Static human face recognition using artificial neural networks

International Nuclear Information System (INIS)

Qamar, R.; Shah, S.H.; Javed-ur-Rehman

2003-01-01

This paper presents a novel method of human face recognition using digital computers. A digital PC camera is used to take the BMP images of the human faces. An artificial neural network using Back Propagation Algorithm is developed as a recognition engine. The BMP images of the faces serve as the input patterns for this engine. A software 'Face Recognition' has been developed to recognize the human faces for which it is trained. Once the neural network is trained for patterns of the faces, the software is able to detect and recognize them with success rate of about 97%. (author)

Expression of cardiac neural crest and heart genes isolated by modified differential display.

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Martinsen, Brad J; Groebner, Nathan J; Frasier, Allison J; Lohr, Jamie L

2003-08-01

The invasion of the cardiac neural crest (CNC) into the outflow tract (OFT) and subsequent outflow tract septation are critical events during vertebrate heart development. We have performed four modified differential display screens in the chick embryo to identify genes that may be involved in CNC, OFT, secondary heart field, and heart development. The screens included differential display of RNA isolated from three different axial segments containing premigratory cranial neural crest cells; of RNA from distal outflow tract, proximal outflow tract, and atrioventricular tissue of embryonic chick hearts; and of RNA isolated from left and right cranial tissues, including the early heart fields. These screens have resulted in the identification of the five cDNA clones presented here, which are expressed in the cardiac neural crest, outflow tract and developing heart in patterns that are unique in heart development.

Real-time camera-based face detection using a modified LAMSTAR neural network system

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Girado, Javier I.; Sandin, Daniel J.; DeFanti, Thomas A.; Wolf, Laura K.

2003-03-01

This paper describes a cost-effective, real-time (640x480 at 30Hz) upright frontal face detector as part of an ongoing project to develop a video-based, tetherless 3D head position and orientation tracking system. The work is specifically targeted for auto-stereoscopic displays and projection-based virtual reality systems. The proposed face detector is based on a modified LAMSTAR neural network system. At the input stage, after achieving image normalization and equalization, a sub-window analyzes facial features using a neural network. The sub-window is segmented, and each part is fed to a neural network layer consisting of a Kohonen Self-Organizing Map (SOM). The output of the SOM neural networks are interconnected and related by correlation-links, and can hence determine the presence of a face with enough redundancy to provide a high detection rate. To avoid tracking multiple faces simultaneously, the system is initially trained to track only the face centered in a box superimposed on the display. The system is also rotationally and size invariant to a certain degree.

Isolation and characterization of neural stem cells from human fetal striatum

International Nuclear Information System (INIS)

Li Xiaoxia; Xu Jinchong; Bai Yun; Wang Xuan; Dai Xin; Liu Yinan; Zhang Jun; Zou Junhua; Shen Li; Li Lingsong

2005-01-01

This paper described that neural stem cells (hsNSCs) were isolated and expanded rapidly from human fetal striatum in adherent culture. The population was serum- and growth factor-dependent and expressed neural stem cell markers. They were capable of multi-differentiation into neurons, astrocytes, and oligodendrocytes. When plated in the dopaminergic neuron inducing medium, human striatum neural stem cells could differentiate into tyrosine hydroxylase positive neurons. hsNSCs were morphologically homogeneous and possessed high proliferation ability. The population doubled every 44.28 h and until now it has divided for more than 82 generations in vitro. Normal human diploid karyotype was unchanged throughout the in vitro culture period. Together, this study has exploited a method for continuous and rapid expansion of human neural stem cells as pure population, which maintained the capacity to generate almost fifty percent neurons. The availability of such cells may hold great interest for basic and applied neuroscience

Culture-sensitive neural substrates of human cognition: a transcultural neuroimaging approach.

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Han, Shihui; Northoff, Georg

2008-08-01

Our brains and minds are shaped by our experiences, which mainly occur in the context of the culture in which we develop and live. Although psychologists have provided abundant evidence for diversity of human cognition and behaviour across cultures, the question of whether the neural correlates of human cognition are also culture-dependent is often not considered by neuroscientists. However, recent transcultural neuroimaging studies have demonstrated that one's cultural background can influence the neural activity that underlies both high- and low-level cognitive functions. The findings provide a novel approach by which to distinguish culture-sensitive from culture-invariant neural mechanisms of human cognition.

Non-Viral Generation of Neural Precursor-like Cells from Adult Human Fibroblasts

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Maucksch C

2012-01-01

Full Text Available Recent studies have reported direct reprogramming of human fibroblasts to mature neurons by the introduction of defined neural genes. This technology has potential use in the areas of neurological disease modeling and drug development. However, use of induced neurons for large-scale drug screening and cell-based replacement strategies is limited due to their inability to expand once reprogrammed. We propose it would be more desirable to induce expandable neural precursor cells directly from human fibroblasts. To date several pluripotent and neural transcription factors have been shown to be capable of converting mouse fibroblasts to neural stem/precursor-like cells when delivered by viral vectors. Here we extend these findings and demonstrate that transient ectopic insertion of the transcription factors SOX2 and PAX6 to adult human fibroblasts through use of non-viral plasmid transfection or protein transduction allows the generation of induced neural precursor (iNP colonies expressing a range of neural stem and pro-neural genes. Upon differentiation, iNP cells give rise to neurons exhibiting typical neuronal morphologies and expressing multiple neuronal markers including tyrosine hydroxylase and GAD65/67. Importantly, iNP-derived neurons demonstrate electrophysiological properties of functionally mature neurons with the capacity to generate action potentials. In addition, iNP cells are capable of differentiating into glial fibrillary acidic protein (GFAP-expressing astrocytes. This study represents a novel virus-free approach for direct reprogramming of human fibroblasts to a neural precursor fate.

Neural correlate of human reciprocity in social interactions.

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Sakaiya, Shiro; Shiraito, Yuki; Kato, Junko; Ide, Hiroko; Okada, Kensuke; Takano, Kouji; Kansaku, Kenji

2013-01-01

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoner's dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions.

Neural correlate of human reciprocity in social interactions

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Shiro eSakaiya

2013-12-01

Full Text Available Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human and strategy (random, tit-for-tat in repeated prisoner’s dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate and theory of mind (ToM regions (i.e., ventromedial prefrontal cortex [VMPFC] and precuneus. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (deactivation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during

Establishment of Human Neural Progenitor Cells from Human Induced Pluripotent Stem Cells with Diverse Tissue Origins

OpenAIRE

Hayato Fukusumi; Tomoko Shofuda; Yohei Bamba; Atsuyo Yamamoto; Daisuke Kanematsu; Yukako Handa; Keisuke Okita; Masaya Nakamura; Shinya Yamanaka; Hideyuki Okano; Yonehiro Kanemura

2016-01-01

Human neural progenitor cells (hNPCs) have previously been generated from limited numbers of human induced pluripotent stem cell (hiPSC) clones. Here, 21 hiPSC clones derived from human dermal fibroblasts, cord blood cells, and peripheral blood mononuclear cells were differentiated using two neural induction methods, an embryoid body (EB) formation-based method and an EB formation method using dual SMAD inhibitors (dSMADi). Our results showed that expandable hNPCs could be generated from hiPS...

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.

Structural Analysis of Three-dimensional Human Neural Tissue derived from Induced Pluripotent Stem Cells

DEFF Research Database (Denmark)

Terrence Brooks, Patrick; Rasmussen, Mikkel Aabech; Hyttel, Poul

2016-01-01

Objective: The present study aimed at establishing a method for production of a three-dimensional (3D) human neural tissue derived from induced pluripotent stem cells (iPSCs) and analyzing the outcome by a combination of tissue ultrastructure and expression of neural markers. Methods: A two......-step cell culture procedure was implemented by subjecting human iPSCs to a 3D scaffoldbased neural differentiation protocol. First, neural fate-inducing small molecules were used to create a neuroepithelial monolayer. Second, the monolayer was trypsinized into single cells and seeded into a porous...... polystyrene scaffold and further cultured to produce a 3D neural tissue. The neural tissue was characterized by a combination of immunohistochemistry and transmission electron microscopy (TEM). Results: iPSCs developed into a 3D neural tissue expressing markers for neural progenitor cells, early neural...

Urea and thiourea modified polypropyleneimine dendrimers clear intracellular α-synuclein aggregates in a human cell line

DEFF Research Database (Denmark)

Laumann, Kristoffer; Boas, Ulrik; Larsen, Hjalte Martin

2015-01-01

Synucleinopathies are neurodegenerative pathologies in which disease progression is closely correlated to brain accumulation of insoluble α-synuclein, a small protein abundantly expressed in neural tissue. Here, two types of modified polypropyleneimine (PPI) dendrimers having either urea or methy......Synucleinopathies are neurodegenerative pathologies in which disease progression is closely correlated to brain accumulation of insoluble α-synuclein, a small protein abundantly expressed in neural tissue. Here, two types of modified polypropyleneimine (PPI) dendrimers having either urea...

Drought in a human-modified world

NARCIS (Netherlands)

Loon, van Anne F.; Stahl, Kerstin; Baldassarre, Di Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko; Gleeson, Tom; Dijk, van Albert I.J.M.; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Ryan; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; Wagener, Thorsten; Lanen, van Henny A.J.

2016-01-01

In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows,

Human neural stem cells over-expressing VEGF provide neuroprotection, angiogenesis and functional recovery in mouse stroke model.

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Hong J Lee

Full Text Available BACKGROUND: Intracerebral hemorrhage (ICH is a lethal stroke type. As mortality approaches 50%, and current medical therapy against ICH shows only limited effectiveness, an alternative approach is required, such as stem cell-based cell therapy. Previously we have shown that intravenously transplanted human neural stem cells (NSCs selectively migrate to the brain and induce behavioral recovery in rat ICH model, and that combined administration of NSCs and vascular endothelial growth factor (VEGF results in improved structural and functional outcome from cerebral ischemia. METHODS AND FINDINGS: We postulated that human NSCs overexpressing VEGF transplanted into cerebral cortex overlying ICH lesion could provide improved survival of grafted NSCs, increased angiogenesis and behavioral recovery in mouse ICH model. ICH was induced in adult mice by unilateral injection of bacterial collagenase into striatum. HB1.F3.VEGF human NSC line produced an amount of VEGF four times higher than parental F3 cell line in vitro, and induced behavioral improvement and 2-3 fold increase in cell survival at two weeks and eight weeks post-transplantation. CONCLUSIONS: Brain transplantation of F3 human NSCs over-expressing VEGF near ICH lesion sites provided differentiation and survival of grafted human NSCs and renewed angiogenesis of host brain and functional recovery of ICH animals. These results suggest a possible application of the human neural stem cell line, which is genetically modified to over-express VEGF, as a therapeutic agent for ICH-stroke.

Developing a hippocampal neural prosthetic to facilitate human memory encoding and recall

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Hampson, Robert E.; Song, Dong; Robinson, Brian S.; Fetterhoff, Dustin; Dakos, Alexander S.; Roeder, Brent M.; She, Xiwei; Wicks, Robert T.; Witcher, Mark R.; Couture, Daniel E.; Laxton, Adrian W.; Munger-Clary, Heidi; Popli, Gautam; Sollman, Myriam J.; Whitlow, Christopher T.; Marmarelis, Vasilis Z.; Berger, Theodore W.; Deadwyler, Sam A.

2018-06-01

Objective. We demonstrate here the first successful implementation in humans of a proof-of-concept system for restoring and improving memory function via facilitation of memory encoding using the patient’s own hippocampal spatiotemporal neural codes for memory. Memory in humans is subject to disruption by drugs, disease and brain injury, yet previous attempts to restore or rescue memory function in humans typically involved only nonspecific, modulation of brain areas and neural systems related to memory retrieval. Approach. We have constructed a model of processes by which the hippocampus encodes memory items via spatiotemporal firing of neural ensembles that underlie the successful encoding of short-term memory. A nonlinear multi-input, multi-output (MIMO) model of hippocampal CA3 and CA1 neural firing is computed that predicts activation patterns of CA1 neurons during the encoding (sample) phase of a delayed match-to-sample (DMS) human short-term memory task. Main results. MIMO model-derived electrical stimulation delivered to the same CA1 locations during the sample phase of DMS trials facilitated short-term/working memory by 37% during the task. Longer term memory retention was also tested in the same human subjects with a delayed recognition (DR) task that utilized images from the DMS task, along with images that were not from the task. Across the subjects, the stimulated trials exhibited significant improvement (35%) in both short-term and long-term retention of visual information. Significance. These results demonstrate the facilitation of memory encoding which is an important feature for the construction of an implantable neural prosthetic to improve human memory.

Convolutional Neural Networks for Human Activity Recognition Using Body-Worn Sensors

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Fernando Moya Rueda

2018-05-01

Full Text Available Human activity recognition (HAR is a classification task for recognizing human movements. Methods of HAR are of great interest as they have become tools for measuring occurrences and durations of human actions, which are the basis of smart assistive technologies and manual processes analysis. Recently, deep neural networks have been deployed for HAR in the context of activities of daily living using multichannel time-series. These time-series are acquired from body-worn devices, which are composed of different types of sensors. The deep architectures process these measurements for finding basic and complex features in human corporal movements, and for classifying them into a set of human actions. As the devices are worn at different parts of the human body, we propose a novel deep neural network for HAR. This network handles sequence measurements from different body-worn devices separately. An evaluation of the architecture is performed on three datasets, the Oportunity, Pamap2, and an industrial dataset, outperforming the state-of-the-art. In addition, different network configurations will also be evaluated. We find that applying convolutions per sensor channel and per body-worn device improves the capabilities of convolutional neural network (CNNs.

Human Neural Stem Cell Transplantation Rescues Functional Deficits in R6/2 and Q140 Huntington's Disease Mice

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Jack C. Reidling

2018-01-01

Full Text Available Huntington's disease (HD is an inherited neurodegenerative disorder with no disease-modifying treatment. Expansion of the glutamine-encoding repeat in the Huntingtin (HTT gene causes broad effects that are a challenge for single treatment strategies. Strategies based on human stem cells offer a promising option. We evaluated efficacy of transplanting a good manufacturing practice (GMP-grade human embryonic stem cell-derived neural stem cell (hNSC line into striatum of HD modeled mice. In HD fragment model R6/2 mice, transplants improve motor deficits, rescue synaptic alterations, and are contacted by nerve terminals from mouse cells. Furthermore, implanted hNSCs are electrophysiologically active. hNSCs also improved motor and late-stage cognitive impairment in a second HD model, Q140 knockin mice. Disease-modifying activity is suggested by the reduction of aberrant accumulation of mutant HTT protein and expression of brain-derived neurotrophic factor (BDNF in both models. These findings hold promise for future development of stem cell-based therapies.

In our own image? Emotional and neural processing differences when observing human-human vs human-robot interactions.

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Wang, Yin; Quadflieg, Susanne

2015-11-01

Notwithstanding the significant role that human-robot interactions (HRI) will play in the near future, limited research has explored the neural correlates of feeling eerie in response to social robots. To address this empirical lacuna, the current investigation examined brain activity using functional magnetic resonance imaging while a group of participants (n = 26) viewed a series of human-human interactions (HHI) and HRI. Although brain sites constituting the mentalizing network were found to respond to both types of interactions, systematic neural variation across sites signaled diverging social-cognitive strategies during HHI and HRI processing. Specifically, HHI elicited increased activity in the left temporal-parietal junction indicative of situation-specific mental state attributions, whereas HRI recruited the precuneus and the ventromedial prefrontal cortex (VMPFC) suggestive of script-based social reasoning. Activity in the VMPFC also tracked feelings of eeriness towards HRI in a parametric manner, revealing a potential neural correlate for a phenomenon known as the uncanny valley. By demonstrating how understanding social interactions depends on the kind of agents involved, this study highlights pivotal sub-routes of impression formation and identifies prominent challenges in the use of humanoid robots. © The Author (2015). Published by Oxford University Press.

Differentiation of insulin-producing cells from human neural progenitor cells.

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Yuichi Hori

2005-04-01

Full Text Available BACKGROUND: Success in islet-transplantation-based therapies for type 1 diabetes, coupled with a worldwide shortage of transplant-ready islets, has motivated efforts to develop renewable sources of islet-replacement tissue. Islets and neurons share features, including common developmental programs, and in some species brain neurons are the principal source of systemic insulin. METHODS AND FINDINGS: Here we show that brain-derived human neural progenitor cells, exposed to a series of signals that regulate in vivo pancreatic islet development, form clusters of glucose-responsive insulin-producing cells (IPCs. During in vitro differentiation of neural progenitor cells with this novel method, genes encoding essential known in vivo regulators of pancreatic islet development were expressed. Following transplantation into immunocompromised mice, IPCs released insulin C-peptide upon glucose challenge, remained differentiated, and did not form detectable tumors. CONCLUSION: Production of IPCs solely through extracellular factor modulation in the absence of genetic manipulations may promote strategies to derive transplantable islet-replacement tissues from human neural progenitor cells and other types of multipotent human stem cells.

Artificial neural network detects human uncertainty

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Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

2018-03-01

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

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

2017-01-01

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

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

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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.

Modified GrabCut for human face segmentation

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Dina Khattab

2014-12-01

Full Text Available GrabCut is a segmentation technique for 2D still color images, which is mainly based on an iterative energy minimization. The energy function of the GrabCut optimization algorithm is based mainly on a probabilistic model for pixel color distribution. Therefore, GrabCut may introduce unacceptable results in the cases of low contrast between foreground and background colors. In this manner, this paper presents a modified GrabCut technique for the segmentation of human faces from images of full humans. The modified technique introduces a new face location model for the energy minimization function of the GrabCut, in addition to the existing color one. This location model considers the distance distribution of the pixels from the silhouette boundary of a fitted head, of a 3D morphable model, to the image. The experimental results of the modified GrabCut have demonstrated better segmentation robustness and accuracy compared to the original GrabCut for human face segmentation.

Novel Modified Elman Neural Network Control for PMSG System Based on Wind Turbine Emulator

OpenAIRE

Lin, Chih-Hong

2013-01-01

The novel modified Elman neural network (NN) controlled permanent magnet synchronous generator (PMSG) system, which is directly driven by a permanent magnet synchronous motor (PMSM) based on wind turbine emulator, is proposed to control output of rectifier (AC/DC power converter) and inverter (DC/AC power converter) in this study. First, a closed loop PMSM drive control based on wind turbine emulator is designed to generate power for the PMSG system according to different wind speeds. Then, t...

Human Embryonic Stem Cells: A Model for the Study of Neural Development and Neurological Diseases

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Piya Prajumwongs

2016-01-01

Full Text Available Although the mechanism of neurogenesis has been well documented in other organisms, there might be fundamental differences between human and those species referring to species-specific context. Based on principles learned from other systems, it is found that the signaling pathways required for neural induction and specification of human embryonic stem cells (hESCs recapitulated those in the early embryo development in vivo at certain degree. This underscores the usefulness of hESCs in understanding early human neural development and reinforces the need to integrate the principles of developmental biology and hESC biology for an efficient neural differentiation.

Analysis of Neural Stem Cells from Human Cortical Brain Structures In Vitro.

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Aleksandrova, M A; Poltavtseva, R A; Marei, M V; Sukhikh, G T

2016-05-01

Comparative immunohistochemical analysis of the neocortex from human fetuses showed that neural stem and progenitor cells are present in the brain throughout the gestation period, at least from week 8 through 26. At the same time, neural stem cells from the first and second trimester fetuses differed by the distribution, morphology, growth, and quantity. Immunocytochemical analysis of neural stem cells derived from fetuses at different gestation terms and cultured under different conditions showed their differentiation capacity. Detailed analysis of neural stem cell populations derived from fetuses on gestation weeks 8-9, 18-20, and 26 expressing Lex/SSEA1 was performed.

Neural Correlates of the Cortisol Awakening Response in Humans.

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Boehringer, Andreas; Tost, Heike; Haddad, Leila; Lederbogen, Florian; Wüst, Stefan; Schwarz, Emanuel; Meyer-Lindenberg, Andreas

2015-08-01

The cortisol rise after awakening (cortisol awakening response, CAR) is a core biomarker of hypothalamic-pituitary-adrenal (HPA) axis regulation related to psychosocial stress and stress-related psychiatric disorders. However, the neural regulation of the CAR has not been examined in humans. Here, we studied neural regulation related to the CAR in a sample of 25 healthy human participants using an established psychosocial stress paradigm together with multimodal functional and structural (voxel-based morphometry) magnetic resonance imaging. Across subjects, a smaller CAR was associated with reduced grey matter volume and increased stress-related brain activity in the perigenual ACC, a region which inhibits HPA axis activity during stress that is implicated in risk mechanisms and pathophysiology of stress-related mental diseases. Moreover, functional connectivity between the perigenual ACC and the hypothalamus, the primary controller of HPA axis activity, was associated with the CAR. Our findings provide support for a role of the perigenual ACC in regulating the CAR in humans and may aid future research on the pathophysiology of stress-related illnesses, such as depression, and environmental risk for illnesses such as schizophrenia.

Protection of visual functions by human neural progenitors in a rat model of retinal disease.

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David M Gamm

2007-03-01

Full Text Available A promising clinical application for stem and progenitor cell transplantation is in rescue therapy for degenerative diseases. This strategy seeks to preserve rather than restore host tissue function by taking advantage of unique properties often displayed by these versatile cells. In studies using different neurodegenerative disease models, transplanted human neural progenitor cells (hNPC protected dying host neurons within both the brain and spinal cord. Based on these reports, we explored the potential of hNPC transplantation to rescue visual function in an animal model of retinal degeneration, the Royal College of Surgeons rat.Animals received unilateral subretinal injections of hNPC or medium alone at an age preceding major photoreceptor loss. Principal outcomes were quantified using electroretinography, visual acuity measurements and luminance threshold recordings from the superior colliculus. At 90-100 days postnatal, a time point when untreated rats exhibit little or no retinal or visual function, hNPC-treated eyes retained substantial retinal electrical activity and visual field with near-normal visual acuity. Functional efficacy was further enhanced when hNPC were genetically engineered to secrete glial cell line-derived neurotrophic factor. Histological examination at 150 days postnatal showed hNPC had formed a nearly continuous pigmented layer between the neural retina and retinal pigment epithelium, as well as distributed within the inner retina. A concomitant preservation of host cone photoreceptors was also observed.Wild type and genetically modified human neural progenitor cells survive for prolonged periods, migrate extensively, secrete growth factors and rescue visual functions following subretinal transplantation in the Royal College of Surgeons rat. These results underscore the potential therapeutic utility of hNPC in the treatment of retinal degenerative diseases and suggest potential mechanisms underlying their effect in

Wireless synapses in bio-inspired neural networks

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Jannson, Tomasz; Forrester, Thomas; Degrood, Kevin

2009-05-01

Wireless (virtual) synapses represent a novel approach to bio-inspired neural networks that follow the infrastructure of the biological brain, except that biological (physical) synapses are replaced by virtual ones based on cellular telephony modeling. Such synapses are of two types: intracluster synapses are based on IR wireless ones, while intercluster synapses are based on RF wireless ones. Such synapses have three unique features, atypical of conventional artificial ones: very high parallelism (close to that of the human brain), very high reconfigurability (easy to kill and to create), and very high plasticity (easy to modify or upgrade). In this paper we analyze the general concept of wireless synapses with special emphasis on RF wireless synapses. Also, biological mammalian (vertebrate) neural models are discussed for comparison, and a novel neural lensing effect is discussed in detail.

A modified dynamic evolving neural-fuzzy approach to modeling customer satisfaction for affective design.

Science.gov (United States)

Kwong, C K; Fung, K Y; Jiang, Huimin; Chan, K Y; Siu, Kin Wai Michael

2013-01-01

Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

A Modified Dynamic Evolving Neural-Fuzzy Approach to Modeling Customer Satisfaction for Affective Design

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C. K. Kwong

2013-01-01

Full Text Available Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1 the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS failed to run due to a large number of inputs; (2 the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort.

Characterization of human neural differentiation from pluripotent stem cells using proteomics/PTMomics

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Braga, Marcella Nunes de Melo; Meyer, Morten; Zeng, Xianmin

2015-01-01

Stem cells are unspecialized cells capable of self-renewal and to differentiate into the large variety of cells in the body. The possibility to differentiate these cells into neural precursors and neural cells in vitro provides the opportunity to study neural development, nerve cell biology, neur...... differentiation from pluripotent stem cells. Moreover, some of the challenges in stem cell biology, differentiation, and proteomics/PTMomics that are not exclusive to neural development will be discussed.......Stem cells are unspecialized cells capable of self-renewal and to differentiate into the large variety of cells in the body. The possibility to differentiate these cells into neural precursors and neural cells in vitro provides the opportunity to study neural development, nerve cell biology...... the understanding of molecular processes in cells. Substantial advances in PTM enrichment methods and mass spectrometry has allowed the characterization of a subset of PTMs in large-scale studies. This review focuses on the current state-of-the-art of proteomic, as well as PTMomic studies related to human neural...

Neural networks of human nature and nurture

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Daniel S. Levine

2009-11-01

Full Text Available Neural network methods have facilitated the unification of several unfortunate splits in psychology, including nature versus nurture. We review the contributions of this methodology and then discuss tentative network theories of caring behavior, of uncaring behavior, and of how the frontal lobes are involved in the choices between them. The implications of our theory are optimistic about the prospects of society to encourage the human potential for caring.

Heparan Sulfate Proteoglycans as Drivers of Neural Progenitors Derived From Human Mesenchymal Stem Cells.

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Okolicsanyi, Rachel K; Oikari, Lotta E; Yu, Chieh; Griffiths, Lyn R; Haupt, Larisa M

2018-01-01

Background: Due to their relative ease of isolation and their high ex vivo and in vitro expansive potential, human mesenchymal stem cells (hMSCs) are an attractive candidate for therapeutic applications in the treatment of brain injury and neurological diseases. Heparan sulfate proteoglycans (HSPGs) are a family of ubiquitous proteins involved in a number of vital cellular processes including proliferation and stem cell lineage differentiation. Methods: Following the determination that hMSCs maintain neural potential throughout extended in vitro expansion, we examined the role of HSPGs in mediating the neural potential of hMSCs. hMSCs cultured in basal conditions (undifferentiated monolayer cultures) were found to co-express neural markers and HSPGs throughout expansion with modulation of the in vitro niche through the addition of exogenous HS influencing cellular HSPG and neural marker expression. Results: Conversion of hMSCs into hMSC Induced Neurospheres (hMSC IN) identified distinctly localized HSPG staining within the spheres along with altered gene expression of HSPG core protein and biosynthetic enzymes when compared to undifferentiated hMSCs. Conclusion: Comparison of markers of pluripotency, neural self-renewal and neural lineage specification between hMSC IN, hMSC and human neural stem cell (hNSC H9) cultures suggest that in vitro generated hMSC IN may represent an intermediary neurogenic cell type, similar to a common neural progenitor cell. In addition, this data demonstrates HSPGs and their biosynthesis machinery, are associated with hMSC IN formation. The identification of specific HSPGs driving hMSC lineage-specification will likely provide new markers to allow better use of hMSCs in therapeutic applications and improve our understanding of human neurogenesis.

Noncoding RNA in the Transcriptional Landscape of Human Neural Progenitor Cell Differentiation

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Patrick eHecht

2015-10-01

Full Text Available Increasing evidence suggests that noncoding RNAs play key roles in cellular processes, particularly in the brain. The present study used RNA sequencing to identify the transcriptional landscape of two human neural progenitor cell lines, SK-N-SH and ReNcell CX, as they differentiate into human cortical projection neurons. Protein coding genes were found to account for 54.8% and 57.0% of expressed genes, respectively, and alignment of RNA sequencing reads revealed that only 25.5-28.1% mapped to exonic regions of the genome. Differential expression analysis in the two cell lines identified altered gene expression in both protein coding and noncoding RNAs as they undergo neural differentiation with 222 differentially expressed genes observed in SK-N-SH cells and 19 differentially expressed genes in ReNcell CX. Interestingly, genes showing differential expression in SK-N-SH cells are enriched in genes implicated in autism spectrum disorder, but not in gene sets related to cancer or Alzheimer’s disease. Weighted gene co-expression network analysis (WGCNA was used to detect modules of co-expressed protein coding and noncoding RNAs in SK-N-SH cells and found four modules to be associated with neural differentiation. These modules contain varying levels of noncoding RNAs ranging from 10.7% to 49.7% with gene ontology suggesting roles in numerous cellular processes important for differentiation. These results indicate that noncoding RNAs are highly expressed in human neural progenitor cells and likely hold key regulatory roles in gene networks underlying neural differentiation and neurodevelopmental disorders.

The use of artificial neural network to evaluate the effects of human ...

African Journals Online (AJOL)

The use of artificial neural network to evaluate the effects of human and physiographic factors on forest stock volume. ... stock volume and human factors in certain topography conditions and provides useful information for the acceptable amount of standing inventory using the present human population in future experiment.

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

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

2009-01-01

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

A Chronically Implantable Bidirectional Neural Interface for Non-human Primates

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Misako Komatsu

2017-09-01

Full Text Available Optogenetics has potential applications in the study of epilepsy and neuroprostheses, and for studies on neural circuit dynamics. However, to achieve translation to clinical usage, optogenetic interfaces that are capable of chronic stimulation and monitoring with minimal brain trauma are required. We aimed to develop a chronically implantable device for photostimulation of the brain of non-human primates. We used a micro-light-emitting diode (LED array with a flexible polyimide film. The array was combined with a whole-cortex electrocorticographic (ECoG electrode array for simultaneous photostimulation and recording. Channelrhodopsin-2 (ChR2 was virally transduced into the cerebral cortex of common marmosets, and then the device was epidurally implanted into their brains. We recorded the neural activity during photostimulation of the awake monkeys for 4 months. The neural responses gradually increased after the virus injection for ~8 weeks and remained constant for another 8 weeks. The micro-LED and ECoG arrays allowed semi-invasive simultaneous stimulation and recording during long-term implantation in the brains of non-human primates. The development of this device represents substantial progress in the field of optogenetic applications.

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

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Cichy, Radoslaw Martin; Khosla, Aditya; Pantazis, Dimitrios; Oliva, Aude

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

Freeze Drying Improves the Shelf-Life of Conductive Polymer Modified Neural Electrodes

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Himadri S. Mandal

2015-08-01

Full Text Available Coating microelectrodes with conductive polymer is widely recognized to decrease impedance and improve performance of implantable neural devices during recording and stimulation. A concern for wide-spread use of this approach is shelf-life, i.e., the electrochemical stability of the coated microelectrodes prior to use. In this work, we investigated the possibility of using the freeze-drying process in order to retain the native low impedance state and, thereby, improve the shelf-life of conductive polymer poly(3,4-ethylenedioxythiophene (PEDOT-PSS modified neural electrodes. Control PEDOT-PSS coated microelectrodes demonstrated a significant increase in impedance at 1 kHz after 41–50 days of room temperature storage. Based on equivalent circuit modeling derived from electrochemical impedance spectroscopy, this increase in impedance could be largely attributed to a decrease in the interfacial capacitance consistent with a collapse and closing of the porous structure of the polymeric coating. Time-dependent electrochemical impedance measurements revealed higher stability of the freeze-dried coated microelectrodes compared to the controls, such that impedance values after 41–50 days appeared to be indistinguishable from the initial levels. This suggests that freeze drying PEDOT-PSS coated microelectrodes correlates with enhanced electrochemical stability during shelf storage.

In vitro characterization of a human neural progenitor cell coexpressing SSEA4 and CD133

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Barraud, Perrine; Stott, Simon; Møllgård, Kjeld

2007-01-01

The stage-specific embryonic antigen 4 (SSEA4) is commonly used as a cell surface marker to identify the pluripotent human embryonic stem (ES) cells. Immunohistochemistry on human embryonic central nervous system revealed that SSEA4 is detectable in the early neuroepithelium, and its expression....... Therefore, we propose that SSEA4 associated with CD133 can be used for both the positive selection and the enrichment of neural stem/progenitor cells from human embryonic forebrain....... decreases as development proceeds. Flow cytometry analysis of forebrain-derived cells demonstrated that the SSEA4-expressing cells are enriched in the neural stem/progenitor cell fraction (CD133(+)), but are rarely codetected with the neural stem cell (NSC) marker CD15. Using a sphere-forming assay, we...

A Grey Wolf Optimizer for Modular Granular Neural Networks for Human Recognition

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Daniela Sánchez

2017-01-01

Full Text Available A grey wolf optimizer for modular neural network (MNN with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition.

Generation of Oligodendrogenic Spinal Neural Progenitor Cells From Human Induced Pluripotent Stem Cells.

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Khazaei, Mohamad; Ahuja, Christopher S; Fehlings, Michael G

2017-08-14

This unit describes protocols for the efficient generation of oligodendrogenic neural progenitor cells (o-NPCs) from human induced pluripotent stem cells (hiPSCs). Specifically, detailed methods are provided for the maintenance and differentiation of hiPSCs, human induced pluripotent stem cell-derived neural progenitor cells (hiPS-NPCs), and human induced pluripotent stem cell-oligodendrogenic neural progenitor cells (hiPSC-o-NPCs) with the final products being suitable for in vitro experimentation or in vivo transplantation. Throughout, cell exposure to growth factors and patterning morphogens has been optimized for both concentration and timing, based on the literature and empirical experience, resulting in a robust and highly efficient protocol. Using this derivation procedure, it is possible to obtain millions of oligodendrogenic-NPCs within 40 days of initial cell plating which is substantially shorter than other protocols for similar cell types. This protocol has also been optimized to use translationally relevant human iPSCs as the parent cell line. The resultant cells have been extensively characterized both in vitro and in vivo and express key markers of an oligodendrogenic lineage. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley and Sons, Inc.

Direct Neural Conversion from Human Fibroblasts Using Self-Regulating and Nonintegrating Viral Vectors

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Shong Lau

2014-12-01

Full Text Available Summary: Recent findings show that human fibroblasts can be directly programmed into functional neurons without passing via a proliferative stem cell intermediate. These findings open up the possibility of generating subtype-specific neurons of human origin for therapeutic use from fetal cell, from patients themselves, or from matched donors. In this study, we present an improved system for direct neural conversion of human fibroblasts. The neural reprogramming genes are regulated by the neuron-specific microRNA, miR-124, such that each cell turns off expression of the reprogramming genes once the cell has reached a stable neuronal fate. The regulated system can be combined with integrase-deficient vectors, providing a nonintegrative and self-regulated conversion system that rids problems associated with the integration of viral transgenes into the host genome. These modifications make the system suitable for clinical use and therefore represent a major step forward in the development of induced neurons for cell therapy. : Lau et al. now use miRNA targeting to build a self-regulating neural conversion system. Combined with nonintegrating vectors, this system can efficiently drive conversion of human fibroblasts into functional induced neurons (iNs suitable for clinical applications.

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

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Chandrasekaran, Abinaya; Avci, Hasan; Ochalek, Anna

2017-01-01

Neural progenitor cells (NPCs) from human induced pluripotent stem cells (hiPSCs) are frequently induced using 3D culture methodologies however, it is unknown whether spheroid-based (3D) neural induction is actually superior to monolayer (2D) neural induction. Our aim was to compare the efficiency......), cortical layer (TBR1, CUX1) and glial markers (SOX9, GFAP, AQP4). Electron microscopy demonstrated that both methods resulted in morphologically similar neural rosettes. However, quantification of NPCs derived from 3D neural induction exhibited an increase in the number of PAX6/NESTIN double positive cells...... the electrophysiological properties between the two induction methods. In conclusion, 3D neural induction increases the yield of PAX6+/NESTIN+ cells and gives rise to neurons with longer neurites, which might be an advantage for the production of forebrain cortical neurons, highlighting the potential of 3D neural...

Novel Modified Elman Neural Network Control for PMSG System Based on Wind Turbine Emulator

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Chih-Hong Lin

2013-01-01

Full Text Available The novel modified Elman neural network (NN controlled permanent magnet synchronous generator (PMSG system, which is directly driven by a permanent magnet synchronous motor (PMSM based on wind turbine emulator, is proposed to control output of rectifier (AC/DC power converter and inverter (DC/AC power converter in this study. First, a closed loop PMSM drive control based on wind turbine emulator is designed to generate power for the PMSG system according to different wind speeds. Then, the rotor speed of the PMSG, the voltage, and current of the power converter are detected simultaneously to yield better power output of the converter. Because the PMSG system is the nonlinear and time-varying system, two sets online trained modified Elman NN controllers are developed for the tracking controllers of DC bus power and AC power to improve output performance of rectifier and inverter. Finally, experimental results are verified to show the effectiveness of the proposed control scheme.

Delineating Neural Structures of Developmental Human Brains with Diffusion Tensor Imaging

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Hao Huang

2010-01-01

Full Text Available The human brain anatomy is characterized by dramatic structural changes during fetal development. It is extraordinarily complex and yet its origin is a simple tubular structure. Revealing detailed anatomy at different stages of brain development not only aids in understanding this highly ordered process, but also provides clues to detect abnormalities caused by genetic or environmental factors. However, anatomical studies of human brain development during the fetal period are surprisingly scarce and histology-based atlases have become available only recently. Diffusion tensor imaging (DTI measures water diffusion to delineate the underlying neural structures. The high contrasts derived from DTI can be used to establish the brain atlas. With DTI tractography, coherent neural structures, such as white matter tracts, can be three-dimensionally reconstructed. The primary eigenvector of the diffusion tensor can be further explored to characterize microstructures in the cerebral wall of the developmental brains. In this mini-review, the application of DTI in order to reveal the structures of developmental fetal brains has been reviewed in the above-mentioned aspects. The fetal brain DTI provides a unique insight for delineating the neural structures in both macroscopic and microscopic levels. The resultant DTI database will provide structural guidance for the developmental study of human fetal brains in basic neuroscience, and reference standards for diagnostic radiology of premature newborns.

