Development of Tool Representations in the Dorsal and Ventral Visual Object Processing Pathways

Science.gov (United States)

Kersey, Alyssa J.; Clark, Tyia S.; Lussier, Courtney A.; Mahon, Bradford Z.; Cantlon, Jessica F.

2016-01-01

Tools represent a special class of objects, because they are processed across both the dorsal and ventral visual object processing pathways. Three core regions are known to be involved in tool processing: the left posterior middle temporal gyrus, the medial fusiform gyrus (bilaterally), and the left inferior parietal lobule. A critical and relatively unexplored issue concerns whether, in development, tool preferences emerge at the same time and to a similar degree across all regions of the tool-processing network. To test this issue, we used functional magnetic resonance imaging to measure the neural amplitude, peak location, and the dispersion of tool-related neural responses in the youngest sample of children tested to date in this domain (ages 4–8 years). We show that children recruit overlapping regions of the adult tool-processing network and also exhibit similar patterns of co-activation across the network to adults. The amplitude and co-activation data show that the core components of the tool-processing network are established by age 4. Our findings on the distributions of peak location and dispersion of activation indicate that the tool network undergoes refinement between ages 4 and 8 years. PMID:26108614

Neural electrical activity and neural network growth.

Science.gov (United States)

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

Small leucine rich proteoglycan family regulates multiple signalling pathways in neural development and maintenance.

Science.gov (United States)

Dellett, Margaret; Hu, Wanzhou; Papadaki, Vasiliki; Ohnuma, Shin-ichi

2012-04-01

The small leucine-rich repeat proteoglycan (SLRPs) family of proteins currently consists of five classes, based on their structural composition and chromosomal location. As biologically active components of the extracellular matrix (ECM), SLRPs were known to bind to various collagens, having a role in regulating fibril assembly, organization and degradation. More recently, as a function of their diverse proteins cores and glycosaminoglycan side chains, SLRPs have been shown to be able to bind various cell surface receptors, growth factors, cytokines and other ECM components resulting in the ability to influence various cellular functions. Their involvement in several signaling pathways such as Wnt, transforming growth factor-β and epidermal growth factor receptor also highlights their role as matricellular proteins. SLRP family members are expressed during neural development and in adult neural tissues, including ocular tissues. This review focuses on describing SLRP family members involvement in neural development with a brief summary of their role in non-neural ocular tissues and in response to neural injury. © 2012 The Authors Development, Growth & Differentiation © 2012 Japanese Society of Developmental Biologists.

The sleep and circadian modulation of neural reward pathways: a protocol for a pair of systematic reviews.

Science.gov (United States)

Byrne, Jamie E M; Murray, Greg

2017-12-02

Animal research suggests that neural reward activation may be systematically modulated by sleep and circadian function. Whether humans also exhibit sleep and circadian modulation of neural reward pathways is unclear. This area is in need of further research, as it has implications for the involvement of sleep and circadian function in reward-related disorders. The aim of this paper is to describe the protocol for a pair of systematic literature reviews to synthesise existing literature related to (1) sleep and (2) circadian modulation of neural reward pathways in healthy human populations. A systematic review of relevant online databases (Scopus, PubMed, Web of Science, ProQuest, PsycINFO and EBSCOhost) will be conducted. Reference lists, relevant reviews and supplementary data will be searched for additional articles. Articles will be included if (a) they contain a sleep- or circadian-related predictor variable with a neural reward outcome variable, (b) use a functional magnetic resonance imaging protocol and (c) use human samples. Articles will be excluded if study participants had disorders known to affect the reward system. The articles will be screened by two independent authors. Two authors will complete the data extraction form, with two authors independently completing the quality assessment tool for the selected articles, with a consensus reached with a third author if needed. Narrative synthesis methods will be used to analyse the data. The findings from this pair of systematic literature reviews will assist in the identification of the pathways involved in the sleep and circadian function modulation of neural reward in healthy individuals, with implications for disorders characterised by dysregulation in sleep, circadian rhythms and reward function. PROSPERO CRD42017064994.

Regional cerebral glucose metabolic changes in oculopalatal myoclonus: implication for neural pathways, underlying the disorder

Energy Technology Data Exchange (ETDEWEB)

Cho, Sang Soo; Moon, So Young; Kim, Ji Soo; Kim, Sang Eun [College of Medicine, Seoul National University, Seoul (Korea, Republic of)

2004-07-01

Palatal myoclonus (PM) is characterized by rhythmic involuntary jerky movements of the soft palate of the throat. When associated with eye movements, it is called oculopalatal myoclonus (OPM). Ordinary PM is characterized by hypertrophic olivary degeneration, a trans-synaptic degeneration following loss of neuronal input to the inferior olivary nucleus due to an interruption of the Guillain-Mollaret triangle usually by a hemorrhage. However, the neural pathways underlying the disorder are uncertain. In an attempt to understand the pathologic neural pathways, we examined the metabolic correlates of this tremulous condition. Brain FDG PET scans were acquired in 8 patients with OPM (age, 49.9{+-}4.6 y: all males: 7 with pontine hemorrhage, 1 with diffuse brainstem infarction) and age-matched 50 healthy males (age, 50.7{+-} 9.0) and the regional glucose metabolism compared using SPM99. For group analysis, the hemispheres containing lesions were assigned to the right side of the brain. Patients with OPM had significant hypometabolism in the ipsilateral (to the lesion) brainstem and superior temporal and parahippocampal gyri (P < 0.05 corrected, k = 100). By contrast, there was significant hypermetabolism in the contralateral middle and inferior temporal gyri, thalamus, middle frontal gyrus and precuneus (P < 0.05 corrected, k=l00). Our data demonstrate the distinct metabolic changes between several ipsilateral and contralateral brain regions (hypometabolism vs. hypermetabolism) in patients with OPM. This may provide clues for understanding the neural pathways underlying the disorder.

Regional cerebral glucose metabolic changes in oculopalatal myoclonus: implication for neural pathways, underlying the disorder

International Nuclear Information System (INIS)

Cho, Sang Soo; Moon, So Young; Kim, Ji Soo; Kim, Sang Eun

2004-01-01

Palatal myoclonus (PM) is characterized by rhythmic involuntary jerky movements of the soft palate of the throat. When associated with eye movements, it is called oculopalatal myoclonus (OPM). Ordinary PM is characterized by hypertrophic olivary degeneration, a trans-synaptic degeneration following loss of neuronal input to the inferior olivary nucleus due to an interruption of the Guillain-Mollaret triangle usually by a hemorrhage. However, the neural pathways underlying the disorder are uncertain. In an attempt to understand the pathologic neural pathways, we examined the metabolic correlates of this tremulous condition. Brain FDG PET scans were acquired in 8 patients with OPM (age, 49.9±4.6 y: all males: 7 with pontine hemorrhage, 1 with diffuse brainstem infarction) and age-matched 50 healthy males (age, 50.7± 9.0) and the regional glucose metabolism compared using SPM99. For group analysis, the hemispheres containing lesions were assigned to the right side of the brain. Patients with OPM had significant hypometabolism in the ipsilateral (to the lesion) brainstem and superior temporal and parahippocampal gyri (P < 0.05 corrected, k = 100). By contrast, there was significant hypermetabolism in the contralateral middle and inferior temporal gyri, thalamus, middle frontal gyrus and precuneus (P < 0.05 corrected, k=l00). Our data demonstrate the distinct metabolic changes between several ipsilateral and contralateral brain regions (hypometabolism vs. hypermetabolism) in patients with OPM. This may provide clues for understanding the neural pathways underlying the disorder

Analysis of the Growth Process of Neural Cells in Culture Environment Using Image Processing Techniques

Science.gov (United States)

Mirsafianf, Atefeh S.; Isfahani, Shirin N.; Kasaei, Shohreh; Mobasheri, Hamid

Here we present an approach for processing neural cells images to analyze their growth process in culture environment. We have applied several image processing techniques for: 1- Environmental noise reduction, 2- Neural cells segmentation, 3- Neural cells classification based on their dendrites' growth conditions, and 4- neurons' features Extraction and measurement (e.g., like cell body area, number of dendrites, axon's length, and so on). Due to the large amount of noise in the images, we have used feed forward artificial neural networks to detect edges more precisely.

Neural and hybrid modeling: an alternative route to efficiently predict the behavior of biotechnological processes aimed at biofuels obtainment.

Science.gov (United States)

Curcio, Stefano; Saraceno, Alessandra; Calabrò, Vincenza; Iorio, Gabriele

2014-01-01

The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

Neural Correlates of Processing Negative and Sexually Arousing Pictures

Science.gov (United States)

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

Morphological covariance in anatomical MRI scans can identify discrete neural pathways in the brain and their disturbances in persons with neuropsychiatric disorders.

Science.gov (United States)

Bansal, Ravi; Hao, Xuejun; Peterson, Bradley S

2015-05-01

We hypothesize that coordinated functional activity within discrete neural circuits induces morphological organization and plasticity within those circuits. Identifying regions of morphological covariation that are independent of morphological covariation in other regions therefore may therefore allow us to identify discrete neural systems within the brain. Comparing the magnitude of these variations in individuals who have psychiatric disorders with the magnitude of variations in healthy controls may allow us to identify aberrant neural pathways in psychiatric illnesses. We measured surface morphological features by applying nonlinear, high-dimensional warping algorithms to manually defined brain regions. We transferred those measures onto the surface of a unit sphere via conformal mapping and then used spherical wavelets and their scaling coefficients to simplify the data structure representing these surface morphological features of each brain region. We used principal component analysis (PCA) to calculate covariation in these morphological measures, as represented by their scaling coefficients, across several brain regions. We then assessed whether brain subregions that covaried in morphology, as identified by large eigenvalues in the PCA, identified specific neural pathways of the brain. To do so, we spatially registered the subnuclei for each eigenvector into the coordinate space of a Diffusion Tensor Imaging dataset; we used these subnuclei as seed regions to track and compare fiber pathways with known fiber pathways identified in neuroanatomical atlases. We applied these procedures to anatomical MRI data in a cohort of 82 healthy participants (42 children, 18 males, age 10.5 ± 2.43 years; 40 adults, 22 males, age 32.42 ± 10.7 years) and 107 participants with Tourette's Syndrome (TS) (71 children, 59 males, age 11.19 ± 2.2 years; 36 adults, 21 males, age 37.34 ± 10.9 years). We evaluated the construct validity of the identified covariation in morphology

The Effect of an Enrichment Reading Program on the Cognitive Processes and Neural Structures of Children Having Reading Difficulties

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Hayriye Gül KURUYER

2017-06-01

Full Text Available The main purpose of the current study is to explain the effect of an enrichment reading program on the cognitive processes and neural structures of children experiencing reading difficulties. The current study was carried out in line with a single-subject research method and the between-subjects multiple probe design belonging to this method. This research focuses on a group of eight students with reading difficulties. Within the context of the study, memory capacities, attention spans, reading-related activation and white matter pathways of the students were determined before and after the application of the enrichment reading program. This determination process was carried out in two stages. Neuro-imaging was performed in the first stage and in the second stage the students’ cognitive processes and neural structures were investigated in terms of focusing attention and memory capacities by using the following tools: Stroop Test TBAG Form, Auditory Verbal Digit Span Test-Form B, Cancellation Test and Number Order Learning Test. The results obtained show that the enrichment reading program resulted in an improvement in the reading profiles of the students having reading difficulties in terms of their cognitive processes and neural structures.

Excess thyroid hormone inhibits embryonic neural stem/progenitor cells proliferation and maintenance through STAT3 signalling pathway.

Science.gov (United States)

Chen, Chunhai; Zhou, Zhou; Zhong, Min; Li, Maoquan; Yang, Xuesen; Zhang, Yanwen; Wang, Yuan; Wei, Aimin; Qu, Mingyue; Zhang, Lei; Xu, Shangcheng; Chen, Shude; Yu, Zhengping

2011-07-01

Hyperthyroidism is prevalent during pregnancy, but little is known about the effects of excess thyroid hormone on the development of embryonic neural stem/progenitor cells (NSCs), and the mechanisms underlying these effects. Previous studies indicate that STAT3 plays a crucial role in determining NSC fate during neurodevelopment. In this study, we investigated the effects of a supraphysiological dose of 3,5,3'-L-triiodothyronine (T3) on the proliferation and maintenance of NSCs derived from embryonic day 13.5 mouse neocortex, and the involvement of STAT3 in this process. Our results suggest that excess T3 treatment inhibits NSC proliferation and maintenance. T3 decreased tyrosine phosphorylation of JAK1, JAK2 and STAT3, and subsequently inhibited STAT3-DNA binding activity. Furthermore, proliferation and maintenance of NSCs were decreased by inhibitors of JAKs and STAT3, indicating that the STAT3 signalling pathway is involved in the process of NSC proliferation and maintenance. Taken together, these results suggest that the STAT3 signalling pathway is involved in the process of T3-induced inhibition of embryonic NSC proliferation and maintenance. These findings provide data for understanding the effects of hyperthyroidism during pregnancy on fetal brain development, and the mechanisms underlying these effects.

High level cognitive information processing in neural networks

Science.gov (United States)

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.

Neural and Hybrid Modeling: An Alternative Route to Efficiently Predict the Behavior of Biotechnological Processes Aimed at Biofuels Obtainment

Directory of Open Access Journals (Sweden)

Stefano Curcio

2014-01-01

Full Text Available The present paper was aimed at showing that advanced modeling techniques, based either on artificial neural networks or on hybrid systems, might efficiently predict the behavior of two biotechnological processes designed for the obtainment of second-generation biofuels from waste biomasses. In particular, the enzymatic transesterification of waste-oil glycerides, the key step for the obtainment of biodiesel, and the anaerobic digestion of agroindustry wastes to produce biogas were modeled. It was proved that the proposed modeling approaches provided very accurate predictions of systems behavior. Both neural network and hybrid modeling definitely represented a valid alternative to traditional theoretical models, especially when comprehensive knowledge of the metabolic pathways, of the true kinetic mechanisms, and of the transport phenomena involved in biotechnological processes was difficult to be achieved.

The gamma model : a new neural network for temporal processing

NARCIS (Netherlands)

Vries, de B.

1992-01-01

In this paper we develop the gamma neural model, a new neural net architecture for processing of temporal patterns. Time varying patterns are normally segmented into a sequence of static patterns that are successively presented to a neural net. In the approach presented here segmentation is avoided.

Differential Contribution of the Guanylyl Cyclase-Cyclic GMP-Protein Kinase G Pathway to the Proliferation of Neural Stem Cells Stimulated by Nitric Oxide

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Bruno P. Carreira

2012-02-01

Full Text Available Nitric oxide (NO is an important inflammatory mediator involved in the initial boost in the proliferation of neural stem cells following brain injury. However, the mechanisms underlying the proliferative effect of NO are still unclear. The aim of this work was to investigate whether cyclic GMP (cGMP and the cGMP-dependent kinase (PKG are involved in the proliferative effect triggered by NO in neural stem cells. For this purpose, cultures of neural stem cells isolated from the mouse subventricular zone (SVZ were used. We observed that long-term exposure to the NO donor (24 h, NOC-18, increased the proliferation of SVZ cells in a cGMP-dependent manner, since the guanylate cyclase inhibitor, ODQ, prevented cell proliferation. Similarly to NOC-18, the cGMP analogue, 8-Br-cGMP, also increased cell proliferation. Interestingly, shorter exposures to NO (6 h increased cell proliferation in a cGMP-independent manner via the ERK/MAP kinase pathway. The selective inhibitor of PKG, KT5823, prevented the proliferative effect induced by NO at 24 h but not at 6 h. In conclusion, the proliferative effect of NO is initially mediated by the ERK/MAPK pathway, and at later stages by the GC/cGMP/PKG pathway. Thus, our work shows that NO induces neural stem cell proliferation by targeting these two pathways in a biphasic manner.

A novel neural-wavelet approach for process diagnostics and complex system modeling

Science.gov (United States)

Gao, Rong

Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

Neural substrates of sublexical processing for spelling.

Science.gov (United States)

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. Copyright © 2016 Elsevier Inc. All rights reserved.

Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

NARCIS (Netherlands)

Veldhoen, S.; Hupkes, D.; Zuidema, W.

2016-01-01

We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

Dissociable neural processes during risky decision-making in individuals with Internet-gaming disorder

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Lu Liu

2017-01-01

Full Text Available Risk-taking is purported to be central to addictive behaviors. However, for Internet gaming disorder (IGD, a condition conceptualized as a behavioral addiction, the neural processes underlying impaired decision-making (risk evaluation and outcome processing related to gains and losses have not been systematically investigated. Forty-one males with IGD and 27 healthy comparison (HC male participants were recruited, and the cups task was used to identify neural processes associated with gain- and loss-related risk- and outcome-processing in IGD. During risk evaluation, the IGD group, compared to the HC participants, showed weaker modulation for experienced risk within the bilateral dorsolateral prefrontal cortex (DLPFC (t = −4.07; t = −3.94; PFWE < 0.05 and inferior parietal lobule (IPL (t = −4.08; t = −4.08; PFWE < 0.05 for potential losses. The modulation of the left DLPFC and bilateral IPL activation were negatively related to addiction severity within the IGD group (r = −0.55; r = −0.61; r = −0.51; PFWE < 0.05. During outcome processing, the IGD group presented greater responses for the experienced reward within the ventral striatum, ventromedial prefrontal cortex, and orbitofrontal cortex (OFC (t = 5.04, PFWE < 0.05 for potential gains, as compared to HC participants. Within the IGD group, the increased reward-related activity in the right OFC was positively associated with severity of IGD (r = 0.51, PFWE < 0.05. These results provide a neurobiological foundation for decision-making deficits in individuals with IGD and suggest an imbalance between hypersensitivity for reward and weaker risk experience and self-control for loss. The findings suggest a biological mechanism for why individuals with IGD may persist in game-seeking behavior despite negative consequences, and treatment development strategies may focus on targeting these neural pathways in this population.

Event-driven processing for hardware-efficient neural spike sorting

Science.gov (United States)

Liu, Yan; Pereira, João L.; Constandinou, Timothy G.

2018-02-01

Objective. The prospect of real-time and on-node spike sorting provides a genuine opportunity to push the envelope of large-scale integrated neural recording systems. In such systems the hardware resources, power requirements and data bandwidth increase linearly with channel count. Event-based (or data-driven) processing can provide here a new efficient means for hardware implementation that is completely activity dependant. In this work, we investigate using continuous-time level-crossing sampling for efficient data representation and subsequent spike processing. Approach. (1) We first compare signals (synthetic neural datasets) encoded with this technique against conventional sampling. (2) We then show how such a representation can be directly exploited by extracting simple time domain features from the bitstream to perform neural spike sorting. (3) The proposed method is implemented in a low power FPGA platform to demonstrate its hardware viability. Main results. It is observed that considerably lower data rates are achievable when using 7 bits or less to represent the signals, whilst maintaining the signal fidelity. Results obtained using both MATLAB and reconfigurable logic hardware (FPGA) indicate that feature extraction and spike sorting accuracies can be achieved with comparable or better accuracy than reference methods whilst also requiring relatively low hardware resources. Significance. By effectively exploiting continuous-time data representation, neural signal processing can be achieved in a completely event-driven manner, reducing both the required resources (memory, complexity) and computations (operations). This will see future large-scale neural systems integrating on-node processing in real-time hardware.

Precision Scaling of Neural Networks for Efficient Audio Processing

OpenAIRE

Ko, Jong Hwan; Fromm, Josh; Philipose, Matthai; Tashev, Ivan; Zarar, Shuayb

2017-01-01

While deep neural networks have shown powerful performance in many audio applications, their large computation and memory demand has been a challenge for real-time processing. In this paper, we study the impact of scaling the precision of neural networks on the performance of two common audio processing tasks, namely, voice-activity detection and single-channel speech enhancement. We determine the optimal pair of weight/neuron bit precision by exploring its impact on both the performance and ...

Neural processing of musical meter in musicians and non-musicians.

Science.gov (United States)

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

2017-11-01

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

Neural network training by Kalman filtering in process system monitoring

International Nuclear Information System (INIS)

Ciftcioglu, Oe.

1996-03-01

Kalman filtering approach for neural network training is described. Its extended form is used as an adaptive filter in a nonlinear environment of the form a feedforward neural network. Kalman filtering approach generally provides fast training as well as avoiding excessive learning which results in enhanced generalization capability. The network is used in a process monitoring application where the inputs are measurement signals. Since the measurement errors are also modelled in Kalman filter the approach yields accurate training with the implication of accurate neural network model representing the input and output relationships in the application. As the process of concern is a dynamic system, the input source of information to neural network is time dependent so that the training algorithm presents an adaptive form for real-time operation for the monitoring task. (orig.)

Optimization of blanking process using neural network simulation

International Nuclear Information System (INIS)

Hambli, R.

2005-01-01

The present work describes a methodology using the finite element method and neural network simulation in order to predict the optimum punch-die clearance during sheet metal blanking processes. A damage model is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. Numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling. The comparative study between the numerical results and the experimental ones shows the good agreement. (author)

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

Science.gov (United States)

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.

The alexithymic brain: the neural pathways linking alexithymia to physical disorders

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Kano Michiko

2013-01-01

Full Text Available Abstract Alexithymia is a personality trait characterized by difficulties in identifying and describing feelings and is associated with psychiatric and psychosomatic disorders. The mechanisms underlying the link between emotional dysregulation and psychosomatic disorders are unclear. Recent progress in neuroimaging has provided important information regarding emotional experience in alexithymia. We have conducted three brain imaging studies on alexithymia, which we describe herein. This article considers the role of emotion in the development of physical symptoms and discusses a possible pathway that we have identified in our neuroimaging studies linking alexithymia with psychosomatic disorders. In terms of socio-affective processing, alexithymics demonstrate lower reactivity in brain regions associated with emotion. Many studies have reported reduced activation in limbic areas (e.g., cingulate cortex, anterior insula, amygdala and the prefrontal cortex when alexithymics attempt to feel other people’s feelings or retrieve their own emotional episodes, compared to nonalexithymics. With respect to primitive emotional reactions such as the response to pain, alexithymics show amplified activity in areas considered to be involved in physical sensation. In addition to greater hormonal arousal responses in alexithymics during visceral pain, increased activity has been reported in the insula, anterior cingulate cortex, and midbrain. Moreover, in complex social situations, alexithymics may not be able to use feelings to guide their behavior appropriately. The Iowa gambling task (IGT was developed to assess decision-making processes based on emotion-guided evaluation. When alexithymics perform the IGT, they fail to learn an advantageous decision-making strategy and show reduced activity in the medial prefrontal cortex, a key area for successful performance of the IGT, and increased activity in the caudate, a region associated with impulsive choice. The

Hybrid digital signal processing and neural networks applications in PWRs

International Nuclear Information System (INIS)

Eryurek, E.; Upadhyaya, B.R.; Kavaklioglu, K.

1991-01-01

Signal validation and plant subsystem tracking in power and process industries require the prediction of one or more state variables. Both heteroassociative and auotassociative neural networks were applied for characterizing relationships among sets of signals. A multi-layer neural network paradigm was applied for sensor and process monitoring in a Pressurized Water Reactor (PWR). This nonlinear interpolation technique was found to be very effective for these applications

Linking Neural and Symbolic Representation and Processing of Conceptual Structures

Directory of Open Access Journals (Sweden)

Frank van der Velde

2017-08-01

Full Text Available 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.

Dopamine system: Manager of neural pathways

Directory of Open Access Journals (Sweden)

Simon eHong

2013-12-01

Full Text Available There are a growing number of roles that midbrain dopamine (DA neurons assume, such as, reward, aversion, alerting and vigor. Here I propose a theory that may be able to explain why the suggested functions of DA came about. It has been suggested that largely parallel cortico-basal ganglia-thalamo-cortico loops exist to control different aspects of behavior. I propose that (1 the midbrain DA system is organized in a similar manner, with different groups of DA neurons corresponding to these parallel neural pathways (NPs. The DA system can be viewed as the manager of these parallel NPs in that it recruits and activates only the task-relevant NPs when they are needed. It is likely that the functions of those NPs that have been consistently activated by the corresponding DA groups are facilitated. I also propose that (2 there are two levels of DA roles: the How and What roles. The How role is encoded in tonic and phasic DA neuron firing patterns and gives a directive to its target NP: how vigorously its function needs to be carried out. The tonic DA firing is to maintain a certain level of DA in the target NPs to support their expected behavioral and mental functions; it is only when a sudden unexpected boost or suppression of activity is required by the relevant target NP that DA neurons in the corresponding NP act in a phasic manner. The What role is the implementational aspect of the role of DA in the target NP, such as binding to D1 receptors to boost working memory. This What aspect of DA explains why DA seems to assume different functions depending on the region of the brain in which it is involved. In terms of the role of the lateral habenula (LHb, the LHb is expected to suppress maladaptive behaviors and mental processes by controlling the DA system. The demand-based smart management by the DA system may have given animals an edge in evolution with adaptive behaviors and a better survival rate in resource-scarce situations.

Neural tube defects – disorders of neurulation and related embryonic processes

Science.gov (United States)

Copp, Andrew J.; Greene, Nicholas D. E.

2014-01-01

Neural tube defects (NTDs) are severe congenital malformations affecting 1 in every 1000 pregnancies. ‘Open’ NTDs result from failure of primary neurulation as seen in anencephaly, myelomeningocele (open spina bifida) and craniorachischisis. Degeneration of the persistently open neural tube in utero leads to loss of neurological function below the lesion level. ‘Closed’ NTDs are skin-covered disorders of spinal cord structure, ranging from asymptomatic spina bifida occulta to severe spinal cord tethering, and usually traceable to disruption of secondary neurulation. ‘Herniation’ NTDs are those in which meninges, with or without brain or spinal cord tissue, become exteriorised through a pathological opening in the skull or vertebral column (e.g. encephalocele and meningocele). NTDs have multifactorial etiology, with genes and environmental factors interacting to determine individual risk of malformation. While over 200 mutant genes cause open NTDs in mice, much less is known about the genetic causation of human NTDs. Recent evidence has implicated genes of the planar cell polarity signalling pathway in a proportion of cases. The embryonic development of NTDs is complex, with diverse cellular and molecular mechanisms operating at different levels of the body axis. Molecular regulatory events include the BMP and Sonic hedgehog pathways which have been implicated in control of neural plate bending. Primary prevention of NTDs has been implemented clinically following the demonstration that folic acid, when taken as a peri-conceptional supplement, can prevent many cases. Not all NTDs respond to folic acid, however, and adjunct therapies are required for prevention of this folic acid-resistant category. PMID:24009034

Nonlinear signal processing using neural networks: Prediction and system modelling

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.; Farber, R.

1987-06-01

The backpropagation learning algorithm for neural networks is developed into a formalism for nonlinear signal processing. We illustrate the method by selecting two common topics in signal processing, prediction and system modelling, and show that nonlinear applications can be handled extremely well by using neural networks. The formalism is a natural, nonlinear extension of the linear Least Mean Squares algorithm commonly used in adaptive signal processing. Simulations are presented that document the additional performance achieved by using nonlinear neural networks. First, we demonstrate that the formalism may be used to predict points in a highly chaotic time series with orders of magnitude increase in accuracy over conventional methods including the Linear Predictive Method and the Gabor-Volterra-Weiner Polynomial Method. Deterministic chaos is thought to be involved in many physical situations including the onset of turbulence in fluids, chemical reactions and plasma physics. Secondly, we demonstrate the use of the formalism in nonlinear system modelling by providing a graphic example in which it is clear that the neural network has accurately modelled the nonlinear transfer function. It is interesting to note that the formalism provides explicit, analytic, global, approximations to the nonlinear maps underlying the various time series. Furthermore, the neural net seems to be extremely parsimonious in its requirements for data points from the time series. We show that the neural net is able to perform well because it globally approximates the relevant maps by performing a kind of generalized mode decomposition of the maps. 24 refs., 13 figs.

Active voltammetric microsensors with neural signal processing.

Energy Technology Data Exchange (ETDEWEB)

Vogt, M. C.

1998-12-11

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

Active voltammetric microsensors with neural signal processing

Science.gov (United States)

Vogt, Michael C.; Skubal, Laura R.

1999-02-01

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

Nonlinear identification of process dynamics using neural networks

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, A.F.; Chong, K.T.

1992-01-01

In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

A new neural framework for visuospatial processing.

Science.gov (United States)

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.

Explicit versus implicit neural processing of musical emotions

OpenAIRE

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

2016-01-01

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 e...

Neural manufacturing: a novel concept for processing modeling, monitoring, and control

Science.gov (United States)

Fu, Chi Y.; Petrich, Loren; Law, Benjamin

1995-09-01

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.

Neural processes underlying cultural differences in cognitive persistence.

Science.gov (United States)

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

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

Science.gov (United States)

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fault detection and diagnosis for complex multivariable processes using neural networks

International Nuclear Information System (INIS)

Weerasinghe, M.

1998-06-01

Development of a reliable fault diagnosis method for large-scale industrial plants is laborious and often difficult to achieve due to the complexity of the targeted systems. The main objective of this thesis is to investigate the application of neural networks to the diagnosis of non-catastrophic faults in an industrial nuclear fuel processing plant. The proposed methods were initially developed by application to a simulated chemical process prior to further validation on real industrial data. The diagnosis of faults at a single operating point is first investigated. Statistical data conditioning methods of data scaling and principal component analysis are investigated to facilitate fault classification and reduce the complexity of neural networks. Successful fault diagnosis was achieved with significantly smaller networks than using all process variables as network inputs. Industrial processes often manufacture at various operating points, but demonstrated applications of neural networks for fault diagnosis usually only consider a single (primary) operating point. Developing a standard neural network scheme for fault diagnosis at all operating points would be usually impractical due to the unavailability of suitable training data for less frequently used (secondary) operating points. To overcome this problem, the application of a single neural network for the diagnosis of faults operating at different points is investigated. The data conditioning followed the same techniques as used for the fault diagnosis of a single operating point. The results showed that a single neural network could be successfully used to diagnose faults at operating points other than that it is trained for, and the data conditioning significantly improved the classification. Artificial neural networks have been shown to be an effective tool for process fault diagnosis. However, a main criticism is that details of the procedures taken to reach the fault diagnosis decisions are embedded in

Doubly stochastic Poisson processes in artificial neural learning.

Science.gov (United States)

Card, H C

1998-01-01

This paper investigates neuron activation statistics in artificial neural networks employing stochastic arithmetic. It is shown that a doubly stochastic Poisson process is an appropriate model for the signals in these circuits.

Electroacupuncture in the repair of spinal cord injury: inhibiting the Notch signaling pathway and promoting neural stem cell proliferation

Directory of Open Access Journals (Sweden)

Xin Geng

2015-01-01

Full Text Available Electroacupuncture for the treatment of spinal cord injury has a good clinical curative effect, but the underlying mechanism is unclear. In our experiments, the spinal cord of adult Sprague-Dawley rats was clamped for 60 seconds. Dazhui (GV14 and Mingmen (GV4 acupoints of rats were subjected to electroacupuncture. Enzyme-linked immunosorbent assay revealed that the expression of serum inflammatory factors was apparently downregulated in rat models of spinal cord injury after electroacupuncture. Hematoxylin-eosin staining and immunohistochemistry results demonstrated that electroacupuncture contributed to the proliferation of neural stem cells in rat injured spinal cord, and suppressed their differentiation into astrocytes. Real-time quantitative PCR and western blot assays showed that electroacupuncture inhibited activation of the Notch signaling pathway induced by spinal cord injury. These findings indicate that electroacupuncture repaired the injured spinal cord by suppressing the Notch signaling pathway and promoting the proliferation of endogenous neural stem cells.

Handbook on neural information processing

CERN Document Server

Maggini, Marco; Jain, Lakhmi

2013-01-01

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include:                         Deep architectures                         Recurrent, recursive, and graph neural networks                         Cellular neural networks                         Bayesian networks                         Approximation capabilities of neural networks                         Semi-supervised learning                         Statistical relational learning                         Kernel methods for structured data                         Multiple classifier systems                         Self organisation and modal learning                         Applications to ...

Distinct pathways of neural coupling for different basic emotions.

Science.gov (United States)

Tettamanti, Marco; Rognoni, Elena; Cafiero, Riccardo; Costa, Tommaso; Galati, Dario; Perani, Daniela

2012-01-16

Emotions are complex events recruiting distributed cortical and subcortical cerebral structures, where the functional integration dynamics within the involved neural circuits in relation to the nature of the different emotions are still unknown. Using fMRI, we measured the neural responses elicited by films representing basic emotions (fear, disgust, sadness, happiness). The amygdala and the associative cortex were conjointly activated by all basic emotions. Furthermore, distinct arrays of cortical and subcortical brain regions were additionally activated by each emotion, with the exception of sadness. Such findings informed the definition of three effective connectivity models, testing for the functional integration of visual cortex and amygdala, as regions processing all emotions, with domain-specific regions, namely: i) for fear, the frontoparietal system involved in preparing adaptive motor responses; ii) for disgust, the somatosensory system, reflecting protective responses against contaminating stimuli; iii) for happiness: medial prefrontal and temporoparietal cortices involved in understanding joyful interactions. Consistently with these domain-specific models, the results of the effective connectivity analysis indicate that the amygdala is involved in distinct functional integration effects with cortical networks processing sensorimotor, somatosensory, or cognitive aspects of basic emotions. The resulting effective connectivity networks may serve to regulate motor and cognitive behavior based on the quality of the induced emotional experience. Copyright © 2011. Published by Elsevier Inc.

Designing neural networks that process mean values of random variables

International Nuclear Information System (INIS)

Barber, Michael J.; Clark, John W.

2014-01-01

We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence

Designing neural networks that process mean values of random variables

Energy Technology Data Exchange (ETDEWEB)

Barber, Michael J. [AIT Austrian Institute of Technology, Innovation Systems Department, 1220 Vienna (Austria); Clark, John W. [Department of Physics and McDonnell Center for the Space Sciences, Washington University, St. Louis, MO 63130 (United States); Centro de Ciências Matemáticas, Universidade de Madeira, 9000-390 Funchal (Portugal)

2014-06-13

We develop a class of neural networks derived from probabilistic models posed in the form of Bayesian networks. Making biologically and technically plausible assumptions about the nature of the probabilistic models to be represented in the networks, we derive neural networks exhibiting standard dynamics that require no training to determine the synaptic weights, that perform accurate calculation of the mean values of the relevant random variables, that can pool multiple sources of evidence, and that deal appropriately with ambivalent, inconsistent, or contradictory evidence. - Highlights: • High-level neural computations are specified by Bayesian belief networks of random variables. • Probability densities of random variables are encoded in activities of populations of neurons. • Top-down algorithm generates specific neural network implementation of given computation. • Resulting “neural belief networks” process mean values of random variables. • Such networks pool multiple sources of evidence and deal properly with inconsistent evidence.

The proliferation of amplifying neural progenitor cells is impaired in the aging brain and restored by the mTOR pathway activation.

Science.gov (United States)

Romine, Jennifer; Gao, Xiang; Xu, Xiao-Ming; So, Kwok Fai; Chen, Jinhui

2015-04-01

A decrease in neurogenesis in the aged brain has been correlated with cognitive decline. The molecular signaling that regulates age-related decline in neurogenesis is still not fully understood. We found that different subtypes of neural stem cells (NSCs) in the hippocampus were differentially impaired by aging. The quiescent NSCs decreased slowly, although the active NSCs exhibited a sharp and dramatic decline from the ages of 6-9 months and became more quiescent at an early stage during the aging process. The activity of the mammalian target of rapamycin (mTOR) signal pathway is compromised in the NSCs of the aged brain. Activating the mTOR signaling pathway increased NSC proliferation and promoted neurogenesis in aged mice. In contrast, inhibiting the mTOR signaling pathway decreased NSCs proliferation. These results indicate that an age-associated decline in neurogenesis is mainly because of the reduction in proliferation of active NSCs, at least partially because of the compromise in the mTOR signaling activity. Stimulating the mTOR signaling revitalizes the NSCs, restores their proliferation, and enhances neurogenesis in the hippocampus of the aged brain. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural mechanisms of order information processing in working memory

Directory of Open Access Journals (Sweden)

Barbara Dolenc

2013-11-01

Full Text Available The ability to encode and maintain the exact order of short sequences of stimuli or events is often crucial to our ability for effective high-order planning. However, it is not yet clear which neural mechanisms underpin this process. Several studies suggest that in comparison with item recognition temporal order coding activates prefrontal and parietal brain regions. Results of various studies tend to favour the hypothesis that the order of the stimuli is represented and encoded on several stages, from primacy and recency estimates to the exact position of the item in a sequence. Different brain regions play a different role in this process. Dorsolateral prefrontal cortex has a more general role in attention, while the premotor cortex is more involved in the process of information grouping. Parietal lobe and hippocampus also play a significant role in order processing as they enable the representation of distance. Moreover, order maintenance is associated with the existence of neural oscillators that operate at different frequencies. Electrophysiological studies revealed that theta and alpha oscillations play an important role in the maintenance of temporal order information. Those EEG oscillations are differentially associated with processes that support the maintenance of order information and item recognition. Various studies suggest a link between prefrontal areas and memory for temporal order, implying that EEG neural oscillations in the prefrontal cortex may play a role in the maintenance of information on temporal order.

Magnocellular pathway for rotation invariant Neocognitron.

Science.gov (United States)

Ting, C H

1993-03-01

In the mammalian visual system, magnocellular pathway and parvocellular pathway cooperatively process visual information in parallel. The magnocellular pathway is more global and less particular about the details while the parvocellular pathway recognizes objects based on the local features. In many aspects, Neocognitron may be regarded as the artificial analogue of the parvocellular pathway. It is interesting then to model the magnocellular pathway. In order to achieve "rotation invariance" for Neocognitron, we propose a neural network model after the magnocellular pathway and expand its roles to include surmising the orientation of the input pattern prior to recognition. With the incorporation of the magnocellular pathway, a basic shift in the original paradigm has taken place. A pattern is now said to be recognized when and only when one of the winners of the magnocellular pathway is validified by the parvocellular pathway. We have implemented the magnocellular pathway coupled with Neocognitron parallel on transputers; our simulation programme is now able to recognize numerals in arbitrary orientation.

