assessment of central tendency may help clarify some of the mixed findings. Third, longitudinal studies on attentional processes are warranted to determine how attention contributes to the development and maintenance of PTSD. Integration of behavioral and neural measures of attention will be useful in understanding the pathophysiology of PTSD. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. 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.

  14. 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

  15. 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