Wnt/Yes-Associated Protein Interactions During Neural Tissue Patterning of Human Induced Pluripotent Stem Cells.

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Bejoy, Julie; Song, Liqing; Zhou, Yi; Li, Yan

2018-04-01

Human induced pluripotent stem cells (hiPSCs) have special ability to self-assemble into neural spheroids or mini-brain-like structures. During the self-assembly process, Wnt signaling plays an important role in regional patterning and establishing positional identity of hiPSC-derived neural progenitors. Recently, the role of Wnt signaling in regulating Yes-associated protein (YAP) expression (nuclear or cytoplasmic), the pivotal regulator during organ growth and tissue generation, has attracted increasing interests. However, the interactions between Wnt and YAP expression for neural lineage commitment of hiPSCs remain poorly explored. The objective of this study is to investigate the effects of Wnt signaling and YAP expression on the cellular population in three-dimensional (3D) neural spheroids derived from hiPSCs. In this study, Wnt signaling was activated using CHIR99021 for 3D neural spheroids derived from human iPSK3 cells through embryoid body formation. Our results indicate that Wnt activation induces nuclear localization of YAP and upregulates the expression of HOXB4, the marker for hindbrain/spinal cord. By contrast, the cells exhibit more rostral forebrain neural identity (expression of TBR1) without Wnt activation. Cytochalasin D was then used to induce cytoplasmic YAP and the results showed the decreased HOXB4 expression. In addition, the incorporation of microparticles in the neural spheroids was investigated for the perturbation of neural patterning. This study may indicate the bidirectional interactions of Wnt signaling and YAP expression during neural tissue patterning, which have the significance in neurological disease modeling, drug screening, and neural tissue regeneration.

Neural representations of social status hierarchy in human inferior parietal cortex.

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Chiao, Joan Y; Harada, Tokiko; Oby, Emily R; Li, Zhang; Parrish, Todd; Bridge, Donna J

2009-01-01

Mental representations of social status hierarchy share properties with that of numbers. Previous neuroimaging studies have shown that the neural representation of numerical magnitude lies within a network of regions within inferior parietal cortex. However the neural basis of social status hierarchy remains unknown. Using fMRI, we studied subjects while they compared social status magnitude of people, objects and symbols, as well as numerical magnitude. Both social status and number comparisons recruited bilateral intraparietal sulci. We also observed a semantic distance effect whereby neural activity within bilateral intraparietal sulci increased for semantically close relative to far numerical and social status comparisons. These results demonstrate that social status and number comparisons recruit distinct and overlapping neuronal representations within human inferior parietal cortex.

Wildlife disease prevalence in human-modified landscapes.

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Brearley, Grant; Rhodes, Jonathan; Bradley, Adrian; Baxter, Greg; Seabrook, Leonie; Lunney, Daniel; Liu, Yan; McAlpine, Clive

2013-05-01

Human-induced landscape change associated with habitat loss and fragmentation places wildlife populations at risk. One issue in these landscapes is a change in the prevalence of disease which may result in increased mortality and reduced fecundity. Our understanding of the influence of habitat loss and fragmentation on the prevalence of wildlife diseases is still in its infancy. What is evident is that changes in disease prevalence as a result of human-induced landscape modification are highly variable. The importance of infectious diseases for the conservation of wildlife will increase as the amount and quality of suitable habitat decreases due to human land-use pressures. We review the experimental and observational literature of the influence of human-induced landscape change on wildlife disease prevalence, and discuss disease transmission types and host responses as mechanisms that are likely to determine the extent of change in disease prevalence. It is likely that transmission dynamics will be the key process in determining a pathogen's impact on a host population, while the host response may ultimately determine the extent of disease prevalence. Finally, we conceptualize mechanisms and identify future research directions to increase our understanding of the relationship between human-modified landscapes and wildlife disease prevalence. This review highlights that there are rarely consistent relationships between wildlife diseases and human-modified landscapes. In addition, variation is evident between transmission types and landscape types, with the greatest positive influence on disease prevalence being in urban landscapes and directly transmitted disease systems. While we have a limited understanding of the potential influence of habitat loss and fragmentation on wildlife disease, there are a number of important areas to address in future research, particularly to account for the variability in increased and decreased disease prevalence. Previous studies

Human Inspired Self-developmental Model of Neural Network (HIM): Introducing Content/Form Computing

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Krajíček, Jiří

This paper presents cross-disciplinary research between medical/psychological evidence on human abilities and informatics needs to update current models in computer science to support alternative methods for computation and communication. In [10] we have already proposed hypothesis introducing concept of human information model (HIM) as cooperative system. Here we continue on HIM design in detail. In our design, first we introduce Content/Form computing system which is new principle of present methods in evolutionary computing (genetic algorithms, genetic programming). Then we apply this system on HIM (type of artificial neural network) model as basic network self-developmental paradigm. Main inspiration of our natural/human design comes from well known concept of artificial neural networks, medical/psychological evidence and Sheldrake theory of "Nature as Alive" [22].

Deep Recurrent Neural Networks for Human Activity Recognition

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Abdulmajid Murad

2017-11-01

Full Text Available Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM and k-nearest neighbors (KNN. Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs and CNNs.

Deep Recurrent Neural Networks for Human Activity Recognition.

Science.gov (United States)

Murad, Abdulmajid; Pyun, Jae-Young

2017-11-06

Adopting deep learning methods for human activity recognition has been effective in extracting discriminative features from raw input sequences acquired from body-worn sensors. Although human movements are encoded in a sequence of successive samples in time, typical machine learning methods perform recognition tasks without exploiting the temporal correlations between input data samples. Convolutional neural networks (CNNs) address this issue by using convolutions across a one-dimensional temporal sequence to capture dependencies among input data. However, the size of convolutional kernels restricts the captured range of dependencies between data samples. As a result, typical models are unadaptable to a wide range of activity-recognition configurations and require fixed-length input windows. In this paper, we propose the use of deep recurrent neural networks (DRNNs) for building recognition models that are capable of capturing long-range dependencies in variable-length input sequences. We present unidirectional, bidirectional, and cascaded architectures based on long short-term memory (LSTM) DRNNs and evaluate their effectiveness on miscellaneous benchmark datasets. Experimental results show that our proposed models outperform methods employing conventional machine learning, such as support vector machine (SVM) and k-nearest neighbors (KNN). Additionally, the proposed models yield better performance than other deep learning techniques, such as deep believe networks (DBNs) and CNNs.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

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Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

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Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

In vitro differentiation of neural cells from human adipose tissue derived stromal cells.

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Dave, Shruti D; Patel, Chetan N; Vanikar, Aruna V; Trivedi, Hargovind L

2018-01-01

Stem cells, including neural stem cells (NSCs), are endowed with self-renewal capability and hence hold great opportunity for the institution of replacement/protective therapy. We propose a method for in vitro generation of stromal cells from human adipose tissue and their differentiation into neural cells. Ten grams of donor adipose tissue was surgically resected from the abdominal wall of the human donor after the participants' informed consents. The resected adipose tissue was minced and incubated for 1 hour in the presence of an enzyme (collagenase-type I) at 37 0 C followed by its centrifugation. After centrifugation, the supernatant and pellets were separated and cultured in a medium for proliferation at 37 0 C with 5% CO2 for 9-10 days in separate tissue culture dishes for generation of mesenchymal stromal cells (MSC). At the end of the culture, MSC were harvested and analyzed. The harvested MSC were subjected for further culture for their differentiation into neural cells for 5-7 days using differentiation medium mainly comprising of neurobasal medium. At the end of the procedure, culture cells were isolated and studied for expression of transcriptional factor proteins: orthodenticle homolog-2 (OTX-2), beta-III-tubulin (β3-Tubulin), glial-fibrillary acid protein (GFAP) and synaptophysin-β2. In total, 50 neural cells-lines were generated. In vitro generated MSC differentiated neural cells' mean quantum was 5.4 ± 6.9 ml with the mean cell count being, 5.27 ± 2.65 × 10 3/ μl. All of them showed the presence of OTX-2, β3-Tubulin, GFAP, synaptophysin-β2. Neural cells can be differentiated in vitro from MSC safely and effectively. In vitro generated neural cells represent a potential therapy for recovery from spinal cord injuries and neurodegenerative disease.

Neural Integration of Information Specifying Human Structure from Form, Motion, and Depth

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Jackson, Stuart; Blake, Randolph

2010-01-01

Recent computational models of biological motion perception operate on ambiguous two-dimensional representations of the body (e.g., snapshots, posture templates) and contain no explicit means for disambiguating the three-dimensional orientation of a perceived human figure. Are there neural mechanisms in the visual system that represent a moving human figure’s orientation in three dimensions? To isolate and characterize the neural mechanisms mediating perception of biological motion, we used an adaptation paradigm together with bistable point-light (PL) animations whose perceived direction of heading fluctuates over time. After exposure to a PL walker with a particular stereoscopically defined heading direction, observers experienced a consistent aftereffect: a bistable PL walker, which could be perceived in the adapted orientation or reversed in depth, was perceived predominantly reversed in depth. A phase-scrambled adaptor produced no aftereffect, yet when adapting and test walkers differed in size or appeared on opposite sides of fixation aftereffects did occur. Thus, this heading direction aftereffect cannot be explained by local, disparity-specific motion adaptation, and the properties of scale and position invariance imply higher-level origins of neural adaptation. Nor is disparity essential for producing adaptation: when suspended on top of a stereoscopically defined, rotating globe, a context-disambiguated “globetrotter” was sufficient to bias the bistable walker’s direction, as were full-body adaptors. In sum, these results imply that the neural signals supporting biomotion perception integrate information on the form, motion, and three-dimensional depth orientation of the moving human figure. Models of biomotion perception should incorporate mechanisms to disambiguate depth ambiguities in two-dimensional body representations. PMID:20089892

Prior Knowledge about Objects Determines Neural Color Representation in Human Visual Cortex.

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Vandenbroucke, A R E; Fahrenfort, J J; Meuwese, J D I; Scholte, H S; Lamme, V A F

2016-04-01

To create subjective experience, our brain must translate physical stimulus input by incorporating prior knowledge and expectations. For example, we perceive color and not wavelength information, and this in part depends on our past experience with colored objects ( Hansen et al. 2006; Mitterer and de Ruiter 2008). Here, we investigated the influence of object knowledge on the neural substrates underlying subjective color vision. In a functional magnetic resonance imaging experiment, human subjects viewed a color that lay midway between red and green (ambiguous with respect to its distance from red and green) presented on either typical red (e.g., tomato), typical green (e.g., clover), or semantically meaningless (nonsense) objects. Using decoding techniques, we could predict whether subjects viewed the ambiguous color on typical red or typical green objects based on the neural response of veridical red and green. This shift of neural response for the ambiguous color did not occur for nonsense objects. The modulation of neural responses was observed in visual areas (V3, V4, VO1, lateral occipital complex) involved in color and object processing, as well as frontal areas. This demonstrates that object memory influences wavelength information relatively early in the human visual system to produce subjective color vision. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

CD133 (Prominin negative human neural stem cells are clonogenic and tripotent.

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Yirui Sun

Full Text Available CD133 (Prominin is widely used as a marker for the identification and isolation of neural precursor cells from normal brain or tumor tissue. However, the assumption that CD133 is expressed constitutively in neural precursor cells has not been examined.In this study, we demonstrate that CD133 and a second marker CD15 are expressed heterogeneously in uniformly undifferentiated human neural stem (NS cell cultures. After fractionation by flow cytometry, clonogenic tripotent cells are found in populations negative or positive for either marker. We further show that CD133 is down-regulated at the mRNA level in cells lacking CD133 immunoreactivity. Cell cycle profiling reveals that CD133 negative cells largely reside in G1/G0, while CD133 positive cells are predominantly in S, G2, or M phase. A similar pattern is apparent in mouse NS cell lines. Compared to mouse NS cells, however, human NS cell cultures harbour an increased proportion of CD133 negative cells and display a longer doubling time. This may in part reflect a sub-population of slow- or non-cycling cells amongst human NS cells because we find that around 5% of cells do not take up BrdU over a 14-day labelling period. Non-proliferating NS cells remain undifferentiated and at least some of them are capable of re-entry into the cell cycle and subsequent continuous expansion.The finding that a significant fraction of clonogenic neural stem cells lack the established markers CD133 and CD15, and that some of these cells may be dormant or slow-cycling, has implications for approaches to identify and isolate neural stem cells and brain cancer stem cells. Our data also suggest the possibility that CD133 may be specifically down-regulated during G0/G1, and this should be considered when this marker is used to identify and isolate other tissue and cancer stem cells.

Efficient and Fast Differentiation of Human Neural Stem Cells from Human Embryonic Stem Cells for Cell Therapy

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Xinxin Han

2017-01-01

Full Text Available Stem cell-based therapies have been used for repairing damaged brain tissue and helping functional recovery after brain injury. Aberrance neurogenesis is related with brain injury, and multipotential neural stem cells from human embryonic stem (hES cells provide a great promise for cell replacement therapies. Optimized protocols for neural differentiation are necessary to produce functional human neural stem cells (hNSCs for cell therapy. However, the qualified procedure is scarce and detailed features of hNSCs originated from hES cells are still unclear. In this study, we developed a method to obtain hNSCs from hES cells, by which we could harvest abundant hNSCs in a relatively short time. Then, we examined the expression of pluripotent and multipotent marker genes through immunostaining and confirmed differentiation potential of the differentiated hNSCs. Furthermore, we analyzed the mitotic activity of these hNSCs. In this report, we provided comprehensive features of hNSCs and delivered the knowledge about how to obtain more high-quality hNSCs from hES cells which may help to accelerate the NSC-based therapies in brain injury treatment.

Comparative sensitivity of human and rat neural cultures to chemical-induced inhibition of neurite outgrowth

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Harrill, Joshua A.; Freudenrich, Theresa M.; Robinette, Brian L.; Mundy, William R., E-mail: mundy.william@epa.gov

2011-11-15

There is a need for rapid, efficient and cost-effective alternatives to traditional in vivo developmental neurotoxicity testing. In vitro cell culture models can recapitulate many of the key cellular processes of nervous system development, including neurite outgrowth, and may be used as screening tools to identify potential developmental neurotoxicants. The present study compared primary rat cortical cultures and human embryonic stem cell-derived neural cultures in terms of: 1) reproducibility of high content image analysis based neurite outgrowth measurements, 2) dynamic range of neurite outgrowth measurements and 3) sensitivity to chemicals which have been shown to inhibit neurite outgrowth. There was a large increase in neurite outgrowth between 2 and 24 h in both rat and human cultures. Image analysis data collected across multiple cultures demonstrated that neurite outgrowth measurements in rat cortical cultures were more reproducible and had higher dynamic range as compared to human neural cultures. Human neural cultures were more sensitive than rat cortical cultures to chemicals previously shown to inhibit neurite outgrowth. Parallel analysis of morphological (neurite count, neurite length) and cytotoxicity (neurons per field) measurements were used to detect selective effects on neurite outgrowth. All chemicals which inhibited neurite outgrowth in rat cortical cultures did so at concentrations which did not concurrently affect the number of neurons per field, indicating selective effects on neurite outgrowth. In contrast, more than half the chemicals which inhibited neurite outgrowth in human neural cultures did so at concentrations which concurrently decreased the number of neurons per field, indicating that effects on neurite outgrowth were secondary to cytotoxicity. Overall, these data demonstrate that the culture models performed differently in terms of reproducibility, dynamic range and sensitivity to neurite outgrowth inhibitors. While human neural

Comparative sensitivity of human and rat neural cultures to chemical-induced inhibition of neurite outgrowth

International Nuclear Information System (INIS)

Harrill, Joshua A.; Freudenrich, Theresa M.; Robinette, Brian L.; Mundy, William R.

2011-01-01

There is a need for rapid, efficient and cost-effective alternatives to traditional in vivo developmental neurotoxicity testing. In vitro cell culture models can recapitulate many of the key cellular processes of nervous system development, including neurite outgrowth, and may be used as screening tools to identify potential developmental neurotoxicants. The present study compared primary rat cortical cultures and human embryonic stem cell-derived neural cultures in terms of: 1) reproducibility of high content image analysis based neurite outgrowth measurements, 2) dynamic range of neurite outgrowth measurements and 3) sensitivity to chemicals which have been shown to inhibit neurite outgrowth. There was a large increase in neurite outgrowth between 2 and 24 h in both rat and human cultures. Image analysis data collected across multiple cultures demonstrated that neurite outgrowth measurements in rat cortical cultures were more reproducible and had higher dynamic range as compared to human neural cultures. Human neural cultures were more sensitive than rat cortical cultures to chemicals previously shown to inhibit neurite outgrowth. Parallel analysis of morphological (neurite count, neurite length) and cytotoxicity (neurons per field) measurements were used to detect selective effects on neurite outgrowth. All chemicals which inhibited neurite outgrowth in rat cortical cultures did so at concentrations which did not concurrently affect the number of neurons per field, indicating selective effects on neurite outgrowth. In contrast, more than half the chemicals which inhibited neurite outgrowth in human neural cultures did so at concentrations which concurrently decreased the number of neurons per field, indicating that effects on neurite outgrowth were secondary to cytotoxicity. Overall, these data demonstrate that the culture models performed differently in terms of reproducibility, dynamic range and sensitivity to neurite outgrowth inhibitors. While human neural

Effects of Chronic Low-Dose Radiation on Human Neural Progenitor Cells

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Katsura, Mari; Cyou-Nakamine, Hiromasa; Zen, Qin; Zen, Yang; Nansai, Hiroko; Amagasa, Shota; Kanki, Yasuharu; Inoue, Tsuyoshi; Kaneki, Kiyomi; Taguchi, Akashi; Kobayashi, Mika; Kaji, Toshiyuki; Kodama, Tatsuhiko; Miyagawa, Kiyoshi; Wada, Youichiro; Akimitsu, Nobuyoshi; Sone, Hideko

2016-01-01

The effects of chronic low-dose radiation on human health have not been well established. Recent studies have revealed that neural progenitor cells are present not only in the fetal brain but also in the adult brain. Since immature cells are generally more radiosensitive, here we investigated the effects of chronic low-dose radiation on cultured human neural progenitor cells (hNPCs) derived from embryonic stem cells. Radiation at low doses of 31, 124 and 496 mGy per 72 h was administered to hNPCs. The effects were estimated by gene expression profiling with microarray analysis as well as morphological analysis. Gene expression was dose-dependently changed by radiation. By thirty-one mGy of radiation, inflammatory pathways involving interferon signaling and cell junctions were altered. DNA repair and cell adhesion molecules were affected by 124 mGy of radiation while DNA synthesis, apoptosis, metabolism, and neural differentiation were all affected by 496 mGy of radiation. These in vitro results suggest that 496 mGy radiation affects the development of neuronal progenitor cells while altered gene expression was observed at a radiation dose lower than 100 mGy. This study would contribute to the elucidation of the clinical and subclinical phenotypes of impaired neuronal development induced by chronic low-dose radiation.

Cell reprogramming by 3D bioprinting of human fibroblasts in polyurethane hydrogel for fabrication of neural-like constructs.

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Ho, Lin; Hsu, Shan-Hui

2018-04-01

3D bioprinting is a technique which enables the direct printing of biodegradable materials with cells into 3D tissue. So far there is no cell reprogramming in situ performed with the 3D bioprinting process. Forkhead box D3 (FoxD3) is a transcription factor and neural crest marker, which was reported to reprogram human fibroblasts into neural crest stem-like cells. In this study, we synthesized a new biodegradable thermo-responsive waterborne polyurethane (PU) gel as a bioink. FoxD3 plasmids and human fibroblasts were co-extruded with the PU hydrogel through the syringe needle tip for cell reprogramming. The rheological properties of the PU hydrogel including the modulus, gelation time, and shear thinning were optimized for the transfection effect of FoxD3 in situ. The corresponding shear rate and shear stress were examined. Results showed that human fibroblasts could be reprogrammed into neural crest stem-like cells with high cell viability during the extrusion process under an average shear stress ∼190 Pa. We further translated the method to the extrusion-based 3D bioprinting, and demonstrated that human fibroblasts co-printed with FoxD3 in the thermo-responsive PU hydrogel could be reprogrammed and differentiated into a neural-tissue like construct at 14 days after induction. The neural-like tissue construct produced by 3D bioprinting from human fibroblasts may be applied to personalized drug screening or neuroregeneration. There is no study so far on cell reprogramming in situ with 3D bioprinting. In this manuscript, a new thermoresponsive polyurethane bioink was developed and employed to deliver FoxD3 plasmid into human fibroblasts by the extrusion-based bioprinting. When the polyurethane gel was extruded through the syringe tip, the shear stress generated may have caused the transient membrane permeability for transfection. The shear stress was optimized for transfection in situ by 3D bioprinting. We demonstrated that human fibroblasts could be

Effect of olanzapine combined with modified electroconvulsive therapy on cytokines, sTNFRs and neural electrophysiological characteristics in patients with schizophrenia

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Wei Cheng

2016-12-01

Full Text Available Objective: To analyze the effect of olanzapine combined with modified electroconvulsive therapy on cytokines, sTNFRs and neural electrophysiological characteristics in patients with schizophrenia. Methods: Patients with schizophrenia treated in our hospital between March 2013 and March 2016 were selected and randomly divided into two groups, the observation group received olanzapine combined with modified electroconvulsive therapy, and the control group received olanzapine therapy. After 6 weeks of treatment, serum levels of soluble tumor necrosis factor receptor (sTNFR, acute phase reaction proteins and brain function indexes as well as the neural electrophysiological characteristics were compared between the two groups. Results: After 6 weeks of treatment, serum sTNFRs, CRP, CER and AAG content of observation group were lower than those of control group while TRF content was higher than that of control group; serum brain function indexes NGF and BDNF content were higher than those of control group while GFAP, S100B, NSE and Hcy content were lower than those of control group; nerve electrophysiology indexes P300, LPP and ERN amplitude were higher than those of control group while LPP amplitude was lower than that of control group. Conclusions: Olanzapine combined with modified electroconvulsive therapy can optimize the condition of schizophrenia, reduce the abnormal degree of nerve electrophysiology and help to improve treatment outcome.

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

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Agnete Kirkeby

2012-06-01

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

A developmental perspective on the neural bases of human empathy.

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Tousignant, Béatrice; Eugène, Fanny; Jackson, Philip L

2017-08-01

While empathy has been widely studied in philosophical and psychological literatures, recent advances in social neuroscience have shed light on the neural correlates of this complex interpersonal phenomenon. In this review, we provide an overview of brain imaging studies that have investigated the neural substrates of human empathy. Based on existing models of the functional architecture of empathy, we review evidence of the neural underpinnings of each main component, as well as their development from infancy. Although early precursors of affective sharing and self-other distinction appear to be present from birth, recent findings also suggest that even higher-order components of empathy such as perspective-taking and emotion regulation demonstrate signs of development during infancy. This merging of developmental and social neuroscience literature thus supports the view that ontogenic development of empathy is rooted in early infancy, well before the emergence of verbal abilities. With age, the refinement of top-down mechanisms may foster more appropriate empathic responses, thus promoting greater altruistic motivation and prosocial behaviors. Copyright © 2016 Elsevier Inc. All rights reserved.

An assessment of the barriers to the consumers' uptake of genetically modified foods: a neural network analysis.

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Rodríguez-Entrena, Macario; Salazar-Ordóñez, Melania; Becerra-Alonso, David

2016-03-30

This paper studies which of the attitudinal, cognitive and socio-economic factors determine the willingness to purchase genetically modified (GM) food, enabling the forecasting of consumers' behaviour in Andalusia, southern Spain. This classification has been made by a standard multilayer perceptron neural network trained with extreme learning machine. Later, an ordered logistic regression was applied to determine whether the neural network can outperform this traditional econometric approach. The results show that the highest relative contributions lie in the variables related to perceived risks of GM food, while the perceived benefits have a lower influence. In addition, an innovative attitude towards food presents a strong link, as does the perception of food safety. The variables with the least relative contribution are subjective knowledge about GM food and the consumers' age. The neural network approach outperforms the correct classification percentage from the ordered logistic regression. The perceived risks must be considered as a critical factor. A strategy to improve the GM food acceptance is to develop a transparent and balanced information framework that makes the potential risk understandable by society, and make them aware of the risk assessments for GM food in the EU. For its success, it is essential to improve the trust in EU institutions and scientific regulatory authorities. © 2015 Society of Chemical Industry.

Differentiation of isolated human umbilical cord mesenchymal stem cells into neural stem cells

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Chen, Song; Zhang, Wei; Wang, Ji-Ming; Duan, Hong-Tao; Kong, Jia-Hui; Wang, Yue-Xin; Dong, Meng; Bi, Xue; Song, Jian

2016-01-01

AIM To investigate whether umbilical cord human mesenchymal stem cell (UC-MSC) was able to differentiate into neural stem cell and neuron in vitro. METHODS The umbilical cords were obtained from pregnant women with their written consent and the approval of the Clinic Ethnics Committee. UC-MSC were isolated by adherent culture in the medium contains 20% fetal bovine serum (FBS), then they were maintained in the medium contain 10% FBS and induced to neural cells in neural differentiation medium. We investigated whether UC-MSC was able to differentiate into neural stem cell and neuron in vitro by using flow cytometry, reverse transcriptase-polymerase chain reaction (RT-PCR) and immunofluorescence (IF) analyzes. RESULTS A substantial number of UC-MSC was harvested using the tissue explants adherent method at about 2wk. Flow cytometric study revealed that these cells expressed common markers of MSCs, such as CD105 (SH2), CD73 (SH3) and CD90. After induction of differentiation of neural stem cells, the cells began to form clusters; RT-PCR and IF showed that the neuron specific enolase (NSE) and neurogenic differentiation 1-positive cells reached 87.3%±14.7% and 72.6%±11.8%, respectively. Cells showed neuronal cell differentiation after induced, including neuron-like protrusions, plump cell body, obviously and stronger refraction. RT-PCR and IF analysis showed that microtubule-associated protein 2 (MAP2) and nuclear factor-M-positive cells reached 43.1%±10.3% and 69.4%±19.5%, respectively. CONCLUSION Human umbilical cord derived MSCs can be cultured and proliferated in vitro and differentiate into neural stem cells, which may be a valuable source for cell therapy of neurodegenerative eye diseases. PMID:26949608

Differentiation of isolated human umbilical cord mesenchymal stem cells into neural stem cells

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Song Chen

2016-01-01

Full Text Available AIM: To investigate whether umbilical cord human mesenchymal stem cell (UC-MSC was able to differentiate into neural stem cell and neuron in vitro. METHODS: The umbilical cords were obtained from pregnant women with their written consent and the approval of the Clinic Ethnics Committee. UC-MSC were isolated by adherent culture in the medium contains 20% fetal bovine serum (FBS, then they were maintained in the medium contain 10% FBS and induced to neural cells in neural differentiation medium. We investigated whether UC-MSC was able to differentiate into neural stem cell and neuron in vitro by using flow cytometry, reverse transcriptase-polymerase chain reaction (RT-PCR and immunofluorescence (IF analyzes. RESULTS: A substantial number of UC-MSC was harvested using the tissue explants adherent method at about 2wk. Flow cytometric study revealed that these cells expressed common markers of MSCs, such as CD105 (SH2, CD73 (SH3 and CD90. After induction of differentiation of neural stem cells, the cells began to form clusters; RT-PCR and IF showed that the neuron specific enolase (NSE and neurogenic differentiation 1-positive cells reached 87.3%±14.7% and 72.6%±11.8%, respectively. Cells showed neuronal cell differentiation after induced, including neuron-like protrusions, plump cell body, obviously and stronger refraction. RT-PCR and IF analysis showed that microtubule-associated protein 2 (MAP2 and nuclear factor-M-positive cells reached 43.1%±10.3% and 69.4%±19.5%, respectively. CONCLUSION: Human umbilical cord derived MSCs can be cultured and proliferated in vitro and differentiate into neural stem cells, which may be a valuable source for cell therapy of neurodegenerative eye diseases.

Neural prediction errors reveal a risk-sensitive reinforcement-learning process in the human brain.

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Niv, Yael; Edlund, Jeffrey A; Dayan, Peter; O'Doherty, John P

2012-01-11

Humans and animals are exquisitely, though idiosyncratically, sensitive to risk or variance in the outcomes of their actions. Economic, psychological, and neural aspects of this are well studied when information about risk is provided explicitly. However, we must normally learn about outcomes from experience, through trial and error. Traditional models of such reinforcement learning focus on learning about the mean reward value of cues and ignore higher order moments such as variance. We used fMRI to test whether the neural correlates of human reinforcement learning are sensitive to experienced risk. Our analysis focused on anatomically delineated regions of a priori interest in the nucleus accumbens, where blood oxygenation level-dependent (BOLD) signals have been suggested as correlating with quantities derived from reinforcement learning. We first provide unbiased evidence that the raw BOLD signal in these regions corresponds closely to a reward prediction error. We then derive from this signal the learned values of cues that predict rewards of equal mean but different variance and show that these values are indeed modulated by experienced risk. Moreover, a close neurometric-psychometric coupling exists between the fluctuations of the experience-based evaluations of risky options that we measured neurally and the fluctuations in behavioral risk aversion. This suggests that risk sensitivity is integral to human learning, illuminating economic models of choice, neuroscientific models of affective learning, and the workings of the underlying neural mechanisms.

The neural code for face orientation in the human fusiform face area.

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Ramírez, Fernando M; Cichy, Radoslaw M; Allefeld, Carsten; Haynes, John-Dylan

2014-09-03

Humans recognize faces and objects with high speed and accuracy regardless of their orientation. Recent studies have proposed that orientation invariance in face recognition involves an intermediate representation where neural responses are similar for mirror-symmetric views. Here, we used fMRI, multivariate pattern analysis, and computational modeling to investigate the neural encoding of faces and vehicles at different rotational angles. Corroborating previous studies, we demonstrate a representation of face orientation in the fusiform face-selective area (FFA). We go beyond these studies by showing that this representation is category-selective and tolerant to retinal translation. Critically, by controlling for low-level confounds, we found the representation of orientation in FFA to be compatible with a linear angle code. Aspects of mirror-symmetric coding cannot be ruled out when FFA mean activity levels are considered as a dimension of coding. Finally, we used a parametric family of computational models, involving a biased sampling of view-tuned neuronal clusters, to compare different face angle encoding models. The best fitting model exhibited a predominance of neuronal clusters tuned to frontal views of faces. In sum, our findings suggest a category-selective and monotonic code of face orientation in the human FFA, in line with primate electrophysiology studies that observed mirror-symmetric tuning of neural responses at higher stages of the visual system, beyond the putative homolog of human FFA. Copyright © 2014 the authors 0270-6474/14/3412155-13$15.00/0.

A scale out approach towards neural induction of human induced pluripotent stem cells for neurodevelopmental toxicity studies.

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Miranda, Cláudia C; Fernandes, Tiago G; Pinto, Sandra N; Prieto, Manuel; Diogo, M Margarida; Cabral, Joaquim M S

2018-05-21

Stem cell's unique properties confer them a multitude of potential applications in the fields of cellular therapy, disease modelling and drug screening fields. In particular, the ability to differentiate neural progenitors (NP) from human induced pluripotent stem cells (hiPSCs) using chemically-defined conditions provides an opportunity to create a simple and straightforward culture platform for application in these fields. Here, we demonstrated that hiPSCs are capable of undergoing neural commitment inside microwells, forming characteristic neural structures resembling neural rosettes and further give rise to glial and neuronal cells. Furthermore, this platform can be applied towards the study of the effect of neurotoxic molecules that impair normal embryonic development. As a proof of concept, the neural teratogenic potential of the antiepileptic drug valproic acid (VPA) was analyzed. It was verified that exposure to VPA, close to typical dosage values (0.3 to 0.75 mM), led to a prevalence of NP structures over neuronal differentiation, as confirmed by analysis of the expression of neural cell adhesion molecule, as well as neural rosette number and morphology assessment. The methodology proposed herein for the generation and neural differentiation of hiPSC aggregates can potentially complement current toxicity tests such as the humanized embryonic stem cell test for the detection of teratogenic compounds that can interfere with normal embryonic development. Copyright © 2018 Elsevier B.V. All rights reserved.

ERK-dependent and -independent pathways trigger human neural progenitor cell migration

International Nuclear Information System (INIS)

Moors, Michaela; Cline, Jason E.; Abel, Josef; Fritsche, Ellen

2007-01-01

Besides differentiation and apoptosis, cell migration is a basic process in brain development in which neural cells migrate several centimeters within the developing brain before reaching their proper positions and forming the right connections. For identifying signaling events that control neural migration and are therefore potential targets of chemicals to disturb normal brain development, we developed a human neurosphere-based migration assay based on normal human neural progenitor (NHNP) cells, in which the distance is measured that cells wander over time. Applying this assay, we investigated the role of the extracellular signal-regulated kinases 1 and 2 (ERK1/2) in the regulation of NHNP cell migration. Exposure to model substances like ethanol or phorbol 12-myristate 13-acetate (PMA) revealed a correlation between ERK1/2 activation and cell migration. The participation of phospho-(P-) ERK1/2 was confirmed by exposure of the cells to the MEK inhibitor PD98059, which directly prohibits ERK1/2 phosphorylation and inhibited cell migration. We identified protein kinase C (PKC) and epidermal growth factor receptor (EGFR) as upstream signaling kinases governing ERK1/2 activation, thereby controlling NHNP cell migration. Additionally, treatments with src kinase inhibitors led to a diminished cell migration without affecting ERK1/2 phosphorylation. Based on these results, we postulate that migration of NHNP cells is controlled via ERK1/2-dependent and -independent pathways

Conversion of adult human peripheral blood mononuclear cells into induced neural stem cell by using episomal vectors

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Xihe Tang

2016-03-01

Full Text Available Human neural stem cells (NSCs hold great promise for research and therapy in neural diseases. Many studies have shown direct induction of NSCs from human fibroblasts, which require an invasive skin biopsy and a prolonged period of expansion in cell culture prior to use. Peripheral blood (PB is routinely used in medical diagnoses, and represents a noninvasive and easily accessible source of cells. Here we show direct derivation of NSCs from adult human PB mononuclear cells (PB-MNCs by employing episomal vectors for transgene delivery. These induced NSCs (iNSCs can expand more than 60 passages, can exhibit NSC morphology, gene expression, differentiation potential, and self-renewing capability and can give rise to multiple functional neural subtypes and glial cells in vitro. Furthermore, the iNSCs carry a specific regional identity and have electrophysiological activity upon differentiation. Our findings provide an easily accessible approach for generating human iNSCs which will facilitate disease modeling, drug screening, and possibly regenerative medicine.

Estimation of hydrogen production in genetically modified E. coli fermentations using an artificial neural network

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Rosales-Colunga, Luis Manuel; De Leon Rodriguez, Antonio [Division de Biologia Molecular, Instituto Potosino de Investigacion Cientifica y Tecnologica, Camino a la Presa San Jose 2055, Col. Lomas 4a secc, San Luis Potosi, SLP 78216 (Mexico); Garcia, Raul Gonzalez [Centro de Investigacion y Estudios de Posgrado, Facultad de Ciencias Quimicas, Universidad Autonoma de San Luis Potosi, Av. Dr. Manuel Nava 6, San Luis Potosi, SLP 78210 (Mexico)

2010-12-15

Biological hydrogen production is an active research area due to the importance of this gas as an energy carrier and the advantages of using biological systems to produce it. A cheap and practical on-line hydrogen determination is desired in those processes. In this study, an artificial neural network (ANN) was developed to estimate the hydrogen production in fermentative processes. A back propagation neural network (BPNN) of one hidden layer with 12 nodes was selected. The BPNN training was done using the conjugated gradient algorithm and on-line measurements of dissolved CO{sub 2}, pH and oxidation-reduction potential during the fermentations of cheese whey by Escherichia coli {delta}hycA {delta}lacI (WDHL) strain with or without pH control. The correlation coefficient between the hydrogen production determined by gas chromatography and the hydrogen production estimated by the BPNN was 0.955. Results showed that the BPNN successfully estimated the hydrogen production using only on-line parameters in genetically modified E. coli fermentations either with or without pH control. This approach could be used for other hydrogen production systems. (author)

Neural network regulation driven by autonomous neural firings

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Cho, Myoung Won

2016-07-01

Biological neurons naturally fire spontaneously due to the existence of a noisy current. Such autonomous firings may provide a driving force for network formation because synaptic connections can be modified due to neural firings. Here, we study the effect of autonomous firings on network formation. For the temporally asymmetric Hebbian learning, bidirectional connections lose their balance easily and become unidirectional ones. Defining the difference between reciprocal connections as new variables, we could express the learning dynamics as if Ising model spins interact with each other in magnetism. We present a theoretical method to estimate the interaction between the new variables in a neural system. We apply the method to some network systems and find some tendencies of autonomous neural network regulation.

Immortalization of human neural stem cells with the c-myc mutant T58A.