Process identification through modular neural networks and rule extraction (extended abstract)

NARCIS (Netherlands)

van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.; Blockeel, Hendrik; Denecker, Marc

2002-01-01

Monolithic neural networks may be trained from measured data to establish knowledge about the process. Unfortunately, this knowledge is not guaranteed to be found and – if at all – hard to extract. Modular neural networks are better suited for this purpose. Domain-ordered by topology, rule

Music Signal Processing Using Vector Product Neural Networks

Science.gov (United States)

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.

Neural correlates of successful semantic processing during propofol sedation

NARCIS (Netherlands)

Adapa, Ram M.; Davis, Matthew H.; Stamatakis, Emmanuel A.; Absalom, Anthony R.; Menon, David K.

Sedation has a graded effect on brain responses to auditory stimuli: perceptual processing persists at sedation levels that attenuate more complex processing. We used fMRI in healthy volunteers sedated with propofol to assess changes in neural responses to spoken stimuli. Volunteers were scanned

Neural network connectivity and response latency modelled by stochastic processes

DEFF Research Database (Denmark)

Tamborrino, Massimiliano

is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...

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

Science.gov (United States)

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

Artificial neural network modelling approach for a biomass gasification process in fixed bed gasifiers

International Nuclear Information System (INIS)

Mikulandrić, Robert; Lončar, Dražen; Böhning, Dorith; Böhme, Rene; Beckmann, Michael

2014-01-01

Highlights: • 2 Different equilibrium models are developed and their performance is analysed. • Neural network prediction models for 2 different fixed bed gasifier types are developed. • The influence of different input parameters on neural network model performance is analysed. • Methodology for neural network model development for different gasifier types is described. • Neural network models are verified for various operating conditions based on measured data. - Abstract: The number of the small and middle-scale biomass gasification combined heat and power plants as well as syngas production plants has been significantly increased in the last decade mostly due to extensive incentives. However, existing issues regarding syngas quality, process efficiency, emissions and environmental standards are preventing biomass gasification technology to become more economically viable. To encounter these issues, special attention is given to the development of mathematical models which can be used for a process analysis or plant control purposes. The presented paper analyses possibilities of neural networks to predict process parameters with high speed and accuracy. After a related literature review and measurement data analysis, different modelling approaches for the process parameter prediction that can be used for an on-line process control were developed and their performance were analysed. Neural network models showed good capability to predict biomass gasification process parameters with reasonable accuracy and speed. Measurement data for the model development, verification and performance analysis were derived from biomass gasification plant operated by Technical University Dresden

Neural PID Control Strategy for Networked Process Control

Directory of Open Access Journals (Sweden)

Jianhua Zhang

2013-01-01

Full Text Available A new method with a two-layer hierarchy is presented based on a neural proportional-integral-derivative (PID iterative learning method over the communication network for the closed-loop automatic tuning of a PID controller. It can enhance the performance of the well-known simple PID feedback control loop in the local field when real networked process control applied to systems with uncertain factors, such as external disturbance or randomly delayed measurements. The proposed PID iterative learning method is implemented by backpropagation neural networks whose weights are updated via minimizing tracking error entropy of closed-loop systems. The convergence in the mean square sense is analysed for closed-loop networked control systems. To demonstrate the potential applications of the proposed strategies, a pressure-tank experiment is provided to show the usefulness and effectiveness of the proposed design method in network process control systems.

Noun and verb processing in aphasia: Behavioural profiles and neural correlates

Directory of Open Access Journals (Sweden)

Reem S.W. Alyahya

Full Text Available The behavioural and neural processes underpinning different word classes, particularly nouns and verbs, have been a long-standing area of interest in psycholinguistic, neuropsychology and aphasiology research. This topic has theoretical implications concerning the organisation of the language system, as well as clinical consequences related to the management of patients with language deficits. Research findings, however, have diverged widely, which might, in part, reflect methodological differences, particularly related to controlling the psycholinguistic variations between nouns and verbs. The first aim of this study, therefore, was to develop a set of neuropsychological tests that assessed single-word production and comprehension with a matched set of nouns and verbs. Secondly, the behavioural profiles and neural correlates of noun and verb processing were explored, based on these novel tests, in a relatively large cohort of 48 patients with chronic post-stroke aphasia. A data-driven approach, principal component analysis (PCA, was also used to determine how noun and verb production and comprehension were related to the patients' underlying fundamental language domains. The results revealed no performance differences between noun and verb production and comprehension once matched on multiple psycholinguistic features including, most critically, imageability. Interestingly, the noun-verb differences found in previous studies were replicated in this study once un-matched materials were used. Lesion-symptom mapping revealed overlapping neural correlates of noun and verb processing along left temporal and parietal regions. These findings support the view that the neural representation of noun and verb processing at single-word level are jointly-supported by distributed cortical regions. The PCA generated five fundamental language and cognitive components of aphasia: phonological production, phonological recognition, semantics, fluency, and

Neural crest contributions to the lamprey head

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McCauley, David W.; Bronner-Fraser, Marianne

2003-01-01

The neural crest is a vertebrate-specific cell population that contributes to the facial skeleton and other derivatives. We have performed focal DiI injection into the cranial neural tube of the developing lamprey in order to follow the migratory pathways of discrete groups of cells from origin to destination and to compare neural crest migratory pathways in a basal vertebrate to those of gnathostomes. The results show that the general pathways of cranial neural crest migration are conserved throughout the vertebrates, with cells migrating in streams analogous to the mandibular and hyoid streams. Caudal branchial neural crest cells migrate ventrally as a sheet of cells from the hindbrain and super-pharyngeal region of the neural tube and form a cylinder surrounding a core of mesoderm in each pharyngeal arch, similar to that seen in zebrafish and axolotl. In addition to these similarities, we also uncovered important differences. Migration into the presumptive caudal branchial arches of the lamprey involves both rostral and caudal movements of neural crest cells that have not been described in gnathostomes, suggesting that barriers that constrain rostrocaudal movement of cranial neural crest cells may have arisen after the agnathan/gnathostome split. Accordingly, neural crest cells from a single axial level contributed to multiple arches and there was extensive mixing between populations. There was no apparent filling of neural crest derivatives in a ventral-to-dorsal order, as has been observed in higher vertebrates, nor did we find evidence of a neural crest contribution to cranial sensory ganglia. These results suggest that migratory constraints and additional neural crest derivatives arose later in gnathostome evolution.

Combinatorial structures and processing in neural blackboard architectures

NARCIS (Netherlands)

van der Velde, Frank; van der Velde, Frank; de Kamps, Marc; Besold, Tarek R.; d'Avila Garcez, Artur; Marcus, Gary F.; Miikkulainen, Risto

2015-01-01

We discuss and illustrate Neural Blackboard Architectures (NBAs) as the basis for variable binding and combinatorial processing the brain. We focus on the NBA for sentence structure. NBAs are based on the notion that conceptual representations are in situ, hence cannot be copied or transported.

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

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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.

Linking neural and symbolic representation and processing of conceptual structures

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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

Autism as an adaptive common variant pathway for human brain development

Directory of Open Access Journals (Sweden)

Mark H. Johnson

2017-06-01

Full Text Available While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency. Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development.

Artificial neural networks in variable process control: application in particleboard manufacture

Energy Technology Data Exchange (ETDEWEB)

Esteban, L. G.; Garcia Fernandez, F.; Palacios, P. de; Conde, M.

2009-07-01

Artificial neural networks are an efficient tool for modelling production control processes using data from the actual production as well as simulated or design of experiments data. In this study two artificial neural networks were combined with the control process charts and it was checked whether the data obtained by the networks were valid for variable process control in particleboard manufacture. The networks made it possible to obtain the mean and standard deviation of the internal bond strength of the particleboard within acceptable margins using known data of thickness, density, moisture content, swelling and absorption. The networks obtained met the acceptance criteria for test values from non-standard test methods, as well as the criteria for using these values in statistical process control. (Author) 47 refs.

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

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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

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

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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.

Interactions between Depression and Facilitation within Neural Networks: Updating the Dual-Process Theory of Plasticity

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Prescott, Steven A.

1998-01-01

Repetitive stimulation often results in habituation of the elicited response. However, if the stimulus is sufficiently strong, habituation may be preceded by transient sensitization or even replaced by enduring sensitization. In 1970, Groves and Thompson formulated the dual-process theory of plasticity to explain these characteristic behavioral changes on the basis of competition between decremental plasticity (depression) and incremental plasticity (facilitation) occurring within the neural network. Data from both vertebrate and invertebrate systems are reviewed and indicate that the effects of depression and facilitation are not exclusively additive but, rather, that those processes interact in a complex manner. Serial ordering of induction of learning, in which a depressing locus precedes the modulatory system responsible for inducing facilitation, causes the facilitation to wane. The parallel and/or serial expression of depression and waning facilitation within the stimulus–response pathway culminates in the behavioral changes that characterize dual-process learning. A mathematical model is presented to formally express and extend understanding of the interactions between depression and facilitation. PMID:10489261

Acute Stress Influences Neural Circuits of Reward Processing

Directory of Open Access Journals (Sweden)

Anthony John Porcelli

2012-11-01

Full Text Available People often make decisions under aversive conditions such as acute stress. Yet, less is known about the process in which acute stress can influence decision-making. A growing body of research has established that reward-related information associated with the outcomes of decisions exerts a powerful influence over the choices people make and that an extensive network of brain regions, prominently featuring the striatum, is involved in the processing of this reward-related information. Thus, an important step in research on the nature of acute stress’ influence over decision-making is to examine how it may modulate responses to rewards and punishments within reward-processing neural circuitry. In the current experiment, we employed a simple reward processing paradigm – where participants received monetary rewards and punishments – known to evoke robust striatal responses. Immediately prior to performing each of two task runs, participants were exposed to acute stress (i.e., cold pressor or a no stress control procedure in a between-subjects fashion. No stress group participants exhibited a pattern of activity within the dorsal striatum and orbitofrontal cortex consistent with past research on outcome processing – specifically, differential responses for monetary rewards over punishments. In contrast, acute stress group participants’ dorsal striatum and orbitofrontal cortex demonstrated decreased sensitivity to monetary outcomes and a lack of differential activity. These findings provide insight into how neural circuits may process rewards and punishments associated with simple decisions under acutely stressful conditions.

Spatially Compact Neural Clusters in the Dorsal Striatum Encode Locomotion Relevant Information.

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Barbera, Giovanni; Liang, Bo; Zhang, Lifeng; Gerfen, Charles R; Culurciello, Eugenio; Chen, Rong; Li, Yun; Lin, Da-Ting

2016-10-05

An influential striatal model postulates that neural activities in the striatal direct and indirect pathways promote and inhibit movement, respectively. Normal behavior requires coordinated activity in the direct pathway to facilitate intended locomotion and indirect pathway to inhibit unwanted locomotion. In this striatal model, neuronal population activity is assumed to encode locomotion relevant information. Here, we propose a novel encoding mechanism for the dorsal striatum. We identified spatially compact neural clusters in both the direct and indirect pathways. Detailed characterization revealed similar cluster organization between the direct and indirect pathways, and cluster activities from both pathways were correlated with mouse locomotion velocities. Using machine-learning algorithms, cluster activities could be used to decode locomotion relevant behavioral states and locomotion velocity. We propose that neural clusters in the dorsal striatum encode locomotion relevant information and that coordinated activities of direct and indirect pathway neural clusters are required for normal striatal controlled behavior. VIDEO ABSTRACT. Published by Elsevier Inc.

From Imitation to Prediction, Data Compression vs Recurrent Neural Networks for Natural Language Processing

Directory of Open Access Journals (Sweden)

Juan Andres Laura

2018-03-01

Full Text Available In recent studies Recurrent Neural Networks were used for generative processes and their surprising performance can be explained by their ability to create good predictions. In addition, Data Compression is also based on prediction. What the problem comes down to is whether a data compressor could be used to perform as well as recurrent neural networks in the natural language processing tasks of sentiment analysis and automatic text generation. If this is possible, then the problem comes down to determining if a compression algorithm is even more intelligent than a neural network in such tasks. In our journey, a fundamental difference between a Data Compression Algorithm and Recurrent Neural Networks has been discovered.

D-FNN Based Modeling and BP Neural Network Decoupling Control of PVC Stripping Process

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Shu-zhi Gao

2014-01-01

Full Text Available PVC stripping process is a kind of complicated industrial process with characteristics of highly nonlinear and time varying. Aiming at the problem of establishing the accurate mathematics model due to the multivariable coupling and big time delay, the dynamic fuzzy neural network (D-FNN is adopted to establish the PVC stripping process model based on the actual process operation datum. Then, the PVC stripping process is decoupled by the distributed neural network decoupling module to obtain two single-input-single-output (SISO subsystems (slurry flow to top tower temperature and steam flow to bottom tower temperature. Finally, the PID controller based on BP neural networks is used to control the decoupled PVC stripper system. Simulation results show the effectiveness of the proposed integrated intelligent control method.

What Can Psychiatric Disorders Tell Us about Neural Processing of the Self?

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Zhao, Weihua; Luo, Lizhu; Li, Qin; Kendrick, Keith M

2013-01-01

Many psychiatric disorders are associated with abnormal self-processing. While these disorders also have a wide-range of complex, and often heterogeneous sets of symptoms involving different cognitive, emotional, and motor domains, an impaired sense of self can contribute to many of these. Research investigating self-processing in healthy subjects has facilitated identification of changes in specific neural circuits which may cause altered self-processing in psychiatric disorders. While there is evidence for altered self-processing in many psychiatric disorders, here we will focus on four of the most studied ones, schizophrenia, autism spectrum disorder (ASD), major depression, and borderline personality disorder (BPD). We review evidence for dysfunction in two different neural systems implicated in self-processing, namely the cortical midline system (CMS) and the mirror neuron system (MNS), as well as contributions from altered inter-hemispheric connectivity (IHC). We conclude that while abnormalities in frontal-parietal activity and/or connectivity in the CMS are common to all four disorders there is more disruption of integration between frontal and parietal regions resulting in a shift toward parietal control in schizophrenia and ASD which may contribute to the greater severity and delusional aspects of their symptoms. Abnormalities in the MNS and in IHC are also particularly evident in schizophrenia and ASD and may lead to disturbances in sense of agency and the physical self in these two disorders. A better future understanding of how changes in the neural systems sub-serving self-processing contribute to different aspects of symptom abnormality in psychiatric disorders will require that more studies carry out detailed individual assessments of altered self-processing in conjunction with measurements of neural functioning.

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

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Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

DNA topoisomerase IIβ stimulates neurite outgrowth in neural differentiated human mesenchymal stem cells through regulation of Rho-GTPases (RhoA/Rock2 pathway) and Nurr1 expression.

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Zaim, Merve; Isik, Sevim

2018-04-25

DNA topoisomerase IIβ (topo IIβ) is known to regulate neural differentiation by inducing the neuronal genes responsible for critical neural differentiation events such as neurite outgrowth and axon guidance. However, the pathways of axon growth controlled by topo IIβ have not been clarified yet. Microarray results of our previous study have shown that topo IIβ silencing in neural differentiated primary human mesenchymal stem cells (hMSCs) significantly alters the expression pattern of genes involved in neural polarity, axonal growth, and guidance, including Rho-GTPases. This study aims to further analyze the regulatory role of topo IIβ on the process of axon growth via regulation of Rho-GTPases. For this purpose, topo IIβ was silenced in neurally differentiated hMSCs. Cells lost their morphology because of topo IIβ deficiency, becoming enlarged and flattened. Additionally, a reduction in both neural differentiation efficiency and neurite length, upregulation in RhoA and Rock2, downregulation in Cdc42 gene expression were detected. On the other hand, cells were transfected with topo IIβ gene to elucidate the possible neuroprotective effect of topo IIβ overexpression on neural-induced hMSCs. Topo IIβ overexpression prompted all the cells to exhibit neural cell morphology as characterized by longer neurites. RhoA and Rock2 expressions were downregulated, whereas Cdc42 expression was upregulated. Nurr1 expression level correlated with topo IIβ in both topo IIβ-overexpressed and -silenced cells. Furthermore, differential translocation of Rho-GTPases was detected by immunostaining in response to topo IIβ. Our results suggest that topo IIβ deficiency could give rise to neurodegeneration through dysregulation of Rho-GTPases. However, further in-vivo research is needed to demonstrate if re-regulation of Rho GTPases by topo IIβ overexpression could be a neuroprotective treatment in the case of neurodegenerative diseases.

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

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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.

Recycling signals in the neural crest

OpenAIRE

Taneyhill, Lisa A.; Bronner-Fraser, Marianne E.

2006-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

Recycling signals in the neural crest.

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Taneyhill, Lisa A; Bronner-Fraser, Marianne

2005-01-01

Vertebrate neural crest cells are multipotent and differentiate into structures that include cartilage and the bones of the face, as well as much of the peripheral nervous system. Understanding how different model vertebrates utilize signaling pathways reiteratively during various stages of neural crest formation and differentiation lends insight into human disorders associated with the neural crest.

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

International Nuclear Information System (INIS)

Saini, K. K.; Saini, Sanju

2008-01-01

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.

Astrocytes mediate synapse elimination through MEGF10 and MERTK pathways

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Chung, Won-Suk; Clarke, Laura E.; Wang, Gordon X.; Stafford, Benjamin K.; Sher, Alexander; Chakraborty, Chandrani; Joung, Julia; Foo, Lynette C.; Thompson, Andrew; Chen, Chinfei; Smith, Stephen J.; Barres, Ben A.

2013-12-01

To achieve its precise neural connectivity, the developing mammalian nervous system undergoes extensive activity-dependent synapse remodelling. Recently, microglial cells have been shown to be responsible for a portion of synaptic pruning, but the remaining mechanisms remain unknown. Here we report a new role for astrocytes in actively engulfing central nervous system synapses. This process helps to mediate synapse elimination, requires the MEGF10 and MERTK phagocytic pathways, and is strongly dependent on neuronal activity. Developing mice deficient in both astrocyte pathways fail to refine their retinogeniculate connections normally and retain excess functional synapses. Finally, we show that in the adult mouse brain, astrocytes continuously engulf both excitatory and inhibitory synapses. These studies reveal a novel role for astrocytes in mediating synapse elimination in the developing and adult brain, identify MEGF10 and MERTK as critical proteins in the synapse remodelling underlying neural circuit refinement, and have important implications for understanding learning and memory as well as neurological disease processes.

Study on algorithm of process neural network for soft sensing in sewage disposal system

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Liu, Zaiwen; Xue, Hong; Wang, Xiaoyi; Yang, Bin; Lu, Siying

2006-11-01

A new method of soft sensing based on process neural network (PNN) for sewage disposal system is represented in the paper. PNN is an extension of traditional neural network, in which the inputs and outputs are time-variation. An aggregation operator is introduced to process neuron, and it makes the neuron network has the ability to deal with the information of space-time two dimensions at the same time, so the data processing enginery of biological neuron is imitated better than traditional neuron. Process neural network with the structure of three layers in which hidden layer is process neuron and input and output are common neurons for soft sensing is discussed. The intelligent soft sensing based on PNN may be used to fulfill measurement of the effluent BOD (Biochemical Oxygen Demand) from sewage disposal system, and a good training result of soft sensing was obtained by the method.

Breakout Prediction Based on BP Neural Network in Continuous Casting Process

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Zhang Ben-guo

2016-01-01

Full Text Available An improved BP neural network model was presented by modifying the learning algorithm of the traditional BP neural network, based on the Levenberg-Marquardt algorithm, and was applied to the breakout prediction system in the continuous casting process. The results showed that the accuracy rate of the model for the temperature pattern of sticking breakout was 96.43%, and the quote rate was 100%, that verified the feasibility of the model.

Engaged listeners: shared neural processing of powerful political speeches.

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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.

Models of neural dynamics in brain information processing - the developments of 'the decade'

International Nuclear Information System (INIS)

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

2002-01-01

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

Harmonics added to a flickering light can upset the balance between ON and OFF pathways to produce illusory colors.

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Rider, Andrew T; Henning, G Bruce; Eskew, Rhea T; Stockman, Andrew

2018-04-24

The neural signals generated by the light-sensitive photoreceptors in the human eye are substantially processed and recoded in the retina before being transmitted to the brain via the optic nerve. A key aspect of this recoding is the splitting of the signals within the two major cone-driven visual pathways into distinct ON and OFF branches that transmit information about increases and decreases in the neural signal around its mean level. While this separation is clearly important physiologically, its effect on perception is unclear. We have developed a model of the ON and OFF pathways in early color processing. Using this model as a guide, we can produce imbalances in the ON and OFF pathways by changing the shapes of time-varying stimulus waveforms and thus make reliable and predictable alterations to the perceived average color of the stimulus-although the physical mean of the waveforms does not change. The key components in the model are the early half-wave rectifying synapses that split retinal photoreceptor outputs into the ON and OFF pathways and later sigmoidal nonlinearities in each pathway. The ability to systematically vary the waveforms to change a perceptual quality by changing the balance of signals between the ON and OFF visual pathways provides a powerful psychophysical tool for disentangling and investigating the neural workings of human vision. Copyright © 2018 the Author(s). Published by PNAS.

Psychological Processing in Chronic Pain: A Neural Systems Approach

OpenAIRE

Simons, Laura; Elman, Igor; Borsook, David

2013-01-01

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 implementati...

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

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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.

USC orthogonal multiprocessor for image processing with neural networks

Science.gov (United States)

Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

1990-07-01

This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

Modeling of an industrial drying process by artificial neural networks

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E. Assidjo

2008-09-01

Full Text Available A suitable method is needed to solve the nonquality problem in the grated coconut industry due to the poor control of product humidity during the process. In this study the possibility of using an artificial neural network (ANN, precisely a Multilayer Perceptron, for modeling the drying step of the production of grated coconut process is highlighted. Drying must confer to the product a final moisture of 3%. Unfortunately, under industrial conditions, this moisture varies from 1.9 to 4.8 %. In order to control this parameter and consequently reduce the proportion of the product that does not meet the humidity specification, a 9-4-1 neural network architecture was established using data gathered from an industrial plant. This Multilayer Perceptron can satisfactorily model the process with less bias, ranging from -0.35 to 0.34%, and can reduce the rate of rejected products from 92% to 3% during the first cycle of drying.

Theory of Neural Information Processing Systems

International Nuclear Information System (INIS)

Galla, Tobias

2006-01-01

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 10 11 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, Kuehn 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

Effects of alexithymia and empathy on the neural processing of social and monetary rewards.

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Goerlich, Katharina Sophia; Votinov, Mikhail; Lammertz, Sarah E; Winkler, Lina; Spreckelmeyer, Katja N; Habel, Ute; Gründer, Gerhard; Gossen, Anna

2017-07-01

Empathy has been found to affect the neural processing of social and monetary rewards. Alexithymia, a subclinical condition showing a close inverse relationship with empathy is linked to dysfunctions of socio-emotional processing in the brain. Whether alexithymia alters the neural processing of rewards, which is currently unknown. Here, we investigated the influence of both alexithymia and empathy on reward processing using a social incentive delay (SID) task and a monetary incentive delay (MID) task in 45 healthy men undergoing functional magnetic resonance imaging. Controlling for temperament-character dimensions and rejection sensitivity, the relationship of alexithymia and empathy with neural activity in several a priori regions of interest (ROIs) was examined by means of partial correlations, while participants anticipated and received social and monetary rewards. Results were considered significant if they survived Holm-Bonferroni correction for multiple comparisons. Alexithymia modulated neural activity in several ROIs of the emotion and reward network, both during the anticipation of social and monetary rewards and in response to the receipt of monetary rewards. In contrast, empathy did not affect reward anticipation and modulated ROI activity only in response to the receipt of social rewards. These results indicate a significant influence of alexithymia on the processing of social and monetary rewards in the healthy brain.

The neural subjective frame: from bodily signals to perceptual consciousness.

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Park, Hyeong-Dong; Tallon-Baudry, Catherine

2014-05-05

The report 'I saw the stimulus' operationally defines visual consciousness, but where does the 'I' come from? To account for the subjective dimension of perceptual experience, we introduce the concept of the neural subjective frame. The neural subjective frame would be based on the constantly updated neural maps of the internal state of the body and constitute a neural referential from which first person experience can be created. We propose to root the neural subjective frame in the neural representation of visceral information which is transmitted through multiple anatomical pathways to a number of target sites, including posterior insula, ventral anterior cingulate cortex, amygdala and somatosensory cortex. We review existing experimental evidence showing that the processing of external stimuli can interact with visceral function. The neural subjective frame is a low-level building block of subjective experience which is not explicitly experienced by itself which is necessary but not sufficient for perceptual experience. It could also underlie other types of subjective experiences such as self-consciousness and emotional feelings. Because the neural subjective frame is tightly linked to homeostatic regulations involved in vigilance, it could also make a link between state and content consciousness.

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

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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

CHD8 regulates neurodevelopmental pathways associated with autism spectrum disorder in neural progenitors

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Sugathan, Aarathi; Biagioli, Marta; Golzio, Christelle; Erdin, Serkan; Blumenthal, Ian; Manavalan, Poornima; Ragavendran, Ashok; Brand, Harrison; Lucente, Diane; Miles, Judith; Sheridan, Steven D.; Stortchevoi, Alexei; Kellis, Manolis; Haggarty, Stephen J.; Katsanis, Nicholas; Gusella, James F.; Talkowski, Michael E.

2014-01-01

Truncating mutations of chromodomain helicase DNA-binding protein 8 (CHD8), and of many other genes with diverse functions, are strong-effect risk factors for autism spectrum disorder (ASD), suggesting multiple mechanisms of pathogenesis. We explored the transcriptional networks that CHD8 regulates in neural progenitor cells (NPCs) by reducing its expression and then integrating transcriptome sequencing (RNA sequencing) with genome-wide CHD8 binding (ChIP sequencing). Suppressing CHD8 to levels comparable with the loss of a single allele caused altered expression of 1,756 genes, 64.9% of which were up-regulated. CHD8 showed widespread binding to chromatin, with 7,324 replicated sites that marked 5,658 genes. Integration of these data suggests that a limited array of direct regulatory effects of CHD8 produced a much larger network of secondary expression changes. Genes indirectly down-regulated (i.e., without CHD8-binding sites) reflect pathways involved in brain development, including synapse formation, neuron differentiation, cell adhesion, and axon guidance, whereas CHD8-bound genes are strongly associated with chromatin modification and transcriptional regulation. Genes associated with ASD were strongly enriched among indirectly down-regulated loci (P neurodevelopmental pathways in which many ASD-associated genes may converge on shared mechanisms of pathogenesis. PMID:25294932

Requirement of mouse BCCIP for neural development and progenitor proliferation.

Directory of Open Access Journals (Sweden)

Yi-Yuan Huang

Full Text Available Multiple DNA repair pathways are involved in the orderly development of neural systems at distinct stages. The homologous recombination (HR pathway is required to resolve stalled replication forks and critical for the proliferation of progenitor cells during neural development. BCCIP is a BRCA2 and CDKN1A interacting protein implicated in HR and inhibition of DNA replication stress. In this study, we determined the role of BCCIP in neural development using a conditional BCCIP knock-down mouse model. BCCIP deficiency impaired embryonic and postnatal neural development, causing severe ataxia, cerebral and cerebellar defects, and microcephaly. These development defects are associated with spontaneous DNA damage and subsequent cell death in the proliferative cell populations of the neural system during embryogenesis. With in vitro neural spheroid cultures, BCCIP deficiency impaired neural progenitor's self-renewal capability, and spontaneously activated p53. These data suggest that BCCIP and its anti-replication stress functions are essential for normal neural development by maintaining an orderly proliferation of neural progenitors.

Neural processing of emotional-intensity predicts emotion regulation choice.

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Shafir, Roni; Thiruchselvam, Ravi; Suri, Gaurav; Gross, James J; Sheppes, Gal

2016-12-01

Emotional-intensity is a core characteristic of affective events that strongly determines how individuals choose to regulate their emotions. Our conceptual framework suggests that in high emotional-intensity situations, individuals prefer to disengage attention using distraction, which can more effectively block highly potent emotional information, as compared with engagement reappraisal, which is preferred in low emotional-intensity. However, existing supporting evidence remains indirect because prior intensity categorization of emotional stimuli was based on subjective measures that are potentially biased and only represent the endpoint of emotional-intensity processing. Accordingly, this study provides the first direct evidence for the role of online emotional-intensity processing in predicting behavioral regulatory-choices. Utilizing the high temporal resolution of event-related potentials, we evaluated online neural processing of stimuli's emotional-intensity (late positive potential, LPP) prior to regulatory-choices between distraction and reappraisal. Results showed that enhanced neural processing of intensity (enhanced LPP amplitudes) uniquely predicted (above subjective measures of intensity) increased tendency to subsequently choose distraction over reappraisal. Additionally, regulatory-choices led to adaptive consequences, demonstrated in finding that actual implementation of distraction relative to reappraisal-choice resulted in stronger attenuation of LPPs and self-reported arousal. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A fuzzy art neural network based color image processing and ...

African Journals Online (AJOL)

To improve the learning process from the input data, a new learning rule was suggested. In this paper, a new method is proposed to deal with the RGB color image pixels, which enables a Fuzzy ART neural network to process the RGB color images. The application of the algorithm was implemented and tested on a set of ...

Noradrenergic modulation of neural erotic stimulus perception.

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Graf, Heiko; Wiegers, Maike; Metzger, Coraline Danielle; Walter, Martin; Grön, Georg; Abler, Birgit

2017-09-01

We recently investigated neuromodulatory effects of the noradrenergic agent reboxetine and the dopamine receptor affine amisulpride in healthy subjects on dynamic erotic stimulus processing. Whereas amisulpride left sexual functions and neural activations unimpaired, we observed detrimental activations under reboxetine within the caudate nucleus corresponding to motivational components of sexual behavior. However, broadly impaired subjective sexual functioning under reboxetine suggested effects on further neural components. We now investigated the same sample under these two agents with static erotic picture stimulation as alternative stimulus presentation mode to potentially observe further neural treatment effects of reboxetine. 19 healthy males were investigated under reboxetine, amisulpride and placebo for 7 days each within a double-blind cross-over design. During fMRI static erotic picture were presented with preceding anticipation periods. Subjective sexual functions were assessed by a self-reported questionnaire. Neural activations were attenuated within the caudate nucleus, putamen, ventral striatum, the pregenual and anterior midcingulate cortex and in the orbitofrontal cortex under reboxetine. Subjective diminished sexual arousal under reboxetine was correlated with attenuated neural reactivity within the posterior insula. Again, amisulpride left neural activations along with subjective sexual functioning unimpaired. Neither reboxetine nor amisulpride altered differential neural activations during anticipation of erotic stimuli. Our results verified detrimental effects of noradrenergic agents on neural motivational but also emotional and autonomic components of sexual behavior. Considering the overlap of neural network alterations with those evoked by serotonergic agents, our results suggest similar neuromodulatory effects of serotonergic and noradrenergic agents on common neural pathways relevant for sexual behavior. Copyright © 2017 Elsevier B.V. and

Dissociated neural processing for decisions in managers and non-managers.

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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.

Autism as an adaptive common variant pathway for human brain development.

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Johnson, Mark H

2017-06-01

While research on focal perinatal lesions has provided evidence for recovery of function, much less is known about processes of brain adaptation resulting from mild but widespread disturbances to neural processing over the early years (such as alterations in synaptic efficiency). Rather than being viewed as a direct behavioral consequence of life-long neural dysfunction, I propose that autism is best viewed as the end result of engaging adaptive processes during a sensitive period. From this perspective, autism is not appropriately described as a disorder of neurodevelopment, but rather as an adaptive common variant pathway of human functional brain development. Copyright © 2017 The Author. Published by Elsevier Ltd.. All rights reserved.

Adaptive model predictive process control using neural networks

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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.

Neural networks in front-end processing and control

International Nuclear Information System (INIS)

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

1992-01-01

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

Neural networks in front-end processing and control

International Nuclear Information System (INIS)

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

1991-07-01

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 we 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. We also briefly discuss the use of the Multi-Layer Perceptron as a non-linear controller in a feedback loop. We 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. We also present some of the difficulties encountered in applying these networks. (author) 13 figs., 9 refs

Neural dynamics of motion processing and speed discrimination.

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Chey, J; Grossberg, S; Mingolla, E

1998-09-01

A neural network model of visual motion perception and speed discrimination is presented. The model shows how a distributed population code of speed tuning, that realizes a size-speed correlation, can be derived from the simplest mechanisms whereby activations of multiple spatially short-range filters of different size are transformed into speed-turned cell responses. These mechanisms use transient cell responses to moving stimuli, output thresholds that covary with filter size, and competition. These mechanisms are proposed to occur in the V1-->MT cortical processing stream. The model reproduces empirically derived speed discrimination curves and simulates data showing how visual speed perception and discrimination can be affected by stimulus contrast, duration, dot density and spatial frequency. Model motion mechanisms are analogous to mechanisms that have been used to model 3-D form and figure-ground perception. The model forms the front end of a larger motion processing system that has been used to simulate how global motion capture occurs, and how spatial attention is drawn to moving forms. It provides a computational foundation for an emerging neural theory of 3-D form and motion perception.

A central neural circuit for itch sensation.

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Mu, Di; Deng, Juan; Liu, Ke-Fei; Wu, Zhen-Yu; Shi, Yu-Feng; Guo, Wei-Min; Mao, Qun-Quan; Liu, Xing-Jun; Li, Hui; Sun, Yan-Gang

2017-08-18

Although itch sensation is an important protective mechanism for animals, chronic itch remains a challenging clinical problem. Itch processing has been studied extensively at the spinal level. However, how itch information is transmitted to the brain and what central circuits underlie the itch-induced scratching behavior remain largely unknown. We found that the spinoparabrachial pathway was activated during itch processing and that optogenetic suppression of this pathway impaired itch-induced scratching behaviors. Itch-mediating spinal neurons, which express the gastrin-releasing peptide receptor, are disynaptically connected to the parabrachial nucleus via glutamatergic spinal projection neurons. Blockade of synaptic output of glutamatergic neurons in the parabrachial nucleus suppressed pruritogen-induced scratching behavior. Thus, our studies reveal a central neural circuit that is critical for itch signal processing. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Can Intrinsic Fluctuations Increase Efficiency in Neural Information Processing?

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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.

Neural processing of speech in children is influenced by bilingual experience

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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

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

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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

Filtering and spectral processing of 1-D signals using cellular neural networks

NARCIS (Netherlands)

Moreira-Tamayo, O.; Pineda de Gyvez, J.

1996-01-01

This paper presents cellular neural networks (CNN) for one-dimensional discrete signal processing. Although CNN has been extensively used in image processing applications, little has been done for 1-dimensional signal processing. We propose a novel CNN architecture to carry out these tasks. This

Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

1992-01-01

This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

AKT signaling displays multifaceted functions in neural crest development.

Science.gov (United States)

Sittewelle, Méghane; Monsoro-Burq, Anne H

2018-05-31

AKT signaling is an essential intracellular pathway controlling cell homeostasis, cell proliferation and survival, as well as cell migration and differentiation in adults. Alterations impacting the AKT pathway are involved in many pathological conditions in human disease. Similarly, during development, multiple transmembrane molecules, such as FGF receptors, PDGF receptors or integrins, activate AKT to control embryonic cell proliferation, migration, differentiation, and also cell fate decisions. While many studies in mouse embryos have clearly implicated AKT signaling in the differentiation of several neural crest derivatives, information on AKT functions during the earliest steps of neural crest development had remained relatively scarce until recently. However, recent studies on known and novel regulators of AKT signaling demonstrate that this pathway plays critical roles throughout the development of neural crest progenitors. Non-mammalian models such as fish and frog embryos have been instrumental to our understanding of AKT functions in neural crest development, both in neural crest progenitors and in the neighboring tissues. This review combines current knowledge acquired from all these different vertebrate animal models to describe the various roles of AKT signaling related to neural crest development in vivo. We first describe the importance of AKT signaling in patterning the tissues involved in neural crest induction, namely the dorsal mesoderm and the ectoderm. We then focus on AKT signaling functions in neural crest migration and differentiation. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural activity, neural connectivity, and the processing of emotionally valenced information in older adults: links with life satisfaction.

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Waldinger, Robert J; Kensinger, Elizabeth A; Schulz, Marc S

2011-09-01

This study examines whether differences in late-life well-being are linked to how older adults encode emotionally valenced information. Using fMRI with 39 older adults varying in life satisfaction, we examined how viewing positive and negative images would affect activation and connectivity of an emotion-processing network. Participants engaged most regions within this network more robustly for positive than for negative images, but within the PFC this effect was moderated by life satisfaction, with individuals higher in satisfaction showing lower levels of activity during the processing of positive images. Participants high in satisfaction showed stronger correlations among network regions-particularly between the amygdala and other emotion processing regions-when viewing positive, as compared with negative, images. Participants low in satisfaction showed no valence effect. Findings suggest that late-life satisfaction is linked with how emotion-processing regions are engaged and connected during processing of valenced information. This first demonstration of a link between neural recruitment and late-life well-being suggests that differences in neural network activation and connectivity may account for the preferential encoding of positive information seen in some older adults.

Vicarious neural processing of outcomes during observational learning.

Directory of Open Access Journals (Sweden)

Elisabetta Monfardini

Full Text Available 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.

Vicarious neural processing of outcomes during observational learning.

Science.gov (United States)

Monfardini, Elisabetta; Gazzola, Valeria; Boussaoud, Driss; Brovelli, Andrea; Keysers, Christian; Wicker, Bruno

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).