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Lidia De Filippis

Full Text Available Human neural stem cells (hNSC represent an essential source of renewable brain cells for both experimental studies and cell replacement therapies. Their relatively slow rate of proliferation and physiological senescence in culture make their use cumbersome under some experimental and pre-clinical settings. The immortalization of hNSC with the v-myc gene (v-IhNSC has been shown to generate stem cells endowed with enhanced proliferative capacity, which greatly facilitates the study of hNSCs, both in vitro and in vivo. Despite the excellent safety properties displayed by v-IhNSCs--which do not transform in vitro and are not tumorigenic in vivo--the v-myc gene contains several mutations and recombination elements, whose role(s and effects remains to be elucidated, yielding unresolved safety concerns. To address this issue, we used a c-myc T58A retroviral vector to establish an immortal cell line (T-IhNSC from the same hNSCs used to generate the original v-IhNSCs and compared their characteristics with the latter, with hNSC and with hNSC immortalized using c-myc wt (c-IhNSC. T-IhNSCs displayed an enhanced self-renewal ability, with their proliferative capacity and clonogenic potential being remarkably comparable to those of v-IhNSC and higher than wild type hNSCs and c-IhNSCs. Upon growth factors removal, T-IhNSC promptly gave rise to well-differentiated neurons, astrocytes and most importantly, to a heretofore undocumented high percentage of human oligodendrocytes (up to 23%. Persistent growth-factor dependence, steady functional properties, lack of ability to generate colonies in soft-agar colony-forming assay and to establish tumors upon orthotopic transplantation, point to the fact that immortalization by c-myc T58A does not bring about tumorigenicity in hNSCs. Hence, this work describes a novel and continuous cell line of immortalized human multipotent neural stem cells, in which the immortalizing agent is represented by a single gene which, in

Capacity of Human Dental Follicle Cells to Differentiate into Neural Cells In Vitro

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Shingo Kanao

2017-01-01

Full Text Available The dental follicle is an ectomesenchymal tissue surrounding the developing tooth germ. Human dental follicle cells (hDFCs have the capacity to commit to differentiation into multiple cell types. Here we investigated the capacity of hDFCs to differentiate into neural cells and the efficiency of a two-step strategy involving floating neurosphere-like bodies for neural differentiation. Undifferentiated hDFCs showed a spindle-like morphology and were positive for neural markers such as nestin, β-III-tubulin, and S100β. The cellular morphology of several cells was neuronal-like including branched dendrite-like processes and neurites. Next, hDFCs were used for neurosphere formation in serum-free medium containing basic fibroblast growth factor, epidermal growth factor, and B27 supplement. The number of cells with neuronal-like morphology and that were strongly positive for neural markers increased with sphere formation. Gene expression of neural markers also increased in hDFCs with sphere formation. Next, gene expression of neural markers was examined in hDFCs during neuronal differentiation after sphere formation. Expression of Musashi-1 and Musashi-2, MAP2, GFAP, MBP, and SOX10 was upregulated in hDFCs undergoing neuronal differentiation via neurospheres, whereas expression of nestin and β-III-tubulin was downregulated. In conclusion, hDFCs may be another optimal source of neural/glial cells for cell-based therapies to treat neurological diseases.

Convolutional neural networks for segmentation and object detection of human semen

DEFF Research Database (Denmark)

Nissen, Malte Stær; Krause, Oswin; Almstrup, Kristian

2017-01-01

We compare a set of convolutional neural network (CNN) architectures for the task of segmenting and detecting human sperm cells in an image taken from a semen sample. In contrast to previous work, samples are not stained or washed to allow for full sperm quality analysis, making analysis harder due...

Dopaminergic differentiation of human neural stem cells mediated by co-cultured rat striatal brain slices

DEFF Research Database (Denmark)

Anwar, Mohammad Raffaqat; Andreasen, Christian Maaløv; Lippert, Solvej Kølvraa

2008-01-01

differentiation, we co-cultured cells from a human neural forebrain-derived stem cell line (hNS1) with rat striatal brain slices. In brief, coronal slices of neonatal rat striatum were cultured on semiporous membrane inserts placed in six-well trays overlying monolayers of hNS1 cells. After 12 days of co......Properly committed neural stem cells constitute a promising source of cells for transplantation in Parkinson's disease, but a protocol for controlled dopaminergic differentiation is not yet available. To establish a setting for identification of secreted neural compounds promoting dopaminergic...

Multiple successional pathways in human-modified tropical landscapes

NARCIS (Netherlands)

Arroyo-Rodríguez, Víctor; Melo, Felipe P.L.; Martínez-Ramos, Miguel; Bongers, Frans; Chazdon, Robin L.; Meave, Jorge A.; Norden, Natalia; Santos, Bráulio A.; Leal, Inara R.; Tabarelli, Marcelo

2017-01-01

Old-growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human-modified tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical

Comparative in silico profiling of epigenetic modifiers in human tissues.

Science.gov (United States)

Son, Mi-Young; Jung, Cho-Rok; Kim, Dae-Soo; Cho, Hyun-Soo

2018-04-06

The technology of tissue differentiation from human pluripotent stem cells has attracted attention as a useful resource for regenerative medicine, disease modeling and drug development. Recent studies have suggested various key factors and specific culture methods to improve the successful tissue differentiation and efficient generation of human induced pluripotent stem cells. Among these methods, epigenetic regulation and epigenetic signatures are regarded as an important hurdle to overcome during reprogramming and differentiation. Thus, in this study, we developed an in silico epigenetic panel and performed a comparative analysis of epigenetic modifiers in the RNA-seq results of 32 human tissues. We demonstrated that an in silico epigenetic panel can identify epigenetic modifiers in order to overcome epigenetic barriers to tissue-specific differentiation.

Lesion-induced increase in survival and migration of human neural progenitor cells releasing GDNF

Science.gov (United States)

Behrstock, Soshana; Ebert, Allison D.; Klein, Sandra; Schmitt, Melanie; Moore, Jeannette M.; Svendsen, Clive N.

2009-01-01

The use of human neural progenitor cells (hNPC) has been proposed to provide neuronal replacement or astrocytes delivering growth factors for brain disorders such as Parkinson’s and Huntington’s disease. Success in such studies likely requires migration from the site of transplantation and integration into host tissue in the face of ongoing damage. In the current study, hNPC modified to release glial cell line derived neurotrophic factor (hNPCGDNF) were transplanted into either intact or lesioned animals. GDNF release itself had no effect on the survival, migration or differentiation of the cells. The most robust migration and survival was found using a direct lesion of striatum (Huntington’s model) with indirect lesions of the dopamine system (Parkinson’s model) or intact animals showing successively less migration and survival. No lesion affected differentiation patterns. We conclude that the type of brain injury dictates migration and integration of hNPC which has important consequences when considering transplantation of these cells as a therapy for neurodegenerative diseases. PMID:19044202

Human eye localization using the modified Hough transform

Czech Academy of Sciences Publication Activity Database

Dobeš, M.; Martínek, J.; Skoupil, D.; Dobešová, Z.; Pospíšil, Jaroslav

2006-01-01

Roč. 117, - (2006), s. 468-473 ISSN 0030-4026 Institutional research plan: CEZ:AV0Z10100522 Keywords : human eye localization * modified Hough transform * eye iris and eyelid shape determination Subject RIV: BH - Optics, Masers, Lasers Impact factor: 0.585, year: 2006

Brief Report: Robo1 Regulates the Migration of Human Subventricular Zone Neural Progenitor Cells During Development.

Science.gov (United States)

Guerrero-Cazares, Hugo; Lavell, Emily; Chen, Linda; Schiapparelli, Paula; Lara-Velazquez, Montserrat; Capilla-Gonzalez, Vivian; Clements, Anna Christina; Drummond, Gabrielle; Noiman, Liron; Thaler, Katrina; Burke, Anne; Quiñones-Hinojosa, Alfredo

2017-07-01

Human neural progenitor cell (NPC) migration within the subventricular zone (SVZ) of the lateral ganglionic eminence is an active process throughout early brain development. The migration of human NPCs from the SVZ to the olfactory bulb during fetal stages resembles what occurs in adult rodents. As the human brain develops during infancy, this migratory stream is drastically reduced in cell number and becomes barely evident in adults. The mechanisms regulating human NPC migration are unknown. The Slit-Robo signaling pathway has been defined as a chemorepulsive cue involved in axon guidance and neuroblast migration in rodents. Slit and Robo proteins expressed in the rodent brain help guide neuroblast migration from the SVZ through the rostral migratory stream to the olfactory bulb. Here, we present the first study on the role that Slit and Robo proteins play in human-derived fetal neural progenitor cell migration (hfNPC). We describe that Robo1 and Robo2 isoforms are expressed in the human fetal SVZ. Furthermore, we demonstrate that Slit2 is able to induce a chemorepellent effect on the migration of hfNPCs derived from the human fetal SVZ. In addition, when Robo1 expression is inhibited, hfNPCs are unable to migrate to the olfactory bulb of mice when injected in the anterior SVZ. Our findings indicate that the migration of human NPCs from the SVZ is partially regulated by the Slit-Robo axis. This pathway could be regulated to direct the migration of NPCs in human endogenous neural cell therapy. Stem Cells 2017;35:1860-1865. © 2017 AlphaMed Press.

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

Science.gov (United States)

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

2017-12-01

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

21 CFR 172.894 - Modified cottonseed products intended for human consumption.

Science.gov (United States)

2010-04-01

... consumption. 172.894 Section 172.894 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES (CONTINUED) FOOD FOR HUMAN CONSUMPTION (CONTINUED) FOOD ADDITIVES PERMITTED FOR DIRECT ADDITION TO FOOD FOR HUMAN CONSUMPTION Multipurpose Additives § 172.894 Modified cottonseed products...

Neural differentiation potential of human bone marrow-derived mesenchymal stromal cells: misleading marker gene expression

Directory of Open Access Journals (Sweden)

Montzka Katrin

2009-03-01

Full Text Available Abstract Background In contrast to pluripotent embryonic stem cells, adult stem cells have been considered to be multipotent, being somewhat more restricted in their differentiation capacity and only giving rise to cell types related to their tissue of origin. Several studies, however, have reported that bone marrow-derived mesenchymal stromal cells (MSCs are capable of transdifferentiating to neural cell types, effectively crossing normal lineage restriction boundaries. Such reports have been based on the detection of neural-related proteins by the differentiated MSCs. In order to assess the potential of human adult MSCs to undergo true differentiation to a neural lineage and to determine the degree of homogeneity between donor samples, we have used RT-PCR and immunocytochemistry to investigate the basal expression of a range of neural related mRNAs and proteins in populations of non-differentiated MSCs obtained from 4 donors. Results The expression analysis revealed that several of the commonly used marker genes from other studies like nestin, Enolase2 and microtubule associated protein 1b (MAP1b are already expressed by undifferentiated human MSCs. Furthermore, mRNA for some of the neural-related transcription factors, e.g. Engrailed-1 and Nurr1 were also strongly expressed. However, several other neural-related mRNAs (e.g. DRD2, enolase2, NFL and MBP could be identified, but not in all donor samples. Similarly, synaptic vesicle-related mRNA, STX1A could only be detected in 2 of the 4 undifferentiated donor hMSC samples. More significantly, each donor sample revealed a unique expression pattern, demonstrating a significant variation of marker expression. Conclusion The present study highlights the existence of an inter-donor variability of expression of neural-related markers in human MSC samples that has not previously been described. This donor-related heterogeneity might influence the reproducibility of transdifferentiation protocols as

Focal Transplantation of Human iPSC-Derived Glial-Rich Neural Progenitors Improves Lifespan of ALS Mice

Directory of Open Access Journals (Sweden)

Takayuki Kondo

2014-08-01

Full Text Available Transplantation of glial-rich neural progenitors has been demonstrated to attenuate motor neuron degeneration and disease progression in rodent models of mutant superoxide dismutase 1 (SOD1-mediated amyotrophic lateral sclerosis (ALS. However, translation of these results into a clinical setting requires a renewable human cell source. Here, we derived glial-rich neural progenitors from human iPSCs and transplanted them into the lumbar spinal cord of ALS mouse models. The transplanted cells differentiated into astrocytes, and the treated mouse group showed prolonged lifespan. Our data suggest a potential therapeutic mechanism via activation of AKT signal. The results demonstrated the efficacy of cell therapy for ALS by the use of human iPSCs as cell source.

Signs of noise-induced neural degeneration in humans

DEFF Research Database (Denmark)

Holtegaard, Pernille; Olsen, Steen Østergaard

2015-01-01

of background noise, while leaving the processing of low-level stimuli unaffected. The purpose of this study was to investigate if signs of such primary neural damage from noise-exposure could also be found in noiseexposed human individuals. It was investigated: (1) if noise-exposed listeners with hearing......Animal studies demonstrated that noise exposure causes a primary and selective loss of auditory-nerve fibres with low spontaneous firing rate. This neuronal impairment, if also present in humans, can be assumed to affect the processing of supra-threshold stimuli, especially in the presence...... thresholds within the “normal” range perform poorer, in terms of their speech recognition threshold in noise (SRTN), and (2) if auditory brainstem responses (ABR) reveal lower amplitude of wave I in the noise-exposed listeners. A test group of noise/music-exposed individuals and a control group were...

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-08-21

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

Multispectral embedding-based deep neural network for three-dimensional human pose recovery

Science.gov (United States)

Yu, Jialin; Sun, Jifeng

2018-01-01

Monocular image-based three-dimensional (3-D) human pose recovery aims to retrieve 3-D poses using the corresponding two-dimensional image features. Therefore, the pose recovery performance highly depends on the image representations. We propose a multispectral embedding-based deep neural network (MSEDNN) to automatically obtain the most discriminative features from multiple deep convolutional neural networks and then embed their penultimate fully connected layers into a low-dimensional manifold. This compact manifold can explore not only the optimum output from multiple deep networks but also the complementary properties of them. Furthermore, the distribution of each hierarchy discriminative manifold is sufficiently smooth so that the training process of our MSEDNN can be effectively implemented only using few labeled data. Our proposed network contains a body joint detector and a human pose regressor that are jointly trained. Extensive experiments conducted on four databases show that our proposed MSEDNN can achieve the best recovery performance compared with the state-of-the-art methods.

Human Age Recognition by Electrocardiogram Signal Based on Artificial Neural Network

Science.gov (United States)

Dasgupta, Hirak

2016-12-01

The objective of this work is to make a neural network function approximation model to detect human age from the electrocardiogram (ECG) signal. The input vectors of the neural network are the Katz fractal dimension of the ECG signal, frequencies in the QRS complex, male or female (represented by numeric constant) and the average of successive R-R peak distance of a particular ECG signal. The QRS complex has been detected by short time Fourier transform algorithm. The successive R peak has been detected by, first cutting the signal into periods by auto-correlation method and then finding the absolute of the highest point in each period. The neural network used in this problem consists of two layers, with Sigmoid neuron in the input and linear neuron in the output layer. The result shows the mean of errors as -0.49, 1.03, 0.79 years and the standard deviation of errors as 1.81, 1.77, 2.70 years during training, cross validation and testing with unknown data sets, respectively.

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

Quantitative Analysis of Human Pluripotency and Neural Specification by In-Depth (PhosphoProteomic Profiling

Directory of Open Access Journals (Sweden)

Ilyas Singec

2016-09-01

Full Text Available Controlled differentiation of human embryonic stem cells (hESCs can be utilized for precise analysis of cell type identities during early development. We established a highly efficient neural induction strategy and an improved analytical platform, and determined proteomic and phosphoproteomic profiles of hESCs and their specified multipotent neural stem cell derivatives (hNSCs. This quantitative dataset (nearly 13,000 proteins and 60,000 phosphorylation sites provides unique molecular insights into pluripotency and neural lineage entry. Systems-level comparative analysis of proteins (e.g., transcription factors, epigenetic regulators, kinase families, phosphorylation sites, and numerous biological pathways allowed the identification of distinct signatures in pluripotent and multipotent cells. Furthermore, as predicted by the dataset, we functionally validated an autocrine/paracrine mechanism by demonstrating that the secreted protein midkine is a regulator of neural specification. This resource is freely available to the scientific community, including a searchable website, PluriProt.

Inhibition of glycogen synthase kinase-3 enhances the differentiation and reduces the proliferation of adult human olfactory epithelium neural precursors

International Nuclear Information System (INIS)

Manceur, Aziza P.; Tseng, Michael; Holowacz, Tamara; Witterick, Ian; Weksberg, Rosanna; McCurdy, Richard D.; Warsh, Jerry J.; Audet, Julie

2011-01-01

The olfactory epithelium (OE) contains neural precursor cells which can be easily harvested from a minimally invasive nasal biopsy, making them a valuable cell source to study human neural cell lineages in health and disease. Glycogen synthase kinase-3 (GSK-3) has been implicated in the etiology and treatment of neuropsychiatric disorders and also in the regulation of murine neural precursor cell fate in vitro and in vivo. In this study, we examined the impact of decreased GSK-3 activity on the fate of adult human OE neural precursors in vitro. GSK-3 inhibition was achieved using ATP-competitive (6-bromoindirubin-3'-oxime and CHIR99021) or substrate-competitive (TAT-eIF2B) inhibitors to eliminate potential confounding effects on cell fate due to off-target kinase inhibition. GSK-3 inhibitors decreased the number of neural precursor cells in OE cell cultures through a reduction in proliferation. Decreased proliferation was not associated with a reduction in cell survival but was accompanied by a reduction in nestin expression and a substantial increase in the expression of the neuronal differentiation markers MAP1B and neurofilament (NF-M) after 10 days in culture. Taken together, these results suggest that GSK-3 inhibition promotes the early stages of neuronal differentiation in cultures of adult human neural precursors and provide insights into the mechanisms by which alterations in GSK-3 signaling affect adult human neurogenesis, a cellular process strongly suspected to play a role in the etiology of neuropsychiatric disorders.

Neural correlates of heat-evoked pain memory in humans.

Science.gov (United States)

Wang, Liping; Gui, Peng; Li, Lei; Ku, Yixuan; Bodner, Mark; Fan, Gaojie; Zhou, Yong-Di; Dong, Xiao-Wei

2016-03-01

The neural processes underlying pain memory are not well understood. To explore these processes, contact heat-evoked potentials (CHEPs) were recorded in humans with electroencephalography (EEG) technique during a delayed matching-to-sample task, a working memory task involving presentations of two successive painful heat stimuli (S-1 and S-2) with different intensities separated by a 2-s interval (the memorization period). At the end of the task, the subject was required to discriminate the stimuli by indicating which (S-1 or S-2) induced more pain. A control task was used, in which no active discrimination was required between stimuli. All event-related potential (ERP) analysis was aligned to the onset of S-1. EEG activity exhibited two successive CHEPs: an N2-P2 complex (∼400 ms after onset of S-1) and an ultralate component (ULC, ∼900 ms). The amplitude of the N2-P2 at vertex, but not the ULC, was significantly correlated with stimulus intensity in these two tasks, suggesting that the N2-P2 represents neural coding of pain intensity. A late negative component (LNC) in the frontal recording region was observed only in the memory task during a 500-ms period before onset of S-2. LNC amplitude differed between stimulus intensities and exhibited significant correlations with the N2-P2 complex. These indicate that the frontal LNC is involved in maintenance of intensity of pain in working memory. Furthermore, alpha-band oscillations observed in parietal recording regions during the late delay displayed significant power differences between tasks. This study provides in the temporal domain previously unidentified neural evidence showing the neural processes involved in working memory of painful stimuli. Copyright © 2016 the American Physiological Society.

Continuous Timescale Long-Short Term Memory Neural Network for Human Intent Understanding

Directory of Open Access Journals (Sweden)

Zhibin Yu

2017-08-01

Full Text Available Understanding of human intention by observing a series of human actions has been a challenging task. In order to do so, we need to analyze longer sequences of human actions related with intentions and extract the context from the dynamic features. The multiple timescales recurrent neural network (MTRNN model, which is believed to be a kind of solution, is a useful tool for recording and regenerating a continuous signal for dynamic tasks. However, the conventional MTRNN suffers from the vanishing gradient problem which renders it impossible to be used for longer sequence understanding. To address this problem, we propose a new model named Continuous Timescale Long-Short Term Memory (CTLSTM in which we inherit the multiple timescales concept into the Long-Short Term Memory (LSTM recurrent neural network (RNN that addresses the vanishing gradient problem. We design an additional recurrent connection in the LSTM cell outputs to produce a time-delay in order to capture the slow context. Our experiments show that the proposed model exhibits better context modeling ability and captures the dynamic features on multiple large dataset classification tasks. The results illustrate that the multiple timescales concept enhances the ability of our model to handle longer sequences related with human intentions and hence proving to be more suitable for complex tasks, such as intention recognition.

Development and function of human cerebral cortex neural networks from pluripotent stem cells in vitro.

Science.gov (United States)

Kirwan, Peter; Turner-Bridger, Benita; Peter, Manuel; Momoh, Ayiba; Arambepola, Devika; Robinson, Hugh P C; Livesey, Frederick J

2015-09-15

A key aspect of nervous system development, including that of the cerebral cortex, is the formation of higher-order neural networks. Developing neural networks undergo several phases with distinct activity patterns in vivo, which are thought to prune and fine-tune network connectivity. We report here that human pluripotent stem cell (hPSC)-derived cerebral cortex neurons form large-scale networks that reflect those found in the developing cerebral cortex in vivo. Synchronised oscillatory networks develop in a highly stereotyped pattern over several weeks in culture. An initial phase of increasing frequency of oscillations is followed by a phase of decreasing frequency, before giving rise to non-synchronous, ordered activity patterns. hPSC-derived cortical neural networks are excitatory, driven by activation of AMPA- and NMDA-type glutamate receptors, and can undergo NMDA-receptor-mediated plasticity. Investigating single neuron connectivity within PSC-derived cultures, using rabies-based trans-synaptic tracing, we found two broad classes of neuronal connectivity: most neurons have small numbers (40). These data demonstrate that the formation of hPSC-derived cortical networks mimics in vivo cortical network development and function, demonstrating the utility of in vitro systems for mechanistic studies of human forebrain neural network biology. © 2015. Published by The Company of Biologists Ltd.

Prolonged Expansion Induces Spontaneous Neural Progenitor Differentiation from Human Gingiva-Derived Mesenchymal Stem Cells.

Science.gov (United States)

Rajan, Thangavelu Soundara; Scionti, Domenico; Diomede, Francesca; Piattelli, Adriano; Bramanti, Placido; Mazzon, Emanuela; Trubiani, Oriana

2017-12-01

Neural crest-derived mesenchymal stem cells (MSCs) obtained from dental tissues received considerable interest in regenerative medicine, particularly in nerve regeneration owing to their embryonic origin and ease of harvest. Proliferation efficacy and differentiation capacity into diverse cell lineages propose dental MSCs as an in vitro tool for disease modeling. In this study, we investigated the spontaneous differentiation efficiency of dental MSCs obtained from human gingiva tissue (hGMSCs) into neural progenitor cells after extended passaging. At passage 41, the morphology of hGMSCs changed from typical fibroblast-like shape into sphere-shaped cells with extending processes. Next-generation transcriptomics sequencing showed increased expression of neural progenitor markers such as NES, MEIS2, and MEST. In addition, de novo expression of neural precursor genes, such as NRN1, PHOX2B, VANGL2, and NTRK3, was noticed in passage 41. Immunocytochemistry results showed suppression of neurogenesis repressors TP53 and p21, whereas Western blot results revealed the expression of neurotrophic factors BDNF and NT3 at passage 41. Our results showed the spontaneous efficacy of hGMSCs to differentiate into neural precursor cells over prolonged passages and that these cells may assist in producing novel in vitro disease models that are associated with neural development.

Exogenous testosterone enhances responsiveness to social threat in the neural circuitry of social aggression in humans.

NARCIS (Netherlands)

Hermans, E.J.; Ramsey, N.F.; Honk, J. van

2008-01-01

BACKGROUND: In a range of species, the androgen steroid testosterone is known to potentiate neural circuits involved in intraspecific aggression. Disorders of impulsive aggression in humans have likewise been associated with high testosterone levels, but human evidence for the link between

Multimodal neural correlates of cognitive control in the Human Connectome Project.

Science.gov (United States)

Lerman-Sinkoff, Dov B; Sui, Jing; Rachakonda, Srinivas; Kandala, Sridhar; Calhoun, Vince D; Barch, Deanna M

2017-12-01

Cognitive control is a construct that refers to the set of functions that enable decision-making and task performance through the representation of task states, goals, and rules. The neural correlates of cognitive control have been studied in humans using a wide variety of neuroimaging modalities, including structural MRI, resting-state fMRI, and task-based fMRI. The results from each of these modalities independently have implicated the involvement of a number of brain regions in cognitive control, including dorsal prefrontal cortex, and frontal parietal and cingulo-opercular brain networks. However, it is not clear how the results from a single modality relate to results in other modalities. Recent developments in multimodal image analysis methods provide an avenue for answering such questions and could yield more integrated models of the neural correlates of cognitive control. In this study, we used multiset canonical correlation analysis with joint independent component analysis (mCCA + jICA) to identify multimodal patterns of variation related to cognitive control. We used two independent cohorts of participants from the Human Connectome Project, each of which had data from four imaging modalities. We replicated the findings from the first cohort in the second cohort using both independent and predictive analyses. The independent analyses identified a component in each cohort that was highly similar to the other and significantly correlated with cognitive control performance. The replication by prediction analyses identified two independent components that were significantly correlated with cognitive control performance in the first cohort and significantly predictive of performance in the second cohort. These components identified positive relationships across the modalities in neural regions related to both dynamic and stable aspects of task control, including regions in both the frontal-parietal and cingulo-opercular networks, as well as regions

Neural Plasticity following Abacus Training in Humans: A Review and Future Directions

Directory of Open Access Journals (Sweden)

Yongxin Li

2016-01-01

Full Text Available The human brain has an enormous capacity to adapt to a broad variety of environmental demands. Previous studies in the field of abacus training have shown that this training can induce specific changes in the brain. However, the neural mechanism underlying these changes remains elusive. Here, we reviewed the behavioral and imaging findings of comparisons between abacus experts and average control subjects and focused on changes in activation patterns and changes in brain structure. Finally, we noted the limitations and the future directions of this field. We concluded that although current studies have provided us with information about the mechanisms of abacus training, more research on abacus training is needed to understand its neural impact.

Inhibition of glycogen synthase kinase-3 enhances the differentiation and reduces the proliferation of adult human olfactory epithelium neural precursors

Energy Technology Data Exchange (ETDEWEB)

Manceur, Aziza P. [Institute of Biomaterials and Biomedical Engineering (IBBME), University of Toronto, Toronto, Ontario (Canada); Donnelly Centre, University of Toronto, Toronto, Ontario (Canada); Tseng, Michael [Laboratory of Cellular and Molecular Pathophysiology, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Ontario (Canada); Department of Psychiatry, University of Toronto, Toronto, ON (Canada); Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Holowacz, Tamara [Donnelly Centre, University of Toronto, Toronto, Ontario (Canada); Witterick, Ian [Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Department of Otolaryngology, Head and Neck Surgery, University of Toronto, ON (Canada); Weksberg, Rosanna [Institute of Medical Science, University of Toronto, Toronto, ON (Canada); The Hospital for Sick Children, Research Institute, Program in Genetics and Genomic Biology, Toronto, Ontario Canada (Canada); McCurdy, Richard D. [The Hospital for Sick Children, Research Institute, Program in Genetics and Genomic Biology, Toronto, Ontario Canada (Canada); Warsh, Jerry J. [Laboratory of Cellular and Molecular Pathophysiology, Centre for Addiction and Mental Health (CAMH), University of Toronto, Toronto, Ontario (Canada); Department of Psychiatry, University of Toronto, Toronto, ON (Canada); Institute of Medical Science, University of Toronto, Toronto, ON (Canada); Audet, Julie, E-mail: julie.audet@utoronto.ca [Institute of Biomaterials and Biomedical Engineering (IBBME), University of Toronto, Toronto, Ontario (Canada); Donnelly Centre, University of Toronto, Toronto, Ontario (Canada)

2011-09-10

The olfactory epithelium (OE) contains neural precursor cells which can be easily harvested from a minimally invasive nasal biopsy, making them a valuable cell source to study human neural cell lineages in health and disease. Glycogen synthase kinase-3 (GSK-3) has been implicated in the etiology and treatment of neuropsychiatric disorders and also in the regulation of murine neural precursor cell fate in vitro and in vivo. In this study, we examined the impact of decreased GSK-3 activity on the fate of adult human OE neural precursors in vitro. GSK-3 inhibition was achieved using ATP-competitive (6-bromoindirubin-3'-oxime and CHIR99021) or substrate-competitive (TAT-eIF2B) inhibitors to eliminate potential confounding effects on cell fate due to off-target kinase inhibition. GSK-3 inhibitors decreased the number of neural precursor cells in OE cell cultures through a reduction in proliferation. Decreased proliferation was not associated with a reduction in cell survival but was accompanied by a reduction in nestin expression and a substantial increase in the expression of the neuronal differentiation markers MAP1B and neurofilament (NF-M) after 10 days in culture. Taken together, these results suggest that GSK-3 inhibition promotes the early stages of neuronal differentiation in cultures of adult human neural precursors and provide insights into the mechanisms by which alterations in GSK-3 signaling affect adult human neurogenesis, a cellular process strongly suspected to play a role in the etiology of neuropsychiatric disorders.

Xenotransplantation of human neural progenitor cells to the subretinal space of nonimmunosuppressed pigs

DEFF Research Database (Denmark)

Warfvinge, Karin; Schwartz, Philip H; Kiilgaard, Jens Folke

2011-01-01

To investigate the feasibility of transplanting human neural progenitor cells (hNPCs) to the retina of nonimmunosuppressed pigs, cultured hNPCs were injected into the subretinal space of 5 adult pigs after laser burns were applied to promote donor cell integration. Postoperatively, the retinal ve...

Origin-Dependent Neural Cell Identities in Differentiated Human iPSCs In Vitro and after Transplantation into the Mouse Brain

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Gunnar Hargus

2014-09-01

Full Text Available The differentiation capability of induced pluripotent stem cells (iPSCs toward certain cell types for disease modeling and drug screening assays might be influenced by their somatic cell of origin. Here, we have compared the neural induction of human iPSCs generated from fetal neural stem cells (fNSCs, dermal fibroblasts, or cord blood CD34+ hematopoietic progenitor cells. Neural progenitor cells (NPCs and neurons could be generated at similar efficiencies from all iPSCs. Transcriptomics analysis of the whole genome and of neural genes revealed a separation of neuroectoderm-derived iPSC-NPCs from mesoderm-derived iPSC-NPCs. Furthermore, we found genes that were similarly expressed in fNSCs and neuroectoderm, but not in mesoderm-derived iPSC-NPCs. Notably, these neural signatures were retained after transplantation into the cortex of mice and paralleled with increased survival of neuroectoderm-derived cells in vivo. These results indicate distinct origin-dependent neural cell identities in differentiated human iPSCs both in vitro and in vivo.

SOX10-Nano-Lantern Reporter Human iPS Cells; A Versatile Tool for Neural Crest Research.

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Tomoko Horikiri

Full Text Available The neural crest is a source to produce multipotent neural crest stem cells that have a potential to differentiate into diverse cell types. The transcription factor SOX10 is expressed through early neural crest progenitors and stem cells in vertebrates. Here we report the generation of SOX10-Nano-lantern (NL reporter human induced pluripotent stem cells (hiPS by using CRISPR/Cas9 systems, that are beneficial to investigate the generation and maintenance of neural crest progenitor cells. SOX10-NL positive cells are produced transiently from hiPS cells by treatment with TGFβ inhibitor SB431542 and GSK3 inhibitor CHIR99021. We found that all SOX10-NL-positive cells expressed an early neural crest marker NGFR, however SOX10-NL-positive cells purified from differentiated hiPS cells progressively attenuate their NL-expression under proliferation. We therefore attempted to maintain SOX10-NL-positive cells with additional signaling on the plane and sphere culture conditions. These SOX10-NL cells provide us to investigate mass culture with neural crest cells for stem cell research.

Application of structured support vector machine backpropagation to a convolutional neural network for human pose estimation.

Science.gov (United States)

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

In this study, for the first time, we show how to formulate a structured support vector machine (SSVM) as two layers in a convolutional neural network, where the top layer is a loss augmented inference layer and the bottom layer is the normal convolutional layer. We show that a deformable part model can be learned with the proposed structured SVM neural network by backpropagating the error of the deformable part model to the convolutional neural network. The forward propagation calculates the loss augmented inference and the backpropagation calculates the gradient from the loss augmented inference layer to the convolutional layer. Thus, we obtain a new type of convolutional neural network called an Structured SVM convolutional neural network, which we applied to the human pose estimation problem. This new neural network can be used as the final layers in deep learning. Our method jointly learns the structural model parameters and the appearance model parameters. We implemented our method as a new layer in the existing Caffe library. Copyright © 2017 Elsevier Ltd. All rights reserved.

Led into temptation? Rewarding brand logos bias the neural encoding of incidental economic decisions.

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Murawski, Carsten; Harris, Philip G; Bode, Stefan; Domínguez D, Juan F; Egan, Gary F

2012-01-01

Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI) study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness.

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.

The human factor: behavioral and neural correlates of humanized perception in moral decision making.

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Majdandžić, Jasminka; Bauer, Herbert; Windischberger, Christian; Moser, Ewald; Engl, Elisabeth; Lamm, Claus

2012-01-01

The extent to which people regard others as full-blown individuals with mental states ("humanization") seems crucial for their prosocial motivation towards them. Previous research has shown that decisions about moral dilemmas in which one person can be sacrificed to save multiple others do not consistently follow utilitarian principles. We hypothesized that this behavior can be explained by the potential victim's perceived humanness and an ensuing increase in vicarious emotions and emotional conflict during decision making. Using fMRI, we assessed neural activity underlying moral decisions that affected fictitious persons that had or had not been experimentally humanized. In implicit priming trials, participants either engaged in mentalizing about these persons (Humanized condition) or not (Neutral condition). In subsequent moral dilemmas, participants had to decide about sacrificing these persons' lives in order to save the lives of numerous others. Humanized persons were sacrificed less often, and the activation pattern during decisions about them indicated increased negative affect, emotional conflict, vicarious emotions, and behavioral control (pgACC/mOFC, anterior insula/IFG, aMCC and precuneus/PCC). Besides, we found enhanced effective connectivity between aMCC and anterior insula, which suggests increased emotion regulation during decisions affecting humanized victims. These findings highlight the importance of others' perceived humanness for prosocial behavior - with aversive affect and other-related concern when imagining harming more "human-like" persons acting against purely utilitarian decisions.

The human factor: behavioral and neural correlates of humanized perception in moral decision making.

Directory of Open Access Journals (Sweden)

Jasminka Majdandžić

Full Text Available The extent to which people regard others as full-blown individuals with mental states ("humanization" seems crucial for their prosocial motivation towards them. Previous research has shown that decisions about moral dilemmas in which one person can be sacrificed to save multiple others do not consistently follow utilitarian principles. We hypothesized that this behavior can be explained by the potential victim's perceived humanness and an ensuing increase in vicarious emotions and emotional conflict during decision making. Using fMRI, we assessed neural activity underlying moral decisions that affected fictitious persons that had or had not been experimentally humanized. In implicit priming trials, participants either engaged in mentalizing about these persons (Humanized condition or not (Neutral condition. In subsequent moral dilemmas, participants had to decide about sacrificing these persons' lives in order to save the lives of numerous others. Humanized persons were sacrificed less often, and the activation pattern during decisions about them indicated increased negative affect, emotional conflict, vicarious emotions, and behavioral control (pgACC/mOFC, anterior insula/IFG, aMCC and precuneus/PCC. Besides, we found enhanced effective connectivity between aMCC and anterior insula, which suggests increased emotion regulation during decisions affecting humanized victims. These findings highlight the importance of others' perceived humanness for prosocial behavior - with aversive affect and other-related concern when imagining harming more "human-like" persons acting against purely utilitarian decisions.

Intranasal oxytocin modulates neural functional connectivity during human social interaction.

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Rilling, James K; Chen, Xiangchuan; Chen, Xu; Haroon, Ebrahim

2018-02-10

Oxytocin (OT) modulates social behavior in primates and many other vertebrate species. Studies in non-primate animals have demonstrated that, in addition to influencing activity within individual brain areas, OT influences functional connectivity across networks of areas involved in social behavior. Previously, we used fMRI to image brain function in human subjects during a dyadic social interaction task following administration of either intranasal oxytocin (INOT) or placebo, and analyzed the data with a standard general linear model. Here, we conduct an extensive re-analysis of these data to explore how OT modulates functional connectivity across a neural network that animal studies implicate in social behavior. OT induced widespread increases in functional connectivity in response to positive social interactions among men and widespread decreases in functional connectivity in response to negative social interactions among women. Nucleus basalis of Meynert, an important regulator of selective attention and motivation with a particularly high density of OT receptors, had the largest number of OT-modulated connections. Regions known to receive mesolimbic dopamine projections such as the nucleus accumbens and lateral septum were also hubs for OT effects on functional connectivity. Our results suggest that the neural mechanism by which OT influences primate social cognition may include changes in patterns of activity across neural networks that regulate social behavior in other animals. © 2018 Wiley Periodicals, Inc.

Generation of Genetically Modified Organotypic Skin Cultures Using Devitalized Human Dermis.

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Li, Jingting; Sen, George L

2015-12-14

Organotypic cultures allow the reconstitution of a 3D environment critical for cell-cell contact and cell-matrix interactions which mimics the function and physiology of their in vivo tissue counterparts. This is exemplified by organotypic skin cultures which faithfully recapitulates the epidermal differentiation and stratification program. Primary human epidermal keratinocytes are genetically manipulable through retroviruses where genes can be easily overexpressed or knocked down. These genetically modified keratinocytes can then be used to regenerate human epidermis in organotypic skin cultures providing a powerful model to study genetic pathways impacting epidermal growth, differentiation, and disease progression. The protocols presented here describe methods to prepare devitalized human dermis as well as to genetically manipulate primary human keratinocytes in order to generate organotypic skin cultures. Regenerated human skin can be used in downstream applications such as gene expression profiling, immunostaining, and chromatin immunoprecipitations followed by high throughput sequencing. Thus, generation of these genetically modified organotypic skin cultures will allow the determination of genes that are critical for maintaining skin homeostasis.

Test of neural inertia in humans during general anaesthesia.

Science.gov (United States)

Kuizenga, M H; Colin, P J; Reyntjens, K M E M; Touw, D J; Nalbat, H; Knotnerus, F H; Vereecke, H E M; Struys, M M R F

2018-03-01

Neural inertia is defined as the tendency of the central nervous system to resist transitions between arousal states. This phenomenon has been observed in mice and Drosophila anaesthetized with volatile anaesthetics: the effect-site concentration required to induce anaesthesia in 50% of the population (C 50 ) was significantly higher than the effect-site concentration for 50% of the population to recover from anaesthesia. We evaluated this phenomenon in humans using propofol or sevoflurane (both with or without remifentanil) as anaesthetic agents. Thirty-six healthy volunteers received four sessions of anaesthesia with different drug combinations in a step-up/step-down design. Propofol or sevoflurane was administered with or without remifentanil. Serum concentrations of propofol and remifentanil were measured from arterial blood samples. Loss and return of responsiveness (LOR-ROR), response to pain (PAIN), Patient State Index (PSI) and spectral edge frequency (SEF) were modeled with NONMEM®. For propofol, the C 50 for induction and recovery of anaesthesia was not significantly different across the different endpoints. For sevoflurane, for all endpoints except SEF, significant differences were found. For some endpoints (LOR and PAIN) the difference was significant only when sevoflurane was combined with remifentanil. Our results nuance earlier findings with volatile anaesthetics in mice and Drosophila. Methodological aspects of the study, such as the measured endpoint, influence the detection of neural inertia. A more thorough definition of neural inertia, with a robust methodological framework for clinical studies is required to advance our knowledge of this phenomenon. NCT 02043938. Copyright © 2017 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.

Glycoconjugates reveal diversity of human neural stem cells (hNSCs) derived from human induced pluripotent stem cells (hiPSCs).

Science.gov (United States)

Kandasamy, Majury; Roll, Lars; Langenstroth, Daniel; Brüstle, Oliver; Faissner, Andreas

2017-06-01

Neural stem cells (NSCs) have the ability to self-renew and to differentiate into various cell types of the central nervous system. This potential can be recapitulated by human induced pluripotent stem cells (hiPSCs) in vitro. The differentiation capacity of hiPSCs is characterized by several stages with distinct morphologies and the expression of various marker molecules. We used the monoclonal antibodies (mAbs) 487 LeX , 5750 LeX and 473HD to analyze the expression pattern of particular carbohydrate motifs as potential markers at six differentiation stages of hiPSCs. Mouse ESCs were used as a comparison. At the pluripotent stage, 487 LeX -, 5750 LeX - and 473HD-related glycans were differently expressed. Later, cells of the three germ layers in embryoid bodies (hEBs) and, even after neuralization of hEBs, subpopulations of cells were labeled with these surface antibodies. At the human rosette-stage of NSCs (hR-NSC), LeX- and 473HD-related epitopes showed antibody-specific expression patterns. We also found evidence that these surface antibodies could be used to distinguish the hR-NSCs from the hSR-NSCs stages. Characterization of hNSCs FGF-2/EGF derived from hSR-NSCs revealed that both LeX antibodies and the 473HD antibody labeled subpopulations of hNSCs FGF-2/EGF . Finally, we identified potential LeX carrier molecules that were spatiotemporally regulated in early and late stages of differentiation. Our study provides new insights into the regulation of glycoconjugates during early human stem cell development. The mAbs 487 LeX , 5750 LeX and 473HD are promising tools for identifying distinct stages during neural differentiation.

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

Science.gov (United States)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Effect of 3D-scaffold formation on differentiation and survival in human neural progenitor cells.

Science.gov (United States)

Ortinau, Stefanie; Schmich, Jürgen; Block, Stephan; Liedmann, Andrea; Jonas, Ludwig; Weiss, Dieter G; Helm, Christiane A; Rolfs, Arndt; Frech, Moritz J

2010-11-11

3D-scaffolds have been shown to direct cell growth and differentiation in many different cell types, with the formation and functionalisation of the 3D-microenviroment being important in determining the fate of the embedded cells. Here we used a hydrogel-based scaffold to investigate the influences of matrix concentration and functionalisation with laminin on the formation of the scaffolds, and the effect of these scaffolds on human neural progenitor cells cultured within them. In this study we used different concentrations of the hydrogel-based matrix PuraMatrix. In some experiments we functionalised the matrix with laminin I. The impact of concentration and treatment with laminin on the formation of the scaffold was examined with atomic force microscopy. Cells from a human fetal neural progenitor cell line were cultured in the different matrices, as well as in a 2D culture system, and were subsequently analysed with antibody stainings against neuronal markers. In parallel, the survival rate of the cells was determined by a live/dead assay. Atomic force microscopy measurements demonstrated that the matrices are formed by networks of isolated PuraMatrix fibres and aggregates of fibres. An increase of the hydrogel concentration led to a decrease in the mesh size of the scaffolds and functionalisation with laminin promoted aggregation of the fibres (bundle formation), which further reduces the density of isolated fibres. We showed that laminin-functionalisation is essential for human neural progenitor cells to build up 3D-growth patterns, and that proliferation of the cells is also affected by the concentration of matrix. In addition we found that 3D-cultures enhanced neuronal differentiation and the survival rate of the cells compared to 2D-cultures. Taken together, we have demonstrated a direct influence of the 3D-scaffold formation on the survival and neuronal differentiation of human neural progenitor cells. These findings emphasize the importance of optimizing 3

Explaining neural signals in human visual cortex with an associative learning model.

Science.gov (United States)

Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

2012-08-01

"Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

Automatic determination of pathological voice transformation coefficients for TDPDOLA using neural network

International Nuclear Information System (INIS)

Belgacem, H.; Cherif, A.

2011-01-01

One of the biggest challenges in vocal transformation with TD-PSOLA technique is the selection of modified parameters that will make a successful speech resynthesis. The best selection methods are by using human ratters. This study focuses on automatic determination of the pathological voice transformation coefficients using an Artificial Neural Network this way by comparing the results to the previous manual work. Four characterizied parameters (RATA-PLP, Jitter, Shimmer and RAP) were chosen. The system is developed with supervised training, consists of recognition (neural network) for synthesis (TD-PSOLA). The experimental results show that the parameter sets selected by the proposed system can be successfully used to resynthesize and demonstrating that our system can assist in vocal of pathological voice's transformation.

Mathematical Modeling and Evaluation of Human Motions in Physical Therapy Using Mixture Density Neural Networks.

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Vakanski, A; Ferguson, J M; Lee, S

2016-12-01

The objective of the proposed research is to develop a methodology for modeling and evaluation of human motions, which will potentially benefit patients undertaking a physical rehabilitation therapy (e.g., following a stroke or due to other medical conditions). The ultimate aim is to allow patients to perform home-based rehabilitation exercises using a sensory system for capturing the motions, where an algorithm will retrieve the trajectories of a patient's exercises, will perform data analysis by comparing the performed motions to a reference model of prescribed motions, and will send the analysis results to the patient's physician with recommendations for improvement. The modeling approach employs an artificial neural network, consisting of layers of recurrent neuron units and layers of neuron units for estimating a mixture density function over the spatio-temporal dependencies within the human motion sequences. Input data are sequences of motions related to a prescribed exercise by a physiotherapist to a patient, and recorded with a motion capture system. An autoencoder subnet is employed for reducing the dimensionality of captured sequences of human motions, complemented with a mixture density subnet for probabilistic modeling of the motion data using a mixture of Gaussian distributions. The proposed neural network architecture produced a model for sets of human motions represented with a mixture of Gaussian density functions. The mean log-likelihood of observed sequences was employed as a performance metric in evaluating the consistency of a subject's performance relative to the reference dataset of motions. A publically available dataset of human motions captured with Microsoft Kinect was used for validation of the proposed method. The article presents a novel approach for modeling and evaluation of human motions with a potential application in home-based physical therapy and rehabilitation. The described approach employs the recent progress in the field of

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

Science.gov (United States)

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

2016-10-01

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

Efficient and rapid derivation of primitive neural stem cells and generation of brain subtype neurons from human pluripotent stem cells.

Science.gov (United States)

Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C

2013-11-01

Human pluripotent stem cells (hPSCs), including human embryonic stem cells and human induced pluripotent stem cells, are unique cell sources for disease modeling, drug discovery screens, and cell therapy applications. The first step in producing neural lineages from hPSCs is the generation of neural stem cells (NSCs). Current methods of NSC derivation involve the time-consuming, labor-intensive steps of an embryoid body generation or coculture with stromal cell lines that result in low-efficiency derivation of NSCs. In this study, we report a highly efficient serum-free pluripotent stem cell neural induction medium that can induce hPSCs into primitive NSCs (pNSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. The pNSCs expressed the neural stem cell markers Pax6, Sox1, Sox2, and Nestin; were negative for Oct4; could be expanded for multiple passages; and could be differentiated into neurons, astrocytes, and oligodendrocytes, in addition to the brain region-specific neuronal subtypes GABAergic, dopaminergic, and motor neurons. Global gene expression of the transcripts of pNSCs was comparable to that of rosette-derived and human fetal-derived NSCs. This work demonstrates an efficient method to generate expandable pNSCs, which can be further differentiated into central nervous system neurons and glia with temporal, spatial, and positional cues of brain regional heterogeneity. This method of pNSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

Led into temptation? Rewarding brand logos bias the neural encoding of incidental economic decisions.

Directory of Open Access Journals (Sweden)

Carsten Murawski

Full Text Available Human decision-making is driven by subjective values assigned to alternative choice options. These valuations are based on reward cues. It is unknown, however, whether complex reward cues, such as brand logos, may bias the neural encoding of subjective value in unrelated decisions. In this functional magnetic resonance imaging (fMRI study, we subliminally presented brand logos preceding intertemporal choices. We demonstrated that priming biased participants' preferences towards more immediate rewards in the subsequent temporal discounting task. This was associated with modulations of the neural encoding of subjective values of choice options in a network of brain regions, including but not restricted to medial prefrontal cortex. Our findings demonstrate the general susceptibility of the human decision making system to apparently incidental contextual information. We conclude that the brain incorporates seemingly unrelated value information that modifies decision making outside the decision-maker's awareness.

Efficient and Rapid Derivation of Primitive Neural Stem Cells and Generation of Brain Subtype Neurons From Human Pluripotent Stem Cells

OpenAIRE

Yan, Yiping; Shin, Soojung; Jha, Balendu Shekhar; Liu, Qiuyue; Sheng, Jianting; Li, Fuhai; Zhan, Ming; Davis, Janine; Bharti, Kapil; Zeng, Xianmin; Rao, Mahendra; Malik, Nasir; Vemuri, Mohan C.

2013-01-01

This study developed a highly efficient serum-free pluripotent stem cell (PSC) neural induction medium that can induce human PSCs into primitive neural stem cells (NSCs) in 7 days, obviating the need for time-consuming, laborious embryoid body generation or rosette picking. This method of primitive NSC derivation sets the stage for the scalable production of clinically relevant neural cells for cell therapy applications in good manufacturing practice conditions.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-07-01

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

Drought in a human-modified world : Reframing drought definitions, understanding, and analysis approaches

NARCIS (Netherlands)

Van Loon, Anne F.; Stahl, Kerstin; Di Baldassarre, Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko|info:eu-repo/dai/nl/364253940; Gleeson, Tom; Van Dijk, Albert I.J.M.|info:eu-repo/dai/nl/304847356; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Adriaan J.; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; wagener, thorsten; van Lanen, Henny A.J.

2016-01-01

In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows,

Generation of Neural Progenitor Spheres from Human Pluripotent Stem Cells in a Suspension Bioreactor.

Science.gov (United States)

Yan, Yuanwei; Song, Liqing; Tsai, Ang-Chen; Ma, Teng; Li, Yan

2016-01-01

Conventional two-dimensional (2-D) culture systems cannot provide large numbers of human pluripotent stem cells (hPSCs) and their derivatives that are demanded for commercial and clinical applications in in vitro drug screening, disease modeling, and potentially cell therapy. The technologies that support three-dimensional (3-D) suspension culture, such as a stirred bioreactor, are generally considered as promising approaches to produce the required cells. Recently, suspension bioreactors have also been used to generate mini-brain-like structure from hPSCs for disease modeling, showing the important role of bioreactor in stem cell culture. This chapter describes a detailed culture protocol for neural commitment of hPSCs into neural progenitor cell (NPC) spheres using a spinner bioreactor. The basic steps to prepare hPSCs for bioreactor inoculation are illustrated from cell thawing to cell propagation. The method for generating NPCs from hPSCs in the spinner bioreactor along with the static control is then described. The protocol in this study can be applied to the generation of NPCs from hPSCs for further neural subtype specification, 3-D neural tissue development, or potential preclinical studies or clinical applications in neurological diseases.

The Human Factor: Behavioral and Neural Correlates of Humanized Perception in Moral Decision Making

Science.gov (United States)

Majdandžić, Jasminka; Bauer, Herbert; Windischberger, Christian; Moser, Ewald; Engl, Elisabeth; Lamm, Claus

2012-01-01

The extent to which people regard others as full-blown individuals with mental states (“humanization”) seems crucial for their prosocial motivation towards them. Previous research has shown that decisions about moral dilemmas in which one person can be sacrificed to save multiple others do not consistently follow utilitarian principles. We hypothesized that this behavior can be explained by the potential victim’s perceived humanness and an ensuing increase in vicarious emotions and emotional conflict during decision making. Using fMRI, we assessed neural activity underlying moral decisions that affected fictitious persons that had or had not been experimentally humanized. In implicit priming trials, participants either engaged in mentalizing about these persons (Humanized condition) or not (Neutral condition). In subsequent moral dilemmas, participants had to decide about sacrificing these persons’ lives in order to save the lives of numerous others. Humanized persons were sacrificed less often, and the activation pattern during decisions about them indicated increased negative affect, emotional conflict, vicarious emotions, and behavioral control (pgACC/mOFC, anterior insula/IFG, aMCC and precuneus/PCC). Besides, we found enhanced effective connectivity between aMCC and anterior insula, which suggests increased emotion regulation during decisions affecting humanized victims. These findings highlight the importance of others’ perceived humanness for prosocial behavior - with aversive affect and other-related concern when imagining harming more “human-like” persons acting against purely utilitarian decisions. PMID:23082194

Ligand-Modified Human Serum Albumin Nanoparticles for Enhanced Gene Delivery.

Science.gov (United States)

Look, Jennifer; Wilhelm, Nadine; von Briesen, Hagen; Noske, Nadja; Günther, Christine; Langer, Klaus; Gorjup, Erwin

2015-09-08

The development of nonviral gene delivery systems is a great challenge to enable safe gene therapy. In this study, ligand-modified nanoparticles based on human serum albumin (HSA) were developed and optimized for an efficient gene therapy. Different glutaraldehyde cross-linking degrees were investigated to optimize the HSA nanoparticles for gene delivery. The peptide sequence arginine-glycine-aspartate (RGD) and the HIV-1 transactivator of transduction sequence (Tat) are well-known as promising targeting ligands. Plasmid DNA loaded HSA nanoparticles were covalently modified on their surface with these different ligands. The transfection potential of the obtained plasmid DNA loaded RGD- and Tat-modified nanoparticles was investigated in vitro, and optimal incubation conditions for these preparations were studied. It turned out that Tat-modified HSA nanoparticles with the lowest cross-linking degree of 20% showed the highest transfection potential. Taken together, ligand-functionalized HSA nanoparticles represent promising tools for efficient and safe gene therapy.

A wireless transmission neural interface system for unconstrained non-human primates.

Science.gov (United States)

Fernandez-Leon, Jose A; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J; Hansen, Bryan J; Hu, Ming; Dragoi, Valentin

2015-10-01

Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

A wireless transmission neural interface system for unconstrained non-human primates

Science.gov (United States)

Fernandez-Leon, Jose A.; Parajuli, Arun; Franklin, Robert; Sorenson, Michael; Felleman, Daniel J.; Hansen, Bryan J.; Hu, Ming; Dragoi, Valentin

2015-10-01

Objective. Studying the brain in large animal models in a restrained laboratory rig severely limits our capacity to examine brain circuits in experimental and clinical applications. Approach. To overcome these limitations, we developed a high-fidelity 96-channel wireless system to record extracellular spikes and local field potentials from the neocortex. A removable, external case of the wireless device is attached to a titanium pedestal placed in the animal skull. Broadband neural signals are amplified, multiplexed, and continuously transmitted as TCP/IP data at a sustained rate of 24 Mbps. A Xilinx Spartan 6 FPGA assembles the digital signals into serial data frames for transmission at 20 kHz though an 802.11n wireless data link on a frequency-shift key-modulated signal at 5.7-5.8 GHz to a receiver up to 10 m away. The system is powered by two CR123A, 3 V batteries for 2 h of operation. Main results. We implanted a multi-electrode array in visual area V4 of one anesthetized monkey (Macaca fascicularis) and in the dorsolateral prefrontal cortex (dlPFC) of a freely moving monkey (Macaca mulatta). The implanted recording arrays were electrically stable and delivered broadband neural data over a year of testing. For the first time, we compared dlPFC neuronal responses to the same set of stimuli (food reward) in restrained and freely moving conditions. Although we did not find differences in neuronal responses as a function of reward type in the restrained and unrestrained conditions, there were significant differences in correlated activity. This demonstrates that measuring neural responses in freely moving animals can capture phenomena that are absent in the traditional head-fixed paradigm. Significance. We implemented a wireless neural interface for multi-electrode recordings in freely moving non-human primates, which can potentially move systems neuroscience to a new direction by allowing one to record neural signals while animals interact with their environment.

Neural differentiation of novel multipotent progenitor cells from cryopreserved human umbilical cord blood

International Nuclear Information System (INIS)

Lee, Myoung Woo; Moon, Young Joon; Yang, Mal Sook; Kim, Sun Kyung; Jang, In Keun; Eom, Young-woo; Park, Joon Seong; Kim, Hugh C.; Song, Kye Yong; Park, Soon Cheol; Lim, Hwan Sub; Kim, Young Jin

2007-01-01

Umbilical cord blood (UCB) is a rich source of hematopoietic stem cells, with practical and ethical advantages. To date, the presence of other stem cells in UCB remains to be established. We investigated whether other stem cells are present in cryopreserved UCB. Seeded mononuclear cells formed adherent colonized cells in optimized culture conditions. Over a 4- to 6-week culture period, colonized cells gradually developed into adherent mono-layer cells, which exhibited homogeneous fibroblast-like morphology and immunophenotypes, and were highly proliferative. Isolated cells were designated 'multipotent progenitor cells (MPCs)'. Under appropriate conditions for 2 weeks, MPCs differentiated into neural tissue-specific cell types, including neuron, astrocyte, and oligodendrocyte. Differentiated cells presented their respective markers, specifically, NF-L and NSE for neurons, GFAP for astrocytes, and myelin/oligodendrocyte for oligodendrocytes. In this study, we successfully isolated MPCs from cryopreserved UCB, which differentiated into the neural tissue-specific cell types. These findings suggest that cryopreserved human UCB is a useful alternative source of neural progenitor cells, such as MPCs, for experimental and therapeutic applications

Hypothetical neural mechanism that may play a role in mental rotation: an attractor neural network model.

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Benusková, L; Estok, S

1998-11-01

We propose an attractor neural network (ANN) model that performs rotation-invariant pattern recognition in such a way that it can account for a neural mechanism being involved in the image transformation accompanying the experience of mental rotation. We compared the performance of our ANN model with the results of the chronometric psychophysical experiments of Cooper and Shepard (Cooper L A and Shepard R N 1973 Visual Information Processing (New York: Academic) pp 204-7) on discrimination of alphanumeric characters presented in various angular departures from their canonical upright position. Comparing the times required for pattern retrieval in its canonical upright position with the reaction times of human subjects, we found agreement in that (i) retrieval times for clockwise and anticlockwise departures of the same angular magnitude (up to 180 degrees) were not different, (ii) retrieval times increased with departure from upright and (iii) increased more sharply as departure from upright approached 180 degrees. The rotation-invariant retrieval of the activity pattern has been accomplished by means of the modified algorithm of Dotsenko (Dotsenko V S 1988 J. Phys. A: Math. Gen. 21 L783-7) proposed for translation-, rotation- and size-invariant pattern recognition, which uses relaxation of neuronal firing thresholds to guide the evolution of the ANN in state space towards the desired memory attractor. The dynamics of neuronal relaxation has been modified for storage and retrieval of low-activity patterns and the original gradient optimization of threshold dynamics has been replaced with optimization by simulated annealing.

Statistical control chart and neural network classification for improving human fall detection

KAUST Repository

Harrou, Fouzi; Zerrouki, Nabil; Sun, Ying; Houacine, Amrane

2017-01-01

This paper proposes a statistical approach to detect and classify human falls based on both visual data from camera and accelerometric data captured by accelerometer. Specifically, we first use a Shewhart control chart to detect the presence of potential falls by using accelerometric data. Unfortunately, this chart cannot distinguish real falls from fall-like actions, such as lying down. To bypass this difficulty, a neural network classifier is then applied only on the detected cases through visual data. To assess the performance of the proposed method, experiments are conducted on the publicly available fall detection databases: the University of Rzeszow's fall detection (URFD) dataset. Results demonstrate that the detection phase play a key role in reducing the number of sequences used as input into the neural network classifier for classification, significantly reducing computational burden and achieving better accuracy.

Expression of Pluripotency Markers in Nonpluripotent Human Neural Stem and Progenitor Cells

DEFF Research Database (Denmark)

Vincent, P.; Benedikz, Eirikur; Uhlén, Per

2017-01-01

Nonpluripotent neural progenitor cells (NPCs) derived from the human fetal central nervous system were found to express a number of messenger RNA (mRNA) species associated with pluripotency, such as NANOG, REX1, and OCT4. The expression was restricted to small subpopulations of NPCs. In contrast...... to pluripotent stem cells, there was no coexpression of the pluripotency-associated genes studied. Although the expression of these genes rapidly declined during the in vitro differentiation of NPCs, we found no evidence that the discrete expression was associated with the markers of multipotent neural stem...... cells (CD133+/CD24lo), the capacity of sphere formation, or high cell proliferation rates. The rate of cell death among NPCs expressing pluripotency-associated genes was also similar to that of other NPCs. Live cell imaging showed that NANOG- and REX1-expressing NPCs continuously changed morphology...

Statistical control chart and neural network classification for improving human fall detection

KAUST Repository

Harrou, Fouzi

2017-01-05

This paper proposes a statistical approach to detect and classify human falls based on both visual data from camera and accelerometric data captured by accelerometer. Specifically, we first use a Shewhart control chart to detect the presence of potential falls by using accelerometric data. Unfortunately, this chart cannot distinguish real falls from fall-like actions, such as lying down. To bypass this difficulty, a neural network classifier is then applied only on the detected cases through visual data. To assess the performance of the proposed method, experiments are conducted on the publicly available fall detection databases: the University of Rzeszow\\'s fall detection (URFD) dataset. Results demonstrate that the detection phase play a key role in reducing the number of sequences used as input into the neural network classifier for classification, significantly reducing computational burden and achieving better accuracy.

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

Directory of Open Access Journals (Sweden)

Philipp Capetian

2016-10-01

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

Using repetitive transcranial magnetic stimulation to study the underlying neural mechanisms of human motor learning and memory.

Science.gov (United States)

Censor, Nitzan; Cohen, Leonardo G

2011-01-01

In the last two decades, there has been a rapid development in the research of the physiological brain mechanisms underlying human motor learning and memory. While conventional memory research performed on animal models uses intracellular recordings, microfusion of protein inhibitors to specific brain areas and direct induction of focal brain lesions, human research has so far utilized predominantly behavioural approaches and indirect measurements of neural activity. Repetitive transcranial magnetic stimulation (rTMS), a safe non-invasive brain stimulation technique, enables the study of the functional role of specific cortical areas by evaluating the behavioural consequences of selective modulation of activity (excitation or inhibition) on memory generation and consolidation, contributing to the understanding of the neural substrates of motor learning. Depending on the parameters of stimulation, rTMS can also facilitate learning processes, presumably through purposeful modulation of excitability in specific brain regions. rTMS has also been used to gain valuable knowledge regarding the timeline of motor memory formation, from initial encoding to stabilization and long-term retention. In this review, we summarize insights gained using rTMS on the physiological and neural mechanisms of human motor learning and memory. We conclude by suggesting possible future research directions, some with direct clinical implications.

Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks

Directory of Open Access Journals (Sweden)

Mohammad S. Islam

2017-01-01

Full Text Available Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation. This study explores using recorded deep brain local field potentials (LFPs for robust movement decoding of Parkinson’s disease (PD and Dystonia patients. The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes. Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands. An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality. The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks. The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier. The overall decoding performance reaches a level of agreement (kappa value at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.

Evolvable Neural Software System

Science.gov (United States)

Curtis, Steven A.

2009-01-01

The Evolvable Neural Software System (ENSS) is composed of sets of Neural Basis Functions (NBFs), which can be totally autonomously created and removed according to the changing needs and requirements of the software system. The resulting structure is both hierarchical and self-similar in that a given set of NBFs may have a ruler NBF, which in turn communicates with other sets of NBFs. These sets of NBFs may function as nodes to a ruler node, which are also NBF constructs. In this manner, the synthetic neural system can exhibit the complexity, three-dimensional connectivity, and adaptability of biological neural systems. An added advantage of ENSS over a natural neural system is its ability to modify its core genetic code in response to environmental changes as reflected in needs and requirements. The neural system is fully adaptive and evolvable and is trainable before release. It continues to rewire itself while on the job. The NBF is a unique, bilevel intelligence neural system composed of a higher-level heuristic neural system (HNS) and a lower-level, autonomic neural system (ANS). Taken together, the HNS and the ANS give each NBF the complete capabilities of a biological neural system to match sensory inputs to actions. Another feature of the NBF is the Evolvable Neural Interface (ENI), which links the HNS and ANS. The ENI solves the interface problem between these two systems by actively adapting and evolving from a primitive initial state (a Neural Thread) to a complicated, operational ENI and successfully adapting to a training sequence of sensory input. This simulates the adaptation of a biological neural system in a developmental phase. Within the greater multi-NBF and multi-node ENSS, self-similar ENI s provide the basis for inter-NBF and inter-node connectivity.

Genetic Modification of Human Pancreatic Progenitor Cells Through Modified mRNA.

Science.gov (United States)

Lu, Song; Chow, Christie C; Zhou, Junwei; Leung, Po Sing; Tsui, Stephen K; Lui, Kathy O

2016-01-01

In this chapter, we describe a highly efficient genetic modification strategy for human pancreatic progenitor cells using modified mRNA-encoding GFP and Neurogenin-3. The properties of modified mRNA offer an invaluable platform to drive protein expression, which has broad applicability in pathway regulation, directed differentiation, and lineage specification. This approach can also be used to regulate expression of other pivotal transcription factors during pancreas development and might have potential therapeutic values in regenerative medicine.

Neurally mediated airway constriction in human and other species: a comparative study using precision-cut lung slices (PCLS.

Directory of Open Access Journals (Sweden)

Marco Schlepütz

Full Text Available The peripheral airway innervation of the lower respiratory tract of mammals is not completely functionally characterized. Recently, we have shown in rats that precision-cut lung slices (PCLS respond to electric field stimulation (EFS and provide a useful model to study neural airway responses in distal airways. Since airway responses are known to exhibit considerable species differences, here we examined the neural responses of PCLS prepared from mice, rats, guinea pigs, sheep, marmosets and humans. Peripheral neurons were activated either by EFS or by capsaicin. Bronchoconstriction in response to identical EFS conditions varied between species in magnitude. Frequency response curves did reveal further species-dependent differences of nerve activation in PCLS. Atropine antagonized the EFS-induced bronchoconstriction in human, guinea pig, sheep, rat and marmoset PCLS, showing cholinergic responses. Capsaicin (10 µM caused bronchoconstriction in human (4 from 7 and guinea pig lungs only, indicating excitatory non-adrenergic non-cholinergic responses (eNANC. However, this effect was notably smaller in human responder (30 ± 7.1% than in guinea pig (79 ± 5.1% PCLS. The transient receptor potential (TRP channel blockers SKF96365 and ruthenium red antagonized airway contractions after exposure to EFS or capsaicin in guinea pigs. In conclusion, the different species show distinct patterns of nerve-mediated bronchoconstriction. In the most common experimental animals, i.e. in mice and rats, these responses differ considerably from those in humans. On the other hand, guinea pig and marmoset monkey mimic human responses well and may thus serve as clinically relevant models to study neural airway responses.

Xenotransplantation of human neural progenitor cells to the subretinal space of nonimmunosuppressed pigs

DEFF Research Database (Denmark)

Warfvinge, Karin; Schwartz, Philip H; Kiilgaard, Jens Folke

2011-01-01

To investigate the feasibility of transplanting human neural progenitor cells (hNPCs) to the retina of nonimmunosuppressed pigs, cultured hNPCs were injected into the subretinal space of 5 adult pigs after laser burns were applied to promote donor cell integration. Postoperatively, the retinal ve...... that modulation of host immunity is likely necessary for prolonged xenograft survival in this model....

An externally head-mounted wireless neural recording device for laboratory animal research and possible human clinical use.

Science.gov (United States)

Yin, Ming; Li, Hao; Bull, Christopher; Borton, David A; Aceros, Juan; Larson, Lawrence; Nurmikko, Arto V

2013-01-01

In this paper we present a new type of head-mounted wireless neural recording device in a highly compact package, dedicated for untethered laboratory animal research and designed for future mobile human clinical use. The device, which takes its input from an array of intracortical microelectrode arrays (MEA) has ninety-seven broadband parallel neural recording channels and was integrated on to two custom designed printed circuit boards. These house several low power, custom integrated circuits, including a preamplifier ASIC, a controller ASIC, plus two SAR ADCs, a 3-axis accelerometer, a 48MHz clock source, and a Manchester encoder. Another ultralow power RF chip supports an OOK transmitter with the center frequency tunable from 3GHz to 4GHz, mounted on a separate low loss dielectric board together with a 3V LDO, with output fed to a UWB chip antenna. The IC boards were interconnected and packaged in a polyether ether ketone (PEEK) enclosure which is compatible with both animal and human use (e.g. sterilizable). The entire system consumes 17mA from a 1.2Ahr 3.6V Li-SOCl2 1/2AA battery, which operates the device for more than 2 days. The overall system includes a custom RF receiver electronics which are designed to directly interface with any number of commercial (or custom) neural signal processors for multi-channel broadband neural recording. Bench-top measurements and in vivo testing of the device in rhesus macaques are presented to demonstrate the performance of the wireless neural interface.

BrainCrafter: An investigation into human-based neural network engineering

DEFF Research Database (Denmark)

Piskur, J.; Greve, P.; Togelius, J.

2015-01-01

This paper presents the online application Brain-Crafter, in which users can manually build artificial neural networks (ANNs) to control a robot in a maze environment. Users can either start to construct networks from scratch or elaborate on networks created by other users. In particular, Brain......Crafter was designed to study how good we as humans are at building ANNs for control problems and if collaborating with other users can facilitate this process. The results in this paper show that (1) some users were in fact able to successfully construct ANNs that solve the navigation tasks, (2) collaboration between...

Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

Science.gov (United States)

Patkin, M. L.; Rogachev, G. N.

2018-02-01

A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

Neural mechanisms underlying human consensus decision-making.

Science.gov (United States)

Suzuki, Shinsuke; Adachi, Ryo; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

2015-04-22

Consensus building in a group is a hallmark of animal societies, yet little is known about its underlying computational and neural mechanisms. Here, we applied a computational framework to behavioral and fMRI data from human participants performing a consensus decision-making task with up to five other participants. We found that participants reached consensus decisions through integrating their own preferences with information about the majority group members' prior choices, as well as inferences about how much each option was stuck to by the other people. These distinct decision variables were separately encoded in distinct brain areas-the ventromedial prefrontal cortex, posterior superior temporal sulcus/temporoparietal junction, and intraparietal sulcus-and were integrated in the dorsal anterior cingulate cortex. Our findings provide support for a theoretical account in which collective decisions are made through integrating multiple types of inference about oneself, others, and environments, processed in distinct brain modules. Copyright © 2015 Elsevier Inc. All rights reserved.

Nonstimulated human uncommitted mesenchymal stem cells express cell markers of mesenchymal and neural lineages.

Science.gov (United States)

Minguell, José J; Fierro, Fernando A; Epuñan, María J; Erices, Alejandro A; Sierralta, Walter D

2005-08-01

Ex vivo cultures of human bone marrow-derived mesenchymal stem cells (MSCs) contain subsets of progenitors exhibiting dissimilar properties. One of these subsets comprises uncommitted progenitors displaying distinctive features, such as morphology, a quiescent condition, growth factor production, and restricted tissue biodistribution after transplantation. In this study, we assessed the competence of these cells to express, in the absence of differentiation stimuli, markers of mesoderm and ectodermic (neural) cell lineages. Fluorescence microscopy analysis showed a unique pattern of expression of osteogenic, chondrogenic, muscle, and neural markers. The depicted "molecular signature" of these early uncommitted progenitors, in the absence of differentiation stimuli, is consistent with their multipotentiality and plasticity as suggested by several in vitro and in vivo studies.

Neural Conversion and Patterning of Human Pluripotent Stem Cells: A Developmental Perspective.

Science.gov (United States)

Zirra, Alexandra; Wiethoff, Sarah; Patani, Rickie

2016-01-01

Since the reprogramming of adult human terminally differentiated somatic cells into induced pluripotent stem cells (hiPSCs) became a reality in 2007, only eight years have passed. Yet over this relatively short period, myriad experiments have revolutionized previous stem cell dogmata. The tremendous promise of hiPSC technology for regenerative medicine has fuelled rising expectations from both the public and scientific communities alike. In order to effectively harness hiPSCs to uncover fundamental mechanisms of disease, it is imperative to first understand the developmental neurobiology underpinning their lineage restriction choices in order to predictably manipulate cell fate to desired derivatives. Significant progress in developmental biology provides an invaluable resource for rationalising directed differentiation of hiPSCs to cellular derivatives of the nervous system. In this paper we begin by reviewing core developmental concepts underlying neural induction in order to provide context for how such insights have guided reductionist in vitro models of neural conversion from hiPSCs. We then discuss early factors relevant in neural patterning, again drawing upon crucial knowledge gained from developmental neurobiological studies. We conclude by discussing open questions relating to these concepts and how their resolution might serve to strengthen the promise of pluripotent stem cells in regenerative medicine.

Neural Conversion and Patterning of Human Pluripotent Stem Cells: A Developmental Perspective

Directory of Open Access Journals (Sweden)

Alexandra Zirra

2016-01-01

Full Text Available Since the reprogramming of adult human terminally differentiated somatic cells into induced pluripotent stem cells (hiPSCs became a reality in 2007, only eight years have passed. Yet over this relatively short period, myriad experiments have revolutionized previous stem cell dogmata. The tremendous promise of hiPSC technology for regenerative medicine has fuelled rising expectations from both the public and scientific communities alike. In order to effectively harness hiPSCs to uncover fundamental mechanisms of disease, it is imperative to first understand the developmental neurobiology underpinning their lineage restriction choices in order to predictably manipulate cell fate to desired derivatives. Significant progress in developmental biology provides an invaluable resource for rationalising directed differentiation of hiPSCs to cellular derivatives of the nervous system. In this paper we begin by reviewing core developmental concepts underlying neural induction in order to provide context for how such insights have guided reductionist in vitro models of neural conversion from hiPSCs. We then discuss early factors relevant in neural patterning, again drawing upon crucial knowledge gained from developmental neurobiological studies. We conclude by discussing open questions relating to these concepts and how their resolution might serve to strengthen the promise of pluripotent stem cells in regenerative medicine.

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

Directory of Open Access Journals (Sweden)

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.

Lifelong learning of human actions with deep neural network self-organization.

Science.gov (United States)

Parisi, German I; Tani, Jun; Weber, Cornelius; Wermter, Stefan

2017-12-01

Lifelong learning is fundamental in autonomous robotics for the acquisition and fine-tuning of knowledge through experience. However, conventional deep neural models for action recognition from videos do not account for lifelong learning but rather learn a batch of training data with a predefined number of action classes and samples. Thus, there is the need to develop learning systems with the ability to incrementally process available perceptual cues and to adapt their responses over time. We propose a self-organizing neural architecture for incrementally learning to classify human actions from video sequences. The architecture comprises growing self-organizing networks equipped with recurrent neurons for processing time-varying patterns. We use a set of hierarchically arranged recurrent networks for the unsupervised learning of action representations with increasingly large spatiotemporal receptive fields. Lifelong learning is achieved in terms of prediction-driven neural dynamics in which the growth and the adaptation of the recurrent networks are driven by their capability to reconstruct temporally ordered input sequences. Experimental results on a classification task using two action benchmark datasets show that our model is competitive with state-of-the-art methods for batch learning also when a significant number of sample labels are missing or corrupted during training sessions. Additional experiments show the ability of our model to adapt to non-stationary input avoiding catastrophic interference. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Δ9-THC Disrupts Gamma (γ)-Band Neural Oscillations in Humans.