Neural mechanisms of context-dependent processing of CO2 avoidance behavior in fruit flies.

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Siju, K P; Bräcker, Lasse B; Grunwald Kadow, I C

2014-01-01

The fruit fly, Drosophila melanogaster, innately avoids even low levels of CO2. CO2 is part of the so-called Drosophila stress odor produced by stressed flies, but also a byproduct of fermenting fruit, a main food source, making the strong avoidance behavior somewhat surprising. Therefore, we addressed whether feeding states might influence the fly's behavior and processing of CO2. In a recent report, we showed that this innate behavior is differentially processed and modified according to the feeding state of the fly. Interestingly, we found that hungry flies require the function of the mushroom body, a higher brain center required for olfactory learning and memory, but thought to be dispensable for innate olfactory behaviors. In addition, we anatomically and functionally characterized a novel bilateral projection neuron connecting the CO2 sensory input to the mushroom body. This neuron was essential for processing of CO2 in the starved fly but not in the fed fly. In this Extra View article, we provide evidence for the potential involvement of the neuromodulator dopamine in state-dependent CO2 avoidance behavior. Taken together, our work demonstrates that CO2 avoidance behavior is mediated by alternative neural pathways in a context-dependent manner. Furthermore, it shows that the mushroom body is not only involved in processing of learned olfactory behavior, as previously suggested, but also in context-dependent innate olfaction.

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

Science.gov (United States)

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. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Statistical process control using optimized neural networks: a case study.

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Addeh, Jalil; Ebrahimzadeh, Ata; Azarbad, Milad; Ranaee, Vahid

2014-09-01

The most common statistical process control (SPC) tools employed for monitoring process changes are control charts. A control chart demonstrates that the process has altered by generating an out-of-control signal. This study investigates the design of an accurate system for the control chart patterns (CCPs) recognition in two aspects. First, an efficient system is introduced that includes two main modules: feature extraction module and classifier module. In the feature extraction module, a proper set of shape features and statistical feature are proposed as the efficient characteristics of the patterns. In the classifier module, several neural networks, such as multilayer perceptron, probabilistic neural network and radial basis function are investigated. Based on an experimental study, the best classifier is chosen in order to recognize the CCPs. Second, a hybrid heuristic recognition system is introduced based on cuckoo optimization algorithm (COA) algorithm to improve the generalization performance of the classifier. The simulation results show that the proposed algorithm has high recognition accuracy. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Using the artificial neural network to control the steam turbine heating process

International Nuclear Information System (INIS)

Nowak, Grzegorz; Rusin, Andrzej

2016-01-01

Highlights: • Inverse Artificial Neural Network has a potential to control the start-up process of a steam turbine. • Two serial neural networks made it possible to model the rotor stress based of steam parameters. • An ANN with feedback enables transient stress modelling with good accuracy. - Abstract: Due to the significant share of renewable energy sources (RES) – wind farms in particular – in the power sector of many countries, power generation systems become sensitive to variable weather conditions. Under unfavourable changes in weather, ensuring required energy supplies involves hasty start-ups of conventional steam power units whose operation should be characterized by higher and higher flexibility. Controlling the process of power engineering machinery operation requires fast predictive models that will make it possible to analyse many parallel scenarios and select the most favourable one. This approach is employed by the algorithm for the inverse neural network control presented in this paper. Based on the current thermal state of the turbine casing, the algorithm controls the steam temperature at the turbine inlet to keep both the start-up rate and the safety of the machine at the allowable level. The method used herein is based on two artificial neural networks (ANN) working in series.

Dissociated neural processing for decisions in managers and non-managers.

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Svenja Caspers

Full Text Available 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.

Neural markers of opposite-sex bias in face processing

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Alice Mado eProverbio

2010-10-01

Full Text Available Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (ORE; Caldara et al., 2004, little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women who were engaged in a secondary perceptual task (landscape detection. The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP to same-sex faces. Analysis of intra-cortical neural generators (swLORETA showed that facial processing-related (FG, BA37, BA20/21 and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24 had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

Neural markers of opposite-sex bias in face processing.

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Proverbio, Alice Mado; Riva, Federica; Martin, Eleonora; Zani, Alberto

2010-01-01

Some behavioral and neuroimaging studies suggest that adults prefer to view attractive faces of the opposite sex more than attractive faces of the same sex. However, unlike the other-race face effect (Caldara et al., 2004), little is known regarding the existence of an opposite-/same-sex bias in face processing. In this study, the faces of 130 attractive male and female adults were foveally presented to 40 heterosexual university students (20 men and 20 women) who were engaged in a secondary perceptual task (landscape detection). The automatic processing of face gender was investigated by recording ERPs from 128 scalp sites. Neural markers of opposite- vs. same-sex bias in face processing included larger and earlier centro-parietal N400s in response to faces of the opposite sex and a larger late positivity (LP) to same-sex faces. Analysis of intra-cortical neural generators (swLORETA) showed that facial processing-related (FG, BA37, BA20/21) and emotion-related brain areas (the right parahippocampal gyrus, BA35; uncus, BA36/38; and the cingulate gyrus, BA24) had higher activations in response to opposite- than same-sex faces. The results of this analysis, along with data obtained from ERP recordings, support the hypothesis that both genders process opposite-sex faces differently than same-sex faces. The data also suggest a hemispheric asymmetry in the processing of opposite-/same-sex faces, with the right hemisphere involved in processing same-sex faces and the left hemisphere involved in processing faces of the opposite sex. The data support previous literature suggesting a right lateralization for the representation of self-image and body awareness.

Nicotine Withdrawal Induces Neural Deficits in Reward Processing.

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Oliver, Jason A; Evans, David E; Addicott, Merideth A; Potts, Geoffrey F; Brandon, Thomas H; Drobes, David J

2017-06-01

Nicotine withdrawal reduces neurobiological responses to nonsmoking rewards. Insight into these reward deficits could inform the development of targeted interventions. This study examined the effect of withdrawal on neural and behavioral responses during a reward prediction task. Smokers (N = 48) attended two laboratory sessions following overnight abstinence. Withdrawal was manipulated by having participants smoke three regular nicotine (0.6 mg yield; satiation) or very low nicotine (0.05 mg yield; withdrawal) cigarettes. Electrophysiological recordings of neural activity were obtained while participants completed a reward prediction task that involved viewing four combinations of predictive and reward-determining stimuli: (1) Unexpected Reward; (2) Predicted Reward; (3) Predicted Punishment; (4) Unexpected Punishment. The task evokes a medial frontal negativity that mimics the phasic pattern of dopaminergic firing in ventral tegmental regions associated with reward prediction errors. Nicotine withdrawal decreased the amplitude of the medial frontal negativity equally across all trial types (p nicotine dependence (p Nicotine withdrawal had equivocal impact across trial types, suggesting reward processing deficits are unlikely to stem from changes in phasic dopaminergic activity during prediction errors. Effects on tonic activity may be more pronounced. Pharmacological interventions directly targeting the dopamine system and behavioral interventions designed to increase reward motivation and responsiveness (eg, behavioral activation) may aid in mitigating withdrawal symptoms and potentially improving smoking cessation outcomes. Findings from this study indicate nicotine withdrawal impacts reward processing signals that are observable in smokers' neural activity. This may play a role in the subjective aversive experience of nicotine withdrawal and potentially contribute to smoking relapse. Interventions that address abnormal responding to both pleasant and

Neural signal processing for identifying failed fuel rods in nuclear reactors

International Nuclear Information System (INIS)

Seixas, Jose M. de; Soares Filho, William; Pereira, Wagner C.A.; Teles, Claudio C.B.

2002-01-01

Ultrasonic pulses were used for automatic detection of failed nuclear fuel rods. For experimental tests of the proposed method, an assembly prototype of 16 x 16 rods was built by using genuine rods but without fuel inside (just air). Some rods were partially filled with water to simulate cracked rods. Using neural signal processing on the received echoes of the emitted ultrasonic pulses, a detection efficiency of 97% was obtained. Neural detection is shown to outperform other classical discriminating methods and can also reveal important features of the signal structure of the received echoes. (author)

Glucagon-like peptide-1 reduces pancreatic β-cell mass through hypothalamic neural pathways in high-fat diet-induced obese rats.

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Ando, Hisae; Gotoh, Koro; Fujiwara, Kansuke; Anai, Manabu; Chiba, Seiichi; Masaki, Takayuki; Kakuma, Tetsuya; Shibata, Hirotaka

2017-07-17

We examined whether glucagon-like peptide-1 (GLP-1) affects β-cell mass and proliferation through neural pathways, from hepatic afferent nerves to pancreatic efferent nerves via the central nervous system, in high-fat diet (HFD)-induced obese rats. The effects of chronic administration of GLP-1 (7-36) and liraglutide, a GLP-1 receptor agonist, on pancreatic morphological alterations, c-fos expression and brain-derived neurotrophic factor (BDNF) content in the hypothalamus, and glucose metabolism were investigated in HFD-induced obese rats that underwent hepatic afferent vagotomy (VgX) and/or pancreatic efferent sympathectomy (SpX). Chronic GLP-1 (7-36) administration to HFD-induced obese rats elevated c-fos expression and BDNF content in the hypothalamus, followed by a reduction in pancreatic β-cell hyperplasia and insulin content, thus resulting in improved glucose tolerance. These responses were abolished by VgX and SpX. Moreover, administration of liraglutide similarly activated the hypothalamic neural pathways, thus resulting in a more profound amelioration of glucose tolerance than native GLP-1 (7-36). These data suggest that GLP-1 normalizes the obesity-induced compensatory increase in β-cell mass and glucose intolerance through a neuronal relay system consisting of hepatic afferent nerves, the hypothalamus, and pancreatic efferent nerves.

Neural Mechanisms and Information Processing in Recognition Systems

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Mamiko Ozaki

2014-10-01

Full Text Available 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.

The Neural Basis of Vocal Pitch Imitation in Humans.

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Belyk, Michel; Pfordresher, Peter Q; Liotti, Mario; Brown, Steven

2016-04-01

Vocal imitation is a phenotype that is unique to humans among all primate species, and so an understanding of its neural basis is critical in explaining the emergence of both speech and song in human evolution. Two principal neural models of vocal imitation have emerged from a consideration of nonhuman animals. One hypothesis suggests that putative mirror neurons in the inferior frontal gyrus pars opercularis of Broca's area may be important for imitation. An alternative hypothesis derived from the study of songbirds suggests that the corticostriate motor pathway performs sensorimotor processes that are specific to vocal imitation. Using fMRI with a sparse event-related sampling design, we investigated the neural basis of vocal imitation in humans by comparing imitative vocal production of pitch sequences with both nonimitative vocal production and pitch discrimination. The strongest difference between these tasks was found in the putamen bilaterally, providing a striking parallel to the role of the analogous region in songbirds. Other areas preferentially activated during imitation included the orofacial motor cortex, Rolandic operculum, and SMA, which together outline the corticostriate motor loop. No differences were seen in the inferior frontal gyrus. The corticostriate system thus appears to be the central pathway for vocal imitation in humans, as predicted from an analogy with songbirds.

Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches

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Manjunath Patel Gowdru Chandrashekarappa

2014-01-01

Full Text Available The present research work is focussed to develop an intelligent system to establish the input-output relationship utilizing forward and reverse mappings of artificial neural networks. Forward mapping aims at predicting the density and secondary dendrite arm spacing (SDAS from the known set of squeeze cast process parameters such as time delay, pressure duration, squeezes pressure, pouring temperature, and die temperature. An attempt is also made to meet the industrial requirements of developing the reverse model to predict the recommended squeeze cast parameters for the desired density and SDAS. Two different neural network based approaches have been proposed to carry out the said task, namely, back propagation neural network (BPNN and genetic algorithm neural network (GA-NN. The batch mode of training is employed for both supervised learning networks and requires huge training data. The requirement of huge training data is generated artificially at random using regression equation derived through real experiments carried out earlier by the same authors. The performances of BPNN and GA-NN models are compared among themselves with those of regression for ten test cases. The results show that both models are capable of making better predictions and the models can be effectively used in shop floor in selection of most influential parameters for the desired outputs.

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

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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

Serotonin, neural markers and memory

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Alfredo eMeneses

2015-07-01

Full Text Available Diverse neuropsychiatric disorders present dysfunctional memory and no effective treatment exits for them; likely as result of the absence of neural markers associated to memory. Neurotransmitter systems and signaling pathways have been implicated in memory and dysfunctional memory; however, their role is poorly understood. Hence, neural markers and cerebral functions and dysfunctions are revised. To our knowledge no previous systematic works have been published addressing these issues. The interactions among behavioral tasks, control groups and molecular changes and/or pharmacological effects are mentioned. Neurotransmitter receptors and signaling pathways, during normal and abnormally functioning memory with an emphasis on the behavioral aspects of memory are revised. With focus on serotonin, since as it is a well characterized neurotransmitter, with multiple pharmacological tools, and well characterized downstream signaling in mammals’ species. 5-HT1A, 5-HT4, 5-HT5, 5-HT6 and 5-HT7 receptors as well as SERT (serotonin transporter seem to be useful neural markers and/or therapeutic targets. Certainly, if the mentioned evidence is replicated, then the translatability from preclinical and clinical studies to neural changes might be confirmed. Hypothesis and theories might provide appropriate limits and perspectives of evidence

Neural correlates of eating disorders: translational potential

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McAdams CJ

2015-09-01

Full Text Available Carrie J McAdams,1,2 Whitney Smith1 1University of Texas at Southwestern Medical Center, 2Department of Psychiatry, Texas Health Presbyterian Hospital of Dallas, Dallas, TX, USA Abstract: Eating disorders are complex and serious psychiatric illnesses whose etiology includes psychological, biological, and social factors. Treatment of eating disorders is challenging as there are few evidence-based treatments and limited understanding of the mechanisms that result in sustained recovery. In the last 20 years, we have begun to identify neural pathways that are altered in eating disorders. Consideration of how these pathways may contribute to an eating disorder can provide an understanding of expected responses to treatments. Eating disorder behaviors include restrictive eating, compulsive overeating, and purging behaviors after eating. Eating disorders are associated with changes in many neural systems. In this targeted review, we focus on three cognitive processes associated with neurocircuitry differences in subjects with eating disorders such as reward, decision-making, and social behavior. We briefly examine how each of these systems function in healthy people, using Neurosynth meta-analysis to identify key regions commonly implicated in these circuits. We review the evidence for disruptions of these regions and systems in eating disorders. Finally, we describe psychiatric and psychological treatments that are likely to function by impacting these regions. Keywords: anorexia nervosa, bulimia nervosa, social cognition, reward processing, decision-making

Neural Substrates for Processing Task-Irrelevant Sad Images in Adolescents

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Wang, Lihong; Huettel, Scott; De Bellis, Michael D.

2008-01-01

Neural systems related to cognitive and emotional processing were examined in adolescents using event-related functional magnetic resonance imaging (fMRI). Ten healthy adolescents performed an emotional oddball task. Subjects detected infrequent circles (targets) within a continual stream of phase-scrambled images (standards). Sad and neutral…

Use of neural networks in process engineering. Thermodynamics, diffusion, and process control and simulation applications

International Nuclear Information System (INIS)

Otero, F

1998-01-01

This article presents the current status of the use of Artificial Neural Networks (ANNs) in process engineering applications where common mathematical methods do not completely represent the behavior shown by experimental observations, results, and plant operating data. Three examples of the use of ANNs in typical process engineering applications such as prediction of activity in solvent-polymer binary systems, prediction of a surfactant self-diffusion coefficient of micellar systems, and process control and simulation are shown. These examples are important for polymerization applications, enhanced-oil recovery, and automatic process control

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

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Chao Wang

Full Text Available It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs were identified: 1 A left-frontotemporal negativity (250-700 ms that was positively associated with word-reading performance; 2 a midline-frontal negativity (450-800 ms that was positively associated with color-naming and incongruent performance; 3 a left-frontal negativity (450-800 ms that was positively associated with switch trial performance; and 4 a centroparietal positivity (450-800 ms that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1 domain-specific task facilitation; 2 switch-specific task-set reconfiguration; 3 preparation for response conflict; and 4 proactive attentional control. Examining the relationship between ERPs and behavioral

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

Science.gov (United States)

Wang, Chao; Ding, Mingzhou; Kluger, Benzi M

2015-01-01

It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral

Neural Adaptation Effects in Conceptual Processing

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Barbara F. M. Marino

2015-07-01

Full Text Available 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.

Neural networks

International Nuclear Information System (INIS)

Denby, Bruce; Lindsey, Clark; Lyons, Louis

1992-01-01

The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

Overexpression of miR‑21 promotes neural stem cell proliferation and neural differentiation via the Wnt/β‑catenin signaling pathway in vitro.

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Zhang, Wei-Min; Zhang, Zhi-Ren; Yang, Xi-Tao; Zhang, Yong-Gang; Gao, Yan-Sheng

2018-01-01

The primary aim of the present study was to examine the effects of microRNA‑21 (miR‑21) on the proliferation and differentiation of rat primary neural stem cells (NSCs) in vitro. miR‑21 was overexpressed in NSCs by transfection with a miR‑21 mimic. The effects of miR‑21 overexpression on NSC proliferation were revealed by Cell Counting kit 8 and 5‑ethynyl‑2'‑deoxyuridine incorporation assay, and miR‑21 overexpression was revealed to increase NSC proliferation. miR‑21 overexpression was confirmed using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR). mRNA and protein expression levels of key molecules (β‑catenin, cyclin D1, p21 and miR‑21) in the Wnt/β‑catenin signaling pathway were studied by RT‑qPCR and western blot analysis. RT‑qPCR and western blot analyses revealed that miR‑21 overexpression increased β‑catenin and cyclin D1 expression, and decreased p21 expression. These results suggested that miR‑21‑induced increase in proliferation was mediated by activation of the Wnt/β‑catenin signaling pathway, since overexpression of miR‑21 increased β‑catenin and cyclin D1 expression and reduced p21 expression. Furthermore, inhibition of the Wnt/β‑catenin pathway with FH535 attenuated the influence of miR‑21 overexpression on NSC proliferation, indicating that the factors activated by miR‑21 overexpression were inhibited by FH535 treatment. Furthermore, overexpression of miR‑21 enhanced the differentiation of NSCs into neurons and inhibited their differentiation into astrocytes. The present study indicated that in primary rat NSCs, overexpression of miR‑21 may promote proliferation and differentiation into neurons via the Wnt/β‑catenin signaling pathway in vitro.

A novel joint-processing adaptive nonlinear equalizer using a modular recurrent neural network for chaotic communication systems.

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Zhao, Haiquan; Zeng, Xiangping; Zhang, Jiashu; Liu, Yangguang; Wang, Xiaomin; Li, Tianrui

2011-01-01

To eliminate nonlinear channel distortion in chaotic communication systems, a novel joint-processing adaptive nonlinear equalizer based on a pipelined recurrent neural network (JPRNN) is proposed, using a modified real-time recurrent learning (RTRL) algorithm. Furthermore, an adaptive amplitude RTRL algorithm is adopted to overcome the deteriorating effect introduced by the nesting process. Computer simulations illustrate that the proposed equalizer outperforms the pipelined recurrent neural network (PRNN) and recurrent neural network (RNN) equalizers. Copyright © 2010 Elsevier Ltd. All rights reserved.

Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia.

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Lerner, Yulia; Bleich-Cohen, Maya; Solnik-Knirsh, Shimrit; Yogev-Seligmann, Galit; Eisenstein, Tamir; Madah, Waheed; Shamir, Alon; Hendler, Talma; Kremer, Ilana

2018-01-01

Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia ( N  = 15), their non-manifesting siblings ( N  = 14) and healthy controls ( N  = 15) listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC) approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings - high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale) revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

Abnormal neural hierarchy in processing of verbal information in patients with schizophrenia

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Yulia Lerner

2018-01-01

Full Text Available Previous research indicates abnormal comprehension of verbal information in patients with schizophrenia. Yet the neural mechanism underlying the breakdown of verbal information processing in schizophrenia is poorly understood. Imaging studies in healthy populations have shown a network of brain areas involved in hierarchical processing of verbal information over time. Here, we identified critical aspects of this hierarchy, examining patients with schizophrenia. Using functional magnetic resonance imaging, we examined various levels of information comprehension elicited by naturally presented verbal stimuli; from a set of randomly shuffled words to an intact story. Specifically, patients with first episode schizophrenia (N = 15, their non-manifesting siblings (N = 14 and healthy controls (N = 15 listened to a narrated story and randomly scrambled versions of it. To quantify the degree of dissimilarity between the groups, we adopted an inter-subject correlation (inter-SC approach, which estimates differences in synchronization of neural responses within and between groups. The temporal topography found in healthy and siblings groups were consistent with our previous findings – high synchronization in responses from early sensory toward high order perceptual and cognitive areas. In patients with schizophrenia, stimuli with short and intermediate temporal scales evoked a typical pattern of reliable responses, whereas story condition (long temporal scale revealed robust and widespread disruption of the inter-SCs. In addition, the more similar the neural activity of patients with schizophrenia was to the average response in the healthy group, the less severe the positive symptoms of the patients. Our findings suggest that system-level neural indication of abnormal verbal information processing in schizophrenia reflects disease manifestations.

Exploration of molecular pathways mediating electric field-directed Schwann cell migration by RNA-Seq

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Yao, Li; Li, Yongchao; Knapp, Jennifer; Smith, Peter

2015-01-01

In peripheral nervous systems, Schwann cells wrap around axons of motor and sensory neurons to form the myelin sheath. Following spinal cord injury, Schwann cells regenerate and migrate to the lesion and are involved in the spinal cord regeneration process. Transplantation of Schwann cells into injured neural tissue results in enhanced spinal axonal regeneration. Effective directional migration of Schwann cells is critical in the neural regeneration process. In this study, we report that Schwann cells migrate anodally in an applied electric field (EF). The directedness and displacement of anodal migration increased significantly when the strength of the EF increased from 50 mV/mm to 200 mV/mm. The EF did not significantly affect the cell migration speed. To explore the genes and signaling pathways that regulate cell migration in EFs, we performed a comparative analysis of differential gene expression between cells stimulated with an EF (100 mV/mm) and those without using next-generation RNA sequencing, verified by RT-qPCR. Based on the cut-off criteria (FC > 1.2, q cells versus EF-stimulated cells. A Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis found that compared to the control group, 21 pathways are down-regulated, while 10 pathways are up-regulated. Differentially expressed genes participate in multiple cellular signaling pathways involved in the regulation of cell migration, including pathways of regulation of actin cytoskeleton, focal adhesion, and PI3K-Akt. PMID:25557037

Modeling of an industrial process of pleuromutilin fermentation using feed-forward neural networks

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L. Khaouane

2013-03-01

Full Text Available This work investigates the use of artificial neural networks in modeling an industrial fermentation process of Pleuromutilin produced by Pleurotus mutilus in a fed-batch mode. Three feed-forward neural network models characterized by a similar structure (five neurons in the input layer, one hidden layer and one neuron in the output layer are constructed and optimized with the aim to predict the evolution of three main bioprocess variables: biomass, substrate and product. Results show a good fit between the predicted and experimental values for each model (the root mean squared errors were 0.4624% - 0.1234 g/L and 0.0016 mg/g respectively. Furthermore, the comparison between the optimized models and the unstructured kinetic models in terms of simulation results shows that neural network models gave more significant results. These results encourage further studies to integrate the mathematical formulae extracted from these models into an industrial control loop of the process.

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

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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. Copyright © 2015 the American Physiological Society.

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Neural correlates of attentional and mnemonic processing in event-based prospective memory.

Science.gov (United States)

Knight, Justin B; Ethridge, Lauren E; Marsh, Richard L; Clementz, Brett A

2010-01-01

Prospective memory (PM), or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT), followed by a LDT with an embedded PM component. Event-based cues were constituted by color and lexicality (red words). Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP) revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions.

A Sparse Auto Encoder Deep Process Neural Network Model and its Application

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Xu Shaohua

2017-01-01

Full Text Available Aiming at the problem of time-varying signal pattern classification, a sparse auto-encoder deep process neural network (SAE-DPNN is proposed. The input of SAE-DPNN is time-varying process signal and the output is pattern category. It combines the time-varying signal classification method of process neural network (PNN and the data feature extraction and hierarchical sparse representation mechanism of sparse automatic encoder (SAE. Based on the feedforward PNN model, SAE-DPNN is constructed by stacking the process neurons, SAE network and softmax classifier. It can maintain the time-sequence and structure of the input signal, express and synthesize the process distribution characteristics of multidimensional time-varying signals and their combinations. SAE-DPNN improves the identification of complex features and distinguishes between different types of signals, realizes the direct classification of time-varying signals. In this paper, the feature extraction and representation mechanism of time-varying signal in SAE-DPNN are analyzed, and a specific learning algorithm is given. The experimental results verify the effectiveness of the model and algorithm.

Neural Correlates of Automatic and Controlled Auditory Processing in Schizophrenia

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Morey, Rajendra A.; Mitchell, Teresa V.; Inan, Seniha; Lieberman, Jeffrey A.; Belger, Aysenil

2009-01-01

Individuals with schizophrenia demonstrate impairments in selective attention and sensory processing. The authors assessed differences in brain function between 26 participants with schizophrenia and 17 comparison subjects engaged in automatic (unattended) and controlled (attended) auditory information processing using event-related functional MRI. Lower regional neural activation during automatic auditory processing in the schizophrenia group was not confined to just the temporal lobe, but also extended to prefrontal regions. Controlled auditory processing was associated with a distributed frontotemporal and subcortical dysfunction. Differences in activation between these two modes of auditory information processing were more pronounced in the comparison group than in the patient group. PMID:19196926

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

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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

Models of neural dynamics in brain information processing - the developments of 'the decade'

Energy Technology Data Exchange (ETDEWEB)

Borisyuk, G N; Borisyuk, R M; Kazanovich, Yakov B [Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation); Ivanitskii, Genrikh R [Institute for Theoretical and Experimental Biophysics, Russian Academy of Sciences, Pushchino, Moscow region (Russian Federation)

2002-10-31

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

Could information theory provide an ecological theory of sensory processing?

Science.gov (United States)

Atick, Joseph J

2011-01-01

The sensory pathways of animals are well adapted to processing a special class of signals, namely stimuli from the animal's environment. An important fact about natural stimuli is that they are typically very redundant and hence the sampled representation of these signals formed by the array of sensory cells is inefficient. One could argue for some animals and pathways, as we do in this review, that efficiency of information representation in the nervous system has several evolutionary advantages. Consequently, one might expect that much of the processing in the early levels of these sensory pathways could be dedicated towards recoding incoming signals into a more efficient form. In this review, we explore the principle of efficiency of information representation as a design principle for sensory processing. We give a preliminary discussion on how this principle could be applied in general to predict neural processing and then discuss concretely some neural systems where it recently has been shown to be successful. In particular, we examine the fly's LMC coding strategy and the mammalian retinal coding in the spatial, temporal and chromatic domains.

Neural processing of reward in adolescent rodents

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Nicholas W. Simon

2015-02-01

Full Text Available Immaturities in adolescent reward processing are thought to contribute to poor decision making and increased susceptibility to develop addictive and psychiatric disorders. Very little is known; however, about how the adolescent brain processes reward. The current mechanistic theories of reward processing are derived from adult models. Here we review recent research focused on understanding of how the adolescent brain responds to rewards and reward-associated events. A critical aspect of this work is that age-related differences are evident in neuronal processing of reward-related events across multiple brain regions even when adolescent rats demonstrate behavior similar to adults. These include differences in reward processing between adolescent and adult rats in orbitofrontal cortex and dorsal striatum. Surprisingly, minimal age related differences are observed in ventral striatum, which has been a focal point of developmental studies. We go on to discuss the implications of these differences for behavioral traits affected in adolescence, such as impulsivity, risk-taking, and behavioral flexibility. Collectively, this work suggests that reward-evoked neural activity differs as a function of age and that regions such as the dorsal striatum that are not traditionally associated with affective processing in adults may be critical for reward processing and psychiatric vulnerability in adolescents.

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

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Soltoggio, Andrea; Lemme, Andre; Reinhart, Felix; Steil, Jochen J.

2013-01-01

Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. PMID:23565092

The principles of artificial neural network information processing

International Nuclear Information System (INIS)

Dai, Ru-Wei

1993-01-01

In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as Perceptron, Back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally, the application of artificial neural network for Chinese Character Recognition is also given. (author)

The principles of artificial neural network information processing

International Nuclear Information System (INIS)

Dai, Ru-Wei

1993-01-01

In this article, the basic structure of an artificial neuron is first introduced. In addition, principles of artificial neural network as well as several important artificial neural models such as perception, back propagation model, Hopfield net, and ART model are briefly discussed and analyzed. Finally the application of artificial neural network for Chinese character recognition is also given. (author)

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

Science.gov (United States)

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.

Binocular depth processing in the ventral visual pathway.

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Verhoef, Bram-Ernst; Vogels, Rufin; Janssen, Peter

2016-06-19

One of the most powerful forms of depth perception capitalizes on the small relative displacements, or binocular disparities, in the images projected onto each eye. The brain employs these disparities to facilitate various computations, including sensori-motor transformations (reaching, grasping), scene segmentation and object recognition. In accordance with these different functions, disparity activates a large number of regions in the brain of both humans and monkeys. Here, we review how disparity processing evolves along different regions of the ventral visual pathway of macaques, emphasizing research based on both correlational and causal techniques. We will discuss the progression in the ventral pathway from a basic absolute disparity representation to a more complex three-dimensional shape code. We will show that, in the course of this evolution, the underlying neuronal activity becomes progressively more bound to the global perceptual experience. We argue that these observations most probably extend beyond disparity processing per se, and pertain to object processing in the ventral pathway in general. We conclude by posing some important unresolved questions whose answers may significantly advance the field, and broaden its scope.This article is part of the themed issue 'Vision in our three-dimensional world'. © 2016 The Author(s).

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

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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.

Emotionally anesthetized: media violence induces neural changes during emotional face processing

OpenAIRE

Stockdale, Laura A.; Morrison, Robert G.; Kmiecik, Matthew J.; Garbarino, James; Silton, Rebecca L.

2015-01-01

Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others’ emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five particip...

Recurrent Artificial Neural Networks and Finite State Natural Language Processing.

Science.gov (United States)

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…

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

Science.gov (United States)

Sebastian, Catherine L; Fontaine, Nathalie M G; Bird, Geoffrey; Blakemore, Sarah-Jayne; Brito, Stephane A De; 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.

An application of neural networks to process and materials control

International Nuclear Information System (INIS)

Howell, J.A.; Whiteson, R.

1991-01-01

Process control consists of two basic elements: a model of the process and knowledge of the desired control algorithm. In some cases the level of the control algorithm is merely supervisory, as in an alarm-reporting or anomaly-detection system. If the model of the process is known, then a set of equations may often be solved explicitly to provide the control algorithm. Otherwise, the model has to be discovered through empirical studies. Neural networks have properties that make them useful in this application. They can learn (make internal models from experience or observations). The problem of anomaly detection in materials control systems fits well into this general control framework. To successfully model a process with a neutral network, a good set of observables must be chosen. These observables must in some sense adequately span the space of representable events, so that a signature metric can be built for normal operation. In this way, a non-normal event, one that does not fit within the signature, can be detected. In this paper, we discuss the issues involved in applying a neural network model to anomaly detection in materials control systems. These issues include data selection and representation, network architecture, prediction of events, the use of simulated data, and software tools. 10 refs., 4 figs., 1 tab

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

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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.

Study of the neural basis of striatal modulation of the jaw-opening reflex.

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Barceló, Ana C; Fillipini, B; Pazo, Jorge Horacio

2010-02-01

Previous experimental data from this laboratory demonstrated the participation of the striatum and dopaminergic pathways in central nociceptive processing. The objective of this study was to examine the possible pathways and neural structures associated with the analgesic action of the striatum. The experiments were carried out in rats anesthetized with urethane. The jaw-opening reflex (JOR) was evoked by electrical stimulation of the tooth pulp of lower incisors and recorded in the anterior belly of the digastric muscles. Intrastriatal microinjection of apomorphine, a nonspecific dopamine agonist, reduced or abolished the JOR amplitude. Electrolytic or kainic acid lesions, unilateral to the apomorphine-injected striatum, of the globus pallidus, substantia nigra pars reticulata, subthalamic nucleus and bilateral lesion the rostroventromedial medulla (RVM), blocked the inhibition of the JOR by striatal stimulation. These findings suggest that the main output nuclei of the striatum and the RVM may be critical elements in the neural pathways mediating the inhibition of the reflex response, evoked in jaw muscles by noxious stimulation of dental pulp.

Prediction of ferric iron precipitation in bioleaching process using partial least squares and artificial neural network

Directory of Open Access Journals (Sweden)

Golmohammadi Hassan

2013-01-01

Full Text Available A quantitative structure-property relationship (QSPR study based on partial least squares (PLS and artificial neural network (ANN was developed for the prediction of ferric iron precipitation in bioleaching process. The leaching temperature, initial pH, oxidation/reduction potential (ORP, ferrous concentration and particle size of ore were used as inputs to the network. The output of the model was ferric iron precipitation. The optimal condition of the neural network was obtained by adjusting various parameters by trial-and-error. After optimization and training of the network according to back-propagation algorithm, a 5-5-1 neural network was generated for prediction of ferric iron precipitation. The root mean square error for the neural network calculated ferric iron precipitation for training, prediction and validation set are 32.860, 40.739 and 35.890, respectively, which are smaller than those obtained by PLS model (180.972, 165.047 and 149.950, respectively. Results obtained reveal the reliability and good predictivity of neural network model for the prediction of ferric iron precipitation in bioleaching process.

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

Directory of Open Access Journals (Sweden)

Yu-Chen Chan

2016-10-01

Full Text Available Hostile jokes provide aggressive catharsis and a feeling of superiority. Behavioral research has found that hostile jokes are perceived as funnier than non-hostile jokes. The purpose of the present study was to identify the neural correlates of the interaction between type and humor by comparing hostile jokes (HJs, non-hostile jokes (NJs, and their corresponding hostile sentences (HSs and non-hostile sentences (NSs. Hostile jokes primarily showed activation in the dorsomedial prefrontal cortex (dmPFC and midbrain compared with the corresponding hostile baseline. Conversely, non-hostile jokes 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 prefrontal cortex (mPFC for the neural correlates of social cognition and socio-emotional processing in response to different types of jokes. Moreover, the processing of hostile jokes showed increased activation in the dmPFC, which suggested cognitive operations of social motivation, whereas the processing of non-hostile jokes displayed increased activation in the vmPFC, which suggested social-affective engagement. Hostile jokes versus non-hostile jokes primarily showed increased activation in the dmPFC and midbrain, whereas non-hostile jokes versus hostile jokes 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 hostile jokes and functional coupling of the vmPFC-midbrain and amygdala-midbrain-NAcc for non-hostile jokes. Surprisingly, the neural correlates of hostile jokes were not perceived as funnier than non-hostile jokes. Future studies could further investigate the neural correlates of potentially important traits of high-hostility tendencies in humor appreciation

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

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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. Visual working memory (VWM) maintains task-relevant information in an online state. Previous studies showed that VWM representations are accessed and modified after changes in the environment. Here, we show that this updating process critically depends on an ongoing mapping between the

Lifecycle assessment of microalgae to biofuel: Comparison of thermochemical processing pathways

International Nuclear Information System (INIS)

Bennion, Edward P.; Ginosar, Daniel M.; Moses, John; Agblevor, Foster; Quinn, Jason C.

2015-01-01

Highlights: • Well to pump environmental assessment of two thermochemical processing pathways. • NER of 1.23 and GHG emissions of −11.4 g CO 2-eq (MJ) −1 for HTL pathway. • HTL represents promising conversion pathway based on use of wet biomass. • NER of 2.27 and GHG emissions of 210 g CO 2-eq (MJ) −1 for pyrolysis pathway. • Pyrolysis pathway: drying microalgae feedstock dominates environmental impact. - Abstract: Microalgae is being investigated as a renewable transportation fuel feedstock based on various advantages that include high annual yields, utilization of poor quality land, does not compete with food, and can be integrated with various waste streams. This study focuses on directly assessing the environmental impact of two different thermochemical conversion technologies for the microalgae-to-biofuel process through life cycle assessment. A system boundary of “well to pump” (WTP) is defined and includes sub-process models of the growth, dewatering, thermochemical bio-oil recovery, bio-oil stabilization, conversion to renewable diesel, and transport to the pump. Models were validated with experimental and literature data and are representative of an industrial-scale microalgae-to-biofuel process. Two different thermochemical bio-oil conversion systems are modeled and compared on a systems level, hydrothermal liquefaction (HTL) and pyrolysis. The environmental impact of the two pathways were quantified on the metrics of net energy ratio (NER), defined here as energy consumed over energy produced, and greenhouse gas (GHG) emissions. Results for WTP biofuel production through the HTL pathway were determined to be 1.23 for the NER and GHG emissions of −11.4 g CO 2-eq (MJ renewable diesel) −1 . Biofuel production through the pyrolysis pathway results in a NER of 2.27 and GHG emissions of 210 g CO 2-eq (MJ renewable diesel) −1 . The large environmental impact associated with the pyrolysis pathway is attributed to feedstock drying

Towards a neural basis of processing musical semantics

Science.gov (United States)

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.