Science.gov (United States)

Cortes-Briones, Jose; Skosnik, Patrick D; Mathalon, Daniel; Cahill, John; Pittman, Brian; Williams, Ashley; Sewell, R Andrew; Ranganathan, Mohini; Roach, Brian; Ford, Judith; D'Souza, Deepak Cyril

2015-08-01

Gamma (γ)-band oscillations play a key role in perception, associative learning, and conscious awareness and have been shown to be disrupted by cannabinoids in animal studies. The goal of this study was to determine whether cannabinoids disrupt γ-oscillations in humans and whether these effects relate to their psychosis-relevant behavioral effects. The acute, dose-related effects of Δ-9-tetrahydrocannabinol (Δ(9)-THC) on the auditory steady-state response (ASSR) were studied in humans (n=20) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, 0.015, and 0.03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. Electroencephalography (EEG) was recorded while subjects listened to auditory click trains presented at 20, 30, and 40 Hz. Psychosis-relevant effects were measured with the Positive and Negative Syndrome scale (PANSS). Δ(9)-THC (0.03 mg/kg) reduced intertrial coherence (ITC) in the 40 Hz condition compared with 0.015 mg/kg and placebo. No significant effects were detected for 30 and 20 Hz stimulation. Furthermore, there was a negative correlation between 40 Hz ITC and PANSS subscales and total scores under the influence of Δ(9)-THC. Δ(9)-THC (0.03 mg/kg) reduced evoked power during 40 Hz stimulation at a trend level. Recent users of cannabis showed blunted Δ(9)-THC effects on ITC and evoked power. We show for the first time in humans that cannabinoids disrupt γ-band neural oscillations. Furthermore, there is a relationship between disruption of γ-band neural oscillations and psychosis-relevant phenomena induced by cannabinoids. These findings add to a growing literature suggesting some overlap between the acute effects of cannabinoids and the behavioral and psychophysiological alterations observed in psychotic disorders.

Generation of human cortical neurons from a new immortal fetal neural stem cell line

International Nuclear Information System (INIS)

Cacci, E.; Villa, A.; Parmar, M.; Cavallaro, M.; Mandahl, N.; Lindvall, O.; Martinez-Serrano, A.; Kokaia, Z.

2007-01-01

Isolation and expansion of neural stem cells (NSCs) of human origin are crucial for successful development of cell therapy approaches in neurodegenerative diseases. Different epigenetic and genetic immortalization strategies have been established for long-term maintenance and expansion of these cells in vitro. Here we report the generation of a new, clonal NSC (hc-NSC) line, derived from human fetal cortical tissue, based on v-myc immortalization. Using immunocytochemistry, we show that these cells retain the characteristics of NSCs after more than 50 passages. Under proliferation conditions, when supplemented with epidermal and basic fibroblast growth factors, the hc-NSCs expressed neural stem/progenitor cell markers like nestin, vimentin and Sox2. When growth factors were withdrawn, proliferation and expression of v-myc and telomerase were dramatically reduced, and the hc-NSCs differentiated into glia and neurons (mostly glutamatergic and GABAergic, as well as tyrosine hydroxylase-positive, presumably dopaminergic neurons). RT-PCR analysis showed that the hc-NSCs retained expression of Pax6, Emx2 and Neurogenin2, which are genes associated with regionalization and cell commitment in cortical precursors during brain development. Our data indicate that this hc-NSC line could be useful for exploring the potential of human NSCs to replace dead or damaged cortical cells in animal models of acute and chronic neurodegenerative diseases. Taking advantage of its clonality and homogeneity, this cell line will also be a valuable experimental tool to study the regulatory role of intrinsic and extrinsic factors in human NSC biology

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity.

Science.gov (United States)

Kafi, Md Abdul; Cho, Hyeon-Yeol; Choi, Jeong Woo

2015-07-02

Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD) or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C), C(RGD)₄ ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot) or three dimensional (rod or pillar) like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD), graphene oxide (GO) and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity

Directory of Open Access Journals (Sweden)

Md. Abdul Kafi

2015-07-01

Full Text Available Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C, C(RGD4 ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot or three dimensional (rod or pillar like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD, graphene oxide (GO and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies.

Natural forest regeneration and ecological restoration in human-modified tropical landscapes

NARCIS (Netherlands)

Martínez-Ramos, Miguel; Pingarroni, Aline; Rodríguez-Velázquez, Jorge; Toledo-Chelala, Lilibeth; Zermeño-Hernández, Isela; Bongers, Frans

2016-01-01

In human-modified tropical landscapes (HMLs) the conservation of biodiversity, functions and services of forest ecosystems depends on persistence of old growth forest remnants, forest regeneration in abandoned agricultural fields, and restoration of degraded lands. Understanding the impacts of

Modification of surface/neuron interfaces for neural cell-type specific responses: a review

International Nuclear Information System (INIS)

Chen, Cen; Kong, Xiangdong; Lee, In-Seop

2016-01-01

Surface/neuron interfaces have played an important role in neural repair including neural prostheses and tissue engineered scaffolds. This comprehensive literature review covers recent studies on the modification of surface/neuron interfaces. These interfaces are identified in cases both where the surfaces of substrates or scaffolds were in direct contact with cells and where the surfaces were modified to facilitate cell adhesion and controlling cell-type specific responses. Different sources of cells for neural repair are described, such as pheochromocytoma neuronal-like cell, neural stem cell (NSC), embryonic stem cell (ESC), mesenchymal stem cell (MSC) and induced pluripotent stem cell (iPS). Commonly modified methods are discussed including patterned surfaces at micro- or nano-scale, surface modification with conducting coatings, and functionalized surfaces with immobilized bioactive molecules. These approaches to control cell-type specific responses have enormous potential implications in neural repair. (paper)

A modified backpropagation algorithm for training neural networks on data with error bars

International Nuclear Information System (INIS)

Gernoth, K.A.; Clark, J.W.

1994-08-01

A method is proposed for training multilayer feedforward neural networks on data contaminated with noise. Specifically, we consider the case that the artificial neural system is required to learn a physical mapping when the available values of the target variable are subject to experimental uncertainties, but are characterized by error bars. The proposed method, based on maximum likelihood criterion for parameter estimation, involves simple modifications of the on-line backpropagation learning algorithm. These include incorporation of the error-bar assignments in a pattern-specific learning rate, together with epochal updating of a new measure of model accuracy that replaces the usual mean-square error. The extended backpropagation algorithm is successfully tested on two problems relevant to the modelling of atomic-mass systematics by neural networks. Provided the underlying mapping is reasonably smooth, neural nets trained with the new procedure are able to learn the true function to a good approximation even in the presence of high levels of Gaussian noise. (author). 26 refs, 2 figs, 5 tabs

Neural Determinants of Task Performance during Feature-Based Attention in Human Cortex

Science.gov (United States)

Gong, Mengyuan

2018-01-01

Abstract Studies of feature-based attention have associated activity in a dorsal frontoparietal network with putative attentional priority signals. Yet, how this neural activity mediates attentional selection and whether it guides behavior are fundamental questions that require investigation. We reasoned that endogenous fluctuations in the quality of attentional priority should influence task performance. Human subjects detected a speed increment while viewing clockwise (CW) or counterclockwise (CCW) motion (baseline task) or while attending to either direction amid distracters (attention task). In an fMRI experiment, direction-specific neural pattern similarity between the baseline task and the attention task revealed a higher level of similarity for correct than incorrect trials in frontoparietal regions. Using transcranial magnetic stimulation (TMS), we disrupted posterior parietal cortex (PPC) and found a selective deficit in the attention task, but not in the baseline task, demonstrating the necessity of this cortical area during feature-based attention. These results reveal that frontoparietal areas maintain attentional priority that facilitates successful behavioral selection. PMID:29497703

Emotional expectations influence neural sensitivity to fearful faces in humans:An event-related potential study

Institute of Scientific and Technical Information of China (English)

无

2010-01-01

The present study tested whether neural sensitivity to salient emotional facial expressions was influenced by emotional expectations induced by a cue that validly predicted the expression of a subsequently presented target face. Event-related potentials (ERPs) elicited by fearful and neutral faces were recorded while participants performed a gender discrimination task under cued (‘expected’) and uncued (‘unexpected’) conditions. The behavioral results revealed that accuracy was lower for fearful compared with neutral faces in the unexpected condition, while accuracy was similar for fearful and neutral faces in the expected condition. ERP data revealed increased amplitudes in the P2 component and 200–250 ms interval for unexpected fearful versus neutral faces. By contrast, ERP responses were similar for fearful and neutral faces in the expected condition. These findings indicate that human neural sensitivity to fearful faces is modulated by emotional expectations. Although the neural system is sensitive to unpredictable emotionally salient stimuli, sensitivity to salient stimuli is reduced when these stimuli are predictable.

Neural patterning of human induced pluripotent stem cells in 3-D cultures for studying biomolecule-directed differential cellular responses.

Science.gov (United States)

Yan, Yuanwei; Bejoy, Julie; Xia, Junfei; Guan, Jingjiao; Zhou, Yi; Li, Yan

2016-09-15

Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune

Absence of visual experience modifies the neural basis of numerical thinking.

Science.gov (United States)

Kanjlia, Shipra; Lane, Connor; Feigenson, Lisa; Bedny, Marina

2016-10-04

In humans, the ability to reason about mathematical quantities depends on a frontoparietal network that includes the intraparietal sulcus (IPS). How do nature and nurture give rise to the neurobiology of numerical cognition? We asked how visual experience shapes the neural basis of numerical thinking by studying numerical cognition in congenitally blind individuals. Blind (n = 17) and blindfolded sighted (n = 19) participants solved math equations that varied in difficulty (e.g., 27 - 12 = x vs. 7 - 2 = x), and performed a control sentence comprehension task while undergoing fMRI. Whole-cortex analyses revealed that in both blind and sighted participants, the IPS and dorsolateral prefrontal cortices were more active during the math task than the language task, and activity in the IPS increased parametrically with equation difficulty. Thus, the classic frontoparietal number network is preserved in the total absence of visual experience. However, surprisingly, blind but not sighted individuals additionally recruited a subset of early visual areas during symbolic math calculation. The functional profile of these "visual" regions was identical to that of the IPS in blind but not sighted individuals. Furthermore, in blindness, number-responsive visual cortices exhibited increased functional connectivity with prefrontal and IPS regions that process numbers. We conclude that the frontoparietal number network develops independently of visual experience. In blindness, this number network colonizes parts of deafferented visual cortex. These results suggest that human cortex is highly functionally flexible early in life, and point to frontoparietal input as a mechanism of cross-modal plasticity in blindness.

Are Protected Areas Required to Maintain Functional Diversity in Human-Modified Landscapes?

Science.gov (United States)

Cottee-Jones, H. Eden W.; Matthews, Thomas J.; Bregman, Tom P.; Barua, Maan; Tamuly, Jatin; Whittaker, Robert J.

2015-01-01

The conversion of forest to agriculture across the world’s tropics, and the limited space for protected areas, has increased the need to identify effective conservation strategies in human-modified landscapes. Isolated trees are believed to conserve elements of ecological structure, providing micro-sites for conservation in matrix landscapes, and facilitating seed dispersal and forest restoration. Here we investigate the role of isolated Ficus trees, which are of critical importance to tropical forest ecosystems, in conserving frugivore composition and function in a human-modified landscape in Assam, India. We surveyed the frugivorous birds feeding at 122 isolated Ficus trees, 33 fruit trees, and 31 other large trees across a range of 32 km from the nearest intact forest. We found that Ficus trees attracted richer and more abundant assemblages of frugivores than the other tree categories. However, incidence function estimates revealed that forest specialist species decreased dramatically within the first kilometre of the forest edge. Despite this, species richness and functional diversity remained consistent across the human-modified landscape, as habitat generalists replaced forest-dependent frugivores, and accounted for most of the ecological function found in Ficus trees near the forest edge. We recommend that isolated Ficus trees are awarded greater conservation status, and suggest that their conservation can support ecologically functional networks of frugivorous bird communities. PMID:25946032

Invariant recognition drives neural representations of action sequences.

Directory of Open Access Journals (Sweden)

Andrea Tacchetti

2017-12-01

Full Text Available Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs, that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences.

Discrete Orthogonal Transforms and Neural Networks for Image Interpolation

Directory of Open Access Journals (Sweden)

J. Polec

1999-09-01

Full Text Available In this contribution we present transform and neural network approaches to the interpolation of images. From transform point of view, the principles from [1] are modified for 1st and 2nd order interpolation. We present several new interpolation discrete orthogonal transforms. From neural network point of view, we present interpolation possibilities of multilayer perceptrons. We use various configurations of neural networks for 1st and 2nd order interpolation. The results are compared by means of tables.

Purification of human induced pluripotent stem cell-derived neural precursors using magnetic activated cell sorting.

Science.gov (United States)

Rodrigues, Gonçalo M C; Fernandes, Tiago G; Rodrigues, Carlos A V; Cabral, Joaquim M S; Diogo, Maria Margarida

2015-01-01

Neural precursor (NP) cells derived from human induced pluripotent stem cells (hiPSCs), and their neuronal progeny, will play an important role in disease modeling, drug screening tests, central nervous system development studies, and may even become valuable for regenerative medicine treatments. Nonetheless, it is challenging to obtain homogeneous and synchronously differentiated NP populations from hiPSCs, and after neural commitment many pluripotent stem cells remain in the differentiated cultures. Here, we describe an efficient and simple protocol to differentiate hiPSC-derived NPs in 12 days, and we include a final purification stage where Tra-1-60+ pluripotent stem cells (PSCs) are removed using magnetic activated cell sorting (MACS), leaving the NP population nearly free of PSCs.

A recurrent neural network based on projection operator for extended general variational inequalities.

Science.gov (United States)

Liu, Qingshan; Cao, Jinde

2010-06-01

Based on the projection operator, a recurrent neural network is proposed for solving extended general variational inequalities (EGVIs). Sufficient conditions are provided to ensure the global convergence of the proposed neural network based on Lyapunov methods. Compared with the existing neural networks for variational inequalities, the proposed neural network is a modified version of the general projection neural network existing in the literature and capable of solving the EGVI problems. In addition, simulation results on numerical examples show the effectiveness and performance of the proposed neural network.

Critical Branching Neural Networks

Science.gov (United States)

Kello, Christopher T.

2013-01-01

It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical…

Non-invasive neural stimulation

Science.gov (United States)

Tyler, William J.; Sanguinetti, Joseph L.; Fini, Maria; Hool, Nicholas

2017-05-01

Neurotechnologies for non-invasively interfacing with neural circuits have been evolving from those capable of sensing neural activity to those capable of restoring and enhancing human brain function. Generally referred to as non-invasive neural stimulation (NINS) methods, these neuromodulation approaches rely on electrical, magnetic, photonic, and acoustic or ultrasonic energy to influence nervous system activity, brain function, and behavior. Evidence that has been surmounting for decades shows that advanced neural engineering of NINS technologies will indeed transform the way humans treat diseases, interact with information, communicate, and learn. The physics underlying the ability of various NINS methods to modulate nervous system activity can be quite different from one another depending on the energy modality used as we briefly discuss. For members of commercial and defense industry sectors that have not traditionally engaged in neuroscience research and development, the science, engineering and technology required to advance NINS methods beyond the state-of-the-art presents tremendous opportunities. Within the past few years alone there have been large increases in global investments made by federal agencies, foundations, private investors and multinational corporations to develop advanced applications of NINS technologies. Driven by these efforts NINS methods and devices have recently been introduced to mass markets via the consumer electronics industry. Further, NINS continues to be explored in a growing number of defense applications focused on enhancing human dimensions. The present paper provides a brief introduction to the field of non-invasive neural stimulation by highlighting some of the more common methods in use or under current development today.

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.

Science.gov (United States)

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.

Imaging of human differentiated 3D neural aggregates using light sheet fluorescence microscopy

Science.gov (United States)

Gualda, Emilio J.; Simão, Daniel; Pinto, Catarina; Alves, Paula M.; Brito, Catarina

2014-01-01

The development of three dimensional (3D) cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex 3D matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy (LSFM) is becoming an excellent tool for fast imaging of such 3D biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment. PMID:25161607

Imaging of human differentiated 3D neural aggregates using light sheet fluorescence microscopy

Directory of Open Access Journals (Sweden)

Emilio J Gualda

2014-08-01

Full Text Available The development of three dimensional cell cultures represents a big step for the better understanding of cell behavior and disease in a more natural like environment, providing not only single but multiple cell type interactions in a complex three dimensional matrix, highly resembling physiological conditions. Light sheet fluorescence microscopy is becoming an excellent tool for fast imaging of such three-dimensional biological structures. We demonstrate the potential of this technique for the imaging of human differentiated 3D neural aggregates in fixed and live samples, namely calcium imaging and cell death processes, showing the power of imaging modality compared with traditional microscopy. The combination of light sheet microscopy and 3D neural cultures will open the door to more challenging experiments involving drug testing at large scale as well as a better understanding of relevant biological processes in a more realistic environment.

Shades of grey; Assessing the contribution of the magno- and parvocellular systems to neural processing of the retinal input in the human visual system from the influence of neural population size and its discharge activity on the VEP.

Science.gov (United States)

Marcar, Valentine L; Baselgia, Silvana; Lüthi-Eisenegger, Barbara; Jäncke, Lutz

2018-03-01

Retinal input processing in the human visual system involves a phasic and tonic neural response. We investigated the role of the magno- and parvocellular systems by comparing the influence of the active neural population size and its discharge activity on the amplitude and latency of four VEP components. We recorded the scalp electric potential of 20 human volunteers viewing a series of dartboard images presented as a pattern reversing and pattern on-/offset stimulus. These patterns were designed to vary both neural population size coding the temporal- and spatial luminance contrast property and the discharge activity of the population involved in a systematic manner. When the VEP amplitude reflected the size of the neural population coding the temporal luminance contrast property of the image, the influence of luminance contrast followed the contrast response function of the parvocellular system. When the VEP amplitude reflected the size of the neural population responding to the spatial luminance contrast property the image, the influence of luminance contrast followed the contrast response function of the magnocellular system. The latencies of the VEP components examined exhibited the same behavior across our stimulus series. This investigation demonstrates the complex interplay of the magno- and parvocellular systems on the neural response as captured by the VEP. It also demonstrates a linear relationship between stimulus property, neural response, and the VEP and reveals the importance of feedback projections in modulating the ongoing neural response. In doing so, it corroborates the conclusions of our previous study.

What is adapted in face adaptation? The neural representations of expression in the human visual system.

Science.gov (United States)

Fox, Christopher J; Barton, Jason J S

2007-01-05

The neural representation of facial expression within the human visual system is not well defined. Using an adaptation paradigm, we examined aftereffects on expression perception produced by various stimuli. Adapting to a face, which was used to create morphs between two expressions, substantially biased expression perception within the morphed faces away from the adapting expression. This adaptation was not based on low-level image properties, as a different image of the same person displaying that expression produced equally robust aftereffects. Smaller but significant aftereffects were generated by images of different individuals, irrespective of gender. Non-face visual, auditory, or verbal representations of emotion did not generate significant aftereffects. These results suggest that adaptation affects at least two neural representations of expression: one specific to the individual (not the image), and one that represents expression across different facial identities. The identity-independent aftereffect suggests the existence of a 'visual semantic' for facial expression in the human visual system.

Gene regulation in adult neural stem cells : Current challenges and possible applications

NARCIS (Netherlands)

Encinas, J.M.; Fitzsimons, C.P.

2017-01-01

Adult neural stem and progenitor cells (NSPCs) offer a unique opportunity for neural regeneration and niche modification in physiopathological conditions, harnessing the capability to modify from neuronal circuits to glial scar. Findings exposing the vast plasticity and potential of NSPCs have

Human Face Recognition Using Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Răzvan-Daniel Albu

2009-10-01

Full Text Available In this paper, I present a novel hybrid face recognition approach based on a convolutional neural architecture, designed to robustly detect highly variable face patterns. The convolutional network extracts successively larger features in a hierarchical set of layers. With the weights of the trained neural networks there are created kernel windows used for feature extraction in a 3-stage algorithm. I present experimental results illustrating the efficiency of the proposed approach. I use a database of 796 images of 159 individuals from Reims University which contains quite a high degree of variability in expression, pose, and facial details.

Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

Science.gov (United States)

Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

2018-01-01

This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

Drive Control Scheme of Electric Power Assisted Wheelchair Based on Neural Network Learning of Human Wheelchair Operation Characteristics

Science.gov (United States)

Tanohata, Naoki; Seki, Hirokazu

This paper describes a novel drive control scheme of electric power assisted wheelchairs based on neural network learning of human wheelchair operation characteristics. “Electric power assisted wheelchair” which enhances the drive force of the operator by employing electric motors is expected to be widely used as a mobility support system for elderly and disabled people. However, some handicapped people with paralysis of the muscles of one side of the body cannot maneuver the wheelchair as desired because of the difference in the right and left input force. Therefore, this study proposes a neural network learning system of such human wheelchair operation characteristics and a drive control scheme with variable distribution and assistance ratios. Some driving experiments will be performed to confirm the effectiveness of the proposed control system.

Neural codes of seeing architectural styles.

Science.gov (United States)

Choo, Heeyoung; Nasar, Jack L; Nikrahei, Bardia; Walther, Dirk B

2017-01-10

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people's visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture.

Alternative splicing events identified in human embryonic stem cells and neural progenitors.

Directory of Open Access Journals (Sweden)

Gene W Yeo

2007-10-01

Full Text Available Human embryonic stem cells (hESCs and neural progenitor (NP cells are excellent models for recapitulating early neuronal development in vitro, and are key to establishing strategies for the treatment of degenerative disorders. While much effort had been undertaken to analyze transcriptional and epigenetic differences during the transition of hESC to NP, very little work has been performed to understand post-transcriptional changes during neuronal differentiation. Alternative RNA splicing (AS, a major form of post-transcriptional gene regulation, is important in mammalian development and neuronal function. Human ESC, hESC-derived NP, and human central nervous system stem cells were compared using Affymetrix exon arrays. We introduced an outlier detection approach, REAP (Regression-based Exon Array Protocol, to identify 1,737 internal exons that are predicted to undergo AS in NP compared to hESC. Experimental validation of REAP-predicted AS events indicated a threshold-dependent sensitivity ranging from 56% to 69%, at a specificity of 77% to 96%. REAP predictions significantly overlapped sets of alternative events identified using expressed sequence tags and evolutionarily conserved AS events. Our results also reveal that focusing on differentially expressed genes between hESC and NP will overlook 14% of potential AS genes. In addition, we found that REAP predictions are enriched in genes encoding serine/threonine kinase and helicase activities. An example is a REAP-predicted alternative exon in the SLK (serine/threonine kinase 2 gene that is differentially included in hESC, but skipped in NP as well as in other differentiated tissues. Lastly, comparative sequence analysis revealed conserved intronic cis-regulatory elements such as the FOX1/2 binding site GCAUG as being proximal to candidate AS exons, suggesting that FOX1/2 may participate in the regulation of AS in NP and hESC. In summary, a new methodology for exon array analysis was introduced

DEVELOPMENT OF WEARABLE HUMAN FALL DETECTION SYSTEM USING MULTILAYER PERCEPTRON NEURAL NETWORK

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Hamideh Kerdegari

2013-02-01

Full Text Available This paper presents an accurate wearable fall detection system which can identify the occurrence of falls among elderly population. A waist worn tri-axial accelerometer was used to capture the movement signals of human body. A set of laboratory-based falls and activities of daily living (ADL were performed by volunteers with different physical characteristics. The collected acceleration patterns were classified precisely to fall and ADL using multilayer perceptron (MLP neural network. This work was resulted to a high accuracy wearable fall-detection system with the accuracy of 91.6%.

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

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Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Laminin enhances the growth of human neural stem cells in defined culture media

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Lathia Justin D

2008-07-01

Full Text Available Abstract Background Human neural stem cells (hNSC have the potential to provide novel cell-based therapies for neurodegenerative conditions such as multiple sclerosis and Parkinson's disease. In order to realise this goal, protocols need to be developed that allow for large quantities of hNSC to be cultured efficiently. As such, it is important to identify factors which enhance the growth of hNSC. In vivo, stem cells reside in distinct microenvironments or niches that are responsible for the maintenance of stem cell populations. A common feature of niches is the presence of the extracellular matrix molecule, laminin. Therefore, this study investigated the effect of exogenous laminin on hNSC growth. Results To measure hNSC growth, we established culture conditions using B27-supplemented medium that enable neurospheres to grow from human neural cells plated at clonal densities. Limiting dilution assays confirmed that neurospheres were derived from single cells at these densities. Laminin was found to increase hNSC numbers as measured by this neurosphere formation. The effect of laminin was to augment the proliferation/survival of the hNSC, rather than promoting the undifferentiated state. In agreement, apoptosis was reduced in dissociated neurospheres by laminin in an integrin β1-dependent manner. Conclusion The addition of laminin to the culture medium enhances the growth of hNSC, and may therefore aid their large-scale production.

Induction of Skin-Derived Precursor Cells from Human Induced Pluripotent Stem Cells.

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Sugiyama-Nakagiri, Yoriko; Fujimura, Tsutomu; Moriwaki, Shigeru

2016-01-01

The generation of full thickness human skin from dissociated cells is an attractive approach not only for treating skin diseases, but also for treating many systemic disorders. However, it is currently not possible to obtain an unlimited number of skin dermal cells. The goal of this study was to develop a procedure to produce skin dermal stem cells from induced pluripotent stem cells (iPSCs). Skin-derived precursor cells (SKPs) were isolated as adult dermal precursors that could differentiate into both neural and mesodermal progenies and could reconstitute the dermis. Thus, we attempted to generate SKPs from iPSCs that could reconstitute the skin dermis. Human iPSCs were initially cultured with recombinant noggin and SB431542, an inhibitor of activin/nodal and TGFβ signaling, to induce neural crest progenitor cells. Those cells were then treated with SKP medium that included CHIR99021, a WNT signal activator. The induction efficacy from neural crest progenitor cells to SKPs was more than 97%. No other modifiers tested were able to induce those cells. Those human iPSC-derived SKPs (hiPSC-SKPs) showed a similar gene expression signature to SKPs isolated from human skin dermis. Human iPSC-SKPs differentiated into neural and mesodermal progenies, including adipocytes, skeletogenic cell types and Schwann cells. Moreover, they could be induced to follicular type keratinization when co-cultured with human epidermal keratinocytes. We here provide a new efficient protocol to create human skin dermal stem cells from hiPSCs that could contribute to the treatment of various skin disorders.

Genetically modified plants and human health.

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Key, Suzie; Ma, Julian K-C; Drake, Pascal Mw

2008-06-01

Genetically modified (or GM) plants have attracted a large amount of media attention in recent years and continue to do so. Despite this, the general public remains largely unaware of what a GM plant actually is or what advantages and disadvantages the technology has to offer, particularly with regard to the range of applications for which they can be used. From the first generation of GM crops, two main areas of concern have emerged, namely risk to the environment and risk to human health. As GM plants are gradually being introduced into the European Union there is likely to be increasing public concern regarding potential health issues. Although it is now commonplace for the press to adopt 'health campaigns', the information they publish is often unreliable and unrepresentative of the available scientific evidence. We consider it important that the medical profession should be aware of the state of the art, and, as they are often the first port of call for a concerned patient, be in a position to provide an informed opinion. This review will examine how GM plants may impact on human health both directly - through applications targeted at nutrition and enhancement of recombinant medicine production - but also indirectly, through potential effects on the environment. Finally, it will examine the most important opposition currently facing the worldwide adoption of this technology: public opinion.

Neural crest cells: from developmental biology to clinical interventions.

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Noisa, Parinya; Raivio, Taneli

2014-09-01

Neural crest cells are multipotent cells, which are specified in embryonic ectoderm in the border of neural plate and epiderm during early development by interconnection of extrinsic stimuli and intrinsic factors. Neural crest cells are capable of differentiating into various somatic cell types, including melanocytes, craniofacial cartilage and bone, smooth muscle, and peripheral nervous cells, which supports their promise for cell therapy. In this work, we provide a comprehensive review of wide aspects of neural crest cells from their developmental biology to applicability in medical research. We provide a simplified model of neural crest cell development and highlight the key external stimuli and intrinsic regulators that determine the neural crest cell fate. Defects of neural crest cell development leading to several human disorders are also mentioned, with the emphasis of using human induced pluripotent stem cells to model neurocristopathic syndromes. © 2014 Wiley Periodicals, Inc.

Use of Traditional and Genetically Modified Probiotics in Human Health: What Does the Future Hold?

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Bermúdez-Humarán, Luis G; Langella, Philippe

2017-09-01

Probiotics are live, nonpathogenic microorganisms that confer benefits to human health when administered in adequate amounts. Among the frequent proposed health benefits attributed to probiotics, their ability to interact with the host immune system is now well demonstrated. Although history has revealed that probiotics were part of fermented foods in the past, clinicians have started to use them therapeutically in regular diets. Moreover, the use of genetically modified probiotics to deliver molecules of therapeutic interest is gaining importance as an extension of the probiotic concept. This chapter summarizes some of the recent findings and perspectives on the use of both traditional and genetically modified probiotics to treat human diseases as well as what the future may hold concerning the use of these probiotics in humans.

Transplantation dose alters the dynamics of human neural stem cell engraftment, proliferation and migration after spinal cord injury

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Katja M. Piltti

2015-09-01

Full Text Available The effect of transplantation dose on the spatiotemporal dynamics of human neural stem cell (hNSC engraftment has not been quantitatively evaluated in the central nervous system. We investigated changes over time in engraftment/survival, proliferation, and migration of multipotent human central nervous system-derived neural stem cells (hCNS-SCns transplanted at doses ranging from 10,000 to 500,000 cells in spinal cord injured immunodeficient mice. Transplant dose was inversely correlated with measures of donor cell proliferation at 2 weeks post-transplant (WPT and dose-normalized engraftment at 16 WPT. Critically, mice receiving the highest cell dose exhibited an engraftment plateau, in which the total number of engrafted human cells never exceeded the initial dose. These data suggest that donor cell expansion was inversely regulated by target niche parameters and/or transplantation density. Investigation of the response of donor cells to the host microenvironment should be a key variable in defining target cell dose in pre-clinical models of CNS disease and injury.

Dual small-molecule targeting of SMAD signaling stimulates human induced pluripotent stem cells toward neural lineages.

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Methichit Wattanapanitch

Full Text Available Incurable neurological disorders such as Parkinson's disease (PD, Huntington's disease (HD, and Alzheimer's disease (AD are very common and can be life-threatening because of their progressive disease symptoms with limited treatment options. To provide an alternative renewable cell source for cell-based transplantation and as study models for neurological diseases, we generated induced pluripotent stem cells (iPSCs from human dermal fibroblasts (HDFs and then differentiated them into neural progenitor cells (NPCs and mature neurons by dual SMAD signaling inhibitors. Reprogramming efficiency was improved by supplementing the histone deacethylase inhibitor, valproic acid (VPA, and inhibitor of p160-Rho associated coiled-coil kinase (ROCK, Y-27632, after retroviral transduction. We obtained a number of iPS colonies that shared similar characteristics with human embryonic stem cells in terms of their morphology, cell surface antigens, pluripotency-associated gene and protein expressions as well as their in vitro and in vivo differentiation potentials. After treatment with Noggin and SB431542, inhibitors of the SMAD signaling pathway, HDF-iPSCs demonstrated rapid and efficient differentiation into neural lineages. Six days after neural induction, neuroepithelial cells (NEPCs were observed in the adherent monolayer culture, which had the ability to differentiate further into NPCs and neurons, as characterized by their morphology and the expression of neuron-specific transcripts and proteins. We propose that our study may be applied to generate neurological disease patient-specific iPSCs allowing better understanding of disease pathogenesis and drug sensitivity assays.

Effects of modified detonation nanodiamonds on the biochemical composition of human blood.

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Baron, A V; Puzyr, A P; Baron, I I; Bondar, V S

2013-04-01

In vitro experiments showed that protein and non-protein components of human blood serum could be absorbed on the surface of modified nanodiamonds obtained by detonation synthesis. The prospects of using nanodiamond as a new absorbent for hemodialysis, plasmapheresis, and laboratory diagnostics are discussed.

Differential expression of the neural cell adhesion molecule NCAM 140 in human pituitary tumors

OpenAIRE

Aletsee-Ufrecht, M. C.; Langley, O. K.; Gratzl, O.; Gratzl, Manfred

1990-01-01

We have analyzed the expression of the intracellular marker protein neuron specific enolase (NSE), synaptophysin (SYN) and of the cell surface marker NCAM (neural cell adhesion molecule) in both normal human hypophysis and in pituitary adenomas in order to explore their potential use as diagnostic tools. All adenomas (4 prolactinomas, 3 growth hormone (GH) producing adenomas and 4 inactive adenomas) showed SYN and NSE immunoreactivity on tissue sections and this was confirmed by immunoblots. ...

Proteolytically modified human beta 2-microglobulin augments the specific cytotoxic activity in murine mixed lymphocyte culture

DEFF Research Database (Denmark)

Nissen, Mogens Holst; Claësson, M H

1987-01-01

the endogenous production of interleukin 2 in the MLC culture; monoclonal antibody which reacts with both the native beta 2-m and M-beta 2-m molecule blocks the augmentation of cytotoxic T lymphocyte production induced by M-beta 2-m; murine as well as human MLC responder cells can proteolytically modify native......A proteolytically modified form of beta 2-microglobulin (beta 2-m) present in the serum of patients suffering from autoimmune, immunodeficient diseases and cancer has been reported in the literature. In the present study we show that human beta 2-m as well as the proteolytically modified human form...... (M-beta 2-m) bind to murine lymphocytes expressing H-2 class I antigens; M-beta 2-m, when added at day 0 and 1 of culture in nanomolar concentrations to a one-way murine allogeneic mixed lymphocyte culture (MLC) augments the generation of specific cytotoxic T lymphocytes; M-beta 2-m increases...

Human neural progenitors derived from integration-free iPSCs for SCI therapy

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Ying Liu

2017-03-01

Full Text Available As a potentially unlimited autologous cell source, patient induced pluripotent stem cells (iPSCs provide great capability for tissue regeneration, particularly in spinal cord injury (SCI. However, despite significant progress made in translation of iPSC-derived neural progenitor cells (NPCs to clinical settings, a few hurdles remain. Among them, non-invasive approach to obtain source cells in a timely manner, safer integration-free delivery of reprogramming factors, and purification of NPCs before transplantation are top priorities to overcome. In this study, we developed a safe and cost-effective pipeline to generate clinically relevant NPCs. We first isolated cells from patients' urine and reprogrammed them into iPSCs by non-integrating Sendai viral vectors, and carried out experiments on neural differentiation. NPCs were purified by A2B5, an antibody specifically recognizing a glycoganglioside on the cell surface of neural lineage cells, via fluorescence activated cell sorting. Upon further in vitro induction, NPCs were able to give rise to neurons, oligodendrocytes and astrocytes. To test the functionality of the A2B5+ NPCs, we grafted them into the contused mouse thoracic spinal cord. Eight weeks after transplantation, the grafted cells survived, integrated into the injured spinal cord, and differentiated into neurons and glia. Our specific focus on cell source, reprogramming, differentiation and purification method purposely addresses timing and safety issues of transplantation to SCI models. It is our belief that this work takes one step closer on using human iPSC derivatives to SCI clinical settings.

Prototype-Incorporated Emotional Neural Network.

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Oyedotun, Oyebade K; Khashman, Adnan

2017-08-15

Artificial neural networks (ANNs) aim to simulate the biological neural activities. Interestingly, many ''engineering'' prospects in ANN have relied on motivations from cognition and psychology studies. So far, two important learning theories that have been subject of active research are the prototype and adaptive learning theories. The learning rules employed for ANNs can be related to adaptive learning theory, where several examples of the different classes in a task are supplied to the network for adjusting internal parameters. Conversely, the prototype-learning theory uses prototypes (representative examples); usually, one prototype per class of the different classes contained in the task. These prototypes are supplied for systematic matching with new examples so that class association can be achieved. In this paper, we propose and implement a novel neural network algorithm based on modifying the emotional neural network (EmNN) model to unify the prototype- and adaptive-learning theories. We refer to our new model as ``prototype-incorporated EmNN''. Furthermore, we apply the proposed model to two real-life challenging tasks, namely, static hand-gesture recognition and face recognition, and compare the result to those obtained using the popular back-propagation neural network (BPNN), emotional BPNN (EmNN), deep networks, an exemplar classification model, and k-nearest neighbor.

Neural computing thermal comfort index for HVAC systems

International Nuclear Information System (INIS)

Atthajariyakul, S.; Leephakpreeda, T.

2005-01-01

The primary purpose of a heating, ventilating and air conditioning (HVAC) system within a building is to make occupants comfortable. Without real time determination of human thermal comfort, it is not feasible for the HVAC system to yield controlled conditions of the air for human comfort all the time. This paper presents a practical approach to determine human thermal comfort quantitatively via neural computing. The neural network model allows real time determination of the thermal comfort index, where it is not practical to compute the conventional predicted mean vote (PMV) index itself in real time. The feed forward neural network model is proposed as an explicit function of the relation of the PMV index to accessible variables, i.e. the air temperature, wet bulb temperature, globe temperature, air velocity, clothing insulation and human activity. An experiment in an air conditioned office room was done to demonstrate the effectiveness of the proposed methodology. The results show good agreement between the thermal comfort index calculated from the neural network model in real time and those calculated from the conventional PMV model

Human Episodic Memory Retrieval Is Accompanied by a Neural Contiguity Effect.

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Folkerts, Sarah; Rutishauser, Ueli; Howard, Marc W

2018-04-25

Cognitive psychologists have long hypothesized that experiences are encoded in a temporal context that changes gradually over time. When an episodic memory is retrieved, the state of context is recovered-a jump back in time. We recorded from single units in the medial temporal lobe of epilepsy patients performing an item recognition task. The population vector changed gradually over minutes during presentation of the list. When a probe from the list was remembered with high confidence, the population vector reinstated the temporal context of the original presentation of that probe during study, a neural contiguity effect that provides a possible mechanism for behavioral contiguity effects. This pattern was only observed for well remembered probes; old probes that were not well remembered showed an anti-contiguity effect. These results constitute the first direct evidence that recovery of an episodic memory in humans is associated with retrieval of a gradually changing state of temporal context, a neural "jump back in time" that parallels the act of remembering. SIGNIFICANCE STATEMENT Episodic memory is the ability to relive a specific experience from one's life. For decades, researchers have hypothesized that, unlike other forms of memory that can be described as simple associations between stimuli, episodic memory depends on the recovery of a neural representation of spatiotemporal context. During study of a sequence of stimuli, the brain state of epilepsy patients changed slowly over at least a minute. When the participant remembered a particular event from the list, this gradually changing state was recovered. This provides direct confirmation of the prediction from computational models of episodic memory. The resolution of this point means that the study of episodic memory can focus on the mechanisms by which this representation of spatiotemporal context is maintained and sometimes recovered. Copyright © 2018 the authors 0270-6474/18/384200-12$15.00/0.

Generation of Regionally Specific Neural Progenitor Cells (NPCs) and Neurons from Human Pluripotent Stem Cells (hPSCs).

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Cutts, Josh; Brookhouser, Nicholas; Brafman, David A

2016-01-01

Neural progenitor cells (NPCs) derived from human pluripotent stem cells (hPSCs) are a multipotent cell population capable of long-term expansion and differentiation into a variety of neuronal subtypes. As such, NPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine. Current methods for the generation of NPCs results in cell populations homogenous for pan-neural markers such as SOX1 and SOX2 but heterogeneous with respect to regional identity. In order to use NPCs and their neuronal derivatives to investigate mechanisms of neurological disorders and develop more physiologically relevant disease models, methods for generation of regionally specific NPCs and neurons are needed. Here, we describe a protocol in which exogenous manipulation of WNT signaling, through either activation or inhibition, during neural differentiation of hPSCs, promotes the formation of regionally homogenous NPCs and neuronal cultures. In addition, we provide methods to monitor and characterize the efficiency of hPSC differentiation to these regionally specific cell identities.

Effects of light emitting diode irradiation on neural differentiation of human umbilical cord-derived mesenchymal cells.

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Dehghani-Soltani, Samereh; Shojaee, Mohammad; Jalalkamali, Mahshid; Babaee, Abdolreza; Nematollahi-Mahani, Seyed Noureddin

2017-08-30

Recently, light emitting diodes (LEDs) have been introduced as a potential physical factor for proliferation and differentiation of various stem cells. Among the mesenchymal stem cells human umbilical cord matrix-derived mesenchymal (hUCM) cells are easily propagated in the laboratory and their low immunogenicity make them more appropriate for regenerative medicine procedures. We aimed at this study to evaluate the effect of red and green light emitted from LED on the neural lineage differentiation of hUCM cells in the presence or absence of retinoic acid (RA). Harvested hUCM cells exhibited mesenchymal and stemness properties. Irradiation of these cells by green and red LED with or without RA pre-treatment successfully differentiated them into neural lineage when the morphology of the induced cells, gene expression pattern (nestin, β-tubulin III and Olig2) and protein synthesis (anti-nestin, anti-β-tubulin III, anti-GFAP and anti-O4 antibodies) was evaluated. These data point for the first time to the fact that LED irradiation and optogenetic technology may be applied for neural differentiation and neuronal repair in regenerative medicine.

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

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Ross, Muriel D.

1991-01-01

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

γ-Secretase modulators reduce endogenous amyloid β42 levels in human neural progenitor cells without altering neuronal differentiation

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D’Avanzo, Carla; Sliwinski, Christopher; Wagner, Steven L.; Tanzi, Rudolph E.; Kim, Doo Yeon; Kovacs, Dora M.

2015-01-01

Soluble γ-secretase modulators (SGSMs) selectively decrease toxic amyloid β (Aβ) peptides (Aβ42). However, their effect on the physiologic functions of γ-secretase has not been tested in human model systems. γ-Secretase regulates fate determination of neural progenitor cells. Thus, we studied the impact of SGSMs on the neuronal differentiation of ReNcell VM (ReN) human neural progenitor cells (hNPCs). Quantitative PCR analysis showed that treatment of neurosphere-like ReN cell aggregate cultures with γ-secretase inhibitors (GSIs), but not SGSMs, induced a 2- to 4-fold increase in the expression of the neuronal markers Tuj1 and doublecortin. GSI treatment also induced neuronal marker protein expression, as shown by Western blot analysis. In the same conditions, SGSM treatment selectively reduced endogenous Aβ42 levels by ∼80%. Mechanistically, we found that Notch target gene expressions were selectively inhibited by a GSI, not by SGSM treatment. We can assert, for the first time, that SGSMs do not affect the neuronal differentiation of hNPCs while selectively decreasing endogenous Aβ42 levels in the same conditions. Our results suggest that our hNPC differentiation system can serve as a useful model to test the impact of GSIs and SGSMs on both endogenous Aβ levels and γ-secretase physiologic functions including endogenous Notch signaling.—D’Avanzo, C., Sliwinski, C., Wagner, S. L., Tanzi, R. E., Kim, D. Y., Kovacs, D. M. γ-Secretase modulators reduce endogenous amyloid β42 levels in human neural progenitor cells without altering neuronal differentiation. PMID:25903103

Genetically modified human bone marrow derived mesenchymal stem cells for improving the outcome of human islet transplantation.

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Vaibhav Mundra

Full Text Available The objective of this study was to determine the potential of human bone marrow derived mesenchymal stem cells (hBMSCs as gene carriers for improving the outcome of human islet transplantation. hBMSCs were characterized for the expression of phenotypic markers and transduced with Adv-hVEGF-hIL-1Ra to overexpress human vascular endothelial growth factor (hVEGF and human interleukin-1 receptor antagonist (hIL-1Ra. Human islets were co-cultured with hBMSCs overexpressing hVEGF and hIL-1Ra. Islet viability was determined by membrane fluorescent method and glucose stimulation test. Transduced hBMSCs and human islets were co-transplanted under the kidney capsule of NOD.Cg-Prkdc(scid Il2rg(tm1Wjl /SzJ (NSG diabetic mice and blood glucose levels were measured over time to demonstrate the efficacy of genetically modified hBMSCs. At the end of study, immunofluorescent staining of kidney section bearing islets was performed for insulin and von Willebrand Factor (vWF. hBMSCs were positive for the expression of CD73, CD90, CD105, CD146 and Stro-1 surface markers as determined by flow cytometry. Transduction of hBMSCs with adenovirus did not affect their stemness and differentiation potential as confirmed by mRNA levels of stem cell markers and adipogenic differentiation of transduced hBMSCs. hBMSCs were efficiently transduced with Adv-hVEGF-hIL-1Ra to overexpress hVEGF and hIL-1Ra. Live dead cell staining and glucose stimulation test have shown that transduced hBMSCs improved the viability of islets against cytokine cocktail. Co-transplantation of human islets with genetically modified hBMSCs improved the glycemic control of diabetic NSG mice as determined by mean blood glucose levels and intraperitoneal glucose tolerance test. Immunofluorescent staining of kidney sections was positive for human insulin and vWF. In conclusion, our results have demonstrated that hBMSCs may be used as gene carriers and nursing cells to improve the outcome of islet

Associative memory model with spontaneous neural activity

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Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

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

MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

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Artur Popko

2013-06-01

Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

CFHR1-Modified Neural Stem Cells Ameliorated Brain Injury in a Mouse Model of Neuromyelitis Optica Spectrum Disorders.

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Shi, Kaibin; Wang, Zhen; Liu, Yuanchu; Gong, Ye; Fu, Ying; Li, Shaowu; Wood, Kristofer; Hao, Junwei; Zhang, Guang-Xian; Shi, Fu-Dong; Yan, Yaping

2016-11-01

A major hurdle for effective stem cell therapy is ongoing inflammation in the target organ. Reconditioning the lesion microenvironment may be an effective way to promote stem cell therapy. In this study, we showed that engineered neural stem cells (NSCs) with complement factor H-related protein 1, a complement inhibitor protein, can attenuate inflammatory infiltration and immune-mediated damage of astrocytes, an important pathogenic progress in patients with neuromyelitis optica spectrum disorders. Furthermore, we demonstrated that transplantation of the complement factor H-related protein 1-modified NSCs effectively blocked the complement activation cascade and inhibited formation of the membrane attack complex, thus contributing to the protection of endogenous and transplanted NSC-differentiated astrocytes. Therefore, manipulation of the lesion microenvironment contributes to a more effective cell replacement therapeutic strategy for autoimmune diseases of the CNS. Copyright © 2016 by The American Association of Immunologists, Inc.

Exposure to titanium dioxide and other metallic oxide nanoparticles induces cytotoxicity on human neural cells and fibroblasts

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James C K Lai

2008-12-01

Full Text Available James C K Lai1, Maria B Lai1, Sirisha Jandhyam1, Vikas V Dukhande1, Alok Bhushan1, Christopher K Daniels1, Solomon W Leung21Department of Biomedical and Pharmaceutical Sciences, College of Pharmacy, and Biomedical Research Institute; 2Department of Civil and Environmental Engineering, College of Engineering and Biomedical Research Institute, Idaho State University, Pocatello, ID, USAAbstract: The use of titanium dioxide (TiO2 in various industrial applications (eg, production of paper, plastics, cosmetics, and paints has been expanding thereby increasing the occupational and other environmental exposure of these nanoparticles to humans and other species. However, the health effects of exposure to TiO2 nanoparticles have not been systematically assessed even though recent studies suggest that such exposure induces inflammatory responses in lung tissue and cells. Because the effects of such nanoparticles on human neural cells are unknown, we have determined the putative cytotoxic effects of these nanoparticles on human astrocytes-like astrocytoma U87 cells and compared their effects on normal human fibroblasts. We found that TiO2 micro- and nanoparticles induced cell death on both human cell types in a concentration-related manner. We further noted that zinc oxide (ZnO nanoparticles were the most effective, TiO2 nanoparticles the second most effective, and magnesium oxide (MgO nanoparticles the least effective in inducing cell death in U87 cells. The cell death mechanisms underlying the effects of TiO2 micro- and nanoparticles on U87 cells include apoptosis, necrosis, and possibly apoptosis-like and necrosis-like cell death types. Thus, our findings may have toxicological and other pathophysiological implications on exposure of humans and other mammalian species to metallic oxide nanoparticles.Keywords: cytotoxicity of titanium dioxide micro- and nanoparticles, cytotoxicity of zinc oxide and magnesium oxide nanoparticles, human neural cells

Comprehensive quantitative comparison of the membrane proteome and PTM-ome of human embryonic stem cells and neural stem cells

DEFF Research Database (Denmark)

Braga, Marcella Nunes de Melo; Schulz, Melanie; Jakobsen, Lene

Introduction: Human embryonic stem cells (hESCs) can differentiate into all three germ layers and self-renew. Due to its ability to differentiate in vitro into human neural stem cells (hNSCs), which can further be differentiated into motor neurons and dopaminergic neurons, these cells are potential...... identified phosphorylated and SA glycosylated proteins, respectively. This study allowed us to identify several significantly regulated proteins during the differentiation process, including proteins involved in the early embryonic development as well as in the neural development. In the latter group...... of proteins we could identify a number of proteins associated with synaptic vesicles, which are vesicles that store neurotransmitters in the nerve-terminals. An example of an upregulated protein in hESCs is the gap junction alpha 1 (GJA1), a phosphorylated protein which plays a crucial role in embryonic...

Investigation of efficient features for image recognition by neural networks.

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Goltsev, Alexander; Gritsenko, Vladimir

2012-04-01

In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessing the relative importance of isolated Ficus trees to insectivorous birds in an Indian human-modified tropical landscape

DEFF Research Database (Denmark)

Matthews, Thomas J.; Cottee-Jones, H. Eden W.; Bregman, Tom P.

2017-01-01

The destruction of forest for agricultural expansion has created a vast estate of human-modified land in tropical regions. One group of organisms that are particularly vulnerable to the loss of forest habitat are insectivorous birds. Despite this, few conservation strategies have been identified...... for this group in human-modified landscapes. We survey the use of 104 isolated trees by insectivorous birds in rural Assam, India. We used an information theoretic model comparison approach to determine the important variables driving insectivorous bird diversity within these isolated trees. Our work...... demonstrates that the conservation of large trees in human-modified landscapes may play an important role in maintaining bird diversity and ecological function beyond the forest edge. More specifically, we found that isolated Ficus trees hold assemblages with particularly high insectivore abundance, richness...

Efficient derivation of multipotent neural stem/progenitor cells from non-human primate embryonic stem cells.

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Hiroko Shimada

Full Text Available The common marmoset (Callithrix jacchus is a small New World primate that has been used as a non-human primate model for various biomedical studies. We previously demonstrated that transplantation of neural stem/progenitor cells (NS/PCs derived from mouse and human embryonic stem cells (ESCs and induced pluripotent stem cells (iPSCs promote functional locomotor recovery of mouse spinal cord injury models. However, for the clinical application of such a therapeutic approach, we need to evaluate the efficacy and safety of pluripotent stem cell-derived NS/PCs not only by xenotransplantation, but also allotransplantation using non-human primate models to assess immunological rejection and tumorigenicity. In the present study, we established a culture method to efficiently derive NS/PCs as neurospheres from common marmoset ESCs. Marmoset ESC-derived neurospheres could be passaged repeatedly and showed sequential generation of neurons and astrocytes, similar to that of mouse ESC-derived NS/PCs, and gave rise to functional neurons as indicated by calcium imaging. Although marmoset ESC-derived NS/PCs could not differentiate into oligodendrocytes under default culture conditions, these cells could abundantly generate oligodendrocytes by incorporating additional signals that recapitulate in vivo neural development. Moreover, principal component analysis of microarray data demonstrated that marmoset ESC-derived NS/PCs acquired similar gene expression profiles to those of fetal brain-derived NS/PCs by repeated passaging. Therefore, marmoset ESC-derived NS/PCs may be useful not only for accurate evaluation by allotransplantation of NS/PCs into non-human primate models, but are also applicable to analysis of iPSCs established from transgenic disease model marmosets.

The Postischemic Environment Differentially Impacts Teratoma or Tumor Formation After Transplantation of Human Embryonic Stem Cell-Derived Neural Progenitors

Czech Academy of Sciences Publication Activity Database

Seminatore, CH.; Polentes, J.; Ellman, D.; Kozubenko, Nataliya; Itier, V.; Tine, S.; Tritschler, L.; Brenot, M.; Guidou, E.; Blondeau, J.; Lhuillier, M.; Bugi, A.; Aubry, L.; Jendelová, Pavla; Syková, Eva; Perrier, A. L.; Finsen, B.; Onteniente, B.

2010-01-01

Roč. 41, č. 1 (2010), s. 153-159 ISSN 0039-2499 Institutional research plan: CEZ:AV0Z50390703 Keywords : brain transplantation * human embryonic stem cells * neural differentiation Subject RIV: FH - Neurology Impact factor: 5.756, year: 2010

Surface Casting Defects Inspection Using Vision System and Neural Network Techniques

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Świłło S.J.

2013-12-01

Full Text Available The paper presents a vision based approach and neural network techniques in surface defects inspection and categorization. Depending on part design and processing techniques, castings may develop surface discontinuities such as cracks and pores that greatly influence the material’s properties Since the human visual inspection for the surface is slow and expensive, a computer vision system is an alternative solution for the online inspection. The authors present the developed vision system uses an advanced image processing algorithm based on modified Laplacian of Gaussian edge detection method and advanced lighting system. The defect inspection algorithm consists of several parameters that allow the user to specify the sensitivity level at which he can accept the defects in the casting. In addition to the developed image processing algorithm and vision system apparatus, an advanced learning process has been developed, based on neural network techniques. Finally, as an example three groups of defects were investigated demonstrates automatic selection and categorization of the measured defects, such as blowholes, shrinkage porosity and shrinkage cavity.

Protein Kinase-A Inhibition Is Sufficient to Support Human Neural Stem Cells Self-Renewal.

Science.gov (United States)

Georges, Pauline; Boissart, Claire; Poulet, Aurélie; Peschanski, Marc; Benchoua, Alexandra

2015-12-01

Human pluripotent stem cell-derived neural stem cells offer unprecedented opportunities for producing specific types of neurons for several biomedical applications. However, to achieve it, protocols of production and amplification of human neural stem cells need to be standardized, cost effective, and safe. This means that small molecules should progressively replace the use of media containing cocktails of protein-based growth factors. Here we have conducted a phenotypical screening to identify pathways involved in the regulation of hNSC self-renewal. We analyzed 80 small molecules acting as kinase inhibitors and identified compounds of the 5-isoquinolinesulfonamide family, described as protein kinase A (PKA) and protein kinase G inhibitors, as candidates to support hNSC self-renewal. Investigating the mode of action of these compounds, we found that modulation of PKA activity was central in controlling the choice between self-renewal or terminal neuronal differentiation of hNSC. We finally demonstrated that the pharmacological inhibition of PKA using the small molecule HA1004 was sufficient to support the full derivation, propagation, and long-term maintenance of stable hNSC in absence of any other extrinsic signals. Our results indicated that tuning of PKA activity is a core mechanism regulating hNSC self-renewal and differentiation and delineate the minimal culture media requirement to maintain undifferentiated hNSC in vitro. © 2015 AlphaMed Press.

Harmine stimulates proliferation of human neural progenitors

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Vanja Dakic

2016-12-01

Full Text Available Harmine is the β-carboline alkaloid with the highest concentration in the psychotropic plant decoction Ayahuasca. In rodents, classical antidepressants reverse the symptoms of depression by stimulating neuronal proliferation. It has been shown that Ayahuasca presents antidepressant effects in patients with depressive disorder. In the present study, we investigated the effects of harmine in cell cultures containing human neural progenitor cells (hNPCs, 97% nestin-positive derived from pluripotent stem cells. After 4 days of treatment, the pool of proliferating hNPCs increased by 71.5%. Harmine has been reported as a potent inhibitor of the dual specificity tyrosine-phosphorylation-regulated kinase (DYRK1A, which regulates cell proliferation and brain development. We tested the effect of analogs of harmine, an inhibitor of DYRK1A (INDY, and an irreversible selective inhibitor of monoamine oxidase (MAO but not DYRK1A (pargyline. INDY but not pargyline induced proliferation of hNPCs similarly to harmine, suggesting that inhibition of DYRK1A is a possible mechanism to explain harmine effects upon the proliferation of hNPCs. Our findings show that harmine enhances proliferation of hNPCs and suggest that inhibition of DYRK1A may explain its effects upon proliferation in vitro and antidepressant effects in vivo.

Treating spinal cord injury in rats with a combination of human fetal neural stem cells and hydrogels modified with serotonin

Czech Academy of Sciences Publication Activity Database

Růžička, Jiří; Romanyuk, Nataliya; Hejčl, Aleš; Vetrík, Miroslav; Hrubý, Martin; Cocks, G.; Cihlář, J.; Přádný, Martin; Price, J.; Syková, Eva; Jendelová, Pavla

2013-01-01

Roč. 73, č. 1 (2013), s. 102-115 ISSN 0065-1400 R&D Projects: GA ČR GAP108/10/1560; GA ČR(CZ) GPP304/11/P633; GA ČR GA13-00939S; GA AV ČR IAA500390902 Grant - others:GA MŠk(CZ) GAUK521712 Institutional support: RVO:68378041 ; RVO:61389013 Keywords : spinal cord hemisection * SPC-01 neural stem cells * hydrogel Subject RIV: FH - Neurology; CD - Macromolecular Chemistry (UMCH-V) Impact factor: 2.244, year: 2013

Over-expression of hNGF in adult human olfactory bulb neural stem cells promotes cell growth and oligodendrocytic differentiation

NARCIS (Netherlands)

H.E.S. Marei (Hany); A. Althani (Asmaa); N. Afifi (Nahla); A. Abd-Elmaksoud (Ahmed); C. Bernardini (Camilla); F. Michetti (Fabrizio); M. Barba (Marta); M. Pescatori (Mario); G. Maira (Giulio); E. Paldino (Emanuela); L. Manni (Luigi); P. Casalbore (Patrizia); C. Cenciarelli (Carlo)

2013-01-01

textabstractThe adult human olfactory bulb neural stem/progenitor cells (OBNC/PC) are promising candidate for cell-based therapy for traumatic and neurodegenerative insults. Exogenous application of NGF was suggested as a promising therapeutic strategy for traumatic and neurodegenerative diseases,

Conversion of Human Fibroblasts to Stably Self-Renewing Neural Stem Cells with a Single Zinc-Finger Transcription Factor

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Ebrahim Shahbazi

2016-04-01

Full Text Available Direct conversion of somatic cells into neural stem cells (NSCs by defined factors holds great promise for mechanistic studies, drug screening, and potential cell therapies for different neurodegenerative diseases. Here, we report that a single zinc-finger transcription factor, Zfp521, is sufficient for direct conversion of human fibroblasts into long-term self-renewable and multipotent NSCs. In vitro, Zfp521-induced NSCs maintained their characteristics in the absence of exogenous factor expression and exhibited morphological, molecular, developmental, and functional properties that were similar to control NSCs. In addition, the single-seeded induced NSCs were able to form NSC colonies with efficiency comparable with control NSCs and expressed NSC markers. The converted cells were capable of surviving, migrating, and attaining neural phenotypes after transplantation into neonatal mouse and adult rat brains, without forming tumors. Moreover, the Zfp521-induced NSCs predominantly expressed rostral genes. Our results suggest a facilitated approach for establishing human NSCs through Zfp521-driven conversion of fibroblasts.

An Efficient Feature Extraction Method with Pseudo-Zernike Moment in RBF Neural Network-Based Human Face Recognition System

Directory of Open Access Journals (Sweden)

Ahmadi Majid

2003-01-01

Full Text Available This paper introduces a novel method for the recognition of human faces in digital images using a new feature extraction method that combines the global and local information in frontal view of facial images. Radial basis function (RBF neural network with a hybrid learning algorithm (HLA has been used as a classifier. The proposed feature extraction method includes human face localization derived from the shape information. An efficient distance measure as facial candidate threshold (FCT is defined to distinguish between face and nonface images. Pseudo-Zernike moment invariant (PZMI with an efficient method for selecting moment order has been used. A newly defined parameter named axis correction ratio (ACR of images for disregarding irrelevant information of face images is introduced. In this paper, the effect of these parameters in disregarding irrelevant information in recognition rate improvement is studied. Also we evaluate the effect of orders of PZMI in recognition rate of the proposed technique as well as RBF neural network learning speed. Simulation results on the face database of Olivetti Research Laboratory (ORL indicate that the proposed method for human face recognition yielded a recognition rate of 99.3%.

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

Investigation of Slow-wave Activity Saturation during Surgical Anesthesia Reveals a Signature of Neural Inertia in Humans.

Science.gov (United States)

Warnaby, Catherine E; Sleigh, Jamie W; Hight, Darren; Jbabdi, Saad; Tracey, Irene

2017-10-01

Previously, we showed experimentally that saturation of slow-wave activity provides a potentially individualized neurophysiologic endpoint for perception loss during anesthesia. Furthermore, it is clear that induction and emergence from anesthesia are not symmetrically reversible processes. The observed hysteresis is potentially underpinned by a neural inertia mechanism as proposed in animal studies. In an advanced secondary analysis of 393 individual electroencephalographic data sets, we used slow-wave activity dose-response relationships to parameterize slow-wave activity saturation during induction and emergence from surgical anesthesia. We determined whether neural inertia exists in humans by comparing slow-wave activity dose responses on induction and emergence. Slow-wave activity saturation occurs for different anesthetics and when opioids and muscle relaxants are used during surgery. There was wide interpatient variability in the hypnotic concentrations required to achieve slow-wave activity saturation. Age negatively correlated with power at slow-wave activity saturation. On emergence, we observed abrupt decreases in slow-wave activity dose responses coincident with recovery of behavioral responsiveness in ~33% individuals. These patients are more likely to have lower power at slow-wave activity saturation, be older, and suffer from short-term confusion on emergence. Slow-wave activity saturation during surgical anesthesia implies that large variability in dosing is required to achieve a targeted potential loss of perception in individual patients. A signature for neural inertia in humans is the maintenance of slow-wave activity even in the presence of very-low hypnotic concentrations during emergence from anesthesia.

Learning and adaptation: neural and behavioural mechanisms behind behaviour change

Science.gov (United States)

Lowe, Robert; Sandamirskaya, Yulia

2018-01-01

This special issue presents perspectives on learning and adaptation as they apply to a number of cognitive phenomena including pupil dilation in humans and attention in robots, natural language acquisition and production in embodied agents (robots), human-robot game play and social interaction, neural-dynamic modelling of active perception and neural-dynamic modelling of infant development in the Piagetian A-not-B task. The aim of the special issue, through its contributions, is to highlight some of the critical neural-dynamic and behavioural aspects of learning as it grounds adaptive responses in robotic- and neural-dynamic systems.

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

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Meeri Eeva-Liisa Mäkinen

2018-03-01

Full Text Available The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging and temporal resolution microelectrode array (MEA. We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling.

GABA and Gap Junctions in the Development of Synchronized Activity in Human Pluripotent Stem Cell-Derived Neural Networks

Science.gov (United States)

Mäkinen, Meeri Eeva-Liisa; Ylä-Outinen, Laura; Narkilahti, Susanna

2018-01-01

The electrical activity of the brain arises from single neurons communicating with each other. However, how single neurons interact during early development to give rise to neural network activity remains poorly understood. We studied the emergence of synchronous neural activity in human pluripotent stem cell (hPSC)-derived neural networks simultaneously on a single-neuron level and network level. The contribution of gamma-aminobutyric acid (GABA) and gap junctions to the development of synchronous activity in hPSC-derived neural networks was studied with GABA agonist and antagonist and by blocking gap junctional communication, respectively. We characterized the dynamics of the network-wide synchrony in hPSC-derived neural networks with high spatial resolution (calcium imaging) and temporal resolution microelectrode array (MEA). We found that the emergence of synchrony correlates with a decrease in very strong GABA excitation. However, the synchronous network was found to consist of a heterogeneous mixture of synchronously active cells with variable responses to GABA, GABA agonists and gap junction blockers. Furthermore, we show how single-cell distributions give rise to the network effect of GABA, GABA agonists and gap junction blockers. Finally, based on our observations, we suggest that the earliest form of synchronous neuronal activity depends on gap junctions and a decrease in GABA induced depolarization but not on GABAA mediated signaling. PMID:29559893

Transcriptional profiling of MEF2-regulated genes in human neural progenitor cells derived from embryonic stem cells

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Shing Fai Chan

2015-03-01

Full Text Available The myocyte enhancer factor 2 (MEF2 family of transcription factors is highly expressed in the brain and constitutes a key determinant of neuronal survival, differentiation, and synaptic plasticity. However, genome-wide transcriptional profiling of MEF2-regulated genes has not yet been fully elucidated, particularly at the neural stem cell stage. Here we report the results of microarray analysis comparing mRNAs isolated from human neural progenitor/stem cells (hNPCs derived from embryonic stem cells expressing a control vector versus progenitors expressing a constitutively-active form of MEF2 (MEF2CA, which increases MEF2 activity. Microarray experiments were performed using the Illumina Human HT-12 V4.0 expression beadchip (GEO#: GSE57184. By comparing vector-control cells to MEF2CA cells, microarray analysis identified 1880 unique genes that were differentially expressed. Among these genes, 1121 genes were up-regulated and 759 genes were down-regulated. Our results provide a valuable resource for identifying transcriptional targets of MEF2 in hNPCs.

Chitosan scaffolds induce human dental pulp stem cells to neural differentiation: potential roles for spinal cord injury therapy.

Science.gov (United States)

Zhang, Jinlong; Lu, Xiaohui; Feng, Guijuan; Gu, Zhifeng; Sun, Yuyu; Bao, Guofeng; Xu, Guanhua; Lu, Yuanzhou; Chen, Jiajia; Xu, Lingfeng; Feng, Xingmei; Cui, Zhiming

2016-10-01

Cell-based transplantation strategies hold great potential for spinal cord injury (SCI) repair. Chitosan scaffolds have therapeutic benefits for spinal cord regeneration. Human dental pulp stem cells (DPSCs) are abundant available stem cells with low immunological incompatibility and can be considered for cell replacement therapy. The purpose of this study is to investigate the role of chitosan scaffolds in the neural differentiation of DPSCs in vitro and to assess the supportive effects of chitosan scaffolds in an animal model of SCI. DPSCs were incubated with chitosan scaffolds. Cell viability and the secretion of neurotrophic factors were analyzed. DPSCs incubated with chitosan scaffolds were treated with neural differentiation medium for 14 days and then neural genes and protein markers were analyzed by Western blot and reverse transcription plus the polymerase chain reaction. Our study revealed a higher cell viability and neural differentiation in the DPSC/chitosan-scaffold group. Compared with the control group, the levels of BDNF, GDNF, b-NGF, and NT-3 were significantly increased in the DPSC/chitosan-scaffold group. The Wnt/β-catenin signaling pathway played a key role in the neural differentiation of DPSCs combined with chitosan scaffolds. Transplantation of DPSCs together with chitosan scaffolds into an SCI rat model resulted in the marked recovery of hind limb locomotor functions. Thus, chitosan scaffolds were non-cytotoxic and provided a conducive and favorable microenvironment for the survival and neural differentiation of DPSCs. Transplantation of DPSCs might therefore be a suitable candidate for treating SCI and other neuronal degenerative diseases.

Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

Directory of Open Access Journals (Sweden)

Anh Vu Le

2017-01-01

Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

Comparative analysis of modified PMV models and SET models to predict human thermal sensation in naturally ventilated buildings

DEFF Research Database (Denmark)

Gao, Jie; Wang, Yi; Wargocki, Pawel

2015-01-01

In this paper, a comparative analysis was performed on the human thermal sensation estimated by modified predicted mean vote (PMV) models and modified standard effective temperature (SET) models in naturally ventilated buildings; the data were collected in field study. These prediction models were....../s, the expectancy factors for the extended PMV model and the extended SET model were from 0.770 to 0.974 and from 1.330 to 1.363, and the adaptive coefficients for the adaptive PMV model and the adaptive SET model were from 0.029 to 0.167 and from-0.213 to-0.195. In addition, the difference in thermal sensation...... between the measured and predicted values using the modified PMV models exceeded 25%, while the difference between the measured thermal sensation and the predicted thermal sensation using modified SET models was approximately less than 25%. It is concluded that the modified SET models can predict human...

Pyrolysed 3D-Carbon Scaffolds Induce Spontaneous Differentiation of Human Neural Stem Cells and Facilitate Real-Time Dopamine Detection

DEFF Research Database (Denmark)

Amato, Letizia; Heiskanen, Arto; Caviglia, Claudia

2014-01-01

Structurally patterned pyrolysed three-dimensional carbon scaffolds (p3Dcarbon) are fabricated and applied for differentiation of human neural stem cells (hNSCs) developed for cell replacement therapy and sensing of released dopamine. In the absence of differentiation factors (DF) the pyrolysed c...

Skin derived precursor Schwann cell-generated acellular matrix modified chitosan/silk scaffolds for bridging rat sciatic nerve gap.

Science.gov (United States)

Zhu, Changlai; Huang, Jing; Xue, Chengbin; Wang, Yaxian; Wang, Shengran; Bao, Shuangxi; Chen, Ruyue; Li, Yuan; Gu, Yun

2017-12-27

Extracellular/acellular matrix has been attracted much research interests for its unique biological characteristics, and ACM modified neural scaffolds shows the remarkable role of promoting peripheral nerve regeneration. In this study, skin-derived precursors pre-differentiated into Schwann cells (SKP-SCs) were used as parent cells to generate acellular(ACM) for constructing a ACM-modified neural scaffold. SKP-SCs were co-cultured with chitosan nerve guidance conduits (NGC) and silk fibroin filamentous fillers, followed by decellularization to stimulate ACM deposition. This NGC-based, SKP-SC-derived ACM-modified neural scaffold was used for bridging a 10 mm long rat sciatic nerve gap. Histological and functional evaluation after grafting demonstrated that regenerative outcomes achieved by this engineered neural scaffold were better than those achieved by a plain chitosan-silk fibroin scaffold, and suggested the benefits of SKP-SC-derived ACM for peripheral nerve repair. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.

Nonequilibrium landscape theory of neural networks

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-01-01

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape–flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments. PMID:24145451

Nonequilibrium landscape theory of neural networks.

Science.gov (United States)

Yan, Han; Zhao, Lei; Hu, Liang; Wang, Xidi; Wang, Erkang; Wang, Jin

2013-11-05

The brain map project aims to map out the neuron connections of the human brain. Even with all of the wirings mapped out, the global and physical understandings of the function and behavior are still challenging. Hopfield quantified the learning and memory process of symmetrically connected neural networks globally through equilibrium energy. The energy basins of attractions represent memories, and the memory retrieval dynamics is determined by the energy gradient. However, the realistic neural networks are asymmetrically connected, and oscillations cannot emerge from symmetric neural networks. Here, we developed a nonequilibrium landscape-flux theory for realistic asymmetrically connected neural networks. We uncovered the underlying potential landscape and the associated Lyapunov function for quantifying the global stability and function. We found the dynamics and oscillations in human brains responsible for cognitive processes and physiological rhythm regulations are determined not only by the landscape gradient but also by the flux. We found that the flux is closely related to the degrees of the asymmetric connections in neural networks and is the origin of the neural oscillations. The neural oscillation landscape shows a closed-ring attractor topology. The landscape gradient attracts the network down to the ring. The flux is responsible for coherent oscillations on the ring. We suggest the flux may provide the driving force for associations among memories. We applied our theory to rapid-eye movement sleep cycle. We identified the key regulation factors for function through global sensitivity analysis of landscape topography against wirings, which are in good agreements with experiments.

An improved genetic algorithm for designing optimal temporal patterns of neural stimulation

Science.gov (United States)

Cassar, Isaac R.; Titus, Nathan D.; Grill, Warren M.

2017-12-01

Objective. Electrical neuromodulation therapies typically apply constant frequency stimulation, but non-regular temporal patterns of stimulation may be more effective and more efficient. However, the design space for temporal patterns is exceedingly large, and model-based optimization is required for pattern design. We designed and implemented a modified genetic algorithm (GA) intended for design optimal temporal patterns of electrical neuromodulation. Approach. We tested and modified standard GA methods for application to designing temporal patterns of neural stimulation. We evaluated each modification individually and all modifications collectively by comparing performance to the standard GA across three test functions and two biophysically-based models of neural stimulation. Main results. The proposed modifications of the GA significantly improved performance across the test functions and performed best when all were used collectively. The standard GA found patterns that outperformed fixed-frequency, clinically-standard patterns in biophysically-based models of neural stimulation, but the modified GA, in many fewer iterations, consistently converged to higher-scoring, non-regular patterns of stimulation. Significance. The proposed improvements to standard GA methodology reduced the number of iterations required for convergence and identified superior solutions.

A comparative transcriptomic analysis of astrocytes differentiation from human neural progenitor cells.

Science.gov (United States)

Magistri, Marco; Khoury, Nathalie; Mazza, Emilia Maria Cristina; Velmeshev, Dmitry; Lee, Jae K; Bicciato, Silvio; Tsoulfas, Pantelis; Faghihi, Mohammad Ali

2016-11-01

Astrocytes are a morphologically and functionally heterogeneous population of cells that play critical roles in neurodevelopment and in the regulation of central nervous system homeostasis. Studies of human astrocytes have been hampered by the lack of specific molecular markers and by the difficulties associated with purifying and culturing astrocytes from adult human brains. Human neural progenitor cells (NPCs) with self-renewal and multipotent properties represent an appealing model system to gain insight into the developmental genetics and function of human astrocytes, but a comprehensive molecular characterization that confirms the validity of this cellular system is still missing. Here we used an unbiased transcriptomic analysis to characterize in vitro culture of human NPCs and to define the gene expression programs activated during the differentiation of these cells into astrocytes using FBS or the combination of CNTF and BMP4. Our results demonstrate that in vitro cultures of human NPCs isolated during the gliogenic phase of neurodevelopment mainly consist of radial glial cells (RGCs) and glia-restricted progenitor cells. In these cells the combination of CNTF and BMP4 activates the JAK/STAT and SMAD signaling cascades, leading to the inhibition of oligodendrocytes lineage commitment and activation of astrocytes differentiation. On the other hand, FBS-derived astrocytes have properties of reactive astrocytes. Our work suggests that in vitro culture of human NPCs represents a valuable cellular system to study human disorders characterized by impairment of astrocytes development and function. Our datasets represent an important resource for researchers studying human astrocytes development and might set the basis for the discovery of novel human-specific astrocyte markers. © 2016 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

The influences and neural correlates of past and present during gambling in humans.