Canonical Wnt signaling transiently stimulates proliferation and enhances neurogenesis in neonatal neural progenitor cultures

International Nuclear Information System (INIS)

Hirsch, Cordula; Campano, Louise M.; Woehrle, Simon; Hecht, Andreas

2007-01-01

Canonical Wnt signaling triggers the formation of heterodimeric transcription factor complexes consisting of β-catenin and T cell factors, and thereby controls the execution of specific genetic programs. During the expansion and neurogenic phases of embryonic neural development canonical Wnt signaling initially controls proliferation of neural progenitor cells, and later neuronal differentiation. Whether Wnt growth factors affect neural progenitor cells postnatally is not known. Therefore, we have analyzed the impact of Wnt signaling on neural progenitors isolated from cerebral cortices of newborn mice. Expression profiling of pathway components revealed that these cells are fully equipped to respond to Wnt signals. However, Wnt pathway activation affected only a subset of neonatal progenitors and elicited a limited increase in proliferation and neuronal differentiation in distinct subsets of cells. Moreover, Wnt pathway activation only transiently stimulated S-phase entry but did not support long-term proliferation of progenitor cultures. The dampened nature of the Wnt response correlates with the predominant expression of inhibitory pathway components and the rapid actuation of negative feedback mechanisms. Interestingly, in differentiating cell cultures activation of canonical Wnt signaling reduced Hes1 and Hes5 expression suggesting that during postnatal neural development, Wnt/β-catenin signaling enhances neurogenesis from progenitor cells by interfering with Notch pathway activity

A customizable stochastic state point process filter (SSPPF) for neural spiking activity.

Science.gov (United States)

Xin, Yao; Li, Will X Y; Min, Biao; Han, Yan; Cheung, Ray C C

2013-01-01

Stochastic State Point Process Filter (SSPPF) is effective for adaptive signal processing. In particular, it has been successfully applied to neural signal coding/decoding in recent years. Recent work has proven its efficiency in non-parametric coefficients tracking in modeling of mammal nervous system. However, existing SSPPF has only been realized in commercial software platforms which limit their computational capability. In this paper, the first hardware architecture of SSPPF has been designed and successfully implemented on field-programmable gate array (FPGA), proving a more efficient means for coefficient tracking in a well-established generalized Laguerre-Volterra model for mammalian hippocampal spiking activity research. By exploring the intrinsic parallelism of the FPGA, the proposed architecture is able to process matrices or vectors with random size, and is efficiently scalable. Experimental result shows its superior performance comparing to the software implementation, while maintaining the numerical precision. This architecture can also be potentially utilized in the future hippocampal cognitive neural prosthesis design.

Dynamic Neural Processing of Linguistic Cues Related to Death

Science.gov (United States)

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

Level of processing modulates the neural correlates of emotional memory formation

OpenAIRE

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

2010-01-01

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 employed a levels-of-processing manipulation to characterize the impact of emotion on encoding with and without the influence of elaborative processes. Participants viewed emotionally negative, neutral, and positive scenes under ...

Erythropoietin reduces neural and cognitive processing of fear in human models of antidepressant drug action

DEFF Research Database (Denmark)

Miskowiak, Kamilla; O'Sullivan, Ursula; Harmer, Catherine J

2007-01-01

with reduced attention to fear. Erythropoietin additionally reduced recognition of fearful facial expressions without affecting recognition of other emotional expressions. These actions occurred in the absence of changes in hematological parameters. CONCLUSIONS: The present study demonstrates that Epo directly......) versus saline on the neural processing of happy and fearful faces in 23 healthy volunteers. Facial expression recognition was assessed outside the scanner. RESULTS: One week after administration, Epo reduced neural response to fearful versus neutral faces in the occipito-parietal cortex consistent...... study aimed to explore the effects of Epo on neural and behavioral measures of emotional processing relevant for depression and the effects of conventional antidepressant medication. METHODS: In the present study, we used functional magnetic resonance imaging to explore the effects of Epo (40,000 IU...

Neural correlates of attentional and mnemonic processing in event-based prospective memory

Directory of Open Access Journals (Sweden)

Justin B Knight

2010-02-01

Full Text Available Prospective memory, or memory for realizing delayed intentions, was examined with an event-based paradigm while simultaneously measuring neural activity with high-density EEG recordings. Specifically, the neural substrates of monitoring for an event-based cue were examined, as well as those perhaps associated with the cognitive processes supporting detection of cues and fulfillment of intentions. Participants engaged in a baseline lexical decision task (LDT, followed by a LDT with an embedded prospective memory (PM component. Event-based cues were constituted by color and lexicality (red words. Behavioral data provided evidence that monitoring, or preparatory attentional processes, were used to detect cues. Analysis of the event-related potentials (ERP revealed visual attentional modulations at 140 and 220 ms post-stimulus associated with preparatory attentional processes. In addition, ERP components at 220, 350, and 400 ms post-stimulus were enhanced for intention-related items. Our results suggest preparatory attention may operate by selectively modulating processing of features related to a previously formed event-based intention, as well as provide further evidence for the proposal that dissociable component processes support the fulfillment of delayed intentions.

Neural correlates of treatment response in depressed bipolar adolescents during emotion processing.

Science.gov (United States)

Diler, Rasim Somer; Ladouceur, Cecile D; Segreti, Annamaria; Almeida, Jorge R C; Birmaher, Boris; Axelson, David A; Phillips, Mary L; Pan, Lisa A

2013-06-01

Depressive mood in adolescents with bipolar disorder (BDd) is associated with significant morbidity and mortality, but we have limited information about neural correlates of depression and treatment response in BDd. Ten adolescents with BDd (8 females, mean age = 15.6 ± 0.9) completed two (fearful and happy) face gender labeling fMRI experiments at baseline and after 6-weeks of open treatment. Whole-brain analysis was used at baseline to compare their neural activity with those of 10 age and sex-matched healthy controls (HC). For comparisons of the neural activity at baseline and after treatment of youth with BDd, region of interest analysis for dorsal/ventral prefrontal, anterior cingulate, and amygdala activity, and significant regions identified by wholebrain analysis between BDd and HC were analyzed. There was significant improvement in depression scores (mean percentage change on the Child Depression Rating Scale-Revised 57 % ± 28). Neural activity after treatment was decreased in left occipital cortex in the intense fearful experiment, but increased in left insula, left cerebellum, and right ventrolateral prefrontal cortex in the intense happy experiment. Greater improvement in depression was associated with baseline higher activity in ventral ACC to mild happy faces. Study sample size was relatively small for subgroup analysis and consisted of mainly female adolescents that were predominantly on psychotropic medications during scanning. Our results of reduced negative emotion processing versus increased positive emotion processing after treatment of depression (improvement of cognitive bias to negative and away from positive) are consistent with the improvement of depression according to Beck's cognitive theory.

Neural processing of auditory signals and modular neural control for sound tropism of walking machines

DEFF Research Database (Denmark)

Manoonpong, Poramate; Pasemann, Frank; Fischer, Joern

2005-01-01

and a neural preprocessing system together with a modular neural controller are used to generate a sound tropism of a four-legged walking machine. The neural preprocessing network is acting as a low-pass filter and it is followed by a network which discerns between signals coming from the left or the right....... The parameters of these networks are optimized by an evolutionary algorithm. In addition, a simple modular neural controller then generates the desired different walking patterns such that the machine walks straight, then turns towards a switched-on sound source, and then stops near to it....

Emotional sounds modulate early neural processing of emotional pictures

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Antje B M Gerdes

2013-10-01

Full Text Available 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 2s. 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.

The method of educational assessment affects children's neural processing and performance: behavioural and fMRI Evidence

Science.gov (United States)

Howard, Steven J.; Burianová, Hana; Calleia, Alysha; Fynes-Clinton, Samuel; Kervin, Lisa; Bokosmaty, Sahar

2017-08-01

Standardised educational assessments are now widespread, yet their development has given comparatively more consideration to what to assess than how to optimally assess students' competencies. Existing evidence from behavioural studies with children and neuroscience studies with adults suggest that the method of assessment may affect neural processing and performance, but current evidence remains limited. To investigate the impact of assessment methods on neural processing and performance in young children, we used functional magnetic resonance imaging to identify and quantify the neural correlates during performance across a range of current approaches to standardised spelling assessment. Results indicated that children's test performance declined as the cognitive load of assessment method increased. Activation of neural nodes associated with working memory further suggests that this performance decline may be a consequence of a higher cognitive load, rather than the complexity of the content. These findings provide insights into principles of assessment (re)design, to ensure assessment results are an accurate reflection of students' true levels of competency.

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

Science.gov (United States)

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

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

Science.gov (United States)

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.

Sadness is unique: Neural processing of emotions in speech prosody in musicians and non-musicians

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Mona ePark

2015-01-01

Full Text Available 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.

Image processing using pulse-coupled neural networks applications in Python

CERN Document Server

Lindblad, Thomas

2013-01-01

Image processing algorithms based on the mammalian visual cortex are powerful tools for extraction information and manipulating images. This book reviews the neural theory and translates them into digital models. Applications are given in areas of image recognition, foveation, image fusion and information extraction. The third edition reflects renewed international interest in pulse image processing with updated sections presenting several newly developed applications. This edition also introduces a suite of Python scripts that assist readers in replicating results presented in the text and to further develop their own applications.

Level of Processing Modulates the Neural Correlates of Emotional Memory Formation

Science.gov (United States)

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…

Programmable neural processing on a smartdust for brain-computer interfaces.

Science.gov (United States)

Yuwen Sun; Shimeng Huang; Oresko, Joseph J; Cheng, Allen C

2010-10-01

Brain-computer interfaces (BCIs) offer tremendous promise for improving the quality of life for disabled individuals. BCIs use spike sorting to identify the source of each neural firing. To date, spike sorting has been performed by either using off-chip analysis, which requires a wired connection penetrating the skull to a bulky external power/processing unit, or via custom application-specific integrated circuits that lack the programmability to perform different algorithms and upgrades. In this research, we propose and test the feasibility of performing on-chip, real-time spike sorting on a programmable smartdust, including feature extraction, classification, compression, and wireless transmission. A detailed power/performance tradeoff analysis using DVFS is presented. Our experimental results show that the execution time and power density meet the requirements to perform real-time spike sorting and wireless transmission on a single neural channel.

Multiscale neural connectivity during human sensory processing in the brain

Science.gov (United States)

Maksimenko, Vladimir A.; Runnova, Anastasia E.; Frolov, Nikita S.; Makarov, Vladimir V.; Nedaivozov, Vladimir; Koronovskii, Alexey A.; Pisarchik, Alexander; Hramov, Alexander E.

2018-05-01

Stimulus-related brain activity is considered using wavelet-based analysis of neural interactions between occipital and parietal brain areas in alpha (8-12 Hz) and beta (15-30 Hz) frequency bands. We show that human sensory processing related to the visual stimuli perception induces brain response resulted in different ways of parieto-occipital interactions in these bands. In the alpha frequency band the parieto-occipital neuronal network is characterized by homogeneous increase of the interaction between all interconnected areas both within occipital and parietal lobes and between them. In the beta frequency band the occipital lobe starts to play a leading role in the dynamics of the occipital-parietal network: The perception of visual stimuli excites the visual center in the occipital area and then, due to the increase of parieto-occipital interactions, such excitation is transferred to the parietal area, where the attentional center takes place. In the case when stimuli are characterized by a high degree of ambiguity, we find greater increase of the interaction between interconnected areas in the parietal lobe due to the increase of human attention. Based on revealed mechanisms, we describe the complex response of the parieto-occipital brain neuronal network during the perception and primary processing of the visual stimuli. The results can serve as an essential complement to the existing theory of neural aspects of visual stimuli processing.

Neural Signaling of Food Healthiness Associated with Emotion Processing.

Science.gov (United States)

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.

Processing of chromatic information in a deep convolutional neural network.

Science.gov (United States)

Flachot, Alban; Gegenfurtner, Karl R

2018-04-01

Deep convolutional neural networks are a class of machine-learning algorithms capable of solving non-trivial tasks, such as object recognition, with human-like performance. Little is known about the exact computations that deep neural networks learn, and to what extent these computations are similar to the ones performed by the primate brain. Here, we investigate how color information is processed in the different layers of the AlexNet deep neural network, originally trained on object classification of over 1.2M images of objects in their natural contexts. We found that the color-responsive units in the first layer of AlexNet learned linear features and were broadly tuned to two directions in color space, analogously to what is known of color responsive cells in the primate thalamus. Moreover, these directions are decorrelated and lead to statistically efficient representations, similar to the cardinal directions of the second-stage color mechanisms in primates. We also found, in analogy to the early stages of the primate visual system, that chromatic and achromatic information were segregated in the early layers of the network. Units in the higher layers of AlexNet exhibit on average a lower responsivity for color than units at earlier stages.

BOOK REVIEW: Theory of Neural Information Processing Systems

Science.gov (United States)

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

Specific neural basis of Chinese idioms processing: an event-related functional MRI study

International Nuclear Information System (INIS)

Chen Shaoqi; Zhang Yanzhen; Xiao Zhuangwei; Zhang Xuexin

2007-01-01

Objective: To address the neural basis of Chinese idioms processing with different kinds of stimuli using an event-related fMRI design. Methods: Sixteen native Chinese speakers were asked to perform a semantic decision task during fMRI scanning. Three kinds of stimuli were used: Real idioms (Real-idiom condition); Literally plausible phrases (Pseudo-idiom condition, the last character of a real idiom was replaced by a character with similar meaning); Literally implausible strings (Non-idiom condition, the last character of a real idiom was replaced by a character with unrelated meaning). Reaction time and correct rate were recorded at the same time. Results: The error rate was 2.6%, 5.2% and 0.9% (F=3.51, P 0.05) for real idioms, pseudo-idioms and wrong idioms, respectively. Similar neural network was activated in all of the three conditions. However, the right hippocampus was only activated in the real idiom condition, and significant activations were found in anterior portion of left inferior frontal gyms (BA47) in real-and pseudo-idiom conditions, but not in non-idiom condition. Conclusion: The right hippocampus plays a specific role in the particular wording of the Chinese idioms. And the left anterior inferior frontal gyms (BA47) may be engaged in the semantic processing of Chinese idioms. The results support the notion that there were specific neural bases for Chinese idioms processing. (authors)

Is There Neural Evidence for an Evidence Accumulation Process in Memory Decisions?

NARCIS (Netherlands)

van Vugt, Marieke K; Beulen, Marijke A; Taatgen, Niels A

2016-01-01

Models of evidence accumulation have been very successful at describing human decision making behavior. Recent years have also seen the first reports of neural correlates of this accumulation process. However, these studies have mostly focused on perceptual decision making tasks, ignoring the role

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

Directory of Open Access Journals (Sweden)

Rachel C. Leung

2018-02-01

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

Neural Systems Underlying Emotional and Non-emotional Interference Processing: An ALE Meta-Analysis of Functional Neuroimaging Studies

OpenAIRE

Xu, Min; Xu, Guiping; Yang, Yang

2016-01-01

Understanding how the nature of interference might influence the recruitments of the neural systems is considered as the key to understanding cognitive control. Although, interference processing in the emotional domain has recently attracted great interest, the question of whether there are separable neural patterns for emotional and non-emotional interference processing remains open. Here, we performed an activation likelihood estimation meta-analysis of 78 neuroimaging experiments, and exam...

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

Science.gov (United States)

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.

Suprahyoid Muscle Complex: A Reliable Neural Assessment Tool For Dysphagia?

DEFF Research Database (Denmark)

Kothari, Mohit; Stubbs, Peter William; Pedersen, Asger Roer

be a non-invasive reliable neural assessment tool for patients with dysphagia. Objective: To investigate the possibility of using the suprahyoid muscle complex (SMC) using surface electromyography (sEMG) to assess changes to neural pathways by determining the reliability of measurements in healthy...

Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

CERN Document Server

Baianu, I C

2004-01-01

A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

Directory of Open Access Journals (Sweden)

Jonathan Cannon

2015-11-01

Full Text Available Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

Science.gov (United States)

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

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

NARCIS (Netherlands)

Simon, J.J.; Walther, S.; Fiebach, C.J.; Friederich, H.C.; Stippich, C.; Weisbrod, M.; Kaiser, S.

2009-01-01

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

Predicting tool life in turning operations using neural networks and image processing

Science.gov (United States)

Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

2018-05-01

A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

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

Science.gov (United States)

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. Copyright © 2014 Elsevier Inc. All rights reserved.

Sequential neural processes in abacus mental addition: an EEG and FMRI case study.

Science.gov (United States)

Ku, Yixuan; Hong, Bo; Zhou, Wenjing; Bodner, Mark; Zhou, Yong-Di

2012-01-01

Abacus experts are able to mentally calculate multi-digit numbers rapidly. Some behavioral and neuroimaging studies have suggested a visuospatial and visuomotor strategy during abacus mental calculation. However, no study up to now has attempted to dissociate temporally the visuospatial neural process from the visuomotor neural process during abacus mental calculation. In the present study, an abacus expert performed the mental addition tasks (8-digit and 4-digit addends presented in visual or auditory modes) swiftly and accurately. The 100% correct rates in this expert's task performance were significantly higher than those of ordinary subjects performing 1-digit and 2-digit addition tasks. ERPs, EEG source localizations, and fMRI results taken together suggested visuospatial and visuomotor processes were sequentially arranged during the abacus mental addition with visual addends and could be dissociated from each other temporally. The visuospatial transformation of the numbers, in which the superior parietal lobule was most likely involved, might occur first (around 380 ms) after the onset of the stimuli. The visuomotor processing, in which the superior/middle frontal gyri were most likely involved, might occur later (around 440 ms). Meanwhile, fMRI results suggested that neural networks involved in the abacus mental addition with auditory stimuli were similar to those in the visual abacus mental addition. The most prominently activated brain areas in both conditions included the bilateral superior parietal lobules (BA 7) and bilateral middle frontal gyri (BA 6). These results suggest a supra-modal brain network in abacus mental addition, which may develop from normal mental calculation networks.

IGF-1 Promotes Brn-4 Expression and Neuronal Differentiation of Neural Stem Cells via the PI3K/Akt Pathway

Science.gov (United States)

Zhang, Xinhua; Zhang, Lei; Cheng, Xiang; Guo, Yuxiu; Sun, Xiaohui; Chen, Geng; Li, Haoming; Li, Pengcheng; Lu, Xiaohui; Tian, Meiling; Qin, Jianbing; Zhou, Hui; Jin, Guohua

2014-01-01

Our previous studies indicated that transcription factor Brn-4 is upregulated in the surgically denervated hippocampus in vivo, promoting neuronal differentiation of hippocampal neural stem cells (NSCs) in vitro. The molecules mediating Brn-4 upregulation in the denervated hippocampus remain unknown. In this study we examined the levels of insulin-like growth factor-1 (IGF-1) in hippocampus following denervation. Surgical denervation led to a significant increase in IGF-1 expression in vivo. We also report that IGF-1 treatment on NSCs in vitro led to a marked acceleration of Brn-4 expression and cell differentiation down neuronal pathways. The promotion effects were blocked by PI3K-specific inhibitor (LY294002), but not MAPK inhibitor (PD98059); levels of phospho-Akt were increased by IGF-1 treatment. In addition, inhibition of IGF-1 receptor (AG1024) and mTOR (rapamycin) both attenuated the increased expression of Brn-4 induced by IGF-1. Together, the results demonstrated that upregulation of IGF-1 induced by hippocampal denervation injury leads to activation of the PI3K/Akt signaling pathway, which in turn gives rise to upregulation of the Brn-4 and subsequent stem cell differentiation down neuronal pathways. PMID:25474202

Using Dual Process Models to Examine Impulsivity Throughout Neural Maturation.

Science.gov (United States)

Leshem, Rotem

2016-01-01

The multivariate construct of impulsivity is examined through neural systems and connections that comprise the executive functioning system. It is proposed that cognitive and behavioral components of impulsivity can be divided into two distinct groups, mediated by (1) the cognitive control system: deficits in top-down cognitive control processes referred to as action/cognitive impulsivity and (2) the socioemotional system: related to bottom-up affective/motivational processes referred to as affective impulsivity. Examination of impulsivity from a developmental viewpoint can guide future research, potentially enabling the selection of more effective interventions for impulsive individuals, based on the cognitive components requiring improvement.

Epidermal wound repair is regulated by the planar cell polarity signaling pathway.

Science.gov (United States)

Caddy, Jacinta; Wilanowski, Tomasz; Darido, Charbel; Dworkin, Sebastian; Ting, Stephen B; Zhao, Quan; Rank, Gerhard; Auden, Alana; Srivastava, Seema; Papenfuss, Tony A; Murdoch, Jennifer N; Humbert, Patrick O; Parekh, Vishwas; Boulos, Nidal; Weber, Thomas; Zuo, Jian; Cunningham, John M; Jane, Stephen M

2010-07-20

The mammalian PCP pathway regulates diverse developmental processes requiring coordinated cellular movement, including neural tube closure and cochlear stereociliary orientation. Here, we show that epidermal wound repair is regulated by PCP signaling. Mice carrying mutant alleles of PCP genes Vangl2, Celsr1, PTK7, and Scrb1, and the transcription factor Grhl3, interact genetically, exhibiting failed wound healing, neural tube defects, and disordered cochlear polarity. Using phylogenetic analysis, ChIP, and gene expression in Grhl3(-)(/-) mice, we identified RhoGEF19, a homolog of a RhoA activator involved in PCP signaling in Xenopus, as a direct target of GRHL3. Knockdown of Grhl3 or RhoGEF19 in keratinocytes induced defects in actin polymerization, cellular polarity, and wound healing, and re-expression of RhoGEF19 rescued these defects in Grhl3-kd cells. These results define a role for Grhl3 in PCP signaling and broadly implicate this pathway in epidermal repair. (c) 2010 Elsevier Inc. All rights reserved.

Elucidating dominant pathways of the nano-particle self-assembly process.

Science.gov (United States)

Zeng, Xiangze; Li, Bin; Qiao, Qin; Zhu, Lizhe; Lu, Zhong-Yuan; Huang, Xuhui

2016-09-14

Self-assembly processes play a key role in the fabrication of functional nano-structures with widespread application in drug delivery and micro-reactors. In addition to the thermodynamics, the kinetics of the self-assembled nano-structures also play an important role in determining the formed structures. However, as the self-assembly process is often highly heterogeneous, systematic elucidation of the dominant kinetic pathways of self-assembly is challenging. Here, based on mass flow, we developed a new method for the construction of kinetic network models and applied it to identify the dominant kinetic pathways for the self-assembly of star-like block copolymers. We found that the dominant pathways are controlled by two competing kinetic parameters: the encounter time Te, characterizing the frequency of collision and the transition time Tt for the aggregate morphology change from rod to sphere. Interestingly, two distinct self-assembly mechanisms, diffusion of an individual copolymer into the aggregate core and membrane closure, both appear at different stages (with different values of Tt) of a single self-assembly process. In particular, the diffusion mechanism dominates the middle-sized semi-vesicle formation stage (with large Tt), while the membrane closure mechanism dominates the large-sized vesicle formation stage (with small Tt). Through the rational design of the hydrophibicity of the copolymer, we successfully tuned the transition time Tt and altered the dominant self-assembly pathways.

Anatomical pathways involved in generating and sensing rhythmic whisker movements

Directory of Open Access Journals (Sweden)

Laurens W.J. Bosman

2011-10-01

Full Text Available The rodent whisker system is widely used as a model system for investigating sensorimotor integration, neural mechanisms of complex cognitive tasks, neural development, and robotics. The whisker pathways to the barrel cortex have received considerable attention. However, many subcortical structures are paramount to the whisker system. They contribute to important processes, like filtering out salient features, integration with other senses and adaptation of the whisker system to the general behavioral state of the animal. We present here an overview of the brain regions and their connections involved in the whisker system. We do not only describe the anatomy and functional roles of the cerebral cortex, but also those of subcortical structures like the striatum, superior colliculus, cerebellum, pontomedullary reticular formation, zona incerta and anterior pretectal nucleus as well as those of level setting systems like the cholinergic, histaminergic, serotonergic and noradrenergic pathways. We conclude by discussing how these brain regions may affect each other and how they together may control the precise timing of whisker movements and coordinate whisker perception.

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

International Nuclear Information System (INIS)

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

Application of fuzzy neural network technologies in management of transport and logistics processes in Arctic

Science.gov (United States)

Levchenko, N. G.; Glushkov, S. V.; Sobolevskaya, E. Yu; Orlov, A. P.

2018-05-01

The method of modeling the transport and logistics process using fuzzy neural network technologies has been considered. The analysis of the implemented fuzzy neural network model of the information management system of transnational multimodal transportation of the process showed the expediency of applying this method to the management of transport and logistics processes in the Arctic and Subarctic conditions. The modular architecture of this model can be expanded by incorporating additional modules, since the working conditions in the Arctic and the subarctic themselves will present more and more realistic tasks. The architecture allows increasing the information management system, without affecting the system or the method itself. The model has a wide range of application possibilities, including: analysis of the situation and behavior of interacting elements; dynamic monitoring and diagnostics of management processes; simulation of real events and processes; prediction and prevention of critical situations.

Neural information processing in cognition: we start to understand the orchestra, but where is the conductor?

Directory of Open Access Journals (Sweden)

Guenther ePalm

2016-01-01

Full Text Available 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.

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

Science.gov (United States)

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. PMID:26858632

The neural cell adhesion molecule

DEFF Research Database (Denmark)

Berezin, V; Bock, E; Poulsen, F M

2000-01-01

During the past year, the understanding of the structure and function of neural cell adhesion has advanced considerably. The three-dimensional structures of several of the individual modules of the neural cell adhesion molecule (NCAM) have been determined, as well as the structure of the complex...... between two identical fragments of the NCAM. Also during the past year, a link between homophilic cell adhesion and several signal transduction pathways has been proposed, connecting the event of cell surface adhesion to cellular responses such as neurite outgrowth. Finally, the stimulation of neurite...

Neural Generalized Predictive Control of a non-linear Process

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1998-01-01

The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability qu...... detail and discuss the implementation difficulties. The neural generalized predictive controller is tested on a pneumatic servo sys-tem.......The use of neural network in non-linear control is made difficult by the fact the stability and robustness is not guaranteed and that the implementation in real time is non-trivial. In this paper we introduce a predictive controller based on a neural network model which has promising stability...... qualities. The controller is a non-linear version of the well-known generalized predictive controller developed in linear control theory. It involves minimization of a cost function which in the present case has to be done numerically. Therefore, we develop the numerical algorithms necessary in substantial...

Neural Indices of Semantic Processing in Early Childhood Distinguish Eventual Stuttering Persistence and Recovery

Science.gov (United States)

Kreidler, Kathryn; Wray, Amanda Hampton; Usler, Evan; Weber, Christine

2017-01-01

Purpose: Maturation of neural processes for language may lag in some children who stutter (CWS), and event-related potentials (ERPs) distinguish CWS who have recovered from those who have persisted. The current study explores whether ERPs indexing semantic processing may distinguish children who will eventually persist in stuttering…

Expanding the occupational health methodology: A concatenated artificial neural network approach to model the burnout process in Chinese nurses.

Science.gov (United States)

Ladstätter, Felix; Garrosa, Eva; Moreno-Jiménez, Bernardo; Ponsoda, Vicente; Reales Aviles, José Manuel; Dai, Junming

2016-01-01

Artificial neural networks are sophisticated modelling and prediction tools capable of extracting complex, non-linear relationships between predictor (input) and predicted (output) variables. This study explores this capacity by modelling non-linearities in the hardiness-modulated burnout process with a neural network. Specifically, two multi-layer feed-forward artificial neural networks are concatenated in an attempt to model the composite non-linear burnout process. Sensitivity analysis, a Monte Carlo-based global simulation technique, is then utilised to examine the first-order effects of the predictor variables on the burnout sub-dimensions and consequences. Results show that (1) this concatenated artificial neural network approach is feasible to model the burnout process, (2) sensitivity analysis is a prolific method to study the relative importance of predictor variables and (3) the relationships among variables involved in the development of burnout and its consequences are to different degrees non-linear. Many relationships among variables (e.g., stressors and strains) are not linear, yet researchers use linear methods such as Pearson correlation or linear regression to analyse these relationships. Artificial neural network analysis is an innovative method to analyse non-linear relationships and in combination with sensitivity analysis superior to linear methods.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

Science.gov (United States)

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Unconscious neural processing differs with method used to render stimuli invisible

Directory of Open Access Journals (Sweden)

Sergey Victor Fogelson

2014-06-01

Full Text Available 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.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Sylvia A. Morelli

2013-05-01

Full Text Available Although many studies have examined the neural basis of experiencing 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. 32 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, while instructed to empathize, 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; 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 versus 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 (DMPFC, MPFC, TPJ, amygdala and social cognition. The current results reveal how attention impacts empathic processes and provides insight into how empathy may unfold in everyday interactions.

Neural cascade of conflict processing: not just time-on-task

Science.gov (United States)

McKay, Cameron C.; van den Berg, Berry; Woldorff, Marty G.

2017-01-01

In visual conflict tasks (e.g., Stroop or flanker), response times (RTs) are generally longer on incongruent trials relative to congruent ones. Two event-related-potential (ERP) components classically associated with the processing of stimulus conflict are the fronto-central, incongruency-related negativity (Ninc) and the posterior late-positive complex (LPC), which are derived from the ERP difference waves for incongruent minus congruent trials. It has been questioned, however, whether these effects, or other neural measures of incongruency (e.g., fMRI responses in the anterior cingulate), reflect true conflict processing, or whether such effects derive mainly from differential time-on-task. To address this question, we leveraged high-temporal-resolution ERP measures of brain activity during two behavioral tasks. The first task, a modified Erikson flanker paradigm (with congruent and incongruent trials), was used to evoke the classic RT and ERP effects associated with conflict. In the second, a non-conflict comparison condition, participants visually discriminated a single stimulus (with easy and hard discrimination conditions). Behaviorally, the parameters were titrated to yield similar RT effects of conflict and difficulty (27 ms). Neurally, both within-task contrasts showed an initial fronto-central negative-polarity wave (N2-latency effect), but they then diverged. In the difficulty difference wave, the initial negativity led directly into the posterior LPC, whereas in the incongruency contrast the initial negativity was followed a by a second fronto-central negative peak (Ninc), which was then followed by a considerably longer-latency LPC. These results provide clear evidence that the longer processing for incongruent stimulus inputs do not just reflect time-on-task or difficulty, but include a true conflict-processing component. PMID:28017818

Neural correlates of gesture processing across human development.

Science.gov (United States)

Wakefield, Elizabeth M; James, Thomas W; James, Karin H

2013-01-01

Co-speech gesture facilitates learning to a greater degree in children than in adults, suggesting that the mechanisms underlying the processing of co-speech gesture differ as a function of development. We suggest that this may be partially due to children's lack of experience producing gesture, leading to differences in the recruitment of sensorimotor networks when comparing adults to children. Here, we investigated the neural substrates of gesture processing in a cross-sectional sample of 5-, 7.5-, and 10-year-old children and adults and focused on relative recruitment of a sensorimotor system that included the precentral gyrus (PCG) and the posterior middle temporal gyrus (pMTG). Children and adults were presented with videos in which communication occurred through different combinations of speech and gesture during a functional magnetic resonance imaging (fMRI) session. Results demonstrated that the PCG and pMTG were recruited to different extents in the two populations. We interpret these novel findings as supporting the idea that gesture perception (pMTG) is affected by a history of gesture production (PCG), revealing the importance of considering gesture processing as a sensorimotor process.

Erythropoietin modulates neural and cognitive processing of emotional information in biomarker models of antidepressant drug action in depressed patients

DEFF Research Database (Denmark)

Miskowiak, Kamilla W; Favaron, Elisa; Hafizi, Sepehr

2010-01-01

Erythropoietin (Epo) has neuroprotective and neurotrophic effects, and may be a novel therapeutic agent in the treatment of psychiatric disorders. We have demonstrated antidepressant-like effects of Epo on the neural and cognitive processing of facial expressions in healthy volunteers. The curren...... study investigates the effects of Epo on the neural and cognitive response to emotional facial expressions in depressed patients.......Erythropoietin (Epo) has neuroprotective and neurotrophic effects, and may be a novel therapeutic agent in the treatment of psychiatric disorders. We have demonstrated antidepressant-like effects of Epo on the neural and cognitive processing of facial expressions in healthy volunteers. The current...

Protein signaling pathways in differentiation of neural stem cells

Czech Academy of Sciences Publication Activity Database

Skalníková, Helena; Vodička, Petr; Pelech, S.; Motlík, Jan; Gadher, S. J.; Kovářová, Hana

2008-01-01

Roč. 8, - (2008), s. 4547-4559 ISSN 1615-9853 R&D Projects: GA MŠk 1M0538 Institutional research plan: CEZ:AV0Z50450515 Keywords : antibody microarray * differentiation * neural stem cells Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.586, year: 2008

High school music classes enhance the neural processing of speech.

Science.gov (United States)

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.

Models of neural networks temporal aspects of coding and information processing in biological systems

CERN Document Server

Hemmen, J; Schulten, Klaus

1994-01-01

Since the appearance of Vol. 1 of Models of Neural Networks in 1991, the theory of neural nets has focused on two paradigms: information coding through coherent firing of the neurons and functional feedback. Information coding through coherent neuronal firing exploits time as a cardinal degree of freedom. This capacity of a neural network rests on the fact that the neuronal action potential is a short, say 1 ms, spike, localized in space and time. Spatial as well as temporal correlations of activity may represent different states of a network. In particular, temporal correlations of activity may express that neurons process the same "object" of, for example, a visual scene by spiking at the very same time. The traditional description of a neural network through a firing rate, the famous S-shaped curve, presupposes a wide time window of, say, at least 100 ms. It thus fails to exploit the capacity to "bind" sets of coherently firing neurons for the purpose of both scene segmentation and figure-ground segregatio...

Control System Design for Cylindrical Tank Process Using Neural Model Predictive Control Technique

Directory of Open Access Journals (Sweden)

M. Sridevi

2010-10-01

Full Text Available Chemical manufacturing and process industry requires innovative technologies for process identification. This paper deals with model identification and control of cylindrical process. Model identification of the process was done using ARMAX technique. A neural model predictive controller was designed for the identified model. The performance of the controllers was evaluated using MATLAB software. The performance of NMPC controller was compared with Smith Predictor controller and IMC controller based on rise time, settling time, overshoot and ISE and it was found that the NMPC controller is better suited for this process.

Process for forming synapses in neural networks and resistor therefor

Science.gov (United States)

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.

Neural correlates of the processing of self-referent emotional information in bulimia nervosa.

Science.gov (United States)

Pringle, A; Ashworth, F; Harmer, C J; Norbury, R; Cooper, M J

2011-10-01

There is increasing interest in understanding the roles of distorted beliefs about the self, ostensibly unrelated to eating, weight and shape, in eating disorders (EDs), but little is known about their neural correlates. We therefore used functional magnetic resonance imaging to investigate the neural correlates of self-referent emotional processing in EDs. During the scan, unmedicated patients with bulimia nervosa (n=11) and healthy controls (n=16) responded to personality words previously found to be related to negative self beliefs in EDs and depression. Rating of the negative personality descriptors resulted in reduced activation in patients compared to controls in parietal, occipital and limbic areas including the amygdala. There was no evidence that reduced activity in patients was secondary to increased cognitive control. Different patterns of neural activation between patients and controls may be the result of either habituation to personally relevant negative self beliefs or of emotional blunting in patients. Copyright © 2011 Elsevier Ltd. All rights reserved.

Prediction of deformations of steel plate by artificial neural network in forming process with induction heating

International Nuclear Information System (INIS)

Nguyen, Truong Thinh; Yang, Young Soo; Bae, Kang Yul; Choi, Sung Nam

2009-01-01

To control a heat source easily in the forming process of steel plate with heating, the electro-magnetic induction process has been used as a substitute of the flame heating process. However, only few studies have analyzed the deformation of a workpiece in the induction heating process by using a mathematical model. This is mainly due to the difficulty of modeling the heat flux from the inductor traveling on the conductive plate during the induction process. In this study, the heat flux distribution over a steel plate during the induction process is first analyzed by a numerical method with the assumption that the process is in a quasi-stationary state around the inductor and also that the heat flux itself greatly depends on the temperature of the workpiece. With the heat flux, heat flow and thermo-mechanical analyses on the plate to obtain deformations during the heating process are then performed with a commercial FEM program for 34 combinations of heating parameters. An artificial neural network is proposed to build a simplified relationship between deformations and heating parameters that can be easily utilized to predict deformations of steel plate with a wide range of heating parameters in the heating process. After its architecture is optimized, the artificial neural network is trained with the deformations obtained from the FEM analyses as outputs and the related heating parameters as inputs. The predicted outputs from the neural network are compared with those of the experiments and the numerical results. They are in good agreement

Murine dishevelled 3 functions in redundant pathways with dishevelled 1 and 2 in normal cardiac outflow tract, cochlea, and neural tube development.

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Etheridge, S Leah; Ray, Saugata; Li, Shuangding; Hamblet, Natasha S; Lijam, Nardos; Tsang, Michael; Greer, Joy; Kardos, Natalie; Wang, Jianbo; Sussman, Daniel J; Chen, Ping; Wynshaw-Boris, Anthony

2008-11-01

Dishevelled (Dvl) proteins are important signaling components of both the canonical beta-catenin/Wnt pathway, which controls cell proliferation and patterning, and the planar cell polarity (PCP) pathway, which coordinates cell polarity within a sheet of cells and also directs convergent extension cell (CE) movements that produce narrowing and elongation of the tissue. Three mammalian Dvl genes have been identified and the developmental roles of Dvl1 and Dvl2 were previously determined. Here, we identify the functions of Dvl3 in development and provide evidence of functional redundancy among the three murine Dvls. Dvl3(-/-) mice died perinatally with cardiac outflow tract abnormalities, including double outlet right ventricle and persistent truncus arteriosis. These mutants also displayed a misorientated stereocilia in the organ of Corti, a phenotype that was enhanced with the additional loss of a single allele of the PCP component Vangl2/Ltap (LtapLp/+). Although neurulation appeared normal in both Dvl3(-/-) and LtapLp/+ mutants, Dvl3(+/-);LtapLp/+ combined mutants displayed incomplete neural tube closure. Importantly, we show that many of the roles of Dvl3 are also shared by Dvl1 and Dvl2. More severe phenotypes were observed in Dvl3 mutants with the deficiency of another Dvl, and increasing Dvl dosage genetically with Dvl transgenes demonstrated the ability of Dvls to compensate for each other to enable normal development. Interestingly, global canonical Wnt signaling appeared largely unaffected in the double Dvl mutants, suggesting that low Dvl levels are sufficient for functional canonical Wnt signals. In summary, we demonstrate that Dvl3 is required for cardiac outflow tract development and describe its importance in the PCP pathway during neurulation and cochlea development. Finally, we establish several developmental processes in which the three Dvls are functionally redundant.

Murine dishevelled 3 functions in redundant pathways with dishevelled 1 and 2 in normal cardiac outflow tract, cochlea, and neural tube development.

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S Leah Etheridge

2008-11-01

Full Text Available Dishevelled (Dvl proteins are important signaling components of both the canonical beta-catenin/Wnt pathway, which controls cell proliferation and patterning, and the planar cell polarity (PCP pathway, which coordinates cell polarity within a sheet of cells and also directs convergent extension cell (CE movements that produce narrowing and elongation of the tissue. Three mammalian Dvl genes have been identified and the developmental roles of Dvl1 and Dvl2 were previously determined. Here, we identify the functions of Dvl3 in development and provide evidence of functional redundancy among the three murine Dvls. Dvl3(-/- mice died perinatally with cardiac outflow tract abnormalities, including double outlet right ventricle and persistent truncus arteriosis. These mutants also displayed a misorientated stereocilia in the organ of Corti, a phenotype that was enhanced with the additional loss of a single allele of the PCP component Vangl2/Ltap (LtapLp/+. Although neurulation appeared normal in both Dvl3(-/- and LtapLp/+ mutants, Dvl3(+/-;LtapLp/+ combined mutants displayed incomplete neural tube closure. Importantly, we show that many of the roles of Dvl3 are also shared by Dvl1 and Dvl2. More severe phenotypes were observed in Dvl3 mutants with the deficiency of another Dvl, and increasing Dvl dosage genetically with Dvl transgenes demonstrated the ability of Dvls to compensate for each other to enable normal development. Interestingly, global canonical Wnt signaling appeared largely unaffected in the double Dvl mutants, suggesting that low Dvl levels are sufficient for functional canonical Wnt signals. In summary, we demonstrate that Dvl3 is required for cardiac outflow tract development and describe its importance in the PCP pathway during neurulation and cochlea development. Finally, we establish several developmental processes in which the three Dvls are functionally redundant.

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

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Gafarov, F M; Gafarova, V R

2016-09-01

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

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

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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.

IGF-1 promotes Brn-4 expression and neuronal differentiation of neural stem cells via the PI3K/Akt pathway.

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Xinhua Zhang

Full Text Available Our previous studies indicated that transcription factor Brn-4 is upregulated in the surgically denervated hippocampus in vivo, promoting neuronal differentiation of hippocampal neural stem cells (NSCs in vitro. The molecules mediating Brn-4 upregulation in the denervated hippocampus remain unknown. In this study we examined the levels of insulin-like growth factor-1 (IGF-1 in hippocampus following denervation. Surgical denervation led to a significant increase in IGF-1 expression in vivo. We also report that IGF-1 treatment on NSCs in vitro led to a marked acceleration of Brn-4 expression and cell differentiation down neuronal pathways. The promotion effects were blocked by PI3K-specific inhibitor (LY294002, but not MAPK inhibitor (PD98059; levels of phospho-Akt were increased by IGF-1 treatment. In addition, inhibition of IGF-1 receptor (AG1024 and mTOR (rapamycin both attenuated the increased expression of Brn-4 induced by IGF-1. Together, the results demonstrated that upregulation of IGF-1 induced by hippocampal denervation injury leads to activation of the PI3K/Akt signaling pathway, which in turn gives rise to upregulation of the Brn-4 and subsequent stem cell differentiation down neuronal pathways.

Neural circuit components of the Drosophila OFF motion vision pathway.

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Meier, Matthias; Serbe, Etienne; Maisak, Matthew S; Haag, Jürgen; Dickson, Barry J; Borst, Alexander

2014-02-17

Detecting the direction of visual motion is an essential task of the early visual system. The Reichardt detector has been proven to be a faithful description of the underlying computation in insects. A series of recent studies addressed the neural implementation of the Reichardt detector in Drosophila revealing the overall layout in parallel ON and OFF channels, its input neurons from the lamina (L1→ON, and L2→OFF), and the respective output neurons to the lobula plate (ON→T4, and OFF→T5). While anatomical studies showed that T4 cells receive input from L1 via Mi1 and Tm3 cells, the neurons connecting L2 to T5 cells have not been identified so far. It is, however, known that L2 contacts, among others, two neurons, called Tm2 and L4, which show a pronounced directionality in their wiring. We characterized the visual response properties of both Tm2 and L4 neurons via Ca(2+) imaging. We found that Tm2 and L4 cells respond with an increase in activity to moving OFF edges in a direction-unselective manner. To investigate their participation in motion vision, we blocked their output while recording from downstream tangential cells in the lobula plate. Silencing of Tm2 and L4 completely abolishes the response to moving OFF edges. Our results demonstrate that both cell types are essential components of the Drosophila OFF motion vision pathway, prior to the computation of directionality in the dendrites of T5 cells. Copyright © 2014 Elsevier Ltd. All rights reserved.

Forward and reverse mapping for milling process using artificial neural networks

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Rashmi L. Malghan

2018-02-01

Full Text Available The data set presented is related to the milling process of AA6061-4.5%Cu-5%SiCp composite. The data primarily concentrates on predicting values of some machining responses, such as cutting force, surface finish and power utilization utilizing using forward back propagation neural network based approach, i.e. ANN based on three process parameters, such as spindle speed, feed rate and depth of cut.The comparing reverse model is likewise created to prescribe the ideal settings of processing parameters for accomplishing the desired responses as indicated by the necessities of the end clients. These modelling approaches are very proficient to foresee the benefits of machining responses and also process parameter settings in light of the experimental technique. Keywords: ANN, Forward mapping, Reverse mapping, Milling process

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

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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

40 CFR 80.1416 - Petition process for evaluation of new renewable fuels pathways.

Science.gov (United States)

2010-07-01

... renewable fuels pathways. 80.1416 Section 80.1416 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY... Petition process for evaluation of new renewable fuels pathways. (a) Pursuant to this section, a party may... fuel pathway has not been evaluated by EPA to determine if it qualifies for a D code pursuant to § 80...

Social cognition and neural substrates of face perception: implications for neurodevelopmental and neuropsychiatric disorders.

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Lazar, Steven M; Evans, David W; Myers, Scott M; Moreno-De Luca, Andres; Moore, Gregory J

2014-04-15

Social cognition is an important aspect of social behavior in humans. Social cognitive deficits are associated with neurodevelopmental and neuropsychiatric disorders. In this study we examine the neural substrates of social cognition and face processing in a group of healthy young adults to examine the neural substrates of social cognition. Fifty-seven undergraduates completed a battery of social cognition tasks and were assessed with electroencephalography (EEG) during a face-perception task. A subset (N=22) were administered a face-perception task during functional magnetic resonance imaging. Variance in the N170 EEG was predicted by social attribution performance and by a quantitative measure of empathy. Neurally, face processing was more bilateral in females than in males. Variance in fMRI voxel count in the face-sensitive fusiform gyrus was predicted by quantitative measures of social behavior, including the Social Responsiveness Scale (SRS) and the Empathizing Quotient. When measured as a quantitative trait, social behaviors in typical and pathological populations share common neural pathways. The results highlight the importance of viewing neurodevelopmental and neuropsychiatric disorders as spectrum phenomena that may be informed by studies of the normal distribution of relevant traits in the general population. Copyright © 2014 Elsevier B.V. All rights reserved.

Neural dynamics of morphological processing in spoken word comprehension: Laterality and automaticity

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Caroline M. Whiting

2013-11-01

Full Text Available Rapid and automatic processing of grammatical complexity is argued to take place during speech comprehension, engaging a left-lateralised fronto-temporal language network. Here we address how neural activity in these regions is modulated by the grammatical properties of spoken words. We used combined magneto- and electroencephalography (MEG, EEG to delineate the spatiotemporal patterns of activity that support the recognition of morphologically complex words in English with inflectional (-s and derivational (-er affixes (e.g. bakes, baker. The mismatch negativity (MMN, an index of linguistic memory traces elicited in a passive listening paradigm, was used to examine the neural dynamics elicited by morphologically complex words. Results revealed an initial peak 130-180 ms after the deviation point with a major source in left superior temporal cortex. The localisation of this early activation showed a sensitivity to two grammatical properties of the stimuli: 1 the presence of morphological complexity, with affixed words showing increased left-laterality compared to non-affixed words; and 2 the grammatical category, with affixed verbs showing greater left-lateralisation in inferior frontal gyrus compared to affixed nouns (bakes vs. beaks. This automatic brain response was additionally sensitive to semantic coherence (the meaning of the stem vs. the meaning of the whole form in fronto-temporal regions. These results demonstrate that the spatiotemporal pattern of neural activity in spoken word processing is modulated by the presence of morphological structure, predominantly engaging the left-hemisphere’s fronto-temporal language network, and does not require focused attention on the linguistic input.

Genetic tracing of the gustatory and trigeminal neural pathways originating from T1R3-expressing taste receptor cells and solitary chemoreceptor cells.

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Ohmoto, Makoto; Matsumoto, Ichiro; Yasuoka, Akihito; Yoshihara, Yoshihiro; Abe, Keiko

2008-08-01

We established transgenic mouse lines expressing a transneuronal tracer, wheat germ agglutinin (WGA), under the control of mouse T1R3 gene promoter/enhancer. In the taste buds, WGA transgene was faithfully expressed in T1R3-positive sweet/umami taste receptor cells. WGA protein was transferred not laterally to the synapse-bearing, sour-responsive type III cells in the taste buds but directly to a subset of neurons in the geniculate and nodose/petrosal ganglia, and further conveyed to a rostro-central region of the nucleus of solitary tract. In addition, WGA was expressed in solitary chemoreceptor cells in the nasal epithelium and transferred along the trigeminal sensory pathway to the brainstem neurons. The solitary chemoreceptor cells endogenously expressed T1R3 together with bitter taste receptors T2Rs. This result shows an exceptional signature of receptor expression. Thus, the t1r3-WGA transgenic mice revealed the sweet/umami gustatory pathways from taste receptor cells and the trigeminal neural pathway from solitary chemoreceptor cells.

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition.

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Scherf, K Suzanne; Elbich, Daniel B; Motta-Mena, Natalie V

2017-01-01

There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women.

Investigating the Influence of Biological Sex on the Behavioral and Neural Basis of Face Recognition

Science.gov (United States)

2017-01-01

Abstract There is interest in understanding the influence of biological factors, like sex, on the organization of brain function. We investigated the influence of biological sex on the behavioral and neural basis of face recognition in healthy, young adults. In behavior, there were no sex differences on the male Cambridge Face Memory Test (CFMT)+ or the female CFMT+ (that we created) and no own-gender bias (OGB) in either group. We evaluated the functional topography of ventral stream organization by measuring the magnitude and functional neural size of 16 individually defined face-, two object-, and two place-related regions bilaterally. There were no sex differences in any of these measures of neural function in any of the regions of interest (ROIs) or in group level comparisons. These findings reveal that men and women have similar category-selective topographic organization in the ventral visual pathway. Next, in a separate task, we measured activation within the 16 face-processing ROIs specifically during recognition of target male and female faces. There were no sex differences in the magnitude of the neural responses in any face-processing region. Furthermore, there was no OGB in the neural responses of either the male or female participants. Our findings suggest that face recognition behavior, including the OGB, is not inherently sexually dimorphic. Face recognition is an essential skill for navigating human social interactions, which is reflected equally in the behavior and neural architecture of men and women. PMID:28497111

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

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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

Auditory pathways and processes: implications for neuropsychological assessment and diagnosis of children and adolescents.

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Bailey, Teresa

2010-01-01

Neuroscience research on auditory processing pathways and their behavioral and electrophysiological correlates has taken place largely outside the field of clinical neuropsychology. Deviations and disruptions in auditory pathways in children and adolescents result in a well-documented range of developmental and learning impairments frequently referred for neuropsychological evaluation. This review is an introduction to research from the last decade. It describes auditory cortical and subcortical pathways and processes and relates recent research to specific conditions and questions neuropsychologists commonly encounter. Auditory processing disorders' comorbidity with ADHD and language-based disorders and research addressing the challenges of assessment and differential diagnosis are discussed.

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

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Takiyama, Ken

2017-12-01

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

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

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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.

Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream.

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Güçlü, Umut; van Gerven, Marcel A J

2015-07-08

Converging evidence suggests that the primate ventral visual pathway encodes increasingly complex stimulus features in downstream areas. We quantitatively show that there indeed exists an explicit gradient for feature complexity in the ventral pathway of the human brain. This was achieved by mapping thousands of stimulus features of increasing complexity across the cortical sheet using a deep neural network. Our approach also revealed a fine-grained functional specialization of downstream areas of the ventral stream. Furthermore, it allowed decoding of representations from human brain activity at an unsurpassed degree of accuracy, confirming the quality of the developed approach. Stimulus features that successfully explained neural responses indicate that population receptive fields were explicitly tuned for object categorization. This provides strong support for the hypothesis that object categorization is a guiding principle in the functional organization of the primate ventral stream. Copyright © 2015 the authors 0270-6474/15/3510005-10$15.00/0.

Learning-induced neural plasticity of speech processing before birth.

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

2013-09-10

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.

Neural network post-processing of grayscale optical correlator

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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.

Abnormal regional spontaneous neural activity in visual pathway in retinal detachment patients: a resting-state functional MRI study

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Huang X

2017-11-01

Full Text Available Xin Huang,1,2,* Dan Li,3,* Hai-Jun Li,3 Yu-Lin Zhong,1 Shelby Freeberg,4 Jing Bao,1 Xian-Jun Zeng,3 Yi Shao1 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Jiangxi Province Clinical Ophthalmology Institute, Nanchang, Jiangxi, People’s Republic of China; 2Department of Ophthalmology, Eye Center, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, Hubei, People’s Republic of China; 3Department of Radiology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 4Department of Ophthalmology, University of Florida, Gainesville, FL, USA *These authors contributed equally to this work Objective: The aim of the study was to investigate changes of brain neural homogeneity in retinal detachment (RD patients using the regional homogeneity (ReHo method to understand their relationships with clinical features. Materials and methods: A total of 30 patients with RD (16 men and 14 women, and 30 healthy controls (HCs (16 men and 14 women closely matched in age and sex were recruited. Resting-state functional magnetic resonance imaging scans were performed for all subjects. The ReHo method was used to investigate the brain regional neural homogeneity. Patients with RD were distinguished from HCs by receiver operating characteristic curve. The relationships between the mean ReHo signal values in many brain regions and clinical features in RD patients were calculated by Pearson correlation analysis. Results: Compared with HCs, RD patients had significantly decreased ReHo values in the right occipital lobe, right superior temporal gyrus, bilateral cuneus and left middle frontal gyrus. Moreover, we found that the mean ReHo signal of the bilateral cuneus showed positive relationships with the duration of the RD (r=0.392, P=0.032. Conclusion: The RD patients showed brain neural homogeneity dysfunction in the visual pathway, which may underline the pathological mechanism

Investigating Circadian Rhythmicity in Pain Sensitivity Using a Neural Circuit Model for Spinal Cord Processing of Pain

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Crodelle, Jennifer; Piltz, Sofia Helena; Booth, Victoria

2017-01-01

Primary processing of painful stimulation occurs in the dorsal horn of the spinal cord. In this article, we introduce mathematical models of the neural circuitry in the dorsal horn responsible for processing nerve fiber inputs from noxious stimulation of peripheral tissues and generating the resu......Primary processing of painful stimulation occurs in the dorsal horn of the spinal cord. In this article, we introduce mathematical models of the neural circuitry in the dorsal horn responsible for processing nerve fiber inputs from noxious stimulation of peripheral tissues and generating...... the resultant pain signal. The differential equation models describe the average firing rates of excitatory and inhibitory interneuron populations, as well as the wide dynamic range (WDR) neurons whose output correlates with the pain signal. The temporal profile of inputs on the different afferent nerve fibers...

[GSH fermentation process modeling using entropy-criterion based RBF neural network model].

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Tan, Zuoping; Wang, Shitong; Deng, Zhaohong; Du, Guocheng

2008-05-01

The prediction accuracy and generalization of GSH fermentation process modeling are often deteriorated by noise existing in the corresponding experimental data. In order to avoid this problem, we present a novel RBF neural network modeling approach based on entropy criterion. It considers the whole distribution structure of the training data set in the parameter learning process compared with the traditional MSE-criterion based parameter learning, and thus effectively avoids the weak generalization and over-learning. Then the proposed approach is applied to the GSH fermentation process modeling. Our results demonstrate that this proposed method has better prediction accuracy, generalization and robustness such that it offers a potential application merit for the GSH fermentation process modeling.

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

Directory of Open Access Journals (Sweden)

Han-Gyol eYi

2014-10-01

Full Text Available 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.

Genetic Algorithms vs. Artificial Neural Networks in Economic Forecasting Process

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Nicolae Morariu

2008-01-01

Full Text Available This paper aims to describe the implementa-tion of a neural network and a genetic algorithm system in order to forecast certain economic indicators of a free market economy. In a free market economy forecasting process precedes the economic planning (a management function, providing important information for the result of the last process. Forecasting represents a starting point in setting of target for a firm, an organization or even a branch of the economy. Thus, the forecasting method used can influence in a significant mode the evolution of an entity. In the following we will describe the forecasting of an economic indicator using two intelligent systems. The difference between the results obtained by this two systems are described in chapter IV.

How right is left? Handedness modulates neural responses during morphosyntactic processing.

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Grey, Sarah; Tanner, Darren; van Hell, Janet G

2017-08-15

Most neurocognitive models of language processing generally assume population-wide homogeneity in the neural mechanisms used during language comprehension, yet individual differences are known to influence these neural mechanisms. In this study, we focus on handedness as an individual difference hypothesized to affect language comprehension. Left-handers and right-handers with a left-handed blood relative, or familial sinistrals, are hypothesized to process language differently than right-handers with no left-handed relatives (Hancock and Bever, 2013; Ullman, 2004). Yet, left-handers are often excluded from neurocognitive language research, and familial sinistrality in right-handers is often not taken into account. In the current study we used event-related potentials to test morphosyntactic processing in three groups that differed in their handedness profiles: left-handers (LH), right-handers with a left-handed blood relative (RH FS+), and right-handers with no reported left-handed blood relative (RH FS-; both right-handed groups were previously tested by Tanner and Van Hell, 2014). Results indicated that the RH FS- group showed only P600 responses during morphosyntactic processing whereas the LH and RH FS+ groups showed biphasic N400-P600 patterns. N400s in LH and RH FS+ groups are consistent with theories that associate left-handedness (self or familial) with increased reliance on lexical/semantic mechanisms during language processing. Inspection of individual-level results illustrated that variability in RH FS- individuals' morphosyntactic processing was remarkably low: most individuals were P600-dominant. In contrast, LH and RH FS+ individuals showed marked variability in brain responses, which was similar for both groups: half of individuals were N400-dominant and half were P600-dominant. Our findings have implications for neurocognitive models of language that have been largely formulated around data from only right-handers without accounting for familial

Differential coding of reward and movement information in the dorsomedial striatal direct and indirect pathways.

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Shin, Jung Hwan; Kim, Dohoung; Jung, Min Whan

2018-01-26

The direct and indirect pathways of the basal ganglia have long been thought to mediate behavioral promotion and inhibition, respectively. However, this classic dichotomous model has been recently challenged. To better understand neural processes underlying reward-based learning and movement control, we recorded from direct (dSPNs) and indirect (iSPNs) pathway spiny projection neurons in the dorsomedial striatum of D1-Cre and D2-Cre mice performing a probabilistic Pavlovian conditioning task. dSPNs tend to increase activity while iSPNs decrease activity as a function of reward value, suggesting the striatum represents value in the relative activity levels of dSPNs versus iSPNs. Lick offset-related activity increase is largely dSPN selective, suggesting dSPN involvement in suppressing ongoing licking behavior. Rapid responses to negative outcome and previous reward-related responses are more frequent among iSPNs than dSPNs, suggesting stronger contributions of iSPNs to outcome-dependent behavioral adjustment. These findings provide new insights into striatal neural circuit operations.

Ethanol production from steam exploded rapeseed straw and the process simulation using artificial neural networks

DEFF Research Database (Denmark)

Talebnia, Farid; Mighani, Moein; Rahimnejad, Mostafa

2015-01-01

and 67% of maximum theoretical value. Next, data of the experimental runs were exploited for modeling the processes by artificial neural networks (ANNs) and performance of the developed models was evaluated. The ANN-based models showed a great potential for time-course prediction of the studied processes....... Efficiency of the joint network for simulating the whole process was also determined and promising results were obtained....

Neural reflex pathways in intestinal inflammation: hypotheses to viable therapy

NARCIS (Netherlands)

Willemze, Rose A.; Luyer, Misha D.; Buurman, Wim A.; de Jonge, Wouter J.

2015-01-01

Studies in neuroscience and immunology have clarified much of the anatomical and cellular basis for bidirectional interactions between the nervous and immune systems. As with other organs, intestinal immune responses and the development of immunity seems to be modulated by neural reflexes.

"Thinking about not-thinking": neural correlates of conceptual processing during Zen meditation.

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Giuseppe Pagnoni

2008-09-01

Full Text Available Recent neuroimaging studies have identified a set of brain regions that are metabolically active during wakeful rest and consistently deactivate in a variety the performance of demanding tasks. This "default network" has been functionally linked to the stream of thoughts occurring automatically in the absence of goal-directed activity and which constitutes an aspect of mental behavior specifically addressed by many meditative practices. Zen meditation, in particular, is traditionally associated with a mental state of full awareness but reduced conceptual content, to be attained via a disciplined regulation of attention and bodily posture. Using fMRI and a simplified meditative condition interspersed with a lexical decision task, we investigated the neural correlates of conceptual processing during meditation in regular Zen practitioners and matched control subjects. While behavioral performance did not differ between groups, Zen practitioners displayed a reduced duration of the neural response linked to conceptual processing in regions of the default network, suggesting that meditative training may foster the ability to control the automatic cascade of semantic associations triggered by a stimulus and, by extension, to voluntarily regulate the flow of spontaneous mentation.

A longitudinal study investigating neural processing of speech envelope modulation rates in children with (a family risk for) dyslexia.

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De Vos, Astrid; Vanvooren, Sophie; Vanderauwera, Jolijn; Ghesquière, Pol; Wouters, Jan

2017-08-01

Recent evidence suggests that a fundamental deficit in the synchronization of neural oscillations to temporal information in speech may underlie phonological processing problems in dyslexia. Since previous studies were performed cross-sectionally in school-aged children or adults, developmental aspects of neural auditory processing in relation to reading acquisition and dyslexia remain to be investigated. The present longitudinal study followed 68 children during development from pre-reader (5 years old) to beginning reader (7 years old) and more advanced reader (9 years old). Thirty-six children had a family risk for dyslexia and 14 children eventually developed dyslexia. EEG recordings of auditory steady-state responses to 4 and 20 Hz modulations, corresponding to syllable and phoneme rates, were collected at each point in time. Our results demonstrate an increase in neural synchronization to phoneme-rate modulations around the onset of reading acquisition. This effect was negatively correlated with later reading and phonological skills, indicating that children who exhibit the largest increase in neural synchronization to phoneme rates, develop the poorest reading and phonological skills. Accordingly, neural synchronization to phoneme-rate modulations was found to be significantly higher in beginning and more advanced readers with dyslexia. We found no developmental effects regarding neural synchronization to syllable rates, nor any effects of a family risk for dyslexia. Altogether, our findings suggest that the onset of reading instruction coincides with an increase in neural responsiveness to phoneme-rate modulations, and that the extent of this increase is related to (the outcome of) reading development. Hereby, dyslexic children persistently demonstrate atypically high neural synchronization to phoneme rates from the beginning of reading acquisition onwards. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aberrant signaling pathways in medulloblastomas: a stem cell connection

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Carolina Oliveira Rodini

2010-12-01

Full Text Available Medulloblastoma is a highly malignant primary tumor of the central nervous system. It represents the most frequent type of solid tumor and the leading cause of death related to cancer in early childhood. Current treatment includes surgery, chemotherapy and radiotherapy which may lead to severe cognitive impairment and secondary brain tumors. New perspectives for therapeutic development have emerged with the identification of stem-like cells displaying high tumorigenic potential and increased radio- and chemo-resistance in gliomas. Under the cancer stem cell hypothesis, transformation of neural stem cells and/or granular neuron progenitors of the cerebellum are though to be involved in medulloblastoma development. Dissecting the genetic and molecular alterations associated with this process should significantly impact both basic and applied cancer research. Based on cumulative evidences in the fields of genetics and molecular biology of medulloblastomas, we discuss the possible involvement of developmental signaling pathways as critical biochemical switches determining normal neurogenesis or tumorigenesis. From the clinical viewpoint, modulation of signaling pathways such as TGFβ, regulating neural stem cell proliferation and tumor development, might be attempted as an alternative strategy for future drug development aiming at more efficient therapies and improved clinical outcome of patients with pediatric brain cancers.

A potential neural substrate for processing functional classes of complex acoustic signals.

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Isabelle George

Full Text Available Categorization is essential to all cognitive processes, but identifying the neural substrates underlying categorization processes is a real challenge. Among animals that have been shown to be able of categorization, songbirds are particularly interesting because they provide researchers with clear examples of categories of acoustic signals allowing different levels of recognition, and they possess a system of specialized brain structures found only in birds that learn to sing: the song system. Moreover, an avian brain nucleus that is analogous to the mammalian secondary auditory cortex (the caudo-medial nidopallium, or NCM has recently emerged as a plausible site for sensory representation of birdsong, and appears as a well positioned brain region for categorization of songs. Hence, we tested responses in this non-primary, associative area to clear and distinct classes of songs with different functions and social values, and for a possible correspondence between these responses and the functional aspects of songs, in a highly social songbird species: the European starling. Our results clearly show differential neuronal responses to the ethologically defined classes of songs, both in the number of neurons responding, and in the response magnitude of these neurons. Most importantly, these differential responses corresponded to the functional classes of songs, with increasing activation from non-specific to species-specific and from species-specific to individual-specific sounds. These data therefore suggest a potential neural substrate for sorting natural communication signals into categories, and for individual vocal recognition of same-species members. Given the many parallels that exist between birdsong and speech, these results may contribute to a better understanding of the neural bases of speech.

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

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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. © 2014 Wiley Periodicals, Inc.

Disruption of visual awareness during the attentional blink is reflected by selective disruption of late-stage neural processing

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Harris, Joseph A.; McMahon, Alex R.; Woldorff, Marty G.

2015-01-01

Any information represented in the brain holds the potential to influence behavior. It is therefore of broad interest to determine the extent and quality of neural processing of stimulus input that occurs with and without awareness. The attentional blink is a useful tool for dissociating neural and behavioral measures of perceptual visual processing across conditions of awareness. The extent of higher-order visual information beyond basic sensory signaling that is processed during the attentional blink remains controversial. To determine what neural processing at the level of visual-object identification occurs in the absence of awareness, electrophysiological responses to images of faces and houses were recorded both within and outside of the attentional blink period during a rapid serial visual presentation (RSVP) stream. Electrophysiological results were sorted according to behavioral performance (correctly identified targets versus missed targets) within these blink and non-blink periods. An early index of face-specific processing (the N170, 140–220 ms post-stimulus) was observed regardless of whether the subject demonstrated awareness of the stimulus, whereas a later face-specific effect with the same topographic distribution (500–700 ms post-stimulus) was only seen for accurate behavioral discrimination of the stimulus content. The present findings suggest a multi-stage process of object-category processing, with only the later phase being associated with explicit visual awareness. PMID:23859644

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

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Martina Reske

Full Text Available Approximately 10% of young adults report non-medical use of stimulants (cocaine, amphetamine, methylphenidate, which puts them at risk for the development of dependence. This fMRI study investigates whether subjects at early stages of stimulant use show altered decision making processing.158 occasional stimulants users (OSU and 50 comparison subjects (CS performed a "risky gains" decision making task during which they could select safe options (cash in 20 cents or gamble them for double or nothing in two consecutive gambles (win or lose 40 or 80 cents, "risky decisions". The primary analysis focused on risky versus safe decisions. Three secondary analyses were conducted: First, a robust regression examined the effect of lifetime exposure to stimulants and marijuana; second, subgroups of OSU with >1000 (n = 42, or <50 lifetime marijuana uses (n = 32, were compared to CS with <50 lifetime uses (n = 46 to examine potential marijuana effects; third, brain activation associated with behavioral adjustment following monetary losses was probed.There were no behavioral differences between groups. OSU showed attenuated activation across risky and safe decisions in prefrontal cortex, insula, and dorsal striatum, exhibited lower anterior cingulate cortex (ACC and dorsal striatum activation for risky decisions and greater inferior frontal gyrus activation for safe decisions. Those OSU with relatively more stimulant use showed greater dorsal ACC and posterior insula attenuation. In comparison, greater lifetime marijuana use was associated with less neural differentiation between risky and safe decisions. OSU who chose more safe responses after losses exhibited similarities with CS relative to those preferring risky options.Individuals at risk for the development of stimulant use disorders presented less differentiated neural processing of risky and safe options. Specifically, OSU show attenuated brain response in regions critical for performance monitoring

Neural activity and emotional processing following military deployment: Effects of mild traumatic brain injury and posttraumatic stress disorder.

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Zuj, Daniel V; Felmingham, Kim L; Palmer, Matthew A; Lawrence-Wood, Ellie; Van Hooff, Miranda; Lawrence, Andrew J; Bryant, Richard A; McFarlane, Alexander C

2017-11-01

Posttraumatic Stress Disorder (PTSD) and mild traumatic brain injury (mTBI) are common comorbidities during military deployment that affect emotional brain processing, yet few studies have examined the independent effects of mTBI and PTSD. The purpose of this study was to examine distinct differences in neural responses to emotional faces in mTBI and PTSD. Twenty-one soldiers reporting high PTSD symptoms were compared to 21 soldiers with low symptoms, and 16 soldiers who reported mTBI-consistent injury and symptoms were compared with 16 soldiers who did not sustain an mTBI. Participants viewed emotional face expressions while their neural activity was recorded (via event-related potentials) prior to and following deployment. The high-PTSD group displayed increased P1 and P2 amplitudes to threatening faces at post-deployment compared to the low-PTSD group. In contrast, the mTBI group displayed reduced face-specific processing (N170 amplitude) to all facial expressions compared to the no-mTBI group. Here, we identified distinctive neural patterns of emotional face processing, with attentional biases towards threatening faces in PTSD, and reduced emotional face processing in mTBI. Copyright © 2017 Elsevier Inc. All rights reserved.

A hybrid artificial neural network as a software sensor for optimal control of a wastewater treatment process.

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Choi, D J; Park, H

2001-11-01

For control and automation of biological treatment processes, lack of reliable on-line sensors to measure water quality parameters is one of the most important problems to overcome. Many parameters cannot be measured directly with on-line sensors. The accuracy of existing hardware sensors is also not sufficient and maintenance problems such as electrode fouling often cause trouble. This paper deals with the development of software sensor techniques that estimate the target water quality parameter from other parameters using the correlation between water quality parameters. We focus our attention on the preprocessing of noisy data and the selection of the best model feasible to the situation. Problems of existing approaches are also discussed. We propose a hybrid neural network as a software sensor inferring wastewater quality parameter. Multivariate regression, artificial neural networks (ANN), and a hybrid technique that combines principal component analysis as a preprocessing stage are applied to data from industrial wastewater processes. The hybrid ANN technique shows an enhancement of prediction capability and reduces the overfitting problem of neural networks. The result shows that the hybrid ANN technique can be used to extract information from noisy data and to describe the nonlinearity of complex wastewater treatment processes.

Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing.

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Delis, Ioannis; Dmochowski, Jacek P; Sajda, Paul; Wang, Qi

2018-03-23

Many real-world decisions rely on active sensing, a dynamic process for directing our sensors (e.g. eyes or fingers) across a stimulus to maximize information gain. Though ecologically pervasive, limited work has focused on identifying neural correlates of the active sensing process. In tactile perception, we often make decisions about an object/surface by actively exploring its shape/texture. Here we investigate the neural correlates of active tactile decision-making by simultaneously measuring electroencephalography (EEG) and finger kinematics while subjects interrogated a haptic surface to make perceptual judgments. Since sensorimotor behavior underlies decision formation in active sensing tasks, we hypothesized that the neural correlates of decision-related processes would be detectable by relating active sensing to neural activity. Novel brain-behavior correlation analysis revealed that three distinct EEG components, localizing to right-lateralized occipital cortex (LOC), middle frontal gyrus (MFG), and supplementary motor area (SMA), respectively, were coupled with active sensing as their activity significantly correlated with finger kinematics. To probe the functional role of these components, we fit their single-trial-couplings to decision-making performance using a hierarchical-drift-diffusion-model (HDDM), revealing that the LOC modulated the encoding of the tactile stimulus whereas the MFG predicted the rate of information integration towards a choice. Interestingly, the MFG disappeared from components uncovered from control subjects performing active sensing but not required to make perceptual decisions. By uncovering the neural correlates of distinct stimulus encoding and evidence accumulation processes, this study delineated, for the first time, the functional role of cortical areas in active tactile decision-making. Copyright © 2018 Elsevier Inc. All rights reserved.

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

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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.

Toward an Interdisciplinary Understanding of Sensory Dysfunction in Autism Spectrum Disorder: An Integration of the Neural and Symptom Literatures

OpenAIRE

Schauder, Kimberly B.; Bennetto, Loisa

2016-01-01

Sensory processing differences have long been associated with autism spectrum disorder (ASD), and they have recently been added to the diagnostic criteria for the disorder. The focus on sensory processing in ASD research has increased substantially in the last decade. This research has been approached from two different perspectives: the first focuses on characterizing the symptoms that manifest in response to real world sensory stimulation, and the second focuses on the neural pathways and m...

Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

Science.gov (United States)

Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

2017-07-28

Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural analysis of bovine ovaries ultrasound images in the identification process of the corpus luteum

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Górna, K.; Jaśkowski, B. M.; Okoń, P.; Czechlowski, M.; Koszela, K.; Zaborowicz, M.; Idziaszek, P.

2017-07-01

The aim of the paper is to shown the neural image analysis as a method useful for identifying the development stage of the domestic bovine corpus luteum on digital USG (UltraSonoGraphy) images. Corpus luteum (CL) is a transient endocrine gland that develops after ovulation from the follicle secretory cells. The aim of CL is the production of progesterone, which regulates many reproductive functions. In the presented studies, identification of the corpus luteum was carried out on the basis of information contained in ultrasound digital images. Development stage of the corpus luteum was considered in two aspects: just before and middle of domination phase and luteolysis and degradation phase. Prior to the classification, the ultrasound images have been processed using a GLCM (Gray Level Co-occurence Matrix). To generate a classification model, a Neural Networks module implemented in the STATISTICA was used. Five representative parameters describing the ultrasound image were used as learner variables. On the output of the artificial neural network was generated information about the development stage of the corpus luteum. Results of this study indicate that neural image analysis combined with GLCM texture analysis may be a useful tool for identifying the bovine corpus luteum in the context of its development phase. Best-generated artificial neural network model was the structure of MLP (Multi Layer Perceptron) 5:5-17-1:1.

The neural basis of emotions varies over time: different regions go with onset- and offset-bound processes underlying emotion intensity.

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Résibois, Maxime; Verduyn, Philippe; Delaveau, Pauline; Rotgé, Jean-Yves; Kuppens, Peter; Van Mechelen, Iven; Fossati, Philippe

2017-08-01

According to theories of emotion dynamics, emotions unfold across two phases in which different types of processes come to the fore: emotion onset and emotion offset. Differences in onset-bound processes are reflected by the degree of explosiveness or steepness of the response at onset, and differences in offset-bound processes by the degree of accumulation or intensification of the subsequent response. Whether onset- and offset-bound processes have distinctive neural correlates and, hence, whether the neural basis of emotions varies over time, still remains unknown. In the present fMRI study, we address this question using a recently developed paradigm that allows to disentangle explosiveness and accumulation. Thirty-one participants were exposed to neutral and negative social feedback, and asked to reflect on its contents. Emotional intensity while reading and thinking about the feedback was measured with an intensity profile tracking approach. Using non-negative matrix factorization, the resulting profile data were decomposed in explosiveness and accumulation components, which were subsequently entered as continuous regressors of the BOLD response. It was found that the neural basis of emotion intensity shifts as emotions unfold over time with emotion explosiveness and accumulation having distinctive neural correlates. © The Author (2017). Published by Oxford University Press.

The Correlation among Neural Dynamic Processing of Conflict Control, Testosterone and Cortisol Levels in 10-Year-Old Children.