Science.gov (United States)

Sacré, Pierre; Subramanian, Sandya; Kerr, Matthew S D; Kahn, Kevin; Johnson, Matthew A; Bulacio, Juan; González-Martínez, Jorge A; Sarma, Sridevi V; Gale, John T

2017-12-07

During financial decision-making tasks, humans often make "rational" decisions, where they maximize expected reward. However, this rationality may compete with a bias that reflects past outcomes. That is, if one just lost money or won money, this may impact future decisions. It is unclear how past outcomes influence future decisions in humans, and how neural circuits encode present and past information. In this study, six human subjects performed a financial decision-making task while we recorded local field potentials from multiple brain structures. We constructed a model for each subject characterizing bets on each trial as a function of present and past information. The models suggest that some patients are more influenced by previous trial outcomes (i.e., previous return and risk) than others who stick to more fixed decision strategies. In addition, past return and present risk modulated with the activity in the cuneus; while present return and past risk modulated with the activity in the superior temporal gyrus and the angular gyrus, respectively. Our findings suggest that these structures play a role in decision-making beyond their classical functions by incorporating predictions and risks in humans' decision strategy, and provide new insight into how humans link their internal biases to decisions.

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...

Memristor-based neural networks

International Nuclear Information System (INIS)

Thomas, Andy

2013-01-01

The synapse is a crucial element in biological neural networks, but a simple electronic equivalent has been absent. This complicates the development of hardware that imitates biological architectures in the nervous system. Now, the recent progress in the experimental realization of memristive devices has renewed interest in artificial neural networks. The resistance of a memristive system depends on its past states and exactly this functionality can be used to mimic the synaptic connections in a (human) brain. After a short introduction to memristors, we present and explain the relevant mechanisms in a biological neural network, such as long-term potentiation and spike time-dependent plasticity, and determine the minimal requirements for an artificial neural network. We review the implementations of these processes using basic electric circuits and more complex mechanisms that either imitate biological systems or could act as a model system for them. (topical review)

Expression of Pluripotency Markers in Nonpluripotent Human Neural Stem and Progenitor Cells.

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Vincent, Per Henrik; Benedikz, Eirikur; Uhlén, Per; Hovatta, Outi; Sundström, Erik

2017-06-15

Nonpluripotent neural progenitor cells (NPCs) derived from the human fetal central nervous system were found to express a number of messenger RNA (mRNA) species associated with pluripotency, such as NANOG, REX1, and OCT4. The expression was restricted to small subpopulations of NPCs. In contrast to pluripotent stem cells, there was no coexpression of the pluripotency-associated genes studied. Although the expression of these genes rapidly declined during the in vitro differentiation of NPCs, we found no evidence that the discrete expression was associated with the markers of multipotent neural stem cells (CD133 + /CD24 lo ), the capacity of sphere formation, or high cell proliferation rates. The rate of cell death among NPCs expressing pluripotency-associated genes was also similar to that of other NPCs. Live cell imaging showed that NANOG- and REX1-expressing NPCs continuously changed morphology, as did the nonexpressing cells. Depletion experiments showed that after the complete removal of the subpopulations of NANOG- and REX1-expressing NPCs, the expression of these genes appeared in other NPCs within a few days. The percentage of NANOG- and REX1-expressing cells returned to that observed before depletion. Our results are best explained by a model in which there is stochastic transient expression of pluripotency-associated genes in proliferating NPCs.

Neural Signature of Value-Based Sensorimotor Prioritization in Humans.

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Blangero, Annabelle; Kelly, Simon P

2017-11-01

value biases in sensorimotor decision making have been widely studied, little is known about the neural processes that set these biases in place beforehand. Here, we report the discovery of a transient, spatially selective neural signal in humans that encodes the relative value of competing decision alternatives and strongly predicts behavioral value biases in decisions made ∼500 ms later. Follow-up manipulations of value differential, reward valence, response modality, sensory features, and time constraints establish that the signal reflects an active, feature- and effector-general preparatory mechanism for value-based prioritization. Copyright © 2017 the authors 0270-6474/17/3710725-13$15.00/0.

Neuron-Based Heredity and Human Evolution

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Don Marshall Gash

2015-06-01

Full Text Available Abstract:Abstract: It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes are in line with Neolamarckian concepts of evolution (Packard, 1901. Evidence is presented of bipartite evolutionary processes – Darwinian and Neolamarckian – driving human descent from a common ancestor shared with the great apes.

Expandable and Rapidly Differentiating Human Induced Neural Stem Cell Lines for Multiple Tissue Engineering Applications

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Dana M. Cairns

2016-09-01

Full Text Available Limited availability of human neurons poses a significant barrier to progress in biological and preclinical studies of the human nervous system. Current stem cell-based approaches of neuron generation are still hindered by prolonged culture requirements, protocol complexity, and variability in neuronal differentiation. Here we establish stable human induced neural stem cell (hiNSC lines through the direct reprogramming of neonatal fibroblasts and adult adipose-derived stem cells. These hiNSCs can be passaged indefinitely and cryopreserved as colonies. Independently of media composition, hiNSCs robustly differentiate into TUJ1-positive neurons within 4 days, making them ideal for innervated co-cultures. In vivo, hiNSCs migrate, engraft, and contribute to both central and peripheral nervous systems. Lastly, we demonstrate utility of hiNSCs in a 3D human brain model. This method provides a valuable interdisciplinary tool that could be used to develop drug screening applications as well as patient-specific disease models related to disorders of innervation and the brain.

23rd Workshop of the Italian Neural Networks Society (SIREN)

CERN Document Server

Esposito, Anna; Morabito, Francesco

2014-01-01

This volume collects a selection of contributions which has been presented at the 23rd Italian Workshop on Neural Networks, the yearly meeting of the Italian Society for Neural Networks (SIREN). The conference was held in Vietri sul Mare, Salerno, Italy during May 23-24, 2013. The annual meeting of SIREN is sponsored by International Neural Network Society (INNS), European Neural Network Society (ENNS) and IEEE Computational Intelligence Society (CIS). The book – as well as the workshop-  is organized in two main components, a special session and a group of regular sessions featuring different aspects and point of views of artificial neural networks, artificial and natural intelligence, as well as psychological and cognitive theories for modeling human behaviors and human machine interactions, including Information Communication applications of compelling interest.  .

Neural evidence that human emotions share core affective properties.

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Wilson-Mendenhall, Christine D; Barrett, Lisa Feldman; Barsalou, Lawrence W

2013-06-01

Research on the "emotional brain" remains centered around the idea that emotions like fear, happiness, and sadness result from specialized and distinct neural circuitry. Accumulating behavioral and physiological evidence suggests, instead, that emotions are grounded in core affect--a person's fluctuating level of pleasant or unpleasant arousal. A neuroimaging study revealed that participants' subjective ratings of valence (i.e., pleasure/displeasure) and of arousal evoked by various fear, happiness, and sadness experiences correlated with neural activity in specific brain regions (orbitofrontal cortex and amygdala, respectively). We observed these correlations across diverse instances within each emotion category, as well as across instances from all three categories. Consistent with a psychological construction approach to emotion, the results suggest that neural circuitry realizes more basic processes across discrete emotions. The implicated brain regions regulate the body to deal with the world, producing the affective changes at the core of emotions and many other psychological phenomena.

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

The Neural Basis of Social Influence in a Dictator Decision

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Zhenyu Wei

2017-12-01

Full Text Available Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants’ decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

The Neural Basis of Social Influence in a Dictator Decision.

Science.gov (United States)

Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong

2017-01-01

Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants' decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing.

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

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Jinah Han

2015-02-01

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

Effects of modifying water environments on water supply and human health

Science.gov (United States)

Takizawa, S.; Nguyen, H. T.; Takeda, T.; Tran, N. T.

2008-12-01

Due to increasing population and per-capita water demand, demands for water are increasing in many parts of the world. Consequently, overuse of limited water resources leaves only small amounts of water in rivers and is bringing about rapid drawdown of groundwater tables. Water resources are affected by human activities such as excessive inputs of nutrients and other contaminants, agriculture and aquaculture expansions, and many development activities. The combined effects of modifying the water environments, both in terms of quantity and quality, on water supply and human health are presented in the paper with some examples from the Asian countries. In rural and sub-urban areas in Bangladesh and Vietnam, for example, the traditional way of obtaining surface water from ponds had been replaced by taking groundwaters to avert the microbial health risks that had arisen from contamination by human wastes. Such a change of water sources, however, has brought about human health impact caused by arsenic on a massive scale. In Thailand, the industrial development has driven the residents to get groundwater leaden with very high fluoride. Monitoring the urine fluoride levels reveal the risk of drinking fluoride-laden groundwaters. Rivers are also affected by extensive exploitation such as sand mining. As a result, turbidity changes abruptly after a heavy rainfall. In cities, due to shrinking water resources they have to take poor quality waters from contaminated sources. Algal blooms are seen in many reservoirs and lakes due to increasing levels of nutrients. Hence, it is likely that algal toxins may enter the water supply systems. Because most of the water treatment plants are not designed to remove those known and unknown contaminants, it is estimated that quite a large number of people are now under the threat of the public health "gtime bomb,"h which may one day bring about mass-scale health problems. In order to mitigate the negative impacts of modifying the water

Human neural stem cells over-expressing choline acetyltransferase restore cognition in rat model of cognitive dysfunction.

Science.gov (United States)

Park, Dongsun; Lee, Hong Jun; Joo, Seong Soo; Bae, Dae-Kwon; Yang, Goeun; Yang, Yun-Hui; Lim, Inja; Matsuo, Akinori; Tooyama, Ikuo; Kim, Yun-Bae; Kim, Seung U

2012-04-01

A human neural stem cell (NSC) line over-expressing human choline acetyltransferase (ChAT) gene was generated and these F3.ChAT NSCs were transplanted into the brain of rat Alzheimer disease (AD) model which was induced by application of ethylcholine mustard aziridinium ion (AF64A) that specifically denatures cholinergic nerves and thereby leads to memory deficit as a salient feature of AD. Transplantation of F3.ChAT human NSCs fully recovered the learning and memory function of AF64A animals, and induced elevated levels of acetylcholine (ACh) in cerebrospinal fluid (CSF). Transplanted F3.ChAT human NSCs were found to migrate to various brain regions including cerebral cortex, hippocampus, striatum and septum, and differentiated into neurons and astrocytes. The present study demonstrates that brain transplantation of human NSCs over-expressing ChAT ameliorates complex learning and memory deficits in AF64A-cholinotoxin-induced AD rat model. Copyright © 2012 Elsevier Inc. All rights reserved.

Perceptual learning modifies the functional specializations of visual cortical areas.

Science.gov (United States)

Chen, Nihong; Cai, Peng; Zhou, Tiangang; Thompson, Benjamin; Fang, Fang

2016-05-17

Training can improve performance of perceptual tasks. This phenomenon, known as perceptual learning, is strongest for the trained task and stimulus, leading to a widely accepted assumption that the associated neuronal plasticity is restricted to brain circuits that mediate performance of the trained task. Nevertheless, learning does transfer to other tasks and stimuli, implying the presence of more widespread plasticity. Here, we trained human subjects to discriminate the direction of coherent motion stimuli. The behavioral learning effect substantially transferred to noisy motion stimuli. We used transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to investigate the neural mechanisms underlying the transfer of learning. The TMS experiment revealed dissociable, causal contributions of V3A (one of the visual areas in the extrastriate visual cortex) and MT+ (middle temporal/medial superior temporal cortex) to coherent and noisy motion processing. Surprisingly, the contribution of MT+ to noisy motion processing was replaced by V3A after perceptual training. The fMRI experiment complemented and corroborated the TMS finding. Multivariate pattern analysis showed that, before training, among visual cortical areas, coherent and noisy motion was decoded most accurately in V3A and MT+, respectively. After training, both kinds of motion were decoded most accurately in V3A. Our findings demonstrate that the effects of perceptual learning extend far beyond the retuning of specific neural populations for the trained stimuli. Learning could dramatically modify the inherent functional specializations of visual cortical areas and dynamically reweight their contributions to perceptual decisions based on their representational qualities. These neural changes might serve as the neural substrate for the transfer of perceptual learning.

Highly efficient methods to obtain homogeneous dorsal neural progenitor cells from human and mouse embryonic stem cells and induced pluripotent stem cells.

Science.gov (United States)

Zhang, Meixiang; Ngo, Justine; Pirozzi, Filomena; Sun, Ying-Pu; Wynshaw-Boris, Anthony

2018-03-15

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have been widely used to generate cellular models harboring specific disease-related genotypes. Of particular importance are ESC and iPSC applications capable of producing dorsal telencephalic neural progenitor cells (NPCs) that are representative of the cerebral cortex and overcome the challenges of maintaining a homogeneous population of cortical progenitors over several passages in vitro. While previous studies were able to derive NPCs from pluripotent cell types, the fraction of dorsal NPCs in this population is small and decreases over several passages. Here, we present three protocols that are highly efficient in differentiating mouse and human ESCs, as well as human iPSCs, into a homogeneous and stable population of dorsal NPCs. These protocols will be useful for modeling cerebral cortical neurological and neurodegenerative disorders in both mouse and human as well as for high-throughput drug screening for therapeutic development. We optimized three different strategies for generating dorsal telencephalic NPCs from mouse and human pluripotent cell types through single or double inhibition of bone morphogenetic protein (BMP) and/or SMAD pathways. Mouse and human pluripotent cells were aggregated to form embryoid bodies in suspension and were treated with dorsomorphin alone (BMP inhibition) or combined with SB431542 (double BMP/SMAD inhibition) during neural induction. Neural rosettes were then selected from plated embryoid bodies to purify the population of dorsal NPCs. We tested the expression of key dorsal NPC markers as well as nonectodermal markers to confirm the efficiency of our three methods in comparison to published and commercial protocols. Single and double inhibition of BMP and/or SMAD during neural induction led to the efficient differentiation of dorsal NPCs, based on the high percentage of PAX6-positive cells and the NPC gene expression profile. There were no statistically

Activation of Group II Metabotropic Glutamate Receptors Increases Proliferation but does not Influence Neuronal Differentiation of a Human Neural Stem Cell Line

DEFF Research Database (Denmark)

Dindler, Anne; Blaabjerg, Morten; Kamand, Morad

2018-01-01

of pharmacological activation and inhibition of mGluR2/3 on proliferation, differentiation and viability of a human neural stem cell line. Immunofluorescence staining revealed the presence of mGluR2/3 receptors on both proliferating and differentiating stem cells, including cells differentiated into β-tubulin III....... Western blot analysis revealed that the active, dimeric form of mGluR2/3 was mainly present on the proliferating cells, which may explain our findings. The present study emphasises the importance of glutamate and mGluRs on regulation of human neural stem cells and suggests a significant role of mGluR2....../3 during cell proliferation. This article is protected by copyright. All rights reserved....

The postischemic environment differentially impacts teratoma or tumor formation after transplantation of human embryonic stem cell-derived neural progenitors

DEFF Research Database (Denmark)

Seminatore, Christine; Polentes, Jerome; Ellman, Ditte

2010-01-01

Risk of tumorigenesis is a major obstacle to human embryonic and induced pluripotent stem cell therapy. Likely linked to the stage of differentiation of the cells at the time of implantation, formation of teratoma/tumors can also be influenced by factors released by the host tissue. We have...... analyzed the relative effects of the stage of differentiation and the postischemic environment on the formation of adverse structures by transplanted human embryonic stem cell-derived neural progenitors....

Comprehensive quantitative comparison of the membrane proteome, phosphoproteome, and sialiome of human embryonic and neural stem cells

DEFF Research Database (Denmark)

Melo-Braga, Marcella Nunes; Schulz, Melanie; Liu, Qiuyue

2014-01-01

Human embryonic stem cells (hESCs) can differentiate into neural stem cells (NSCs), which can further be differentiated into neurons and glia cells. Therefore, these cells have huge potential as source for treatment of neurological diseases. Membrane-associated proteins are very important......ESCs and NSCs as well as to investigate potential new markers for these two cell stages, we performed large-scale quantitative membrane-proteomic of hESCs and NSCs. This approach employed membrane purification followed by peptide dimethyl labeling and peptide enrichment to study the membrane subproteome as well...... in which 78% of phosphopeptides were identified with ≥99% confidence in site assignment and 1810 unique formerly sialylated N-linked glycopeptides. Several proteins were identified as significantly regulated in hESCs and NSC, including proteins involved in the early embryonic and neural development...

Diagnostic Efficacy of Modified Coagglutination Test in the Diagnosis of Human Brucellosis

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Mohite S.T

2013-07-01

Full Text Available Background: Laboratory help is must for thediagnosis of human brucellosis due to proteanclinical manifestations. As culture is hazardous,time consuming and less sensitive, serologicaltests are preferred for the diagnosis. Aggluti-nation tests like Rose Bengal PlateTest (RBPT, Serum Agglutination tests (SAT,2-Mercaptoethanol test (2-ME that are com-monly employed for the diagnosis either lacksensitivity or specificity. Coombs test andBrucellacapt though are sensitive and specific,workout costly. Therefore, modifiedcoagglutination test was developed and its di-agnostic efficacy was evaluated. Aims and Ob-jectives: To develop modified coagglutinationtest for the diagnosis of human brucellosis andcompare it with Coombs test. Materials andMethods: Serum samples collected from 191brucellosis patients and 100 controls were sub-jected to 2-ME, Coombs test and modifiedcoagglutination test (MCOAG. Blood culturewas performed by Castaneda’s method in all thepatients. Results: Significant difference in thepositivity rate was seen between MCOAG and2-ME. The results of MCOAG were compa-rable with Coombs test. Conclusions: Modi-fied coagglutination test is a better option toCoombs test for the serodiagnosis of brucel-losis in resource constrained countries as it issensitive, specific and cost effective.

Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

Science.gov (United States)

Van Loon, Anne F.; Stahl, Kerstin; Di Baldassarre, Giuliano; Clark, Julian; Rangecroft, Sally; Wanders, Niko; Gleeson, Tom; Van Dijk, Albert I. J. M.; Tallaksen, Lena M.; Hannaford, Jamie; Uijlenhoet, Remko; Teuling, Adriaan J.; Hannah, David M.; Sheffield, Justin; Svoboda, Mark; Verbeiren, Boud; Wagener, Thorsten; Van Lanen, Henny A. J.

2016-09-01

In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to accommodate changes in the normal situation (i.e. what

Extracts of human atherosclerotic lesions modify LDL inducing enhanced macrophage uptake

International Nuclear Information System (INIS)

Hoff, H.F.; O'Neill, J.

1986-01-01

Both an LDL-like fraction isolated from human aortic plaques and LDL incubated with cultured aortic endothelial or smooth muscle cells have been shown to be internalized by macrophages in vitro in an unregulated fashion leading to foam cell formation. Lipid peroxidation induced by free radicals released from cells was shown to be responsible for cell-modified LDL. The authors incubated LDL with a supernatant fraction of leached, i.e. non-homogenized, extracts of aortic plaques for one hour at 37 0 C, to determine whether extracellular components present in arteries were also capable of modifying LDL. Extract-treated LDL showed the following changes relative to untreated LDL: 1) increased electrophretic mobility, 2) altered pattern of B-100 on SDS-PAGE, i.e. presence of a doublet with higher M/sub r/ than B-100, and 3) enhanced uptake by cultured mouse peritoneal macrophages as measured by increased degradation of 125 I-LDL, and increased stimulation of cholesterol esterification using 14 C-oleate. Extracts from homogenized plaques and grossly normal intima induced similar changes. The modification was tissue specific in that extracts of arteries but not of liver, muscle or skin modified LDL. Protease degradation of LDL during incubation was probably not responsible since inhibitors did not prevent modification. It is possible that products of lipid peroxidation present in extracellular lipid of arteries may propagate free radicals or be incorporated into LDL, leading to modifications similar to those found in cell-modified LDL

GBM secretome induces transient transformation of human neural precursor cells.

Science.gov (United States)

Venugopal, Chitra; Wang, X Simon; Manoranjan, Branavan; McFarlane, Nicole; Nolte, Sara; Li, Meredith; Murty, Naresh; Siu, K W Michael; Singh, Sheila K

2012-09-01

Glioblastoma (GBM) is the most aggressive primary brain tumor in humans, with a uniformly poor prognosis. The tumor microenvironment is composed of both supportive cellular substrates and exogenous factors. We hypothesize that exogenous factors secreted by brain tumor initiating cells (BTICs) could predispose normal neural precursor cells (NPCs) to transformation. When NPCs are grown in GBM-conditioned media, and designated as "tumor-conditioned NPCs" (tcNPCs), they become highly proliferative and exhibit increased stem cell self-renewal, or the unique ability of stem cells to asymmetrically generate another stem cell and a daughter cell. tcNPCs also show an increased transcript level of stem cell markers such as CD133 and ALDH and growth factor receptors such as VEGFR1, VEGFR2, EGFR and PDGFRα. Media analysis by ELISA of GBM-conditioned media reveals an elevated secretion of growth factors such as EGF, VEGF and PDGF-AA when compared to normal neural stem cell-conditioned media. We also demonstrate that tcNPCs require prolonged or continuous exposure to the GBM secretome in vitro to retain GBM BTIC characteristics. Our in vivo studies reveal that tcNPCs are unable to form tumors, confirming that irreversible transformation events may require sustained or prolonged presence of the GBM secretome. Analysis of GBM-conditioned media by mass spectrometry reveals the presence of secreted proteins Chitinase-3-like 1 (CHI3L1) and H2A histone family member H2AX. Collectively, our data suggest that GBM-secreted factors are capable of transiently altering normal NPCs, although for retention of the transformed phenotype, sustained or prolonged secretome exposure or additional transformation events are likely necessary.

Stimulation of neural differentiation in human bone marrow mesenchymal stem cells by extremely low-frequency electromagnetic fields incorporated with MNPs.

Science.gov (United States)

Choi, Yun-Kyong; Lee, Dong Heon; Seo, Young-Kwon; Jung, Hyun; Park, Jung-Keug; Cho, Hyunjin

2014-10-01

Human bone marrow-derived mesenchymal stem cells (hBM-MSCs) have been investigated as a new cell-therapeutic solution due to their capacity that could differentiate into neural-like cells. Extremely low-frequency electromagnetic fields (ELF-EMFs) therapy has emerged as a novel technique, using mechanical stimulus to differentiate hBM-MSCs and significantly enhance neuronal differentiation to affect cellular and molecular reactions. Magnetic iron oxide (Fe3O4) nanoparticles (MNPs) have recently achieved widespread use for biomedical applications and polyethylene glycol (PEG)-labeled nanoparticles are used to increase their circulation time, aqueous solubility, biocompatibility, and nonspecific cellular uptake as well as to decrease immunogenicity. Many studies have used MNP-labeled cells for differentiation, but there have been no reports of MNP-labeled neural differentiation combined with EMFs. In this study, synthesized PEG-phospholipid encapsulated magnetite (Fe3O4) nanoparticles are used on hBM-MSCs to improve their intracellular uptake. The PEGylated nanoparticles were exposed to the cells under 50 Hz of EMFs to improve neural differentiation. First, we measured cell viability and intracellular iron content in hBM-MSCs after treatment with MNPs. Analysis was conducted by RT-PCR, and immunohistological analysis using neural cell type-specific genes and antibodies after exposure to 50 Hz electromagnetic fields. These results suggest that electromagnetic fields enhance neural differentiation in hBM-MSCs incorporated with MNPs and would be an effective method for differentiating neural cells.

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles

International Nuclear Information System (INIS)

Oh, Jung-Hwa; Son, Mi-Young; Choi, Mi-Sun; Kim, Soojin; Choi, A-young; Lee, Hyang-Ae; Kim, Ki-Suk; Kim, Janghwan; Song, Chang Woo; Yoon, Seokjoo

2016-01-01

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10–200 μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24 h. The results showed that Ag NPs evoked significant toxicity in hESC-derived NPCs at 24 h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. - Highlights: • This system served as a suitable model for developmental neurotoxicity testing. • Ag NPs induce the apoptosis in human neural cells by ROS generation. • Genes for development of neurons were dysregulated in response to Ag NPs. • Molecular events during early developmental neurotoxicity were proposed.

Integrative analysis of genes and miRNA alterations in human embryonic stem cells-derived neural cells after exposure to silver nanoparticles

Energy Technology Data Exchange (ETDEWEB)

Oh, Jung-Hwa [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Son, Mi-Young [Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahangno, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Department of functional genomics, University of Science & Technology, 217 Gajungro, Yuseong-gu, Daejeon 34113 (Korea, Republic of); Choi, Mi-Sun; Kim, Soojin; Choi, A-young [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Lee, Hyang-Ae; Kim, Ki-Suk [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Kim, Janghwan [Korea Research Institute of Bioscience and Biotechnology (KRIBB), 125 Gwahangno, Yuseong-gu, Daejeon 34141 (Korea, Republic of); Department of functional genomics, University of Science & Technology, 217 Gajungro, Yuseong-gu, Daejeon 34113 (Korea, Republic of); Song, Chang Woo, E-mail: cwsong@kitox.re.kr [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of); Yoon, Seokjoo, E-mail: sjyoon@kitox.re.kr [Korea Institute of Toxicology (KIT), Daejeon 34114 (Korea, Republic of); Department of human and environmental toxicology, University of Science & Technology, Daejeon 34113 (Korea, Republic of)

2016-05-15

Given the rapid growth of engineered and customer products made of silver nanoparticles (Ag NPs), understanding their biological and toxicological effects on humans is critically important. The molecular developmental neurotoxic effects associated with exposure to Ag NPs were analyzed at the physiological and molecular levels, using an alternative cell model: human embryonic stem cell (hESC)-derived neural stem/progenitor cells (NPCs). In this study, the cytotoxic effects of Ag NPs (10–200 μg/ml) were examined in these hESC-derived NPCs, which have a capacity for neurogenesis in vitro, at 6 and 24 h. The results showed that Ag NPs evoked significant toxicity in hESC-derived NPCs at 24 h in a dose-dependent manner. In addition, Ag NPs induced cell cycle arrest and apoptosis following a significant increase in oxidative stress in these cells. To further clarify the molecular mechanisms of the toxicological effects of Ag NPs at the transcriptional and post-transcriptional levels, the global expression profiles of genes and miRNAs were analyzed in hESC-derived NPCs after Ag NP exposure. The results showed that Ag NPs induced oxidative stress and dysfunctional neurogenesis at the molecular level in hESC-derived NPCs. Based on this hESC-derived neural cell model, these findings have increased our understanding of the molecular events underlying developmental neurotoxicity induced by Ag NPs in humans. - Highlights: • This system served as a suitable model for developmental neurotoxicity testing. • Ag NPs induce the apoptosis in human neural cells by ROS generation. • Genes for development of neurons were dysregulated in response to Ag NPs. • Molecular events during early developmental neurotoxicity were proposed.

Classification of Company Performance using Weighted Probabilistic Neural Network

Science.gov (United States)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

Sacred or Neural?

DEFF Research Database (Denmark)

Runehov, Anne Leona Cesarine

Are religious spiritual experiences merely the product of the human nervous system? Anne L.C. Runehov investigates the potential of contemporary neuroscience to explain religious experiences. Following the footsteps of Michael Persinger, Andrew Newberg and Eugene d'Aquili she defines...... the terminological bounderies of "religious experiences" and explores the relevant criteria for the proper evaluation of scientific research, with a particular focus on the validity of reductionist models. Runehov's theis is that the perspectives looked at do not necessarily exclude each other but can be merged....... The question "sacred or neural?" becomes a statement "sacred and neural". The synergies thus produced provide manifold opportunities for interdisciplinary dialogue and research....

Breakout Prediction Based on BP Neural Network in Continuous Casting Process

Directory of Open Access Journals (Sweden)

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.

ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation

OpenAIRE

Visin, Francesco; Ciccone, Marco; Romero, Adriana; Kastner, Kyle; Cho, Kyunghyun; Bengio, Yoshua; Matteucci, Matteo; Courville, Aaron

2015-01-01

We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks (RNN) to retrieve distant dependencies. The proposed architecture, called ReSeg, is based on the recently introduced ReNet model for image classification. We modify and extend it to perform the more challenging task of semantic segmentation. Each ReNet layer is composed of four RNN that sweep the image horizontally ...

Differential Responses of Human Fetal Brain Neural Stem Cells to Zika Virus Infection

Directory of Open Access Journals (Sweden)

Erica L. McGrath

2017-03-01

Full Text Available Zika virus (ZIKV infection causes microcephaly in a subset of infants born to infected pregnant mothers. It is unknown whether human individual differences contribute to differential susceptibility of ZIKV-related neuropathology. Here, we use an Asian-lineage ZIKV strain, isolated from the 2015 Mexican outbreak (Mex1-7, to infect primary human neural stem cells (hNSCs originally derived from three individual fetal brains. All three strains of hNSCs exhibited similar rates of Mex1-7 infection and reduced proliferation. However, Mex1-7 decreased neuronal differentiation in only two of the three stem cell strains. Correspondingly, ZIKA-mediated transcriptome alterations were similar in these two strains but significantly different from that of the third strain with no ZIKV-induced neuronal reduction. This study thus confirms that an Asian-lineage ZIKV strain infects primary hNSCs and demonstrates a cell-strain-dependent response of hNSCs to ZIKV infection.

Differential Responses of Human Fetal Brain Neural Stem Cells to Zika Virus Infection.

Science.gov (United States)

McGrath, Erica L; Rossi, Shannan L; Gao, Junling; Widen, Steven G; Grant, Auston C; Dunn, Tiffany J; Azar, Sasha R; Roundy, Christopher M; Xiong, Ying; Prusak, Deborah J; Loucas, Bradford D; Wood, Thomas G; Yu, Yongjia; Fernández-Salas, Ildefonso; Weaver, Scott C; Vasilakis, Nikos; Wu, Ping

2017-03-14

Zika virus (ZIKV) infection causes microcephaly in a subset of infants born to infected pregnant mothers. It is unknown whether human individual differences contribute to differential susceptibility of ZIKV-related neuropathology. Here, we use an Asian-lineage ZIKV strain, isolated from the 2015 Mexican outbreak (Mex1-7), to infect primary human neural stem cells (hNSCs) originally derived from three individual fetal brains. All three strains of hNSCs exhibited similar rates of Mex1-7 infection and reduced proliferation. However, Mex1-7 decreased neuronal differentiation in only two of the three stem cell strains. Correspondingly, ZIKA-mediated transcriptome alterations were similar in these two strains but significantly different from that of the third strain with no ZIKV-induced neuronal reduction. This study thus confirms that an Asian-lineage ZIKV strain infects primary hNSCs and demonstrates a cell-strain-dependent response of hNSCs to ZIKV infection. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Long-term culture and differentiation of CNS precursors derived from anterior human neural rosettes following exposure to ventralizing factors

International Nuclear Information System (INIS)

Colleoni, Silvia; Galli, Cesare; Giannelli, Serena G.; Armentero, Marie-Therese; Blandini, Fabio; Broccoli, Vania; Lazzari, Giovanna

2010-01-01

In this study we demonstrated that neural rosettes derived from human ES cells can give rise either to neural crest precursors, following expansion in presence of bFGF and EGF, or to dopaminergic precursors after exposure to ventralizing factors Shh and FGF8. Both regionalised precursors are capable of extensive proliferation and differentiation towards the corresponding terminally differentiated cell types. In particular, peripheral neurons, cartilage, bone, smooth muscle cells and also pigmented cells were obtained from neural crest precursors while tyrosine hydroxylase and Nurr1 positive dopaminergic neurons were derived from FGF8 and Shh primed rosette cells. Gene expression and immunocytochemistry analyses confirmed the expression of dorsal and neural crest genes such as Sox10, Slug, p75, FoxD3, Pax7 in neural precursors from bFGF-EGF exposed rosettes. By contrast, priming of rosettes with FGF8 and Shh induced the expression of dopaminergic markers Engrailed1, Pax2, Pitx3, floor plate marker FoxA2 and radial glia markers Blbp and Glast, the latter in agreement with the origin of dopaminergic precursors from floor plate radial glia. Moreover, in vivo transplant of proliferating Shh/FGF8 primed precursors in parkinsonian rats demonstrated engraftment and terminal dopaminergic differentiation. In conclusion, we demonstrated the derivation of long-term self-renewing precursors of selected regional identity as potential cell reservoirs for cell therapy applications, such as CNS degenerative diseases, or for the development of toxicological tests.

Long-term culture and differentiation of CNS precursors derived from anterior human neural rosettes following exposure to ventralizing factors

Energy Technology Data Exchange (ETDEWEB)

Colleoni, Silvia, E-mail: silviacolleoni@avantea.it [Laboratorio di Tecnologie della Riproduzione, Avantea, Via Porcellasco 7/f, 26100 Cremona (Italy); Galli, Cesare [Laboratorio di Tecnologie della Riproduzione, Avantea, Via Porcellasco 7/f, 26100 Cremona (Italy); Dipartimento Clinico Veterinario, Universita di Bologna, Via Tolara di Sopra 50, 40064 Ozzano Emilia (Italy); Giannelli, Serena G. [Stem Cells and Neurogenesis Unit, Division of Neuroscience, San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan (Italy); Armentero, Marie-Therese; Blandini, Fabio [Laboratory of Functional Neurochemistry, Interdepartmental Research Center for Parkinson' s Disease, Neurological Institute C. Mondino, Via Mondino 2, 27100 Pavia (Italy); Broccoli, Vania, E-mail: broccoli.vania@hsr.it [Stem Cells and Neurogenesis Unit, Division of Neuroscience, San Raffaele Scientific Institute, Via Olgettina 58, 20132 Milan (Italy); Lazzari, Giovanna, E-mail: giovannalazzari@avantea.it [Laboratorio di Tecnologie della Riproduzione, Avantea, Via Porcellasco 7/f, 26100 Cremona (Italy)

2010-04-15

In this study we demonstrated that neural rosettes derived from human ES cells can give rise either to neural crest precursors, following expansion in presence of bFGF and EGF, or to dopaminergic precursors after exposure to ventralizing factors Shh and FGF8. Both regionalised precursors are capable of extensive proliferation and differentiation towards the corresponding terminally differentiated cell types. In particular, peripheral neurons, cartilage, bone, smooth muscle cells and also pigmented cells were obtained from neural crest precursors while tyrosine hydroxylase and Nurr1 positive dopaminergic neurons were derived from FGF8 and Shh primed rosette cells. Gene expression and immunocytochemistry analyses confirmed the expression of dorsal and neural crest genes such as Sox10, Slug, p75, FoxD3, Pax7 in neural precursors from bFGF-EGF exposed rosettes. By contrast, priming of rosettes with FGF8 and Shh induced the expression of dopaminergic markers Engrailed1, Pax2, Pitx3, floor plate marker FoxA2 and radial glia markers Blbp and Glast, the latter in agreement with the origin of dopaminergic precursors from floor plate radial glia. Moreover, in vivo transplant of proliferating Shh/FGF8 primed precursors in parkinsonian rats demonstrated engraftment and terminal dopaminergic differentiation. In conclusion, we demonstrated the derivation of long-term self-renewing precursors of selected regional identity as potential cell reservoirs for cell therapy applications, such as CNS degenerative diseases, or for the development of toxicological tests.

In vitro effects of Epidiferphane™ on adult human neural progenitor cells

Science.gov (United States)

Neural stem cells have the capacity to respond to their environment, migrate to the injury site and generate functional cell types, and thus they hold great promise for cell therapies. In addition to representing a source for central nervous system (CNS) repair, neural stem and progenitor cells als...

Beneficial effect of human induced pluripotent stem cell-derived neural precursors in spinal cord injury repair

Czech Academy of Sciences Publication Activity Database

Romanyuk, Nataliya; Amemori, Takashi; Turnovcová, Karolína; Procházka, Pavel; Onteniente, B.; Syková, Eva; Jendelová, Pavla

2015-01-01

Roč. 24, č. 9 (2015), s. 1781-1797 ISSN 0963-6897 R&D Projects: GA MŠk LH12024; GA ČR(CZ) GA13-00939S; GA ČR(CZ) GBP304/12/G069; GA MŠk(CZ) ED1.1.00/02.0109; GA MŠk(CZ) LO1309 Institutional support: RVO:68378041 Keywords : human induced pluripotent stem cells * neural precursors * spinal cord injury Subject RIV: FH - Neurology Impact factor: 3.427, year: 2015

Human conditionally immortalized neural stem cells improve locomotor function after spinal cord injury in the rat

Czech Academy of Sciences Publication Activity Database

Amemori, Takashi; Romanyuk, Nataliya; Jendelová, Pavla; Herynek, V.; Turnovcová, Karolína; Procházka, Pavel; Kapcalová, Miroslava; Cocks, G.; Price, J.; Syková, Eva

2013-01-01

Roč. 4, č. 3 (2013), s. 68 ISSN 1757-6512 R&D Projects: GA ČR(CZ) GAP304/12/1370; GA ČR GA13-00939S; GA MŠk LH12024; GA ČR(CZ) GBP304/12/G069 Grant - others:GA MZd(CZ) 00023001IKEM Institutional support: RVO:68378041 Keywords : human fetal neural stem cells * spinal cord injury * motor neuron differentiation Subject RIV: FH - Neurology Impact factor: 4.634, year: 2013

Composite modified Luneburg model of human eye lens.

Science.gov (United States)

Gómez-Correa, J E; Balderas-Mata, S E; Pierscionek, B K; Chávez-Cerda, S

2015-09-01

A new lens model based on the gradient-index Luneburg lens and composed of two oblate half spheroids of different curvatures is presented. The spherically symmetric Luneburg lens is modified to create continuous isoindicial contours and to incorporate curvatures that are similar to those found in a human lens. The imaging capabilities of the model and the changes in the gradient index profile are tested for five object distances, for a fixed geometry and for a fixed image distance. The central refractive index decreases with decreasing object distance. This indicates that in order to focus at the same image distance as is required in the eye, a decrease in refractive power is needed for rays from closer objects that meet the lens surface at steeper angles compared to rays from more distant objects. This ensures a highly focused image with no spherical aberration.