Science.gov (United States)

Shangguan, Fangfang; Liu, Tongran; Liu, Xiuying; Shi, Jiannong

2017-01-01

Cognitive control is related to goal-directed self-regulation abilities, which is fundamental for human development. Conflict control includes the neural processes of conflict monitoring and conflict resolution. Testosterone and cortisol are essential hormones for the development of cognitive functions. However, there are no studies that have investigated the correlation of these two hormones with conflict control in preadolescents. In this study, we aimed to explore whether testosterone, cortisol, and testosterone/cortisol ratio worked differently for preadolescent's conflict control processes in varied conflict control tasks. Thirty-two 10-year-old children (16 boys and 16 girls) were enrolled. They were instructed to accomplish three conflict control tasks with different conflict dimensions, including the Flanker, Simon, and Stroop tasks, and electrophysiological signals were recorded. Salivary samples were collected from each child. The testosterone and cortisol levels were determined by enzyme-linked immunosorbent assay. The electrophysiological results showed that the incongruent trials induced greater N2/N450 and P3/SP responses than the congruent trials during neural processes of conflict monitoring and conflict resolution in the Flanker and Stroop tasks. The hormonal findings showed that (1) the testosterone/cortisol ratio was correlated with conflict control accuracy and conflict resolution in the Flanker task; (2) the testosterone level was associated with conflict control performance and neural processing of conflict resolution in the Stroop task; (3) the cortisol level was correlated with conflict control performance and neural processing of conflict monitoring in the Simon task. In conclusion, in 10-year-old children, the fewer processes a task needs, the more likely there is an association between the T/C ratios and the behavioral and brain response, and the dual-hormone effects on conflict resolution may be testosterone-driven in the Stroop and

The Correlation among Neural Dynamic Processing of Conflict Control, Testosterone and Cortisol Levels in 10-Year-Old Children

Directory of Open Access Journals (Sweden)

Fangfang Shangguan

2017-06-01

Full Text Available Cognitive control is related to goal-directed self-regulation abilities, which is fundamental for human development. Conflict control includes the neural processes of conflict monitoring and conflict resolution. Testosterone and cortisol are essential hormones for the development of cognitive functions. However, there are no studies that have investigated the correlation of these two hormones with conflict control in preadolescents. In this study, we aimed to explore whether testosterone, cortisol, and testosterone/cortisol ratio worked differently for preadolescent’s conflict control processes in varied conflict control tasks. Thirty-two 10-year-old children (16 boys and 16 girls were enrolled. They were instructed to accomplish three conflict control tasks with different conflict dimensions, including the Flanker, Simon, and Stroop tasks, and electrophysiological signals were recorded. Salivary samples were collected from each child. The testosterone and cortisol levels were determined by enzyme-linked immunosorbent assay. The electrophysiological results showed that the incongruent trials induced greater N2/N450 and P3/SP responses than the congruent trials during neural processes of conflict monitoring and conflict resolution in the Flanker and Stroop tasks. The hormonal findings showed that (1 the testosterone/cortisol ratio was correlated with conflict control accuracy and conflict resolution in the Flanker task; (2 the testosterone level was associated with conflict control performance and neural processing of conflict resolution in the Stroop task; (3 the cortisol level was correlated with conflict control performance and neural processing of conflict monitoring in the Simon task. In conclusion, in 10-year-old children, the fewer processes a task needs, the more likely there is an association between the T/C ratios and the behavioral and brain response, and the dual-hormone effects on conflict resolution may be testosterone-driven in

PROCESSING THE INFORMATION CONTENT ON THE BASIS OF FUZZY NEURAL MODEL OF DECISION MAKING

Directory of Open Access Journals (Sweden)

Nina V. Komleva

2013-01-01

Full Text Available The article is devoted to the issues of mathematical modeling of the decision-making process of information content processing based on the fuzzy neural network TSK. Integral rating assessment of the content, which is necessary for taking a decision about its further usage, is made depended on varying characteristics. Mechanism for building individual trajectory and forming individual competence is provided to make the intellectual content search.

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

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

2017-07-15

Neural networks that span the medial temporal lobe (MTL), prefrontal cortex, and posterior cortical regions are essential to episodic memory function in humans. Encoding and retrieval are supported by the engagement of both distinct neural pathways across the cortex and common structures within the medial temporal lobes. However, the degree to which memory performance can be determined by neural processing that is common to encoding and retrieval remains to be determined. To identify neural signatures of successful memory function, we administered a delayed free-recall task to 187 neurosurgical patients implanted with subdural or intraparenchymal depth electrodes. We developed multivariate classifiers to identify patterns of spectral power across the brain that independently predicted successful episodic encoding and retrieval. During encoding and retrieval, patterns of increased high frequency activity in prefrontal, MTL, and inferior parietal cortices, accompanied by widespread decreases in low frequency power across the brain predicted successful memory function. Using a cross-decoding approach, we demonstrate the ability to predict memory function across distinct phases of the free-recall task. Furthermore, we demonstrate that classifiers that combine information from both encoding and retrieval states can outperform task-independent models. These findings suggest that the engagement of a core memory network during either encoding or retrieval shapes the ability to remember the past, despite distinct neural interactions that facilitate encoding and retrieval. Copyright © 2017 Elsevier Inc. All rights reserved.

Fluid Intelligence and Automatic Neural Processes in Facial Expression Perception

DEFF Research Database (Denmark)

Liu, Tongran; Xiao, Tong; Li, Xiaoyan

2015-01-01

The relationship between human fluid intelligence and social-emotional abilities has been a topic of considerable interest. The current study investigated whether adolescents with different intellectual levels had different automatic neural processing of facial expressions. Two groups of adolescent...... males were enrolled: a high IQ group and an average IQ group. Age and parental socioeconomic status were matched between the two groups. Participants counted the numbers of the central cross changes while paired facial expressions were presented bilaterally in an oddball paradigm. There were two.......2). Participants were required to concentrate on the primary task of counting the central cross changes and to ignore the expressions to ensure that facial expression processing was automatic. Event-related potentials (ERPs) were obtained during the tasks. The visual mismatch negativity (vMMN) components were...

Dissecting the hypothalamic pathways that underlie innate behaviors.

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Zha, Xi; Xu, Xiaohong

2015-12-01

Many complex behaviors that do not require learning are displayed and are termed innate. Although traditionally the subject matter of ethology, innate behaviors offer a unique entry point for neuroscientists to dissect the physiological mechanisms governing complex behaviors. Since the last century, converging evidence has implicated the hypothalamus as the central brain area that controls innate behaviors. Recent studies using cutting-edge tools have revealed that genetically-defined populations of neurons residing in distinct hypothalamic nuclei and their associated neural pathways regulate the initiation and maintenance of diverse behaviors including feeding, sleep, aggression, and parental care. Here, we review the newly-defined hypothalamic pathways that regulate each innate behavior. In addition, emerging general principles of the neural control of complex behaviors are discussed.

Neural Processing of Emotional Musical and Nonmusical Stimuli in Depression.

Directory of Open Access Journals (Sweden)

Rebecca J Lepping

Full Text Available 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.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.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.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.

Neural Networks for Optimal Control

DEFF Research Database (Denmark)

Sørensen, O.

1995-01-01

Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process.......Two neural networks are trained to act as an observer and a controller, respectively, to control a non-linear, multi-variable process....

Prediction of Increasing Production Activities using Combination of Query Aggregation on Complex Events Processing and Neural Network

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Achmad Arwan

2016-07-01

Full Text Available AbstrakProduksi, order, penjualan, dan pengiriman adalah serangkaian event yang saling terkait dalam industri manufaktur. Selanjutnya hasil dari event tersebut dicatat dalam event log. Complex Event Processing adalah metode yang digunakan untuk menganalisis apakah terdapat pola kombinasi peristiwa tertentu (peluang/ancaman yang terjadi pada sebuah sistem, sehingga dapat ditangani secara cepat dan tepat. Jaringan saraf tiruan adalah metode yang digunakan untuk mengklasifikasi data peningkatan proses produksi. Hasil pencatatan rangkaian proses yang menyebabkan peningkatan produksi digunakan sebagai data latih untuk mendapatkan fungsi aktivasi dari jaringan saraf tiruan. Penjumlahan hasil catatan event log dimasukkan ke input jaringan saraf tiruan untuk perhitungan nilai aktivasi. Ketika nilai aktivasi lebih dari batas yang ditentukan, maka sistem mengeluarkan sinyal untuk meningkatkan produksi, jika tidak, sistem tetap memantau kejadian. Hasil percobaan menunjukkan bahwa akurasi dari metode ini adalah 77% dari 39 rangkaian aliran event.Kata kunci: complex event processing, event, jaringan saraf tiruan, prediksi peningkatan produksi, proses. AbstractProductions, orders, sales, and shipments are series of interrelated events within manufacturing industry. Further these events were recorded in the event log. Complex event processing is a method that used to analyze whether there are patterns of combinations of certain events (opportunities / threats that occur in a system, so it can be addressed quickly and appropriately. Artificial neural network is a method that we used to classify production increase activities. The series of events that cause the increase of the production used as a dataset to train the weight of neural network which result activation value. An aggregate stream of events inserted into the neural network input to compute the value of activation. When the value is over a certain threshold (the activation value results

Neural substrates of decision-making.

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Broche-Pérez, Y; Herrera Jiménez, L F; Omar-Martínez, E

2016-06-01

Decision-making is the process of selecting a course of action from among 2 or more alternatives by considering the potential outcomes of selecting each option and estimating its consequences in the short, medium and long term. The prefrontal cortex (PFC) has traditionally been considered the key neural structure in decision-making process. However, new studies support the hypothesis that describes a complex neural network including both cortical and subcortical structures. The aim of this review is to summarise evidence on the anatomical structures underlying the decision-making process, considering new findings that support the existence of a complex neural network that gives rise to this complex neuropsychological process. Current evidence shows that the cortical structures involved in decision-making include the orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), and dorsolateral prefrontal cortex (DLPFC). This process is assisted by subcortical structures including the amygdala, thalamus, and cerebellum. Findings to date show that both cortical and subcortical brain regions contribute to the decision-making process. The neural basis of decision-making is a complex neural network of cortico-cortical and cortico-subcortical connections which includes subareas of the PFC, limbic structures, and the cerebellum. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.

Dynamic changes in the inner ear function and vestibular neural pathway related to the progression of labyrinthine infarction in patient with an anterior inferior cerebellar artery infarction.

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Kim, Duk Rim; Lee, Hyo-Jeong; Kim, Hyung-Jong; Hong, Sung Kwang

2011-12-01

To describe changes in the inner ear function and the vestibular neural pathway according to the progression of a labyrinthine infarction in a patient with an anterior inferior cerebellar artery (AICA) infarction. A 58-year-old woman with hypertension who presented with isolated inner ear symptoms similar to those of endolymphatic hydrops but finally progressed to an AICA infarction. Serial neurotologic testing according to progression to an AICA infarction and antiplatelet therapy. Radiologic findings and neurotologic parameters, including pure tone audiogram thresholds, spontaneous nystagmus, summating potentials/action potentials on electrocochleography, interaural amplitude difference on the vestibular-evoked myogenic potential test, canal paresis and fixation index on the bithermal caloric test, and gain on oculomotor tests. Our patient initially presented with sudden hearing loss and was diagnosed with an acute AICA infarction on a follow up MRI. Dynamic change in neurotologic testing was observed during disease progression. The vertigo and motion intolerance improved gradually after antiplatelet therapy. Changes in the clinical profile, which were documented during a transition from isolated labyrinthine ischemia to an AICA infarction, suggest that sensitivity to an ischemic injury is variable in different components of the labyrinthine organs in addition to providing a new insight into the response of vestibular neural pathway to ischemic injury.

Laterality Biases to Chimeric Faces in Asperger Syndrome: What Is Right about Face-Processing?

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Ashwin, Chris; Wheelwright, Sally; Baron-Cohen, Simon

2005-01-01

People show a left visual field (LVF) bias for faces, i.e., involving the right hemisphere of the brain. Lesion and neuroimaging studies confirm the importance of the right-hemisphere and suggest separable neural pathways for processing facial identity vs. emotions. We investigated the hemispheric processing of faces in adults with and without…

White matter pathways in persistent developmental stuttering: Lessons from tractography.

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Kronfeld-Duenias, Vered; Civier, Oren; Amir, Ofer; Ezrati-Vinacour, Ruth; Ben-Shachar, Michal

2018-03-01

Fluent speech production relies on the coordinated processing of multiple brain regions. This highlights the role of neural pathways that connect distinct brain regions in producing fluent speech. Here, we aim to investigate the role of the white matter pathways in persistent developmental stuttering (PDS), where speech fluency is disrupted. We use diffusion weighted imaging and tractography to compare the white matter properties between adults who do and do not stutter. We compare the diffusion properties along 18 major cerebral white matter pathways. We complement the analysis with an overview of the methodology and a roadmap of the pathways implicated in PDS according to the existing literature. We report differences in the microstructural properties of the anterior callosum, the right inferior longitudinal fasciculus and the right cingulum in people who stutter compared with fluent controls. Persistent developmental stuttering is consistently associated with differences in bilateral distributed networks. We review evidence showing that PDS involves differences in bilateral dorsal fronto-temporal and fronto-parietal pathways, in callosal pathways, in several motor pathways and in basal ganglia connections. This entails an important role for long range white matter pathways in this disorder. Using a wide-lens analysis, we demonstrate differences in additional, right hemispheric pathways, which go beyond the replicable findings in the literature. This suggests that the affected circuits may extend beyond the known language and motor pathways. Copyright © 2017 Elsevier Inc. All rights reserved.

Neural pulse frequency modulation of an exponentially correlated Gaussian process

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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.

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

Science.gov (United States)

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

Directory of Open Access Journals (Sweden)

Bardia Yousefi

2014-01-01

Full Text Available Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility.

Synergic Functions of miRNAs Determine Neuronal Fate of Adult Neural Stem Cells

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Meritxell Pons-Espinal

2017-04-01

Full Text Available Summary: Adult neurogenesis requires the precise control of neuronal versus astrocyte lineage determination in neural stem cells. While microRNAs (miRNAs are critically involved in this step during development, their actions in adult hippocampal neural stem cells (aNSCs has been unclear. As entry point to address that question we chose DICER, an endoribonuclease essential for miRNA biogenesis and other RNAi-related processes. By specific ablation of Dicer in aNSCs in vivo and in vitro, we demonstrate that miRNAs are required for the generation of new neurons, but not astrocytes, in the adult murine hippocampus. Moreover, we identify 11 miRNAs, of which 9 have not been previously characterized in neurogenesis, that determine neurogenic lineage fate choice of aNSCs at the expense of astrogliogenesis. Finally, we propose that the 11 miRNAs sustain adult hippocampal neurogenesis through synergistic modulation of 26 putative targets from different pathways. : In this article, the authors demonstrate that Dicer-dependent miRNAs are required for the generation of new neurons, but not astrocytes, in the adult hippocampus in vivo and in vitro. The authors identify a new set of 11 miRNAs that synergistically converge on multiple targets in different pathways to sustain neurogenic lineage fate commitment in aNSCs. Keywords: mouse, hippocampus, neural stem cells, fate choice, adult neurogenesis, astrogliogenesis, DICER, microRNAs, synergy

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

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Crabtree, Gregg W.; Gogos, Joseph A.

2014-01-01

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations. PMID:25505409

Adaptive neural network controller for the molten steel level control of strip casting processes

International Nuclear Information System (INIS)

Chen, Hung Yi; Huang, Shiuh Jer

2010-01-01

The twin-roll strip casting process is a steel-strip production method which combines continuous casting and hot rolling processes. The production line from molten liquid steel to the final steel-strip is shortened and the production cost is reduced significantly as compared to conventional continuous casting. The quality of strip casting process depends on many process parameters, such as molten steel level in the pool, solidification position, and roll gap. Their relationships are complex and the strip casting process has the properties of nonlinear uncertainty and time-varying characteristics. It is difficult to establish an accurate process model for designing a model-based controller to monitor the strip quality. In this paper, a model-free adaptive neural network controller is developed to overcome this problem. The proposed control strategy is based on a neural network structure combined with a sliding-mode control scheme. An adaptive rule is employed to on-line adjust the weights of radial basis functions by using the reaching condition of a specified sliding surface. This surface has the on-line learning ability to respond to the system's nonlinear and time-varying behaviors. Since this model-free controller has a simple control structure and small number of control parameters, it is easy to implement. Simulation results, based on a semi experimental system dynamic model and parameters, are executed to show the control performance of the proposed intelligent controller. In addition, the control performance is compared with that of a traditional Pid controller

Taurine Induces Proliferation of Neural Stem Cells and Synapse Development in the Developing Mouse Brain

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Shivaraj, Mattu Chetana; Marcy, Guillaume; Low, Guoliang; Ryu, Jae Ryun; Zhao, Xianfeng; Rosales, Francisco J.; Goh, Eyleen L. K.

2012-01-01

Taurine is a sulfur-containing amino acid present in high concentrations in mammalian tissues. It has been implicated in several processes involving brain development and neurotransmission. However, the role of taurine in hippocampal neurogenesis during brain development is still unknown. Here we show that taurine regulates neural progenitor cell (NPC) proliferation in the dentate gyrus of the developing brain as well as in cultured early postnatal (P5) hippocampal progenitor cells and hippocampal slices derived from P5 mice brains. Taurine increased cell proliferation without having a significant effect on neural differentiation both in cultured P5 NPCs as well as cultured hippocampal slices and in vivo. Expression level analysis of synaptic proteins revealed that taurine increases the expression of Synapsin 1 and PSD 95. We also found that taurine stimulates the phosphorylation of ERK1/2 indicating a possible role of the ERK pathway in mediating the changes that we observed, especially in proliferation. Taken together, our results demonstrate a role for taurine in neural stem/progenitor cell proliferation in developing brain and suggest the involvement of the ERK1/2 pathways in mediating these actions. Our study also shows that taurine influences the levels of proteins associated with synapse development. This is the first evidence showing the effect of taurine on early postnatal neuronal development using a combination of in vitro, ex-vivo and in vivo systems. PMID:22916184

Rac1 Guides Porf-2 to Wnt Pathway to Mediate Neural Stem Cell Proliferation

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Xi-Tao Yang

2017-06-01

Full Text Available The molecular and cellular mechanisms underlying the anti-proliferative effects of preoptic regulator factor 2 (Porf-2 on neural stem cells (NSCs remain largely unknown. Here, we found that Porf-2 inhibits the activity of ras-related C3 botulinum toxin substrate 1 (Rac1 protein in hippocampus-derived rat NSCs. Reduced Rac1 activity impaired the nuclear translocation of β-catenin, ultimately causing a repression of NSCs proliferation. Porf-2 knockdown enhanced NSCs proliferation but not in the presence of small molecule inhibitors of Rac1 or Wnt. At the same time, the repression of NSCs proliferation caused by Porf-2 overexpression was counteracted by small molecule activators of Rac1 or Wnt. By using a rat optic nerve crush model, we observed that Porf-2 knockdown enhanced the recovery of visual function. In particular, optic nerve injury in rats led to increased Wnt family member 3a (Wnt3a protein expression, which we found responsible for enhancing Porf-2 knockdown-induced NSCs proliferation. These findings suggest that Porf-2 exerts its inhibitory effect on NSCs proliferation via Rac1-Wnt/β-catenin pathway. Porf-2 may therefore represent and interesting target for optic nerve injury recovery and therapy.

Neural correlates of sublexical processing in phonological working memory.

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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

Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

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Mori, Shinichiro

2017-08-01

To develop real-time image processing for image-guided radiotherapy, we evaluated several neural network models for use with different imaging modalities, including X-ray fluoroscopic image denoising. Setup images of prostate cancer patients were acquired with two oblique X-ray fluoroscopic units. Two types of residual network were designed: a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN). We changed the convolutional kernel size and number of convolutional layers for both networks, and the number of pooling and upsampling layers for rCAE. The ground-truth image was applied to the contrast-limited adaptive histogram equalization (CLAHE) method of image processing. Network models were trained to keep the quality of the output image close to that of the ground-truth image from the input image without image processing. For image denoising evaluation, noisy input images were used for the training. More than 6 convolutional layers with convolutional kernels >5×5 improved image quality. However, this did not allow real-time imaging. After applying a pair of pooling and upsampling layers to both networks, rCAEs with >3 convolutions each and rCNNs with >12 convolutions with a pair of pooling and upsampling layers achieved real-time processing at 30 frames per second (fps) with acceptable image quality. Use of our suggested network achieved real-time image processing for contrast enhancement and image denoising by the use of a conventional modern personal computer. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

High school music classes enhance the neural processing of speech

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Adam eTierney

2013-12-01

Full Text Available 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 two years of group music classes in high school enhance the subcortical 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 subcortical responses of the music training group were earlier than at pretraining, 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.

Endogenous testosterone levels are associated with neural activity in men with schizophrenia during facial emotion processing.

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Ji, Ellen; Weickert, Cynthia Shannon; Lenroot, Rhoshel; Catts, Stanley V; Vercammen, Ans; White, Christopher; Gur, Raquel E; Weickert, Thomas W

2015-06-01

Growing evidence suggests that testosterone may play a role in the pathophysiology of schizophrenia given that testosterone has been linked to cognition and negative symptoms in schizophrenia. Here, we determine the extent to which serum testosterone levels are related to neural activity in affective processing circuitry in men with schizophrenia. Functional magnetic resonance imaging was used to measure blood-oxygen-level-dependent signal changes as 32 healthy controls and 26 people with schizophrenia performed a facial emotion identification task. Whole brain analyses were performed to determine regions of differential activity between groups during processing of angry versus non-threatening faces. A follow-up ROI analysis using a regression model in a subset of 16 healthy men and 16 men with schizophrenia was used to determine the extent to which serum testosterone levels were related to neural activity. Healthy controls displayed significantly greater activation than people with schizophrenia in the left inferior frontal gyrus (IFG). There was no significant difference in circulating testosterone levels between healthy men and men with schizophrenia. Regression analyses between activation in the IFG and circulating testosterone levels revealed a significant positive correlation in men with schizophrenia (r=.63, p=.01) and no significant relationship in healthy men. This study provides the first evidence that circulating serum testosterone levels are related to IFG activation during emotion face processing in men with schizophrenia but not in healthy men, which suggests that testosterone levels modulate neural processes relevant to facial emotion processing that may interfere with social functioning in men with schizophrenia. Crown Copyright © 2015. Published by Elsevier B.V. All rights reserved.

Direct process estimation from tomographic data using artificial neural systems

Science.gov (United States)

Mohamad-Saleh, Junita; Hoyle, Brian S.; Podd, Frank J.; Spink, D. M.

2001-07-01

The paper deals with the goal of component fraction estimation in multicomponent flows, a critical measurement in many processes. Electrical capacitance tomography (ECT) is a well-researched sensing technique for this task, due to its low-cost, non-intrusion, and fast response. However, typical systems, which include practicable real-time reconstruction algorithms, give inaccurate results, and existing approaches to direct component fraction measurement are flow-regime dependent. In the investigation described, an artificial neural network approach is used to directly estimate the component fractions in gas-oil, gas-water, and gas-oil-water flows from ECT measurements. A 2D finite- element electric field model of a 12-electrode ECT sensor is used to simulate ECT measurements of various flow conditions. The raw measurements are reduced to a mutually independent set using principal components analysis and used with their corresponding component fractions to train multilayer feed-forward neural networks (MLFFNNs). The trained MLFFNNs are tested with patterns consisting of unlearned ECT simulated and plant measurements. Results included in the paper have a mean absolute error of less than 1% for the estimation of various multicomponent fractions of the permittivity distribution. They are also shown to give improved component fraction estimation compared to a well known direct ECT method.

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

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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…

Neural Correlates of Sensory Substitution in Vestibular Pathways Following Complete Vestibular Loss

Science.gov (United States)

Sadeghi, Soroush G.; Minor, Lloyd B.; Cullen, Kathleen E.

2012-01-01

Sensory substitution is the term typically used in reference to sensory prosthetic devices designed to replace input from one defective modality with input from another modality. Such devices allow an alternative encoding of sensory information that is no longer directly provided by the defective modality in a purposeful and goal-directed manner. The behavioral recovery that follows complete vestibular loss is impressive and has long been thought to take advantage of a natural form of sensory substitution in which head motion information is no longer provided by vestibular inputs, but instead by extra-vestibular inputs such as proprioceptive and motor efference copy signals. Here we examined the neuronal correlates of this behavioral recovery after complete vestibular loss in alert behaving monkeys (Macaca mulata). We show for the first time that extra-vestibular inputs substitute for the vestibular inputs to stabilize gaze at the level of single neurons in the VOR premotor circuitry. The summed weighting of neck proprioceptive and efference copy information was sufficient to explain simultaneously observed behavioral improvements in gaze stability. Furthermore, by altering correspondence between intended and actual head movement we revealed a four-fold increase in the weight of neck motor efference copy signals consistent with the enhanced behavioral recovery observed when head movements are voluntary versus unexpected. Thus, taken together our results provide direct evidence that the substitution by extra-vestibular inputs in vestibular pathways provides a neural correlate for the improvements in gaze stability that are observed following the total loss of vestibular inputs. PMID:23077054

Acoustic richness modulates the neural networks supporting intelligible speech processing.

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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. Copyright © 2015 Elsevier

Vision and visual information processing in cubozoans

DEFF Research Database (Denmark)

Bielecki, Jan

relationship between acuity and light sensitivity. Animals have evolved a wide variety of solutions to this problem such as folded membranes, to have a larger receptive surfaces, and lenses, to focus light onto the receptive membranes. On the neural capacity side, complex eyes demand huge processing network...... animals in a wide range of behaviours. It is intuitive that a complex eye is energetically very costly, not only in components but also in neural involvement. The increasing behavioural demand added pressure on design specifications and eye evolution is considered an optimization of the inverse...... fit their need. Visual neuroethology integrates optics, sensory equipment, neural network and motor output to explain how animals can perform behaviour in response to a specific visual stimulus. In this doctoral thesis, I will elucidate the individual steps in a visual neuroethological pathway...

Neural processing of high and low spatial frequency information in faces changes across development: qualitative changes in face processing during adolescence.

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Peters, Judith C; Vlamings, Petra; Kemner, Chantal

2013-05-01

Face perception in adults depends on skilled processing of interattribute distances ('configural' processing), which is disrupted for faces presented in inverted orientation (face inversion effect or FIE). Children are not proficient in configural processing, and this might relate to an underlying immaturity to use facial information in low spatial frequency (SF) ranges, which capture the coarse information needed for configural processing. We hypothesized that during adolescence a shift from use of high to low SF information takes place. Therefore, we studied the influence of SF content on neural face processing in groups of children (9-10 years), adolescents (14-15 years) and young adults (21-29 years) by measuring event-related potentials (ERPs) to upright and inverted faces which varied in SF content. Results revealed that children show a neural FIE in early processing stages (i.e. P1; generated in early visual areas), suggesting a superficial, global facial analysis. In contrast, ERPs of adults revealed an FIE at later processing stages (i.e. N170; generated in face-selective, higher visual areas). Interestingly, adolescents showed FIEs in both processing stages, suggesting a hybrid developmental stage. Furthermore, adolescents and adults showed FIEs for stimuli containing low SF information, whereas such effects were driven by both low and high SF information in children. These results indicate that face processing has a protracted maturational course into adolescence, and is dependent on changes in SF processing. During adolescence, sensitivity to configural cues is developed, which aids the fast and holistic processing that is so special for faces. © 2013 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Left hemispheric dominance during auditory processing in a noisy environment

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Ross Bernhard

2007-11-01

Full Text Available Abstract Background In daily life, we are exposed to different sound inputs simultaneously. During neural encoding in the auditory pathway, neural activities elicited by these different sounds interact with each other. In the present study, we investigated neural interactions elicited by masker and amplitude-modulated test stimulus in primary and non-primary human auditory cortex during ipsi-lateral and contra-lateral masking by means of magnetoencephalography (MEG. Results We observed significant decrements of auditory evoked responses and a significant inter-hemispheric difference for the N1m response during both ipsi- and contra-lateral masking. Conclusion The decrements of auditory evoked neural activities during simultaneous masking can be explained by neural interactions evoked by masker and test stimulus in peripheral and central auditory systems. The inter-hemispheric differences of N1m decrements during ipsi- and contra-lateral masking reflect a basic hemispheric specialization contributing to the processing of complex auditory stimuli such as speech signals in noisy environments.

Neural Networks as a Tool for Georadar Data Processing

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Szymczyk Piotr

2015-12-01

Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

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

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Chad Edward Forbes

2012-11-01

Full Text Available 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, 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.

Complex-Valued Neural Networks

CERN Document Server

Hirose, Akira

2012-01-01

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate courses in electrical engineering, informatics, control engineering, mechanics, robotics, bioengineering, and other relevant fields. In the second edition the recent trends in CVNNs research are included, resulting in e.g. almost a doubled number of references. The parametron invented in 1954 is also referred to with discussion on analogy and disparity. Also various additional arguments on the advantages of the complex-valued neural networks enhancing the difference to real-valued neural networks are given in various sections. The book is useful for those beginning their studies, for instance, in adaptive signal processing for highly functional sensing and imaging, control in unknown and changing environment, robotics inspired by human neural systems, and brain-like information processing, as well as interdisciplina...

Xenopus reduced folate carrier regulates neural crest development epigenetically.

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Jiejing Li

Full Text Available Folic acid deficiency during pregnancy causes birth neurocristopathic malformations resulting from aberrant development of neural crest cells. The Reduced folate carrier (RFC is a membrane-bound receptor for facilitating transfer of reduced folate into the cells. RFC knockout mice are embryonic lethal and develop multiple malformations, including neurocristopathies. Here we show that XRFC is specifically expressed in neural crest tissues in Xenopus embryos and knockdown of XRFC by specific morpholino results in severe neurocristopathies. Inhibition of RFC blocked the expression of a series of neural crest marker genes while overexpression of RFC or injection of 5-methyltetrahydrofolate expanded the neural crest territories. In animal cap assays, knockdown of RFC dramatically reduced the mono- and trimethyl-Histone3-K4 levels and co-injection of the lysine methyltransferase hMLL1 largely rescued the XRFC morpholino phenotype. Our data revealed that the RFC mediated folate metabolic pathway likely potentiates neural crest gene expression through epigenetic modifications.

The neural circuits that generate tics in Tourette's syndrome.

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Wang, Zhishun; Maia, Tiago V; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S

2011-12-01

The purpose of this study was to examine neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette's syndrome. Functional magnetic resonance imaging data were acquired from 13 individuals with Tourette's syndrome and 21 healthy comparison subjects during spontaneous or simulated tics. Independent component analysis with hierarchical partner matching was used to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. Granger causality was used to investigate causal interactions among these regions. The Tourette's syndrome group exhibited stronger neural activity and interregional causality than healthy comparison subjects throughout all portions of the motor pathway, including the sensorimotor cortex, putamen, pallidum, and substantia nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette's syndrome group was stronger during spontaneous tics than during voluntary tics in the somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette's syndrome group than in the healthy comparison group within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (the caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may result in their failure to control tic behaviors or the premonitory urges that generate them. Our findings, taken together, suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico

Neural networks mediating sentence reading in the deaf

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Elizabeth Ann Hirshorn

2014-06-01

Full Text Available The present work addresses the neural bases of sentence reading in deaf populations. To better understand the relative role of deafness and English knowledge in shaping the neural networks that mediate sentence reading, three populations with different degrees of English knowledge and depth of hearing loss were included – deaf signers, oral deaf and hearing individuals. The three groups were matched for reading comprehension and scanned while reading sentences. A similar neural network of left perisylvian areas was observed, supporting the view of a shared network of areas for reading despite differences in hearing and English knowledge. However, differences were observed, in particular in the auditory cortex, with deaf signers and oral deaf showing greatest bilateral superior temporal gyrus (STG recruitment as compared to hearing individuals. Importantly, within deaf individuals, the same STG area in the left hemisphere showed greater recruitment as hearing loss increased. To further understand the functional role of such auditory cortex re-organization after deafness, connectivity analyses were performed from the STG regions identified above. Connectivity from the left STG toward areas typically associated with semantic processing (BA45 and thalami was greater in deaf signers and in oral deaf as compared to hearing. In contrast, connectivity from left STG toward areas identified with speech-based processing was greater in hearing and in oral deaf as compared to deaf signers. These results support the growing literature indicating recruitment of auditory areas after congenital deafness for visually-mediated language functions, and establish that both auditory deprivation and language experience shape its functional reorganization. Implications for differential reliance on semantic vs. phonological pathways during reading in the three groups is discussed.

Transcriptional profiling of adult neural stem-like cells from the human brain.

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Cecilie Jonsgar Sandberg

Full Text Available There is a great potential for the development of new cell replacement strategies based on adult human neural stem-like cells. However, little is known about the hierarchy of cells and the unique molecular properties of stem- and progenitor cells of the nervous system. Stem cells from the adult human brain can be propagated and expanded in vitro as free floating neurospheres that are capable of self-renewal and differentiation into all three cell types of the central nervous system. Here we report the first global gene expression study of adult human neural stem-like cells originating from five human subventricular zone biopsies (mean age 42, range 33-60. Compared to adult human brain tissue, we identified 1,189 genes that were significantly up- and down-regulated in adult human neural stem-like cells (1% false discovery rate. We found that adult human neural stem-like cells express stem cell markers and have reduced levels of markers that are typical of the mature cells in the nervous system. We report that the genes being highly expressed in adult human neural stem-like cells are associated with developmental processes and the extracellular region of the cell. The calcium signaling pathway and neuroactive ligand-receptor interactions are enriched among the most differentially regulated genes between adult human neural stem-like cells and adult human brain tissue. We confirmed the expression of 10 of the most up-regulated genes in adult human neural stem-like cells in an additional sample set that included adult human neural stem-like cells (n = 6, foetal human neural stem cells (n = 1 and human brain tissues (n = 12. The NGFR, SLITRK6 and KCNS3 receptors were further investigated by immunofluorescence and shown to be heterogeneously expressed in spheres. These receptors could potentially serve as new markers for the identification and characterisation of neural stem- and progenitor cells or as targets for manipulation of cellular

Hedgehog signaling pathway in neuroblastoma differentiation.

Science.gov (United States)

Souzaki, Ryota; Tajiri, Tatsuro; Souzaki, Masae; Kinoshita, Yoshiaki; Tanaka, Sakura; Kohashi, Kenichi; Oda, Yoshinao; Katano, Mitsuo; Taguchi, Tomoaki

2010-12-01

The hedgehog (Hh) signaling pathway is activated in some adult cancers. On the other hand, the Hh signaling pathway plays an important role in the development of the neural crest in embryos. The aim of this study is to show the activation of Hh signaling pathway in neuroblastoma (NB), a pediatric malignancy arising from neural crest cells, and to reveal the meaning of the Hh signaling pathway in NB development. This study analyzed the expression of Sonic hedgehog (Shh), GLI1, and Patched 1 (Ptch1), transactivators of Hh signaling pathway, by immunohistochemistry in 82 NB and 10 ganglioneuroblastoma cases. All 92 cases were evaluated for the status of MYCN amplification. Of the 92 cases, 67 (73%) were positive for Shh, 62 cases (67%) were positive for GLI1, and 73 cases (79%) were positive for Ptch1. Only 2 (10%) of the 20 cases with MYCN amplification were positive for Shh and GLI1, and 4 cases (20%) were positive for Ptch1 (MYCN amplification vs no MYCN amplification, P ≦ .01). The percentage of GLI1-positive cells in the cases with INSS stage 1 without MYCN amplification was significantly higher than that with INSS stage 4. Of 72 cases without MYCN amplification, 60 were GLI1-positive. Twelve cases were GLI1-negative, and the prognosis of the GLI1-positive cases was significantly better than that of the GLI1-negative cases (P = .015). Most of NBs without MYCN amplification were positive for Shh, GLI1, and Ptch1. In the cases without MYCN amplification, the high expression of GLI1 was significantly associated with early clinical stage and a good prognosis of the patients. In contrast to adult cancers, the activation of the Hh signaling pathway in NB may be associated with the differentiation of the NB. Copyright © 2010 Elsevier Inc. All rights reserved.

Overweight adolescents' brain response to sweetened beverages mirrors addiction pathways.

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Feldstein Ewing, Sarah W; Claus, Eric D; Hudson, Karen A; Filbey, Francesca M; Yakes Jimenez, Elizabeth; Lisdahl, Krista M; Kong, Alberta S

2017-08-01

Many adolescents struggle with overweight/obesity, which exponentially increases in the transition to adulthood. Overweight/obesity places youth at risk for serious health conditions, including type 2 diabetes. In adults, neural substrates implicated in addiction (e.g., orbitofrontal cortex (OFC), striatum, amygdala, and ventral tegmental area) have been found to be relevant to risk for overweight/obesity. In this study, we examined three hypotheses to disentangle the potential overlap between addiction and overweight/obesity processing by examining (1) brain response to high vs. low calorie beverages, (2) the strength of correspondence between biometrics, including body mass index (BMI) and insulin resistance, and brain response and (3) the relationship between a measure of food addiction and brain response using an established fMRI gustatory cue exposure task with a sample of overweight/obese youth (M age = 16.46; M BMI = 33.1). Greater BOLD response was observed across the OFC, inferior frontal gyrus (IFG), nucleus accumbens, right amygdala, and additional frontoparietal and temporal regions in neural processing of high vs. low calorie beverages. Further, BMI scores positively correlated with BOLD activation in the high calorie > low calorie contrast in the right postcentral gyrus and central operculum. Insulin resistance positively correlated with BOLD activation across the bilateral middle/superior temporal gyrus, left OFC, and superior parietal lobe. No relationships were observed between measures of food addiction and brain response. These findings support the activation of parallel addiction-related neural pathways in adolescents' high calorie processing, while also suggesting the importance of refining conceptual and neurocognitive models to fit this developmental period.

Additive Feed Forward Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1999-01-01

This paper demonstrates a method to control a non-linear, multivariable, noisy process using trained neural networks. The basis for the method is a trained neural network controller acting as the inverse process model. A training method for obtaining such an inverse process model is applied....... A suitable 'shaped' (low-pass filtered) reference is used to overcome problems with excessive control action when using a controller acting as the inverse process model. The control concept is Additive Feed Forward Control, where the trained neural network controller, acting as the inverse process model......, is placed in a supplementary pure feed-forward path to an existing feedback controller. This concept benefits from the fact, that an existing, traditional designed, feedback controller can be retained without any modifications, and after training the connection of the neural network feed-forward controller...

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Yu-Chen eChan

2016-04-01

Full Text Available 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

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

Science.gov (United States)

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

2013-04-01

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

Differences in neural responses to reward and punishment processing between anorexia nervosa subtypes: An fMRI study.

Science.gov (United States)

Murao, Ema; Sugihara, Genichi; Isobe, Masanori; Noda, Tomomi; Kawabata, Michiko; Matsukawa, Noriko; Takahashi, Hidehiko; Murai, Toshiya; Noma, Shun'ichi

2017-09-01

Anorexia nervosa (AN) includes the restricting (AN-r) and binge-eating/purging (AN-bp) subtypes, which have been reported to differ regarding their underlying pathophysiologies as well as their behavioral patterns. However, the differences in neural mechanisms of reward systems between AN subtypes remain unclear. The aim of the present study was to explore differences in the neural processing of reward and punishment between AN subtypes. Twenty-three female patients with AN (11 AN-r and 12 AN-bp) and 20 healthy women underwent functional magnetic resonance imaging while performing a monetary incentive delay task. Whole-brain one-way analysis of variance was conducted to test between-group differences. There were significant group differences in brain activation in the rostral anterior cingulate cortex and right posterior insula during loss anticipation, with increased brain activation in the AN-bp group relative to the AN-r and healthy women groups. No significant differences were found during gain anticipation. AN-bp patients showed altered neural responses to punishment in brain regions implicated in emotional arousal. Our findings suggest that individuals with AN-bp are more sensitive to potential punishment than individuals with AN-r and healthy individuals at the neural level. The present study provides preliminary evidence that there are neurobiological differences between AN subtypes with regard to the reward system, especially punishment processing. © 2017 The Authors. Psychiatry and Clinical Neurosciences © 2017 Japanese Society of Psychiatry and Neurology.

SYNAPTIC DEPRESSION IN DEEP NEURAL NETWORKS FOR SPEECH PROCESSING.

Science.gov (United States)

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.

A pilot study investigating changes in neural processing after mindfulness training in elite athletes.

Science.gov (United States)

Haase, Lori; May, April C; Falahpour, Maryam; Isakovic, Sara; Simmons, Alan N; Hickman, Steven D; Liu, Thomas T; Paulus, Martin P

2015-01-01

The ability to pay close attention to the present moment can be a crucial factor for performing well in a competitive situation. Training mindfulness is one approach to potentially improve elite athletes' ability to focus their attention on the present moment. However, virtually nothing is known about whether these types of interventions alter neural systems that are important for optimal performance. This pilot study examined whether an intervention aimed at improving mindfulness [Mindful Performance Enhancement, Awareness and Knowledge (mPEAK)] changes neural activation patterns during an interoceptive challenge. Participants completed a task involving anticipation and experience of loaded breathing during functional magnetic resonance imaging recording. There were five main results following mPEAK training: (1) elite athletes self-reported higher levels of interoceptive awareness and mindfulness and lower levels of alexithymia; (2) greater insula and anterior cingulate cortex (ACC) activation during anticipation and post-breathing load conditions; (3) increased ACC activation during the anticipation condition was associated with increased scores on the describing subscale of the Five Facet Mindfulness Questionnaire; (4) increased insula activation during the post-load condition was associated with decreases in the Toronto Alexithymia Scale identifying feelings subscale; (5) decreased resting state functional connectivity between the PCC and the right medial frontal cortex and the ACC. Taken together, this pilot study suggests that mPEAK training may lead to increased attention to bodily signals and greater neural processing during the anticipation and recovery from interoceptive perturbations. This association between attention to and processing of interoceptive afferents may result in greater adaptation during stressful situations in elite athletes.

Computational modeling of neural plasticity for self-organization of neural networks.

Science.gov (United States)

Chrol-Cannon, Joseph; Jin, Yaochu

2014-11-01

Self-organization in biological nervous systems during the lifetime is known to largely occur through a process of plasticity that is dependent upon the spike-timing activity in connected neurons. In the field of computational neuroscience, much effort has been dedicated to building up computational models of neural plasticity to replicate experimental data. Most recently, increasing attention has been paid to understanding the role of neural plasticity in functional and structural neural self-organization, as well as its influence on the learning performance of neural networks for accomplishing machine learning tasks such as classification and regression. Although many ideas and hypothesis have been suggested, the relationship between the structure, dynamics and learning performance of neural networks remains elusive. The purpose of this article is to review the most important computational models for neural plasticity and discuss various ideas about neural plasticity's role. Finally, we suggest a few promising research directions, in particular those along the line that combines findings in computational neuroscience and systems biology, and their synergetic roles in understanding learning, memory and cognition, thereby bridging the gap between computational neuroscience, systems biology and computational intelligence. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Methodology for automatic process of the fired ceramic tile's internal defect using IR images and artificial neural network

OpenAIRE

Andrade, Roberto Márcio de; Eduardo, Alexandre Carlos

2011-01-01

In the ceramic industry, rarely testing systems were employed to on-line detect the presence of defects in ceramic tiles. This paper is concerned with the problem of automatic inspection of ceramic tiles using Infrared Images and Artificial Neural Network (ANN). The performance of the technique has been evaluated theoretically and experimentally from laboratory and on line tile samples. It has been performed system for IR image processing and, utilizing an Artificial Neural Network (ANN), det...

Bioprinting for Neural Tissue Engineering.

Science.gov (United States)

Knowlton, Stephanie; Anand, Shivesh; Shah, Twisha; Tasoglu, Savas

2018-01-01

Bioprinting is a method by which a cell-encapsulating bioink is patterned to create complex tissue architectures. Given the potential impact of this technology on neural research, we review the current state-of-the-art approaches for bioprinting neural tissues. While 2D neural cultures are ubiquitous for studying neural cells, 3D cultures can more accurately replicate the microenvironment of neural tissues. By bioprinting neuronal constructs, one can precisely control the microenvironment by specifically formulating the bioink for neural tissues, and by spatially patterning cell types and scaffold properties in three dimensions. We review a range of bioprinted neural tissue models and discuss how they can be used to observe how neurons behave, understand disease processes, develop new therapies and, ultimately, design replacement tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Use of neural network based auto-associative memory as a data compressor for pre-processing optical emission spectra in gas thermometry with the help of neural network

International Nuclear Information System (INIS)

Dolenko, S.A.; Filippov, A.V.; Pal, A.F.; Persiantsev, I.G.; Serov, A.O.

2003-01-01

Determination of temperature from optical emission spectra is an inverse problem that is often very difficult to solve, especially when substantial noise is present. One of the means that can be used to solve such a problem is a neural network trained on the results of modeling of spectra at different temperatures (Dolenko, et al., in: I.C. Parmee (Ed.), Adaptive Computing in Design and Manufacture, Springer, London, 1998, p. 345). Reducing the dimensionality of the input data prior to application of neural network can increase the accuracy and stability of temperature determination. In this study, such pre-processing is performed with another neural network working as an auto-associative memory with a narrow bottleneck in the hidden layer. The improvement in the accuracy and stability of temperature determination in presence of noise is demonstrated on model spectra similar to those recorded in a DC-discharge CVD reactor

Neural components of altruistic punishment

Directory of Open Access Journals (Sweden)

Emily eDu

2015-02-01

Full Text Available Altruistic punishment, which occurs when an individual incurs a cost to punish in response to unfairness or a norm violation, may play a role in perpetuating cooperation. The neural correlates underlying costly punishment have only recently begun to be explored. Here we review the current state of research on the neural basis of altruism from the perspectives of costly punishment, emphasizing the importance of characterizing elementary neural processes underlying a decision to punish. In particular, we emphasize three cognitive processes that contribute to the decision to altruistically punish in most scenarios: inequity aversion, cost-benefit calculation, and social reference frame to distinguish self from others. Overall, we argue for the importance of understanding the neural correlates of altruistic punishment with respect to the core computations necessary to achieve a decision to punish.

A probablistic neural network classification system for signal and image processing

Energy Technology Data Exchange (ETDEWEB)

Bowman, B. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

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

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

Science.gov (United States)

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.

Multidimensional analysis of the abnormal neural oscillations associated with lexical processing in schizophrenia.

Science.gov (United States)

Xu, Tingting; Stephane, Massoud; Parhi, Keshab K

2013-04-01

The neural mechanisms of language abnormalities, the core symptoms in schizophrenia, remain unclear. In this study, a new experimental paradigm, combining magnetoencephalography (MEG) techniques and machine intelligence methodologies, was designed to gain knowledge about the frequency, brain location, and time of occurrence of the neural oscillations that are associated with lexical processing in schizophrenia. The 248-channel MEG recordings were obtained from 12 patients with schizophrenia and 10 healthy controls, during a lexical processing task, where the patients discriminated correct from incorrect lexical stimuli that were visually presented. Event-related desynchronization/synchronization (ERD/ERS) was computed along the frequency, time, and space dimensions combined, that resulted in a large spectral-spatial-temporal ERD/ERS feature set. Machine intelligence techniques were then applied to select a small subset of oscillation patterns that are abnormal in patients with schizophrenia, according to their discriminating power in patient and control classification. Patients with schizophrenia showed abnormal ERD/ERS patterns during both lexical encoding and post-encoding periods. The top-ranked features were located at the occipital and left frontal-temporal areas, and covered a wide frequency range, including δ (1-4 Hz), α (8-12 Hz), β (12-32 Hz), and γ (32-48 Hz) bands. These top features could discriminate the patient group from the control group with 90.91% high accuracy, which demonstrates significant brain oscillation abnormalities in patients with schizophrenia at the specific frequency, time, and brain location indicated by these top features. As neural oscillation abnormality may be due to the mechanisms of the disease, the spectral, spatial, and temporal content of the discriminating features can offer useful information for helping understand the physiological basis of the language disorder in schizophrenia, as well as the pathology of the

The PINK1-Parkin pathway is involved in the regulation of mitochondrial remodeling process

International Nuclear Information System (INIS)

Park, Jeehye; Lee, Gina; Chung, Jongkyeong

2009-01-01

The two Parkinson's disease (PD) genes, PTEN-induced kinase 1 (PINK1) and parkin, are linked in a common pathway which affects mitochondrial integrity and function. However, it is still not known what this pathway does in the mitochondria. Therefore, we investigated its physiological function in Drosophila. Because Drosophila PINK1 and parkin mutants show changes in mitochondrial morphology in both indirect flight muscles and dopaminergic neurons, we here investigated whether the PINK1-Parkin pathway genetically interacts with the regulators of mitochondrial fusion and fission such as Drp1, which promotes mitochondrial fission, and Opa1 or Marf, which induces mitochondrial fusion. Surprisingly, DrosophilaPINK1 and parkin mutant phenotypes were markedly suppressed by overexpression of Drp1 or downregulation of Opa1 or Marf, indicating that the PINK1-Parkin pathway regulates mitochondrial remodeling process in the direction of promoting mitochondrial fission. Therefore, we strongly suggest that mitochondrial fusion and fission process could be a prominent therapeutic target for the treatment of PD.

Neural processing of race during imitation: self-similarity versus social status

Science.gov (United States)

Reynolds Losin, Elizabeth A.; Cross, Katy A.; Iacoboni, Marco; Dapretto, Mirella

2017-01-01

People preferentially imitate others who are similar to them or have high social status. Such imitative biases are thought to have evolved because they increase the efficiency of cultural acquisition. Here we focused on distinguishing between self-similarity and social status as two candidate mechanisms underlying neural responses to a person’s race during imitation. We used fMRI to measure neural responses when 20 African American (AA) and 20 European American (EA) young adults imitated AA, EA and Chinese American (CA) models and also passively observed their gestures and faces. We found that both AA and EA participants exhibited more activity in lateral fronto-parietal and visual regions when imitating AAs compared to EAs or CAs. These results suggest that racial self-similarity is not likely to modulate neural responses to race during imitation, in contrast with findings from previous neuroimaging studies of face perception and action observation. Furthermore, AA and EA participants associated AAs with lower social status than EAs or CAs, suggesting that the social status associated with different racial groups may instead modulate neural activity during imitation of individuals from those groups. Taken together, these findings suggest that neural responses to race during imitation are driven by socially-learned associations rather than self-similarity. This may reflect the adaptive role of imitation in social learning, where learning from higher-status models can be more beneficial. This study provides neural evidence consistent with evolutionary theories of cultural acquisition. PMID:23813738

Neural computation of visual imaging based on Kronecker product in the primary visual cortex

Directory of Open Access Journals (Sweden)

Guozheng Yao

2010-03-01

that the function of cortical column in cortex V1 is considered as the basic unit of visual image processing (such unit can implement basic multiplication of visual primitives, such as contour, line, and edge, rather than a set of tiled array filter. Fourier Transformation is replaced with Kronecker product, which greatly reduces the computational complexity. The neurobiological basis of this idea is that a visual image can be represented as a linear combination of orderly orthogonal primitive image containing some local feature. In the visual pathway, the image patches are topographically mapped onto cortex V1 through parallel multi-channels and then are processed independently by functional columns. Clearly, the above new perspective has some reference significance to exploring the neural mechanisms on the human visual information processing.

Consciousness and neural plasticity

DEFF Research Database (Denmark)

changes or to abandon the strong identity thesis altogether. Were one to pursue a theory according to which consciousness is not an epiphenomenon to brain processes, consciousness may in fact affect its own neural basis. The neural correlate of consciousness is often seen as a stable structure, that is...

Artificial neural network approach to modeling of alcoholic fermentation of thick juice from sugar beet processing

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Jokić Aleksandar I.

2012-01-01

Full Text Available In this paper the bioethanol production in batch culture by free Saccharomyces cerevisiae cells from thick juice as intermediate product of sugar beet processing was examined. The obtained results suggest that it is possible to decrease fermentation time for the cultivation medium based on thick juice with starting sugar content of 5-15 g kg-1. For the fermentation of cultivation medium based on thick juice with starting sugar content of 20 and 25 g kg-1 significant increase in ethanol content was attained during the whole fermentation process, resulting in 12.51 and 10.95 dm3 m-3 ethanol contents after 48 h, respectively. Other goals of this work were to investigate the possibilities for experimental results prediction using artificial neural networks (ANNs and to find its optimal topology. A feed-forward back-propagation artificial neural network was used to test the hypothesis. As input variables fermentation time and starting sugar content were used. Neural networks had one output value, ethanol content, yeast cell number or sugar content. There was one hidden layer and the optimal number of neurons was found to be nine for all selected network outputs. In this study transfer function was tansig and the selected learning rule was Levenberg-Marquardt. Results suggest that artificial neural networks are good prediction tool for selected network outputs. It was found that experimental results are in very good agreement with computed ones. The coefficient of determination (the R-squared was found to be 0.9997, 0.9997 and 0.9999 for ethanol content, yeast cell number and sugar content, respectively.

Neural Networks for Non-linear Control

DEFF Research Database (Denmark)

Sørensen, O.

1994-01-01

This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process.......This paper describes how a neural network, structured as a Multi Layer Perceptron, is trained to predict, simulate and control a non-linear process....

Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

International Nuclear Information System (INIS)

Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

2003-01-01

Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

An RNA-binding protein, Qki5, regulates embryonic neural stem cells through pre-mRNA processing in cell adhesion signaling.

Science.gov (United States)

Hayakawa-Yano, Yoshika; Suyama, Satoshi; Nogami, Masahiro; Yugami, Masato; Koya, Ikuko; Furukawa, Takako; Zhou, Li; Abe, Manabu; Sakimura, Kenji; Takebayashi, Hirohide; Nakanishi, Atsushi; Okano, Hideyuki; Yano, Masato

2017-09-15

Cell type-specific transcriptomes are enabled by the action of multiple regulators, which are frequently expressed within restricted tissue regions. In the present study, we identify one such regulator, Quaking 5 (Qki5), as an RNA-binding protein (RNABP) that is expressed in early embryonic neural stem cells and subsequently down-regulated during neurogenesis. mRNA sequencing analysis in neural stem cell culture indicates that Qki proteins play supporting roles in the neural stem cell transcriptome and various forms of mRNA processing that may result from regionally restricted expression and subcellular localization. Also, our in utero electroporation gain-of-function study suggests that the nuclear-type Qki isoform Qki5 supports the neural stem cell state. We next performed in vivo transcriptome-wide protein-RNA interaction mapping to search for direct targets of Qki5 and elucidate how Qki5 regulates neural stem cell function. Combined with our transcriptome analysis, this mapping analysis yielded a bona fide map of Qki5-RNA interaction at single-nucleotide resolution, the identification of 892 Qki5 direct target genes, and an accurate Qki5-dependent alternative splicing rule in the developing brain. Last, our target gene list provides the first compelling evidence that Qki5 is associated with specific biological events; namely, cell-cell adhesion. This prediction was confirmed by histological analysis of mice in which Qki proteins were genetically ablated, which revealed disruption of the apical surface of the lateral wall in the developing brain. These data collectively indicate that Qki5 regulates communication between neural stem cells by mediating numerous RNA processing events and suggest new links between splicing regulation and neural stem cell states. © 2017 Hayakawa-Yano et al.; Published by Cold Spring Harbor Laboratory Press.

Dynamic decomposition of spatiotemporal neural signals.

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Luca Ambrogioni

2017-05-01

Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

Aberrant Neural Connectivity during Emotional Processing Associated with Posttraumatic Stress.

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Sadeh, Naomi; Spielberg, Jeffrey M; Warren, Stacie L; Miller, Gregory A; Heller, Wendy

2014-11-01

Given the complexity of the brain, characterizing relations among distributed brain regions is likely essential to describing the neural instantiation of posttraumatic stress symptoms. This study examined patterns of functional connectivity among key brain regions implicated in the pathophysiology of posttraumatic stress disorder (PTSD) in 35 trauma-exposed adults using an emotion-word Stroop task. PTSD symptom severity (particularly hyperarousal symptoms) moderated amygdala-mPFC coupling during the processing of unpleasant words, and this moderation correlated positively with reported real-world impairment and amygdala reactivity. Reexperiencing severity moderated hippocampus-insula coupling during pleasant and unpleasant words. Results provide evidence that PTSD symptoms differentially moderate functional coupling during emotional interference and underscore the importance of examining network connectivity in research on PTSD. They suggest that hyperarousal is associated with negative mPFC-amygdala coupling and that reexperiencing is associated with altered insula-hippocampus function, patterns of connectivity that may represent separable indicators of dysfunctional inhibitory control during affective processing.

Simplified LQG Control with Neural Networks

DEFF Research Database (Denmark)

Sørensen, O.

1997-01-01

A new neural network application for non-linear state control is described. One neural network is modelled to form a Kalmann predictor and trained to act as an optimal state observer for a non-linear process. Another neural network is modelled to form a state controller and trained to produce...

Application of neural networks in coastal engineering

Digital Repository Service at National Institute of Oceanography (India)

Mandal, S.

the neural network attractive. A neural network is an information processing system modeled on the structure of the dynamic process. It can solve the complex/nonlinear problems quickly once trained by operating on problems using an interconnected number...

Modelling and performance analysis of clinical pathways using the stochastic process algebra PEPA.

Science.gov (United States)

Yang, Xian; Han, Rui; Guo, Yike; Bradley, Jeremy; Cox, Benita; Dickinson, Robert; Kitney, Richard

2012-01-01

Hospitals nowadays have to serve numerous patients with limited medical staff and equipment while maintaining healthcare quality. Clinical pathway informatics is regarded as an efficient way to solve a series of hospital challenges. To date, conventional research lacks a mathematical model to describe clinical pathways. Existing vague descriptions cannot fully capture the complexities accurately in clinical pathways and hinders the effective management and further optimization of clinical pathways. Given this motivation, this paper presents a clinical pathway management platform, the Imperial Clinical Pathway Analyzer (ICPA). By extending the stochastic model performance evaluation process algebra (PEPA), ICPA introduces a clinical-pathway-specific model: clinical pathway PEPA (CPP). ICPA can simulate stochastic behaviours of a clinical pathway by extracting information from public clinical databases and other related documents using CPP. Thus, the performance of this clinical pathway, including its throughput, resource utilisation and passage time can be quantitatively analysed. A typical clinical pathway on stroke extracted from a UK hospital is used to illustrate the effectiveness of ICPA. Three application scenarios are tested using ICPA: 1) redundant resources are identified and removed, thus the number of patients being served is maintained with less cost; 2) the patient passage time is estimated, providing the likelihood that patients can leave hospital within a specific period; 3) the maximum number of input patients are found, helping hospitals to decide whether they can serve more patients with the existing resource allocation. ICPA is an effective platform for clinical pathway management: 1) ICPA can describe a variety of components (state, activity, resource and constraints) in a clinical pathway, thus facilitating the proper understanding of complexities involved in it; 2) ICPA supports the performance analysis of clinical pathway, thereby assisting

Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations.

Science.gov (United States)

Giese, Martin A; Rizzolatti, Giacomo

2015-10-07

Action recognition has received enormous interest in the field of neuroscience over the last two decades. In spite of this interest, the knowledge in terms of fundamental neural mechanisms that provide constraints for underlying computations remains rather limited. This fact stands in contrast with a wide variety of speculative theories about how action recognition might work. This review focuses on new fundamental electrophysiological results in monkeys, which provide constraints for the detailed underlying computations. In addition, we review models for action recognition and processing that have concrete mathematical implementations, as opposed to conceptual models. We think that only such implemented models can be meaningfully linked quantitatively to physiological data and have a potential to narrow down the many possible computational explanations for action recognition. In addition, only concrete implementations allow judging whether postulated computational concepts have a feasible implementation in terms of realistic neural circuits. Copyright © 2015 Elsevier Inc. All rights reserved.

Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

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Huixia Zhao

Full Text Available The insect-machine interface (IMI is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L. via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe, ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

Neuromechanism study of insect-machine interface: flight control by neural electrical stimulation.

Science.gov (United States)

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect-machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee-machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control.

Neuromechanism Study of Insect–Machine Interface: Flight Control by Neural Electrical Stimulation

Science.gov (United States)

Zhao, Huixia; Zheng, Nenggan; Ribi, Willi A.; Zheng, Huoqing; Xue, Lei; Gong, Fan; Zheng, Xiaoxiang; Hu, Fuliang

2014-01-01

The insect–machine interface (IMI) is a novel approach developed for man-made air vehicles, which directly controls insect flight by either neuromuscular or neural stimulation. In our previous study of IMI, we induced flight initiation and cessation reproducibly in restrained honeybees (Apis mellifera L.) via electrical stimulation of the bilateral optic lobes. To explore the neuromechanism underlying IMI, we applied electrical stimulation to seven subregions of the honeybee brain with the aid of a new method for localizing brain regions. Results showed that the success rate for initiating honeybee flight decreased in the order: α-lobe (or β-lobe), ellipsoid body, lobula, medulla and antennal lobe. Based on a comparison with other neurobiological studies in honeybees, we propose that there is a cluster of descending neurons in the honeybee brain that transmits neural excitation from stimulated brain areas to the thoracic ganglia, leading to flight behavior. This neural circuit may involve the higher-order integration center, the primary visual processing center and the suboesophageal ganglion, which is also associated with a possible learning and memory pathway. By pharmacologically manipulating the electrically stimulated honeybee brain, we have shown that octopamine, rather than dopamine, serotonin and acetylcholine, plays a part in the circuit underlying electrically elicited honeybee flight. Our study presents a new brain stimulation protocol for the honeybee–machine interface and has solved one of the questions with regard to understanding which functional divisions of the insect brain participate in flight control. It will support further studies to uncover the involved neurons inside specific brain areas and to test the hypothesized involvement of a visual learning and memory pathway in IMI flight control. PMID:25409523

Optical-Correlator Neural Network Based On Neocognitron

Science.gov (United States)

Chao, Tien-Hsin; Stoner, William W.

1994-01-01

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Autism spectrum disorders and drug addiction: Common pathways, common molecules, distinct disorders?

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Patrick E. Rothwell

2016-02-01

Full Text Available Autism spectrum disorders (ASDs and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP and methyl CpG-binding protein-2 (MECP2, which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Autism Spectrum Disorders and Drug Addiction: Common Pathways, Common Molecules, Distinct Disorders?

Science.gov (United States)

Rothwell, Patrick E

2016-01-01

Autism spectrum disorders (ASDs) and drug addiction do not share substantial comorbidity or obvious similarities in etiology or symptomatology. It is thus surprising that a number of recent studies implicate overlapping neural circuits and molecular signaling pathways in both disorders. The purpose of this review is to highlight this emerging intersection and consider implications for understanding the pathophysiology of these seemingly distinct disorders. One area of overlap involves neural circuits and neuromodulatory systems in the striatum and basal ganglia, which play an established role in addiction and reward but are increasingly implicated in clinical and preclinical studies of ASDs. A second area of overlap relates to molecules like Fragile X mental retardation protein (FMRP) and methyl CpG-binding protein-2 (MECP2), which are best known for their contribution to the pathogenesis of syndromic ASDs, but have recently been shown to regulate behavioral and neurobiological responses to addictive drug exposure. These shared pathways and molecules point to common dimensions of behavioral dysfunction, including the repetition of behavioral patterns and aberrant reward processing. The synthesis of knowledge gained through parallel investigations of ASDs and addiction may inspire the design of new therapeutic interventions to correct common elements of striatal dysfunction.

Understanding the role of speech production in reading: Evidence for a print-to-speech neural network using graphical analysis.

Science.gov (United States)

Cummine, Jacqueline; Cribben, Ivor; Luu, Connie; Kim, Esther; Bahktiari, Reyhaneh; Georgiou, George; Boliek, Carol A

2016-05-01

The neural circuitry associated with language processing is complex and dynamic. Graphical models are useful for studying complex neural networks as this method provides information about unique connectivity between regions within the context of the entire network of interest. Here, the authors explored the neural networks during covert reading to determine the role of feedforward and feedback loops in covert speech production. Brain activity of skilled adult readers was assessed in real word and pseudoword reading tasks with functional MRI (fMRI). The authors provide evidence for activity coherence in the feedforward system (inferior frontal gyrus-supplementary motor area) during real word reading and in the feedback system (supramarginal gyrus-precentral gyrus) during pseudoword reading. Graphical models provided evidence of an extensive, highly connected, neural network when individuals read real words that relied on coordination of the feedforward system. In contrast, when individuals read pseudowords the authors found a limited/restricted network that relied on coordination of the feedback system. Together, these results underscore the importance of considering multiple pathways and articulatory loops during language tasks and provide evidence for a print-to-speech neural network. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Neural Differentiation of Human Adipose Tissue-Derived Stem Cells Involves Activation of the Wnt5a/JNK Signalling

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Sujeong Jang

2015-01-01

Full Text Available Stem cells are a powerful resource for cell-based transplantation therapies, but understanding of stem cell differentiation at the molecular level is not clear yet. We hypothesized that the Wnt pathway controls stem cell maintenance and neural differentiation. We have characterized the transcriptional expression of Wnt during the neural differentiation of hADSCs. After neural induction, the expressions of Wnt2, Wnt4, and Wnt11 were decreased, but the expression of Wnt5a was increased compared with primary hADSCs in RT-PCR analysis. In addition, the expression levels of most Fzds and LRP5/6 ligand were decreased, but not Fzd3 and Fzd5. Furthermore, Dvl1 and RYK expression levels were downregulated in NI-hADSCs. There were no changes in the expression of ß-catenin and GSK3ß. Interestingly, Wnt5a expression was highly increased in NI-hADSCs by real time RT-PCR analysis and western blot. Wnt5a level was upregulated after neural differentiation and Wnt3, Dvl2, and Naked1 levels were downregulated. Finally, we found that the JNK expression was increased after neural induction and ERK level was decreased. Thus, this study shows for the first time how a single Wnt5a ligand can activate the neural differentiation pathway through the activation of Wnt5a/JNK pathway by binding Fzd3 and Fzd5 and directing Axin/GSK-3ß in hADSCs.

Vaccination and the TAP-independent antigen processing pathways.

Science.gov (United States)

López, Daniel; Lorente, Elena; Barriga, Alejandro; Johnstone, Carolina; Mir, Carmen

2013-09-01

The cytotoxic CD8(+) T lymphocyte-mediated cellular response is important for the elimination of virus-infected cells and requires the prior recognition of short viral peptide antigens previously translocated to the endoplasmic reticulum by the transporter associated with antigen processing (TAP). However, individuals with nonfunctional TAP complexes or infected cells with TAP molecules blocked by specific viral proteins, such as the cowpoxvirus, a component of the first source of early empirical vaccination against smallpox, are still able to present several HLA class I ligands generated by the TAP-independent antigen processing pathways to specific cytotoxic CD8(+) T lymphocytes. Currently, bioterrorism and emerging infectious diseases have renewed interest in poxviruses. Recent works that have identified HLA class I ligands and epitopes in virus-infected TAP-deficient cells have implications for the study of both the effectiveness of early empirical vaccination and the analysis of HLA class I antigen processing in TAP-deficient subjects.

Neural correlates of socioeconomic status in the developing human brain.

Science.gov (United States)

Noble, Kimberly G; Houston, Suzanne M; Kan, Eric; Sowell, Elizabeth R

2012-07-01

Socioeconomic disparities in childhood are associated with remarkable differences in cognitive and socio-emotional development during a time when dramatic changes are occurring in the brain. Yet, the neurobiological pathways through which socioeconomic status (SES) shapes development remain poorly understood. Behavioral evidence suggests that language, memory, social-emotional processing, and cognitive control exhibit relatively large differences across SES. Here we investigated whether volumetric differences could be observed across SES in several neural regions that support these skills. In a sample of 60 socioeconomically diverse children, highly significant SES differences in regional brain volume were observed in the hippocampus and the amygdala. In addition, SES × age interactions were observed in the left superior temporal gyrus and left inferior frontal gyrus, suggesting increasing SES differences with age in these regions. These results were not explained by differences in gender, race or IQ. Likely mechanisms include differences in the home linguistic environment and exposure to stress, which may serve as targets for intervention at a time of high neural plasticity. © 2012 Blackwell Publishing Ltd.

Power to punish norm violations affects the neural processes of fairness-related decision making

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Xuemei eCheng

2015-12-01

Full Text Available 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.

Mechanisms underlying metabolic and neural defects in zebrafish and human multiple acyl-CoA dehydrogenase deficiency (MADD.

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Yuanquan Song

2009-12-01

Full Text Available In humans, mutations in electron transfer flavoprotein (ETF or electron transfer flavoprotein dehydrogenase (ETFDH lead to MADD/glutaric aciduria type II, an autosomal recessively inherited disorder characterized by a broad spectrum of devastating neurological, systemic and metabolic symptoms. We show that a zebrafish mutant in ETFDH, xavier, and fibroblast cells from MADD patients demonstrate similar mitochondrial and metabolic abnormalities, including reduced oxidative phosphorylation, increased aerobic glycolysis, and upregulation of the PPARG-ERK pathway. This metabolic dysfunction is associated with aberrant neural proliferation in xav, in addition to other neural phenotypes and paralysis. Strikingly, a PPARG antagonist attenuates aberrant neural proliferation and alleviates paralysis in xav, while PPARG agonists increase neural proliferation in wild type embryos. These results show that mitochondrial dysfunction, leading to an increase in aerobic glycolysis, affects neurogenesis through the PPARG-ERK pathway, a potential target for therapeutic intervention.

Signal transduction in mitogenesis: Further evidence for multiple pathways

International Nuclear Information System (INIS)

Rozengurt, E.; Erusalimsky, J.; Mehmet, H.; Morris, C.; Nanberg, E.; Sinnett-Smith, J.

1988-01-01

Growth factors are implicated in a wide variety of physiological and pathological processes, including embryogenesis, hematopoiesis, would healing, immune responses, atherosclerosis, and neoplasia. An important link between growth factors and their receptors and oncogene products has also been established. Thus, the elucidation of the mechanism of action of growth factors has emerged as one of the fundamental problems in biology and may prove crucial for understanding the unrestrained proliferation of cancer cells. A new and intriguing development is the discovery that neuropeptides localized in neural and neuroendocrine cells of mammalian tissue can also act as growth factors for cells in culture. Furthermore, indirect evidence is accumulating that the mitogenic effects of neuropeptides may be relevant for a variety of long-term biological processes, including development and oncogenesis. In this context, the peptides of the bombesin family are of particular significance. These peptides are potent mitogens for Swiss 3T3 cells and may act as autocrine growth factors for small cell lung cancer. Here, the authors summarize their recent studies using bombesin-like peptides for elucidating the signal transduction pathways leading to mitogenesis and compare these pathways with those elicited by other growth factors

Neural correlates and neural computations in posterior parietal cortex during perceptual decision-making

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Alexander eHuk

2012-10-01

Full Text Available A recent line of work has found remarkable success in relating perceptual decision-making and the spiking activity in the macaque lateral intraparietal area (LIP. In this review, we focus on questions about the neural computations in LIP that are not answered by demonstrations of neural correlates of psychological processes. We highlight three areas of limitations in our current understanding of the precise neural computations that might underlie neural correlates of decisions: (1 empirical questions not yet answered by existing data; (2 implementation issues related to how neural circuits could actually implement the mechanisms suggested by both physiology and psychology; and (3 ecological constraints related to the use of well-controlled laboratory tasks and whether they provide an accurate window on sensorimotor computation. These issues motivate the adoption of a more general encoding-decoding framework that will be fruitful for more detailed contemplation of how neural computations in LIP relate to the formation of perceptual decisions.

Revealing complex function, process and pathway interactions with high-throughput expression and biological annotation data.

Science.gov (United States)

Singh, Nitesh Kumar; Ernst, Mathias; Liebscher, Volkmar; Fuellen, Georg; Taher, Leila

2016-10-20

The biological relationships both between and within the functions, processes and pathways that operate within complex biological systems are only poorly characterized, making the interpretation of large scale gene expression datasets extremely challenging. Here, we present an approach that integrates gene expression and biological annotation data to identify and describe the interactions between biological functions, processes and pathways that govern a phenotype of interest. The product is a global, interconnected network, not of genes but of functions, processes and pathways, that represents the biological relationships within the system. We validated our approach on two high-throughput expression datasets describing organismal and organ development. Our findings are well supported by the available literature, confirming that developmental processes and apoptosis play key roles in cell differentiation. Furthermore, our results suggest that processes related to pluripotency and lineage commitment, which are known to be critical for development, interact mainly indirectly, through genes implicated in more general biological processes. Moreover, we provide evidence that supports the relevance of cell spatial organization in the developing liver for proper liver function. Our strategy can be viewed as an abstraction that is useful to interpret high-throughput data and devise further experiments.

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Science.gov (United States)

Zhang, Xingyu; Kim, Joyce; Patzer, Rachel E; Pitts, Stephen R; Patzer, Aaron; Schrager, Justin D

2017-10-26

To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements. Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model. Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN. The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient

Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

Science.gov (United States)

Konno, Hidetoshi; Tamura, Yoshiyasu

2018-01-01

In neural spike counting experiments, it is known that there are two main features: (i) the counting number has a fractional power-law growth with time and (ii) the waiting time (i.e., the inter-spike-interval) distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs) is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii) can be modeled by the method of SSPPs. Namely, the first one (i) associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP).

Chemically Induced Reprogramming of Somatic Cells to Pluripotent Stem Cells and Neural Cells.

Science.gov (United States)

Biswas, Dhruba; Jiang, Peng

2016-02-06

The ability to generate transplantable neural cells in a large quantity in the laboratory is a critical step in the field of developing stem cell regenerative medicine for neural repair. During the last few years, groundbreaking studies have shown that cell fate of adult somatic cells can be reprogrammed through lineage specific expression of transcription factors (TFs)-and defined culture conditions. This key concept has been used to identify a number of potent small molecules that could enhance the efficiency of reprogramming with TFs. Recently, a growing number of studies have shown that small molecules targeting specific epigenetic and signaling pathways can replace all of the reprogramming TFs. Here, we provide a detailed review of the studies reporting the generation of chemically induced pluripotent stem cells (ciPSCs), neural stem cells (ciNSCs), and neurons (ciN). We also discuss the main mechanisms of actions and the pathways that the small molecules regulate during chemical reprogramming.

COMT val108/158 met genotype affects neural but not cognitive processing in healthy individuals.

Science.gov (United States)

Dennis, Nancy A; Need, Anna C; LaBar, Kevin S; Waters-Metenier, Sheena; Cirulli, Elizabeth T; Kragel, James; Goldstein, David B; Cabeza, Roberto

2010-03-01

The relationship between cognition and a functional polymorphism in the catechol-O-methlytransferase (COMT) gene, val108/158met, is one of debate in the literature. Furthermore, based on the dopaminergic differences associated with the COMT val108/158met genotype, neural differences during cognition may be present, regardless of genotypic differences in cognitive performance. To investigate these issues the current study aimed to 1) examine the effects of COMT genotype using a large sample of healthy individuals (n = 496-1218) and multiple cognitive measures, and using a subset of the sample (n = 22), 2) examine whether COMT genotype effects medial temporal lobe (MTL) and frontal activity during successful relational memory processing, and 3) investigate group differences in functional connectivity associated with successful relational memory processing. Results revealed no significant group difference in cognitive performance between COMT genotypes in any of the 19 cognitive measures. However, in the subset sample, COMT val homozygotes exhibited significantly decreased MTL and increased prefrontal activity during both successful relational encoding and retrieval, and reduced connectivity between these regions compared with met homozygotes. Taken together, the results suggest that although the COMT val108/158met genotype has no effect on cognitive behavioral measures in healthy individuals, it is associated with differences in neural process underlying cognitive output.

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

Science.gov (United States)

Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

Windowed active sampling for reliable neural learning

NARCIS (Netherlands)

Barakova, E.I; Spaanenburg, L

The composition of the example set has a major impact on the quality of neural learning. The popular approach is focused on extensive pre-processing to bridge the representation gap between process measurement and neural presentation. In contrast, windowed active sampling attempts to solve these

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

Science.gov (United States)

Rice, Katherine; Redcay, Elizabeth

2016-04-01

Mounting evidence suggests that social interaction changes how communicative behaviors (e.g., spoken language, gaze) are processed, but the precise neural bases by which social-interactive context may alter communication remain unknown. Various perspectives suggest that live interactions are more rewarding, more attention-grabbing, or require increased mentalizing-thinking about the thoughts of others. Dissociating between these possibilities is difficult because most extant neuroimaging paradigms examining social interaction have not directly compared live paradigms to conventional "offline" (or recorded) paradigms. We developed a novel fMRI paradigm to assess whether and how an interactive context changes the processing of speech matched in content and vocal characteristics. Participants listened to short vignettes--which contained no reference to people or mental states--believing that some vignettes were prerecorded and that others were presented over a real-time audio-feed by a live social partner. In actuality, all speech was prerecorded. Simply believing that speech was live increased activation in each participant's own mentalizing regions, defined using a functional localizer. Contrasting live to recorded speech did not reveal significant differences in attention or reward regions. Further, higher levels of autistic-like traits were associated with altered neural specialization for live interaction. These results suggest that humans engage in ongoing mentalizing about social partners, even when such mentalizing is not explicitly required, illustrating how social context shapes social cognition. Understanding communication in social context has important implications for typical and atypical social processing, especially for disorders like autism where social difficulties are more acute in live interaction. Copyright © 2015 Elsevier Inc. All rights reserved.

Adolescent transformations of behavioral and neural processes as potential targets for prevention.

Science.gov (United States)

Eldreth, Dana; Hardin, Michael G; Pavletic, Nevia; Ernst, Monique

2013-06-01

Adolescence is a transitional period in development that is marked by a distinct, typical behavioral profile of high rates of exploration, novelty-seeking, and emotional lability. While these behaviors generally assist the adolescent transition to independence, they can also confer vulnerability for excessive risk-taking and psychopathology, particularly in the context of specific environmental or genetic influences. As prevention research depends on the identification of targets of vulnerability, the following review will discuss the interplay among motivational systems including reward-related, avoidance-related, and regulatory processes in typical and atypical adolescent development. Each set of processes will be discussed in relation to their underlying neural correlates and distinct developmental trajectories. Evidence suggests that typical adolescent behavior and the risk for atypical development are mediated by heightened adolescent responsiveness of reward-related and avoidance-related systems under specific conditions, concurrent with poor modulation by immature regulatory processes. Finally, we will propose strategies to exploit heightened reward processing to reinforce inhibitory control, which is an essential component of regulatory processes in prevention interventions.

Human neural progenitors express functional lysophospholipid receptors that regulate cell growth and morphology

Directory of Open Access Journals (Sweden)

Callihan Phillip

2008-12-01

Full Text Available Abstract Background Lysophospholipids regulate the morphology and growth of neurons, neural cell lines, and neural progenitors. A stable human neural progenitor cell line is not currently available in which to study the role of lysophospholipids in human neural development. We recently established a stable, adherent human embryonic stem cell-derived neuroepithelial (hES-NEP cell line which recapitulates morphological and phenotypic features of neural progenitor cells isolated from fetal tissue. The goal of this study was to determine if hES-NEP cells express functional lysophospholipid receptors, and if activation of these receptors mediates cellular responses critical for neural development. Results Our results demonstrate that Lysophosphatidic Acid (LPA and Sphingosine-1-phosphate (S1P receptors are functionally expressed in hES-NEP cells and are coupled to multiple cellular signaling pathways. We have shown that transcript levels for S1P1 receptor increased significantly in the transition from embryonic stem cell to hES-NEP. hES-NEP cells express LPA and S1P receptors coupled to Gi/o G-proteins that inhibit adenylyl cyclase and to Gq-like phospholipase C activity. LPA and S1P also induce p44/42 ERK MAP kinase phosphorylation in these cells and stimulate cell proliferation via Gi/o coupled receptors in an Epidermal Growth Factor Receptor (EGFR- and ERK-dependent pathway. In contrast, LPA and S1P stimulate transient cell rounding and aggregation that is independent of EGFR and ERK, but dependent on the Rho effector p160 ROCK. Conclusion Thus, lysophospholipids regulate neural progenitor growth and morphology through distinct mechanisms. These findings establish human ES cell-derived NEP cells as a model system for studying the role of lysophospholipids in neural progenitors.

Neural constructivism or self-organization?

NARCIS (Netherlands)

van der Maas, H.L.J.; Molenaar, P.C.M.

2000-01-01

Comments on the article by S. R. Quartz et al (see record 1998-00749-001) which discussed the constructivist perspective of interaction between cognition and neural processes during development and consequences for theories of learning. Three arguments are given to show that neural constructivism

YAP/TAZ enhance mammalian embryonic neural stem cell characteristics in a Tead-dependent manner

Energy Technology Data Exchange (ETDEWEB)

Han, Dasol; Byun, Sung-Hyun; Park, Soojeong; Kim, Juwan; Kim, Inhee; Ha, Soobong; Kwon, Mookwang; Yoon, Keejung, E-mail: keejung@skku.edu

2015-02-27

Mammalian brain development is regulated by multiple signaling pathways controlling cell proliferation, migration and differentiation. Here we show that YAP/TAZ enhance embryonic neural stem cell characteristics in a cell autonomous fashion using diverse experimental approaches. Introduction of retroviral vectors expressing YAP or TAZ into the mouse embryonic brain induced cell localization in the ventricular zone (VZ), which is the embryonic neural stem cell niche. This change in cell distribution in the cortical layer is due to the increased stemness of infected cells; YAP-expressing cells were colabeled with Sox2, a neural stem cell marker, and YAP/TAZ increased the frequency and size of neurospheres, indicating enhanced self-renewal- and proliferative ability of neural stem cells. These effects appear to be TEA domain family transcription factor (Tead)–dependent; a Tead binding-defective YAP mutant lost the ability to promote neural stem cell characteristics. Consistently, in utero gene transfer of a constitutively active form of Tead2 (Tead2-VP16) recapitulated all the features of YAP/TAZ overexpression, and dominant negative Tead2-EnR resulted in marked cell exit from the VZ toward outer cortical layers. Taken together, these results indicate that the Tead-dependent YAP/TAZ signaling pathway plays important roles in neural stem cell maintenance by enhancing stemness of neural stem cells during mammalian brain development. - Highlights: • Roles of YAP and Tead in vivo during mammalian brain development are clarified. • Expression of YAP promotes embryonic neural stem cell characteristics in vivo in a cell autonomous fashion. • Enhancement of neural stem cell characteristics by YAP depends on Tead. • Transcriptionally active form of Tead alone can recapitulate the effects of YAP. • Transcriptionally repressive form of Tead severely reduces stem cell characteristics.

YAP/TAZ enhance mammalian embryonic neural stem cell characteristics in a Tead-dependent manner

International Nuclear Information System (INIS)

Han, Dasol; Byun, Sung-Hyun; Park, Soojeong; Kim, Juwan; Kim, Inhee; Ha, Soobong; Kwon, Mookwang; Yoon, Keejung

2015-01-01

Mammalian brain development is regulated by multiple signaling pathways controlling cell proliferation, migration and differentiation. Here we show that YAP/TAZ enhance embryonic neural stem cell characteristics in a cell autonomous fashion using diverse experimental approaches. Introduction of retroviral vectors expressing YAP or TAZ into the mouse embryonic brain induced cell localization in the ventricular zone (VZ), which is the embryonic neural stem cell niche. This change in cell distribution in the cortical layer is due to the increased stemness of infected cells; YAP-expressing cells were colabeled with Sox2, a neural stem cell marker, and YAP/TAZ increased the frequency and size of neurospheres, indicating enhanced self-renewal- and proliferative ability of neural stem cells. These effects appear to be TEA domain family transcription factor (Tead)–dependent; a Tead binding-defective YAP mutant lost the ability to promote neural stem cell characteristics. Consistently, in utero gene transfer of a constitutively active form of Tead2 (Tead2-VP16) recapitulated all the features of YAP/TAZ overexpression, and dominant negative Tead2-EnR resulted in marked cell exit from the VZ toward outer cortical layers. Taken together, these results indicate that the Tead-dependent YAP/TAZ signaling pathway plays important roles in neural stem cell maintenance by enhancing stemness of neural stem cells during mammalian brain development. - Highlights: • Roles of YAP and Tead in vivo during mammalian brain development are clarified. • Expression of YAP promotes embryonic neural stem cell characteristics in vivo in a cell autonomous fashion. • Enhancement of neural stem cell characteristics by YAP depends on Tead. • Transcriptionally active form of Tead alone can recapitulate the effects of YAP. • Transcriptionally repressive form of Tead severely reduces stem cell characteristics

High school music classes enhance the neural processing of speech

OpenAIRE

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 two years of group music classes in high school enhance the subcortical encoding of speech. To tease apart the relationships between music and neural...

Andrographolide Promotes Neural Differentiation of Rat Adipose Tissue-Derived Stromal Cells through Wnt/β-Catenin Signaling Pathway

Directory of Open Access Journals (Sweden)

Yan Liang

2017-01-01

Full Text Available Adipose tissue-derived stromal cells (ADSCs are a high-yield source of pluripotent stem cells for use in cell-based therapies. We explored the effect of andrographolide (ANDRO, one of the ingredients of the medicinal herb extract on the neural differentiation of rat ADSCs and associated molecular mechanisms. We observed that rat ADSCs were small and spindle-shaped and expressed multiple stem cell markers including nestin. They were multipotent as evidenced by adipogenic, osteogenic, chondrogenic, and neural differentiation under appropriate conditions. The proportion of cells exhibiting neural-like morphology was higher, and neurites developed faster in the ANDRO group than in the control group in the same neural differentiation medium. Expression levels of the neural lineage markers MAP2, tau, GFAP, and β-tubulin III were higher in the ANDRO group. ANDRO induced a concentration-dependent increase in Wnt/β-catenin signaling as evidenced by the enhanced expression of nuclear β-catenin and the inhibited form of GSK-3β (pSer9. Thus, this study shows for the first time how by enhancing the neural differentiation of ADSCs we expect that ANDRO pretreatment may increase the efficacy of adult stem cell transplantation in nervous system diseases, but more exploration is needed.

Planning pesticides usage for herbal and animal pests based on intelligent classification system with image processing and neural networks

Directory of Open Access Journals (Sweden)

Dimililer Kamil

2018-01-01

Full Text Available Pests are divided into two as herbal and animal pests in agriculture, and detection and use of minimum pesticides are quite challenging task. Last three decades, researchers have been improving their studies on these manners. Therefore, effective, efficient, and as well as intelligent systems are designed and modelled. In this paper, an intelligent classification system is designed for detecting pests as herbal or animal to use of proper pesticides accordingly. The designed system suggests two main stages. Firstly, images are processed using different image processing techniques that images have specific distinguishing geometric patterns. The second stage is neural network phase for classification. A backpropagation neural network is used for training and testing with processed images. System is tested, and experiment results show efficiency and effective classification rate. Autonomy and time efficiency within the pesticide usage are also discussed.

Hepatocyte growth factor/scatter factor-MET signaling in neural crest-derived melanocyte development.

Science.gov (United States)

Kos, L; Aronzon, A; Takayama, H; Maina, F; Ponzetto, C; Merlino, G; Pavan, W

1999-02-01

The mechanisms governing development of neural crest-derived melanocytes, and how alterations in these pathways lead to hypopigmentation disorders, are not completely understood. Hepatocyte growth factor/scatter factor (HGF/SF) signaling through the tyrosine-kinase receptor, MET, is capable of promoting the proliferation, increasing the motility, and maintaining high tyrosinase activity and melanin synthesis of melanocytes in vitro. In addition, transgenic mice that ubiquitously overexpress HGF/SF demonstrate hyperpigmentation in the skin and leptomenigenes and develop melanomas. To investigate whether HGF/ SF-MET signaling is involved in the development of neural crest-derived melanocytes, transgenic embryos, ubiquitously overexpressing HGF/SF, were analyzed. In HGF/SF transgenic embryos, the distribution of melanoblasts along the characteristic migratory pathway was not affected. However, additional ectopically localized melanoblasts were also observed in the dorsal root ganglia and neural tube, as early as 11.5 days post coitus (p.c.). We utilized an in vitro neural crest culture assay to further explore the role of HGF/SF-MET signaling in neural crest development. HGF/SF added to neural crest cultures increased melanoblast number, permitted differentiation into pigmented melanocytes, promoted melanoblast survival, and could replace mast-cell growth factor/Steel factor (MGF) in explant cultures. To examine whether HGF/SF-MET signaling is required for the proper development of melanocytes, embryos with a targeted Met null mutation (Met-/-) were analysed. In Met-/- embryos, melanoblast number and location were not overtly affected up to 14 days p.c. These results demonstrate that HGF/SF-MET signaling influences, but is not required for, the initial development of neural crest-derived melanocytes in vivo and in vitro.

Emotionally anesthetized: media violence induces neural changes during emotional face processing.

Science.gov (United States)

Stockdale, Laura A; Morrison, Robert G; Kmiecik, Matthew J; Garbarino, James; Silton, Rebecca L

2015-10-01

Media violence exposure causes increased aggression and decreased prosocial behavior, suggesting that media violence desensitizes people to the emotional experience of others. Alterations in emotional face processing following exposure to media violence may result in desensitization to others' emotional states. This study used scalp electroencephalography methods to examine the link between exposure to violence and neural changes associated with emotional face processing. Twenty-five participants were shown a violent or nonviolent film clip and then completed a gender discrimination stop-signal task using emotional faces. Media violence did not affect the early visual P100 component; however, decreased amplitude was observed in the N170 and P200 event-related potentials following the violent film, indicating that exposure to film violence leads to suppression of holistic face processing and implicit emotional processing. Participants who had just seen a violent film showed increased frontal N200/P300 amplitude. These results suggest that media violence exposure may desensitize people to emotional stimuli and thereby require fewer cognitive resources to inhibit behavior. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

A Fuzzy Neural Network Based on Non-Euclidean Distance Clustering for Quality Index Model in Slashing Process

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Yuxian Zhang

2015-01-01

Full Text Available The quality index model in slashing process is difficult to build by reason of the outliers and noise data from original data. To the above problem, a fuzzy neural network based on non-Euclidean distance clustering is proposed in which the input space is partitioned into many local regions by the fuzzy clustering based on non-Euclidean distance so that the computation complexity is decreased, and fuzzy rule number is determined by validity function based on both the separation and the compactness among clusterings. Then, the premise parameters and consequent parameters are trained by hybrid learning algorithm. The parameters identification is realized; meanwhile the convergence condition of consequent parameters is obtained by Lyapunov function. Finally, the proposed method is applied to build the quality index model in slashing process in which the experimental data come from the actual slashing process. The experiment results show that the proposed fuzzy neural network for quality index model has lower computation complexity and faster convergence time, comparing with GP-FNN, BPNN, and RBFNN.

Pathway-based analysis of genome-wide siRNA screens reveals the regulatory landscape of APP processing.

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Luiz Miguel Camargo

Full Text Available The progressive aggregation of Amyloid-β (Aβ in the brain is a major trait of Alzheimer's Disease (AD. Aβ is produced as a result of proteolytic processing of the β-amyloid precursor protein (APP. Processing of APP is mediated by multiple enzymes, resulting in the production of distinct peptide products: the non-amyloidogenic peptide sAPPα and the amyloidogenic peptides sAPPβ, Aβ40, and Aβ42. Using a pathway-based approach, we analyzed a large-scale siRNA screen that measured the production of different APP proteolytic products. Our analysis identified many of the biological processes/pathways that are known to regulate APP processing and have been implicated in AD pathogenesis, as well as revealing novel regulatory mechanisms. Furthermore, we also demonstrate that some of these processes differentially regulate APP processing, with some mechanisms favouring production of certain peptide species over others. For example, synaptic transmission having a bias towards regulating Aβ40 production over Aβ42 as well as processes involved in insulin and pancreatic biology having a bias for sAPPβ production over sAPPα. In addition, some of the pathways identified as regulators of APP processing contain genes (CLU, BIN1, CR1, PICALM, TREM2, SORL1, MEF2C, DSG2, EPH1A recently implicated with AD through genome wide association studies (GWAS and associated meta-analysis. In addition, we provide supporting evidence and a deeper mechanistic understanding of the role of diabetes in AD. The identification of these processes/pathways, their differential impact on APP processing, and their relationships to each other, provide a comprehensive systems biology view of the "regulatory landscape" of APP.

The Involvement of Endogenous Neural Oscillations in the Processing of Rhythmic Input: More Than a Regular Repetition of Evoked Neural Responses

Science.gov (United States)

Zoefel, Benedikt; ten Oever, Sanne; Sack, Alexander T.

2018-01-01

It is undisputed that presenting a rhythmic stimulus leads to a measurable brain response that follows the rhythmic structure of this stimulus. What is still debated, however, is the question whether this brain response exclusively reflects a regular repetition of evoked responses, or whether it also includes entrained oscillatory activity. Here we systematically present evidence in favor of an involvement of entrained neural oscillations in the processing of rhythmic input while critically pointing out which questions still need to be addressed before this evidence could be considered conclusive. In this context, we also explicitly discuss the potential functional role of such entrained oscillations, suggesting that these stimulus-aligned oscillations reflect, and serve as, predictive processes, an idea often only implicitly assumed in the literature. PMID:29563860

Alzheimer disease: functional abnormalities in the dorsal visual pathway.

LENUS (Irish Health Repository)

Bokde, Arun L W

2012-02-01

PURPOSE: To evaluate whether patients with Alzheimer disease (AD) have altered activation compared with age-matched healthy control (HC) subjects during a task that typically recruits the dorsal visual pathway. MATERIALS AND METHODS: The study was performed in accordance with the Declaration of Helsinki, with institutional ethics committee approval, and all subjects provided written informed consent. Two tasks were performed to investigate neural function: face matching and location matching. Twelve patients with mild AD and 14 age-matched HC subjects were included. Brain activation was measured by using functional magnetic resonance imaging. Group statistical analyses were based on a mixed-effects model corrected for multiple comparisons. RESULTS: Task performance was not statistically different between the two groups, and within groups there were no differences in task performance. In the HC group, the visual perception tasks selectively activated the visual pathways. Conversely in the AD group, there was no selective activation during performance of these same tasks. Along the dorsal visual pathway, the AD group recruited additional regions, primarily in the parietal and frontal lobes, for the location-matching task. There were no differences in activation between groups during the face-matching task. CONCLUSION: The increased activation in the AD group may represent a compensatory mechanism for decreased processing effectiveness in early visual areas of patients with AD. The findings support the idea that the dorsal visual pathway is more susceptible to putative AD-related neuropathologic changes than is the ventral visual pathway.

Cultural influences on the neural correlate of moral decision making processes.

Science.gov (United States)

Han, Hyemin; Glover, Gary H; Jeong, Changwoo

2014-02-01

This study compares the neural substrate of moral decision making processes between Korean and American participants. By comparison with Americans, Korean participants showed increased activity in the right putamen associated with socio-intuitive processes and right superior frontal gyrus associated with cognitive control processes under a moral-personal condition, and in the right postcentral sulcus associated with mental calculation in familiar contexts under a moral-impersonal condition. On the other hand, American participants showed a significantly higher degree of activity in the bilateral anterior cingulate cortex (ACC) associated with conflict resolution under the moral-personal condition, and in the right medial frontal gyrus (MFG) associated with simple cognitive branching in non-familiar contexts under the moral-impersonal condition when a more lenient threshold was applied, than Korean participants. These findings support the ideas of the interactions between the cultural background, education, and brain development, proposed in the field of cultural psychology and educational psychology. The study introduces educational implications relevant to moral psychologists and educators. Copyright © 2013 Elsevier B.V. All rights reserved.

Impact of load-related neural processes on feature binding in visuospatial working memory.

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Nicole A Kochan

Full Text Available BACKGROUND: The capacity of visual working memory (WM is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. OBJECTIVE: To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. METHODS AND FINDINGS: 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. CONCLUSIONS AND SIGNIFICANCE: The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this

Genetic Algorithm Optimized Neural Networks Ensemble as ...

African Journals Online (AJOL)

NJD

Improvements in neural network calibration models by a novel approach using neural network ensemble (NNE) for the simultaneous ... process by training a number of neural networks. .... Matlab® version 6.1 was employed for building principal component ... provide a fair simulation of calibration data set with some degree.

Germ layers, the neural crest and emergent organization in development and evolution.

Science.gov (United States)

Hall, Brian K

2018-04-10

Discovered in chick embryos by Wilhelm His in 1868 and named the neural crest by Arthur Milnes Marshall in 1879, the neural crest cells that arise from the neural folds have since been shown to differentiate into almost two dozen vertebrate cell types and to have played major roles in the evolution of such vertebrate features as bone, jaws, teeth, visceral (pharyngeal) arches, and sense organs. I discuss the discovery that ectodermal neural crest gave rise to mesenchyme and the controversy generated by that finding; the germ layer theory maintained that only mesoderm could give rise to mesenchyme. A second topic of discussion is germ layers (including the neural crest) as emergent levels of organization in animal development and evolution that facilitated major developmental and evolutionary change. The third topic is gene networks, gene co-option, and the evolution of gene-signaling pathways as key to developmental and evolutionary transitions associated with the origin and evolution of the neural crest and neural crest cells. © 2018 Wiley Periodicals, Inc.

A Translational Approach to Vocalization Deficits and Neural Recovery after Behavioral Treatment in Parkinson Disease

Science.gov (United States)

Ciucci, Michelle R.; Vinney, Lisa; Wahoske, Emerald J.; Connor, Nadine P.

2010-01-01

Parkinson disease is characterized by a complex neuropathological profile that primarily affects dopaminergic neural pathways in the basal ganglia, including pathways that modulate cranial sensorimotor functions such as swallowing, voice and speech. Prior work from our lab has shown that the rat model of unilateral 6-hydroxydopamine infusion to…

Volumetric multimodality neural network for brain tumor segmentation

Science.gov (United States)

Silvana Castillo, Laura; Alexandra Daza, Laura; Carlos Rivera, Luis; Arbeláez, Pablo

2017-11-01

Brain lesion segmentation is one of the hardest tasks to be solved in computer vision with an emphasis on the medical field. We present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric data along with information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. Our method is based on DeepMedic, the state of the art in brain lesion segmentation. We develop a new architecture with more convolutional layers, organized in three parallel pathways with different input resolution, and additional fully connected layers. We tested our method over the 2015 BraTS Challenge dataset, reaching an average dice coefficient of 84%, while the standard DeepMedic implementation reached 74%.

Neural networks underlying language and social cognition during self-other processing in Autism spectrum disorders.

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Kana, Rajesh K; Sartin, Emma B; Stevens, Carl; Deshpande, Hrishikesh D; Klein, Christopher; Klinger, Mark R; Klinger, Laura Grofer

2017-07-28

The social communication impairments defining autism spectrum disorders (ASD) may be built upon core deficits in perspective-taking, language processing, and self-other representation. Self-referential processing entails the ability to incorporate self-awareness, self-judgment, and self-memory in information processing. Very few studies have examined the neural bases of integrating self-other representation and semantic processing in individuals with ASD. The main objective of this functional MRI study is to examine the role of language and social brain networks in self-other processing in young adults with ASD. Nineteen high-functioning male adults with ASD and 19 age-sex-and-IQ-matched typically developing (TD) control participants made "yes" or "no" judgments of whether an adjective, presented visually, described them (self) or their favorite teacher (other). Both ASD and TD participants showed significantly increased activity in the medial prefrontal cortex (MPFC) during self and other processing relative to letter search. Analyses of group differences revealed significantly reduced activity in left inferior frontal gyrus (LIFG), and left inferior parietal lobule (LIPL) in ASD participants, relative to TD controls. ASD participants also showed significantly weaker functional connectivity of the anterior cingulate cortex (ACC) with several brain areas while processing self-related words. The LIFG and IPL are important regions functionally at the intersection of language and social roles; reduced recruitment of these regions in ASD participants may suggest poor level of semantic and social processing. In addition, poor connectivity of the ACC may suggest the difficulty in meeting the linguistic and social demands of this task in ASD. Overall, this study provides new evidence of the altered recruitment of the neural networks underlying language and social cognition in ASD. Published by Elsevier Ltd.

The Neural Circuits that Generate Tics in Gilles de la Tourette Syndrome

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Wang, Zhishun; Maia, Tiago V.; Marsh, Rachel; Colibazzi, Tiziano; Gerber, Andrew; Peterson, Bradley S.

2014-01-01

Objective To study neural activity and connectivity within cortico-striato-thalamo-cortical circuits and to reveal circuit-based neural mechanisms that govern tic generation in Tourette syndrome. Method We acquired fMRI data from 13 participants with Tourette syndrome and 21 controls during spontaneous or simulated tics. We used independent component analysis with hierarchical partner matching to isolate neural activity within functionally distinct regions of cortico-striato-thalamo-cortical circuits. We used Granger causality to investigate causal interactions among these regions. Results We found that the Tourette group exhibited stronger neural activity and interregional causality than controls throughout all portions of the motor pathway including sensorimotor cortex, putamen, pallidum, and substania nigra. Activity in these areas correlated positively with the severity of tic symptoms. Activity within the Tourette group was stronger during spontaneous tics than during voluntary tics in somatosensory and posterior parietal cortices, putamen, and amygdala/hippocampus complex, suggesting that activity in these regions may represent features of the premonitory urges that generate spontaneous tic behaviors. In contrast, activity was weaker in the Tourette group than in controls within portions of cortico-striato-thalamo-cortical circuits that exert top-down control over motor pathways (caudate and anterior cingulate cortex), and progressively less activity in these regions accompanied more severe tic symptoms, suggesting that faulty activity in these circuits may fail to control tic behaviors or the premonitory urges that generate them. Conclusions Our findings taken together suggest that tics are caused by the combined effects of excessive activity in motor pathways and reduced activation in control portions of cortico-striato-thalamo-cortical circuits. PMID:21955933

Stochastic modeling for neural spiking events based on fractional superstatistical Poisson process

Directory of Open Access Journals (Sweden)

Hidetoshi Konno

2018-01-01

Full Text Available In neural spike counting experiments, it is known that there are two main features: (i the counting number has a fractional power-law growth with time and (ii the waiting time (i.e., the inter-spike-interval distribution has a heavy tail. The method of superstatistical Poisson processes (SSPPs is examined whether these main features are properly modeled. Although various mixed/compound Poisson processes are generated with selecting a suitable distribution of the birth-rate of spiking neurons, only the second feature (ii can be modeled by the method of SSPPs. Namely, the first one (i associated with the effect of long-memory cannot be modeled properly. Then, it is shown that the two main features can be modeled successfully by a class of fractional SSPP (FSSPP.

A neural model of motion processing and visual navigation by cortical area MST.

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Grossberg, S; Mingolla, E; Pack, C

1999-12-01

Cells in the dorsal medial superior temporal cortex (MSTd) process optic flow generated by self-motion during visually guided navigation. A neural model shows how interactions between well-known neural mechanisms (log polar cortical magnification, Gaussian motion-sensitive receptive fields, spatial pooling of motion-sensitive signals and subtractive extraretinal eye movement signals) lead to emergent properties that quantitatively simulate neurophysiological data about MSTd cell properties and psychophysical data about human navigation. Model cells match MSTd neuron responses to optic flow stimuli placed in different parts of the visual field, including position invariance, tuning curves, preferred spiral directions, direction reversals, average response curves and preferred locations for stimulus motion centers. The model shows how the preferred motion direction of the most active MSTd cells can explain human judgments of self-motion direction (heading), without using complex heading templates. The model explains when extraretinal eye movement signals are needed for accurate heading perception, and when retinal input is sufficient, and how heading judgments depend on scene layouts and rotation rates.

Effects of modality on the neural correlates of encoding processes supporting recollection and familiarity

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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 later recollection, or whether overlapping subsequent memory and study condition effects are also evident when later memory is familiarity-based. Subjects (N = 17) underwent fMRI scanning while studying a series of visually and auditorily presented words. Memory for the words was subsequently tested with a modified Remember/Know procedure. Auditorily selective subsequent familiarity effects were evident in bilateral temporal regions that also responded preferentially to auditory items. Although other interpretations are possible, these findings suggest that overlap between study condition-selective subsequent memory effects and regions selectively sensitive to study demands is not uniquely associated with later recollection. In addition, modality-independent subsequent memory effects were identified in several cortical regions. In every case, the effects were greatest for later recollected items, and smaller for items later recognized on the basis of familiarity. The implications of this quantitative dissociation for dual-process models of recognition memory are discussed. PMID:21852431

Neural bases of congenital amusia in tonal language speakers.

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Zhang, Caicai; Peng, Gang; Shao, Jing; Wang, William S-Y

2017-03-01

Congenital amusia is a lifelong neurodevelopmental disorder of fine-grained pitch processing. In this fMRI study, we examined the neural bases of congenial amusia in speakers of a tonal language - Cantonese. Previous studies on non-tonal language speakers suggest that the neural deficits of congenital amusia lie in the music-selective neural circuitry in the right inferior frontal gyrus (IFG). However, it is unclear whether this finding can generalize to congenital amusics in tonal languages. Tonal language experience has been reported to shape the neural processing of pitch, which raises the question of how tonal language experience affects the neural bases of congenital amusia. To investigate this question, we examined the neural circuitries sub-serving the processing of relative pitch interval in pitch-matched Cantonese level tone and musical stimuli in 11 Cantonese-speaking amusics and 11 musically intact controls. Cantonese-speaking amusics exhibited abnormal brain activities in a widely distributed neural network during the processing of lexical tone and musical stimuli. Whereas the controls exhibited significant activation in the right superior temporal gyrus (STG) in the lexical tone condition and in the cerebellum regardless of the lexical tone and music conditions, no activation was found in the amusics in those regions, which likely reflects a dysfunctional neural mechanism of relative pitch processing in the amusics. Furthermore, the amusics showed abnormally strong activation of the right middle frontal gyrus and precuneus when the pitch stimuli were repeated, which presumably reflect deficits of attending to repeated pitch stimuli or encoding them into working memory. No significant group difference was found in the right IFG in either the whole-brain analysis or region-of-interest analysis. These findings imply that the neural deficits in tonal language speakers might differ from those in non-tonal language speakers, and overlap partly with the

Complex-valued neural networks advances and applications

CERN Document Server

Hirose, Akira

2013-01-01

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and

The impact of acute stress on the neural processing of food cues in bulimia nervosa: Replication in two samples.

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Collins, Brittany; Breithaupt, Lauren; McDowell, Jennifer E; Miller, L Stephen; Thompson, James; Fischer, Sarah

2017-07-01

The impact of acute stress on the neural processing of food cues in bulimia nervosa (BN) is unknown, despite theory that acute stress decreases cognitive control over food and hence increases vulnerability to environmental triggers for binge eating. Thus, the goals of this manuscript were to explore the impact of acute stress on the neural processing of food cues in BN. In Study 1, 10 women with Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5; American Psychiatric Association, 2013) BN and 10 healthy controls participated in an fMRI paradigm examining the neural correlates of visual food cue processing pre and post an acute stress induction. Whole brain analysis indicated that women with BN exhibited significant decreases in activation in the precuneus, associated with self-referential processing, the paracingulate gyrus, and the anterior vermis of the cerebellum. Healthy controls exhibited increased activation in these regions in response to food cues poststress. In Study 2, 17 women with DSM-5 BN or otherwise specified feeding and eating disorder with BN symptoms participated in the same paradigm. A region of interest analysis replicated findings from Study 1. Replication of imaging findings in 2 different samples suggests the potential importance of these regions in relation to BN. Decreased activation in the precuneus, specifically, is consistent with models of BN that posit that binge eating serves as a concrete distraction from aversive internal stimuli. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Biological neural networks as model systems for designing future parallel processing computers

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Ross, Muriel D.

1991-01-01

One of the more interesting debates of the present day centers on whether human intelligence can be simulated by computer. The author works under the premise that neurons individually are not smart at all. Rather, they are physical units which are impinged upon continuously by other matter that influences the direction of voltage shifts across the units membranes. It is only the action of a great many neurons, billions in the case of the human nervous system, that intelligent behavior emerges. What is required to understand even the simplest neural system is painstaking analysis, bit by bit, of the architecture and the physiological functioning of its various parts. The biological neural network studied, the vestibular utricular and saccular maculas of the inner ear, are among the most simple of the mammalian neural networks to understand and model. While there is still a long way to go to understand even this most simple neural network in sufficient detail for extrapolation to computers and robots, a start was made. Moreover, the insights obtained and the technologies developed help advance the understanding of the more complex neural networks that underlie human intelligence.

Epigenetics and Neural developmental disorders: Washington DC, September 18 and 19, 2006.

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Zhao, Xinyu; Pak, ChangHui; Smrt, Richard D; Jin, Peng

2007-01-01

Neural developmental disorders, such as autism, Rett Syndrome, Fragile X syndrome, and Angelman syndrome manifest during early postnatal neural development. Although the genes responsible for some of these disorders have been identified, how the mutations of these genes affect neural development is currently unclear. Emerging evidence suggest that these disorders share common underlying defects in neuronal morphology, synaptic connectivity and brain plasticity. In particular, alterations in dendritic branching and spine morphology play a central role in the pathophysiology of most mental retardation disorders, suggesting that common pathways regulating neuronal function may be affected. Epigenetic modulations, mediated by DNA methylation, RNA-associated silencing, and histone modification, can serve as an intermediate process that imprints dynamic environmental experiences on the "fixed" genome, resulting in stable alterations in phenotypes. Disturbance in epigenetic regulations can lead to inappropriate expression or silencing of genes, causing an array of multi-system disorders and neoplasias. Rett syndrome, the most common form of mental retardation in young girls, is due to l mutation of MECP2, encoding a methylated DNA binding protein that translates DNA methylation into gene repression. Angelman syndrome is due to faulty genomic imprinting or maternal mutations in UBE3A. Fragile X Syndrome, in most cases, results from the hypermethylation of FMR1 promoter, hence the loss of expression of functional FMRP protein. Autism, with its complex etiology, may have strong epigenetic link. Together, these observations strongly suggest that epigenetic mechanisms may play a critical role in brain development and etiology of related disorders. This report summarizes the scientific discussions and major conclusions from a recent conference that aimed to gain insight into the common molecular pathways affected among these disorders and discover potential therapeutic targets

Petri neural network model for the effect of controlled thermomechanical process parameters on the mechanical properties of HSLA steels

Energy Technology Data Exchange (ETDEWEB)

Datta, S.

1999-10-01

The effect of composition and controlled thermomechanical process parameters on the mechanical properties of HSLA steels is modelled using the Widrow-Hoff's concept of training a neural net with feed-forward topology by applying Rumelhart's back propagation type algorithm for supervised learning, using a Petri like net structure. The data used are from laboratory experiments as well as from the published literature. The results from the neural network are found to be consistent and in good agreement with the experimented results. (author)

Tactile spatial working memory activates the dorsal extrastriate cortical pathway in congenitally blind individuals.

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Bonino, D; Ricciardi, E; Sani, L; Gentili, C; Vanello, N; Guazzelli, M; Vecchi, T; Pietrini, P

2008-09-01

In sighted individuals, both the visual and tactile version of the same spatial working memory task elicited neural responses in the dorsal "where" cortical pathway (Ricciardi et al., 2006). Whether the neural response during the tactile working memory task is due to visually-based spatial imagery or rather reflects a more abstract, supramodal organization of the dorsal cortical pathway remains to be determined. To understand the role of visual experience on the functional organization of the dorsal cortical stream, using functional magnetic resonance imaging (fMRI) here we examined brain response in four individuals with congenital or early blindness and no visual recollection, while they performed the same tactile spatial working memory task, a one-back recognition of 2D and 3D matrices. The blind subjects showed a significant activation in bilateral posterior parietal cortex, dorsolateral and inferior prefrontal areas, precuneus, lateral occipital cortex, and cerebellum. Thus, dorsal occipito-parietal areas are involved in mental imagery dealing with spatial components in subjects without prior visual experience and in response to a non-visual task. These data indicate that recruitment of the dorsal cortical pathway in response to the tactile spatial working memory task is not mediated by visually-based imagery and that visual experience is not a prerequisite for the development of a more abstract functional organization of the dorsal stream. These findings, along with previous data indicating a similar supramodal functional organization within the ventral cortical pathway and the motion processing brain regions, may contribute to explain how individuals who are born deprived of sight are able to interact effectively with the surrounding world.

Image processing and analysis using neural networks for optometry area

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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.

Adaptive Filtering Using Recurrent Neural Networks

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Parlos, Alexander G.; Menon, Sunil K.; Atiya, Amir F.

2005-01-01

A method for adaptive (or, optionally, nonadaptive) filtering has been developed for estimating the states of complex process systems (e.g., chemical plants, factories, or manufacturing processes at some level of abstraction) from time series of measurements of system inputs and outputs. The method is based partly on the fundamental principles of the Kalman filter and partly on the use of recurrent neural networks. The standard Kalman filter involves an assumption of linearity of the mathematical model used to describe a process system. The extended Kalman filter accommodates a nonlinear process model but still requires linearization about the state estimate. Both the standard and extended Kalman filters involve the often unrealistic assumption that process and measurement noise are zero-mean, Gaussian, and white. In contrast, the present method does not involve any assumptions of linearity of process models or of the nature of process noise; on the contrary, few (if any) assumptions are made about process models, noise models, or the parameters of such models. In this regard, the method can be characterized as one of nonlinear, nonparametric filtering. The method exploits the unique ability of neural networks to approximate nonlinear functions. In a given case, the process model is limited mainly by limitations of the approximation ability of the neural networks chosen for that case. Moreover, despite the lack of assumptions regarding process noise, the method yields minimum- variance filters. In that they do not require statistical models of noise, the neural- network-based state filters of this method are comparable to conventional nonlinear least-squares estimators.