Modified Convolutional Neural Network Based on Dropout and the Stochastic Gradient Descent Optimizer

Directory of Open Access Journals (Sweden)

Jing Yang

2018-03-01

Full Text Available This study proposes a modified convolutional neural network (CNN algorithm that is based on dropout and the stochastic gradient descent (SGD optimizer (MCNN-DS, after analyzing the problems of CNNs in extracting the convolution features, to improve the feature recognition rate and reduce the time-cost of CNNs. The MCNN-DS has a quadratic CNN structure and adopts the rectified linear unit as the activation function to avoid the gradient problem and accelerate convergence. To address the overfitting problem, the algorithm uses an SGD optimizer, which is implemented by inserting a dropout layer into the all-connected and output layers, to minimize cross entropy. This study used the datasets MNIST, HCL2000, and EnglishHand as the benchmark data, analyzed the performance of the SGD optimizer under different learning parameters, and found that the proposed algorithm exhibited good recognition performance when the learning rate was set to [0.05, 0.07]. The performances of WCNN, MLP-CNN, SVM-ELM, and MCNN-DS were compared. Statistical results showed the following: (1 For the benchmark MNIST, the MCNN-DS exhibited a high recognition rate of 99.97%, and the time-cost of the proposed algorithm was merely 21.95% of MLP-CNN, and 10.02% of SVM-ELM; (2 Compared with SVM-ELM, the average improvement in the recognition rate of MCNN-DS was 2.35% for the benchmark HCL2000, and the time-cost of MCNN-DS was only 15.41%; (3 For the EnglishHand test set, the lowest recognition rate of the algorithm was 84.93%, the highest recognition rate was 95.29%, and the average recognition rate was 89.77%.

The Effects of Low-Dose Bisphenol A and Bisphenol F on Neural Differentiation of a Fetal Brain-Derived Neural Progenitor Cell Line.

Science.gov (United States)

Fujiwara, Yuki; Miyazaki, Wataru; Koibuchi, Noriyuki; Katoh, Takahiko

2018-01-01

Environmental chemicals are known to disrupt the endocrine system in humans and to have adverse effects on several organs including the developing brain. Recent studies indicate that exposure to environmental chemicals during gestation can interfere with neuronal differentiation, subsequently affecting normal brain development in newborns. Xenoestrogen, bisphenol A (BPA), which is widely used in plastic products, is one such chemical. Adverse effects of exposure to BPA during pre- and postnatal periods include the disruption of brain function. However, the effect of BPA on neural differentiation remains unclear. In this study, we explored the effects of BPA or bisphenol F (BPF), an alternative compound for BPA, on neural differentiation using ReNcell, a human fetus-derived neural progenitor cell line. Maintenance in growth factor-free medium initiated the differentiation of ReNcell to neuronal cells including neurons, astrocytes, and oligodendrocytes. We exposed the cells to BPA or BPF for 3 days from the period of initiation and performed real-time PCR for neural markers such as β III-tubulin and glial fibrillary acidic protein (GFAP), and Olig2. The β III-tubulin mRNA level decreased in response to BPA, but not BPF, exposure. We also observed that the number of β III-tubulin-positive cells in the BPA-exposed group was less than that of the control group. On the other hand, there were no changes in the MAP2 mRNA level. These results indicate that BPA disrupts neural differentiation in human-derived neural progenitor cells, potentially disrupting brain development.

The Effects of Low-Dose Bisphenol A and Bisphenol F on Neural Differentiation of a Fetal Brain-Derived Neural Progenitor Cell Line

Directory of Open Access Journals (Sweden)

Yuki Fujiwara

2018-02-01

Full Text Available Environmental chemicals are known to disrupt the endocrine system in humans and to have adverse effects on several organs including the developing brain. Recent studies indicate that exposure to environmental chemicals during gestation can interfere with neuronal differentiation, subsequently affecting normal brain development in newborns. Xenoestrogen, bisphenol A (BPA, which is widely used in plastic products, is one such chemical. Adverse effects of exposure to BPA during pre- and postnatal periods include the disruption of brain function. However, the effect of BPA on neural differentiation remains unclear. In this study, we explored the effects of BPA or bisphenol F (BPF, an alternative compound for BPA, on neural differentiation using ReNcell, a human fetus-derived neural progenitor cell line. Maintenance in growth factor-free medium initiated the differentiation of ReNcell to neuronal cells including neurons, astrocytes, and oligodendrocytes. We exposed the cells to BPA or BPF for 3 days from the period of initiation and performed real-time PCR for neural markers such as β III-tubulin and glial fibrillary acidic protein (GFAP, and Olig2. The β III-tubulin mRNA level decreased in response to BPA, but not BPF, exposure. We also observed that the number of β III-tubulin-positive cells in the BPA-exposed group was less than that of the control group. On the other hand, there were no changes in the MAP2 mRNA level. These results indicate that BPA disrupts neural differentiation in human-derived neural progenitor cells, potentially disrupting brain development.

Solving differential equations with unknown constitutive relations as recurrent neural networks

Energy Technology Data Exchange (ETDEWEB)

Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.; Tartakovsky, Alexandre M.

2017-12-08

We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learning literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.

Left-Right Asymmetry of Maturation Rates in Human Embryonic Neural Development.

Science.gov (United States)

de Kovel, Carolien G F; Lisgo, Steven; Karlebach, Guy; Ju, Jia; Cheng, Gang; Fisher, Simon E; Francks, Clyde

2017-08-01

Left-right asymmetry is a fundamental organizing feature of the human brain, and neuropsychiatric disorders such as schizophrenia sometimes involve alterations of brain asymmetry. As early as 8 weeks postconception, the majority of human fetuses move their right arms more than their left arms, but because nerve fiber tracts are still descending from the forebrain at this stage, spinal-muscular asymmetries are likely to play an important developmental role. We used RNA sequencing to measure gene expression levels in the left and right spinal cords, and the left and right hindbrains, of 18 postmortem human embryos aged 4 to 8 weeks postconception. Genes showing embryonic lateralization were tested for an enrichment of signals in genome-wide association data for schizophrenia. The left side of the embryonic spinal cord was found to mature faster than the right side. Both sides transitioned from transcriptional profiles associated with cell division and proliferation at earlier stages to neuronal differentiation and function at later stages, but the two sides were not in synchrony (p = 2.2 E-161). The hindbrain showed a left-right mirrored pattern compared with the spinal cord, consistent with the well-known crossing over of function between these two structures. Genes that showed lateralization in the embryonic spinal cord were enriched for association signals with schizophrenia (p = 4.3 E-05). These are the earliest stage left-right differences of human neural development ever reported. Disruption of the lateralized developmental program may play a role in the genetic susceptibility to schizophrenia. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

An efficient genotyping method for genome-modified animals and human cells generated with CRISPR/Cas9 system.

Science.gov (United States)

Zhu, Xiaoxiao; Xu, Yajie; Yu, Shanshan; Lu, Lu; Ding, Mingqin; Cheng, Jing; Song, Guoxu; Gao, Xing; Yao, Liangming; Fan, Dongdong; Meng, Shu; Zhang, Xuewen; Hu, Shengdi; Tian, Yong

2014-09-19

The rapid generation of various species and strains of laboratory animals using CRISPR/Cas9 technology has dramatically accelerated the interrogation of gene function in vivo. So far, the dominant approach for genotyping of genome-modified animals has been the T7E1 endonuclease cleavage assay. Here, we present a polyacrylamide gel electrophoresis-based (PAGE) method to genotype mice harboring different types of indel mutations. We developed 6 strains of genome-modified mice using CRISPR/Cas9 system, and utilized this approach to genotype mice from F0 to F2 generation, which included single and multiplexed genome-modified mice. We also determined the maximal detection sensitivity for detecting mosaic DNA using PAGE-based assay as 0.5%. We further applied PAGE-based genotyping approach to detect CRISPR/Cas9-mediated on- and off-target effect in human 293T and induced pluripotent stem cells (iPSCs). Thus, PAGE-based genotyping approach meets the rapidly increasing demand for genotyping of the fast-growing number of genome-modified animals and human cell lines created using CRISPR/Cas9 system or other nuclease systems such as TALEN or ZFN.

[Biological and neural bases of partner preferences in rodents: models to understand human pair bonds].

Science.gov (United States)

Coria-Avila, G A; Hernández-Aguilar, M E; Toledo-Cárdenas, R; García-Hernández, L I; Manzo, J; Pacheco, P; Miquel, M; Pfaus, J G

To analyse the biological and neural bases of partner preference formation in rodents as models to understand human pair bonding. Rodents are social individuals, capable of forming short- or long-lasting partner preferences that develop slowly by stimuli like cohabitation, or rapidly by stimuli like sex and stress. Dopamine, corticosteroids, oxytocin, vasopressin, and opioids form the neurochemical substrate for pair bonding in areas like the nucleus accumbens, the prefrontal cortex, the piriform cortex, the medial preoptic area, the ventral tegmental area and the medial amygdala, among others. Additional areas may participate depending on the nature of the conditioned stimuli by which and individual recognizes a preferred partner. Animal models help us understand that the capacity of an individual to display long-lasting and selective preferences depends on neural bases, selected throughout evolution. The challenge in neuroscience is to use this knowledge to create new solutions for mental problems associated with the incapacity of an individual to display a social bond, keep one, or cope with the disruption of a consolidated one.

Neural networks and their potential application in nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1991-01-01

A neural network is a data processing system consisting of a number of simple, highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Indeed, neural networks exhibit characteristics and capabilities not provided by any other technology. Examples include reading Japanese Kanji characters and human handwriting, reading a typewritten manuscript aloud, compensating for alignment errors in robots, interpreting very noise signals (e.g., electroencephalograms), modeling complex systems that cannot be modeled mathematically, and predicting whether proposed loans will be good or fail. This paper presents a brief tutorial on neural networks and describes research on the potential applications to nuclear power plants

The neural bases for valuing social equality.

Science.gov (United States)

Aoki, Ryuta; Yomogida, Yukihito; Matsumoto, Kenji

2015-01-01

The neural basis of how humans value and pursue social equality has become a major topic in social neuroscience research. Although recent studies have identified a set of brain regions and possible mechanisms that are involved in the neural processing of equality of outcome between individuals, how the human brain processes equality of opportunity remains unknown. In this review article, first we describe the importance of the distinction between equality of outcome and equality of opportunity, which has been emphasized in philosophy and economics. Next, we discuss possible approaches for empirical characterization of human valuation of equality of opportunity vs. equality of outcome. Understanding how these two concepts are distinct and interact with each other may provide a better explanation of complex human behaviors concerning fairness and social equality. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Perceived threat predicts the neural sequelae of combat stress

NARCIS (Netherlands)

van Wingen, G. A.; Geuze, E.; Vermetten, E.; Fernández, G.

2011-01-01

Exposure to severe stressors increases the risk for psychiatric disorders in vulnerable individuals, but can lead to positive outcomes for others. However, it remains unknown how severe stress affects neural functioning in humans and what factors mediate individual differences in the neural sequelae

Perceived threat predicts the neural sequelae of combat stress.

NARCIS (Netherlands)

Wingen, G.A. van; Geuze, E.; Vermetten, E.; Fernandez, G.S.E.

2011-01-01

Exposure to severe stressors increases the risk for psychiatric disorders in vulnerable individuals, but can lead to positive outcomes for others. However, it remains unknown how severe stress affects neural functioning in humans and what factors mediate individual differences in the neural sequelae

Neural networks and its application in biomedical engineering

International Nuclear Information System (INIS)

Husnain, S.K.; Bhatti, M.I.

2002-01-01

Artificial network (ANNs) is an information processing system that has certain performance characteristics in common with biological neural networks. A neural network is characterized by connections between the neurons, method of determining the weights on the connections and its activation functions while a biological neuron has three types of components that are of particular interest in understanding an artificial neuron: its dendrites, soma, and axon. The actin of the chemical transmitter modifies the incoming signal. The study of neural networks is an extremely interdisciplinary field. Computer-based diagnosis is an increasingly used method that tries to improve the quality of health care. Systems on Neural Networks have been developed extensively in the last ten years with the hope that medical diagnosis and therefore medical care would improve dramatically. The addition of a symbolic processing layer enhances the ANNs in a number of ways. It is, for instance, possible to supplement a network that is purely diagnostic with a level that recommends or nodes in order to more closely simulate the nervous system. (author)

INCREASED MATERNAL SERUM ALPHA-FETOPROTEIN AND HUMAN CHORIONIC-GONADOTROPIN IN COMPROMISED PREGNANCIES OTHER THAN FOR NEURAL-TUBE DEFECTS OR DOWN-SYNDROME

NARCIS (Netherlands)

BEEKHUIS, [No Value; VANLITH, JMM; DEWOLF, BTHM; MANTINGH, A

Intrauterine fetal death occurred in four women who were 'screen-positive' in a screening programme for neural tube defects (NTDs) and Down syndrome (DS). These women had very high levels of maternal serum alpha-fetoprotein (MSAFP) and maternal serum human chorionic gonadotropin (MShCG). Therefore,

Modulation of neural circuits: how stimulus context shapes innate behavior in Drosophila

OpenAIRE

Su, Chih-Ying; Wang, Jing W.

2014-01-01

Remarkable advances have been made in recent years in our understanding of innate behavior and the underlying neural circuits. In particular, a wealth of neuromodulatory mechanisms have been uncovered that can alter the input-output relationship of a hereditary neural circuit. It is now clear that this inbuilt flexibility allows animals to modify their behavioral responses according to environmental cues, metabolic demands and physiological states. Here, we discuss recent insights into how mo...

Real power transfer allocation method with the application of artificial neural network

Energy Technology Data Exchange (ETDEWEB)

Mustafa, M.W.; Khalid, S.N.; Shareef, H.; Khairuddin, A. [Technological Univ. of Malaysia, Skudai, Johor Bahru (Malaysia). Dept. of Electrical Power Enginering

2008-07-01

This paper presented a newly modified nodal equations method for identifying the real power transfer between generators and load. The objective was to represent each load current as a function of the generator's current and load voltages. The modified admittance matrix of a circuit was used to decompose the load voltage dependent term into components of generator dependent terms. By using these two decompositions of current and voltage terms, the real power transfer between loads and generators was obtained. The robustness of the proposed method was demonstrated on the modified IEEE 30-bus system. An appropriate Artificial Neural Network (ANN) was also created to solve the same problem in a simpler and faster manner with very good accuracy. For this purpose, supervised learning paradigm and feedforward architecture were chosen for the proposed ANN power transfer allocation technique. The method could be adapted to other larger systems by modifying the neural network structure. This technique can be used to solve some of the difficult real power pricing and costing issues and to ensure fairness and transparency in the deregulated environment of power system operation. 22 refs., 5 tabs., 8 figs.

Anomaly detection in an automated safeguards system using neural networks

International Nuclear Information System (INIS)

Whiteson, R.; Howell, J.A.

1992-01-01

An automated safeguards system must be able to detect an anomalous event, identify the nature of the event, and recommend a corrective action. Neural networks represent a new way of thinking about basic computational mechanisms for intelligent information processing. In this paper, we discuss the issues involved in applying a neural network model to the first step of this process: anomaly detection in materials accounting systems. We extend our previous model to a 3-tank problem and compare different neural network architectures and algorithms. We evaluate the computational difficulties in training neural networks and explore how certain design principles affect the problems. The issues involved in building a neural network architecture include how the information flows, how the network is trained, how the neurons in a network are connected, how the neurons process information, and how the connections between neurons are modified. Our approach is based on the demonstrated ability of neural networks to model complex, nonlinear, real-time processes. By modeling the normal behavior of the processes, we can predict how a system should be behaving and, therefore, detect when an abnormality occurs

Artificial intelligence: Deep neural reasoning

Science.gov (United States)

Jaeger, Herbert

2016-10-01

The human brain can solve highly abstract reasoning problems using a neural network that is entirely physical. The underlying mechanisms are only partially understood, but an artificial network provides valuable insight. See Article p.471

IR wireless cluster synapses of HYDRA very large neural networks

Science.gov (United States)

Jannson, Tomasz; Forrester, Thomas

2008-04-01

RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

Spontaneous calcium transients in human neural progenitor cells mediated by transient receptor potential channels.

Science.gov (United States)

Morgan, Peter J; Hübner, Rayk; Rolfs, Arndt; Frech, Moritz J

2013-09-15

Calcium signals affect many developmental processes, including proliferation, migration, survival, and apoptosis, processes that are of particular importance in stem cells intended for cell replacement therapies. The mechanisms underlying Ca(2+) signals, therefore, have a role in determining how stem cells respond to their environment, and how these responses might be controlled in vitro. In this study, we examined the spontaneous Ca(2+) activity in human neural progenitor cells during proliferation and differentiation. Pharmacological characterization indicates that in proliferating cells, most activity is the result of transient receptor potential (TRP) channels that are sensitive to Gd(3+) and La(3+), with the more subtype selective antagonist Ruthenium red also reducing activity, suggesting the involvement of transient receptor potential vanilloid (TRPV) channels. In differentiating cells, Gd(3+) and La(3+)-sensitive TRP channels also appear to underlie the spontaneous activity; however, no sub-type-specific antagonists had any effect. Protein levels of TRPV2 and TRPV3 decreased in differentiated cells, which is demonstrated by western blot. Thus, it appears that TRP channels represent the main route of Ca(2+) entry in human neural progenitor cells (hNPCs), but the responsible channel types are subject to substitution under differentiating conditions. The level of spontaneous activity could be increased and decreased by lowering and raising the extracellular K(+) concentration. Proliferating cells in low K(+) slowed the cell cycle, with a disproportionate increased percentage of cells in G1 phase and a reduction in S phase. Taken together, these results suggest a link between external K(+) concentration, spontaneous Ca(2+) transients, and cell cycle distribution, which is able to influence the fate of stem and progenitor cells.

A Modified Feature Selection and Artificial Neural Network-Based Day-Ahead Load Forecasting Model for a Smart Grid

Directory of Open Access Journals (Sweden)

Ashfaq Ahmad

2015-12-01

Full Text Available In the operation of a smart grid (SG, day-ahead load forecasting (DLF is an important task. The SG can enhance the management of its conventional and renewable resources with a more accurate DLF model. However, DLF model development is highly challenging due to the non-linear characteristics of load time series in SGs. In the literature, DLF models do exist; however, these models trade off between execution time and forecast accuracy. The newly-proposed DLF model will be able to accurately predict the load of the next day with a fair enough execution time. Our proposed model consists of three modules; the data preparation module, feature selection and the forecast module. The first module makes the historical load curve compatible with the feature selection module. The second module removes redundant and irrelevant features from the input data. The third module, which consists of an artificial neural network (ANN, predicts future load on the basis of selected features. Moreover, the forecast module uses a sigmoid function for activation and a multi-variate auto-regressive model for weight updating during the training process. Simulations are conducted in MATLAB to validate the performance of our newly-proposed DLF model in terms of accuracy and execution time. Results show that our proposed modified feature selection and modified ANN (m(FS + ANN-based model for SGs is able to capture the non-linearity(ies in the history load curve with 97 . 11 % accuracy. Moreover, this accuracy is achieved at the cost of a fair enough execution time, i.e., we have decreased the average execution time of the existing FS + ANN-based model by 38 . 50 % .

Genotoxic effect and antigen binding characteristics of SLE auto-antibodies to peroxynitrite-modified human DNA.

Science.gov (United States)

Khan, Md Asad; Alam, Khursheed; Mehdi, Syed Hassan; Rizvi, M Moshahid A

2017-12-01

Systemic lupus erythematosus (SLE) is an inflammatory autoimmune disease characterized by auto-antibodies against native deoxyribonucleic acid after modification and is one of the reasons for the development of SLE. Here, we have evaluated the structural perturbations in human placental DNA by peroxynitrite using spectroscopy, thermal denaturation and high-performance liquid chromatography (HPLC). Peroxynitrite is a powerful potent bi-functional oxidative/nitrative agent that is produced both endogenously and exogenously. In experimental animals, the peroxynitrite-modified DNA was found to be highly immunogenic. The induced antibodies showed cross-reactions with different types of DNA and nitrogen bases that were modified with peroxynitrite by inhibition ELISA. The antibody activity was inhibited by approximately 89% with its immunogen as the inhibitor. The antigen-antibodies interaction between induced antibodies with peroxynitrite-modified DNA showed retarded mobility as compared to the native form. Furthermore, significantly increased binding was also observed in SLE autoantibodies with peroxynitrite-modified DNA than native form. Moreover, DNA isolated from lymphocyte of SLE patients revealed significant recognition of anti-peroxynitrite-modified DNA immunoglobulin G (IgG). Our data indicates that DNA modified with peroxynitrite presents unique antigenic determinants that may induce autoantibody response in SLE. Copyright © 2017 Elsevier Inc. All rights reserved.

A computational model incorporating neural stem cell dynamics reproduces glioma incidence across the lifespan in the human population.

Directory of Open Access Journals (Sweden)

Roman Bauer

Full Text Available Glioma is the most common form of primary brain tumor. Demographically, the risk of occurrence increases until old age. Here we present a novel computational model to reproduce the probability of glioma incidence across the lifespan. Previous mathematical models explaining glioma incidence are framed in a rather abstract way, and do not directly relate to empirical findings. To decrease this gap between theory and experimental observations, we incorporate recent data on cellular and molecular factors underlying gliomagenesis. Since evidence implicates the adult neural stem cell as the likely cell-of-origin of glioma, we have incorporated empirically-determined estimates of neural stem cell number, cell division rate, mutation rate and oncogenic potential into our model. We demonstrate that our model yields results which match actual demographic data in the human population. In particular, this model accounts for the observed peak incidence of glioma at approximately 80 years of age, without the need to assert differential susceptibility throughout the population. Overall, our model supports the hypothesis that glioma is caused by randomly-occurring oncogenic mutations within the neural stem cell population. Based on this model, we assess the influence of the (experimentally indicated decrease in the number of neural stem cells and increase of cell division rate during aging. Our model provides multiple testable predictions, and suggests that different temporal sequences of oncogenic mutations can lead to tumorigenesis. Finally, we conclude that four or five oncogenic mutations are sufficient for the formation of glioma.

Design of Robust Neural Network Classifiers

DEFF Research Database (Denmark)

Larsen, Jan; Andersen, Lars Nonboe; Hintz-Madsen, Mads

1998-01-01

This paper addresses a new framework for designing robust neural network classifiers. The network is optimized using the maximum a posteriori technique, i.e., the cost function is the sum of the log-likelihood and a regularization term (prior). In order to perform robust classification, we present...... a modified likelihood function which incorporates the potential risk of outliers in the data. This leads to the introduction of a new parameter, the outlier probability. Designing the neural classifier involves optimization of network weights as well as outlier probability and regularization parameters. We...... suggest to adapt the outlier probability and regularisation parameters by minimizing the error on a validation set, and a simple gradient descent scheme is derived. In addition, the framework allows for constructing a simple outlier detector. Experiments with artificial data demonstrate the potential...

Bioactivity of a modified human Glucagon-like peptide-1.

Directory of Open Access Journals (Sweden)

Fangfang Xu

Full Text Available Diabetes has become the third largest cause of death in humans worldwide. Therefore, effective treatment for this disease remains a critical issue. Glucagon-like peptide-1 (GLP-1 plays an important role in glucose homeostasis, and therefore represents a promising candidate to use for the treatment of diabetes. Native GLP-1, however, is quickly degraded in in the circulatory system; which limits its clinical application. In the present study, a chemically-synthesized, modified analogue of human GLP-1 (mGLP-1 was designed. Our analyses indicated that, relative to native GLP-1, mGLP-1 is more resistant to trypsin and pancreatin degradation. mGLP-1 promotes mouse pancreatic β-cell proliferation by up-regulating the expression level of cyclin E, CDK2, Bcl-2 and down-regulating Bax, p21, and stimulates insulin secretion. An oral glucose tolerance test indicated that mGLP-1 significantly improved glucose tolerance in mice. Intraperitoneal injections of mGLP-1 into streptozotocin (STZ-induced type 2 diabetic mice significantly reduced blood sugar levels and stimulated insulin secretion. Oral gavages of mGLP-1 in diabetic mice did not result in significant hypoglycemic activity.

Sequential and parallel image restoration: neural network implementations.

Science.gov (United States)

Figueiredo, M T; Leitao, J N

1994-01-01

Sequential and parallel image restoration algorithms and their implementations on neural networks are proposed. For images degraded by linear blur and contaminated by additive white Gaussian noise, maximum a posteriori (MAP) estimation and regularization theory lead to the same high dimension convex optimization problem. The commonly adopted strategy (in using neural networks for image restoration) is to map the objective function of the optimization problem into the energy of a predefined network, taking advantage of its energy minimization properties. Departing from this approach, we propose neural implementations of iterative minimization algorithms which are first proved to converge. The developed schemes are based on modified Hopfield (1985) networks of graded elements, with both sequential and parallel updating schedules. An algorithm supported on a fully standard Hopfield network (binary elements and zero autoconnections) is also considered. Robustness with respect to finite numerical precision is studied, and examples with real images are presented.

Modulation of neural circuits: how stimulus context shapes innate behavior in Drosophila.

Science.gov (United States)

Su, Chih-Ying; Wang, Jing W

2014-12-01

Remarkable advances have been made in recent years in our understanding of innate behavior and the underlying neural circuits. In particular, a wealth of neuromodulatory mechanisms have been uncovered that can alter the input-output relationship of a hereditary neural circuit. It is now clear that this inbuilt flexibility allows animals to modify their behavioral responses according to environmental cues, metabolic demands and physiological states. Here, we discuss recent insights into how modulation of neural circuits impacts innate behavior, with a special focus on how environmental cues and internal physiological states shape different aspects of feeding behavior in Drosophila. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

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

2015-06-01

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

Neural decoding of collective wisdom with multi-brain computing.

Science.gov (United States)

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally

Markers of neural degeneration and regeneration in Down ...

African Journals Online (AJOL)

Iman Ehsan Abdel-Meguid

2012-11-02

Nov 2, 2012 ... The Egyptian Journal of Medical Human Genetics www.ejmhg.eg.net ... stem cells (TCSCs), including neural TCSCs and endothelial. TCSCs [10,11]. ..... directs human embryonic stem cell proliferation and differentia- tion into.

Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

Hypothetical Pattern Recognition Design Using Multi-Layer Perceptorn Neural Network For Supervised Learning

Directory of Open Access Journals (Sweden)

Md. Abdullah-al-mamun

2015-08-01

Full Text Available Abstract Humans are capable to identifying diverse shape in the different pattern in the real world as effortless fashion due to their intelligence is grow since born with facing several learning process. Same way we can prepared an machine using human like brain called Artificial Neural Network that can be recognize different pattern from the real world object. Although the various techniques is exists to implementation the pattern recognition but recently the artificial neural network approaches have been giving the significant attention. Because the approached of artificial neural network is like a human brain that is learn from different observation and give a decision the previously learning rule. Over the 50 years research now a days pattern recognition for machine learning using artificial neural network got a significant achievement. For this reason many real world problem can be solve by modeling the pattern recognition process. The objective of this paper is to present the theoretical concept for pattern recognition design using Multi-Layer Perceptorn neural networkin the algorithm of artificial Intelligence as the best possible way of utilizing available resources to make a decision that can be a human like performance.

Neural codes of seeing architectural styles

OpenAIRE

Choo, Heeyoung; Nasar, Jack L.; Nikrahei, Bardia; Walther, Dirk B.

2017-01-01

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people′s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding sugges...

Interaction of adult human neural crest-derived stem cells with a nanoporous titanium surface is sufficient to induce their osteogenic differentiation

Directory of Open Access Journals (Sweden)

Matthias Schürmann

2014-07-01

Full Text Available Osteogenic differentiation of various adult stem cell populations such as neural crest-derived stem cells is of great interest in the context of bone regeneration. Ideally, exogenous differentiation should mimic an endogenous differentiation process, which is partly mediated by topological cues. To elucidate the osteoinductive potential of porous substrates with different pore diameters (30 nm, 100 nm, human neural crest-derived stem cells isolated from the inferior nasal turbinate were cultivated on the surface of nanoporous titanium covered membranes without additional chemical or biological osteoinductive cues. As controls, flat titanium without any topological features and osteogenic medium was used. Cultivation of human neural crest-derived stem cells on 30 nm pores resulted in osteogenic differentiation as demonstrated by alkaline phosphatase activity after seven days as well as by calcium deposition after 3 weeks of cultivation. In contrast, cultivation on flat titanium and on membranes equipped with 100 nm pores was not sufficient to induce osteogenic differentiation. Moreover, we demonstrate an increase of osteogenic transcripts including Osterix, Osteocalcin and up-regulation of Integrin β1 and α2 in the 30 nm pore approach only. Thus, transplantation of stem cells pre-cultivated on nanostructured implants might improve the clinical outcome by support of the graft adherence and acceleration of the regeneration process.

Cetuximab modified collagen scaffold directs neurogenesis of injury-activated endogenous neural stem cells for acute spinal cord injury repair.

Science.gov (United States)

Li, Xing; Zhao, Yannan; Cheng, Shixiang; Han, Sufang; Shu, Muya; Chen, Bing; Chen, Xuyi; Tang, Fengwu; Wang, Nuo; Tu, Yue; Wang, Bin; Xiao, Zhifeng; Zhang, Sai; Dai, Jianwu

2017-08-01

Studies have shown that endogenous neural stem cells (NSCs) activated by spinal cord injury (SCI) primarily generate astrocytes to form glial scar. The NSCs do not differentiate into neurons because of the adverse microenvironment. In this study, we defined the activation timeline of endogenous NSCs in rats with severe SCI. These injury-activated NSCs then migrated into the lesion site. Cetuximab, an EGFR signaling antagonist, significantly increased neurogenesis in the lesion site. Meanwhile, implanting cetuximab modified linear ordered collagen scaffolds (LOCS) into SCI lesion sites in dogs resulted in neuronal regeneration, including neuronal differentiation, maturation, myelination, and synapse formation. The neuronal regeneration eventually led to a significant locomotion recovery. Furthermore, LOCS implantation could also greatly decrease chondroitin sulfate proteoglycan (CSPG) deposition at the lesion site. These findings suggest that endogenous neurogenesis following acute complete SCI is achievable in species ranging from rodents to large animals via functional scaffold implantation. LOCS-based Cetuximab delivery system has a promising therapeutic effect on activating endogenous neurogenesis, reducing CSPGs deposition and improving motor function recovery. Copyright © 2017 Elsevier Ltd. All rights reserved.

Heart murmur detection based on wavelet transformation and a synergy between artificial neural network and modified neighbor annealing methods.

Science.gov (United States)

Eslamizadeh, Gholamhossein; Barati, Ramin

2017-05-01

Early recognition of heart disease plays a vital role in saving lives. Heart murmurs are one of the common heart problems. In this study, Artificial Neural Network (ANN) is trained with Modified Neighbor Annealing (MNA) to classify heart cycles into normal and murmur classes. Heart cycles are separated from heart sounds using wavelet transformer. The network inputs are features extracted from individual heart cycles, and two classification outputs. Classification accuracy of the proposed model is compared with five multilayer perceptron trained with Levenberg-Marquardt, Extreme-learning-machine, back-propagation, simulated-annealing, and neighbor-annealing algorithms. It is also compared with a Self-Organizing Map (SOM) ANN. The proposed model is trained and tested using real heart sounds available in the Pascal database to show the applicability of the proposed scheme. Also, a device to record real heart sounds has been developed and used for comparison purposes too. Based on the results of this study, MNA can be used to produce considerable results as a heart cycle classifier. Copyright © 2017 Elsevier B.V. All rights reserved.

Amelioration of motor/sensory dysfunction and spasticity in a rat model of acute lumbar spinal cord injury by human neural stem cell transplantation

Czech Academy of Sciences Publication Activity Database

van Gorp, S.; Leerink, M.; Kakinohana, O.; Platoshyn, O.; Santucci, C.; Galik, J.; Joosten, E. A.; Hruška-Plocháň, Marian; Goldberg, D.; Marsala, S.; Johe, K.; Ciacci, J. D.; Marsala, M.

2013-01-01

Roč. 4, č. 57 (2013) ISSN 1757-6512 Institutional support: RVO:67985904 Keywords : spinal cord injury * human neural stem cells * spinal grafting * functional recovery * rat Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 4.634, year: 2013

Neural synchronization during face-to-face communication.

Science.gov (United States)

Jiang, Jing; Dai, Bohan; Peng, Danling; Zhu, Chaozhe; Liu, Li; Lu, Chunming

2012-11-07

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

Human iPSC-Derived Neural Progenitors Are an Effective Drug Discovery Model for Neurological mtDNA Disorders.

Science.gov (United States)

Lorenz, Carmen; Lesimple, Pierre; Bukowiecki, Raul; Zink, Annika; Inak, Gizem; Mlody, Barbara; Singh, Manvendra; Semtner, Marcus; Mah, Nancy; Auré, Karine; Leong, Megan; Zabiegalov, Oleksandr; Lyras, Ekaterini-Maria; Pfiffer, Vanessa; Fauler, Beatrix; Eichhorst, Jenny; Wiesner, Burkhard; Huebner, Norbert; Priller, Josef; Mielke, Thorsten; Meierhofer, David; Izsvák, Zsuzsanna; Meier, Jochen C; Bouillaud, Frédéric; Adjaye, James; Schuelke, Markus; Wanker, Erich E; Lombès, Anne; Prigione, Alessandro

2017-05-04

Mitochondrial DNA (mtDNA) mutations frequently cause neurological diseases. Modeling of these defects has been difficult because of the challenges associated with engineering mtDNA. We show here that neural progenitor cells (NPCs) derived from human induced pluripotent stem cells (iPSCs) retain the parental mtDNA profile and exhibit a metabolic switch toward oxidative phosphorylation. NPCs derived in this way from patients carrying a deleterious homoplasmic mutation in the mitochondrial gene MT-ATP6 (m.9185T>C) showed defective ATP production and abnormally high mitochondrial membrane potential (MMP), plus altered calcium homeostasis, which represents a potential cause of neural impairment. High-content screening of FDA-approved drugs using the MMP phenotype highlighted avanafil, which we found was able to partially rescue the calcium defect in patient NPCs and differentiated neurons. Overall, our results show that iPSC-derived NPCs provide an effective model for drug screening to target mtDNA disorders that affect the nervous system. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural crest stem cell population in craniomaxillofacial development and tissue repair

Directory of Open Access Journals (Sweden)

M La Noce

2014-10-01

Full Text Available Neural crest cells, delaminating from the neural tube during migration, undergo an epithelial-mesenchymal transition and differentiate into several cell types strongly reinforcing the mesoderm of the craniofacial body area – giving rise to bone, cartilage and other tissues and cells of this human body area. Recent studies on craniomaxillofacial neural crest-derived cells have provided evidence for the tremendous plasticity of these cells. Actually, neural crest cells can respond and adapt to the environment in which they migrate and the cranial mesoderm plays an important role toward patterning the identity of the migrating neural crest cells. In our experience, neural crest-derived stem cells, such as dental pulp stem cells, can actively proliferate, repair bone and give rise to other tissues and cytotypes, including blood vessels, smooth muscle, adipocytes and melanocytes, highlighting that their use in tissue engineering is successful. In this review, we provide an overview of the main pathways involved in neural crest formation, delamination, migration and differentiation; and, in particular, we concentrate our attention on the translatability of the latest scientific progress. Here we try to suggest new ideas and strategies that are needed to fully develop the clinical use of these cells. This effort should involve both researchers/clinicians and improvements in good manufacturing practice procedures. It is important to address studies towards clinical application or take into consideration that studies must have an effective therapeutic prospect for humans. New approaches and ideas must be concentrated also toward stem cell recruitment and activation within the human body, overcoming the classical grafting.

Neural Differentiation of Human Pluripotent Stem Cells for Nontherapeutic Applications: Toxicology, Pharmacology, and In Vitro Disease Modeling

Directory of Open Access Journals (Sweden)

May Shin Yap

2015-01-01

Full Text Available Human pluripotent stem cells (hPSCs derived from either blastocyst stage embryos (hESCs or reprogrammed somatic cells (iPSCs can provide an abundant source of human neuronal lineages that were previously sourced from human cadavers, abortuses, and discarded surgical waste. In addition to the well-known potential therapeutic application of these cells in regenerative medicine, these are also various promising nontherapeutic applications in toxicological and pharmacological screening of neuroactive compounds, as well as for in vitro modeling of neurodegenerative and neurodevelopmental disorders. Compared to alternative research models based on laboratory animals and immortalized cancer-derived human neural cell lines, neuronal cells differentiated from hPSCs possess the advantages of species specificity together with genetic and physiological normality, which could more closely recapitulate in vivo conditions within the human central nervous system. This review critically examines the various potential nontherapeutic applications of hPSC-derived neuronal lineages and gives a brief overview of differentiation protocols utilized to generate these cells from hESCs and iPSCs.

Genetically-modified pig mesenchymal stromal cells: xenoantigenicity and effect on human T-cell xenoresponses.

Science.gov (United States)

Ezzelarab, Mohamed; Ezzelarab, Corin; Wilhite, Tyler; Kumar, Goutham; Hara, Hidetaka; Ayares, David; Cooper, David K C

2011-01-01

Mesenchymal stromal cells (MSC) are being investigated as immunomodulatory therapy in the field of transplantation, particularly islet transplantation. While MSC can regenerate across species barriers, the immunoregulatory influence of genetically modified pig MSC (pMSC) on the human and non-human primate T-cell responses has not been studied. Mesenchymal stromal cells from wild-type (WT), α1,3-galactosyltransferase gene knockout (GTKO) and GTKO pigs transgenic for the human complement-regulatory protein CD46 (GTKO/CD46) were isolated and tested for differentiation. Antibody binding and T-cell responses to WT and GTKO pMSC in comparison with GTKO pig aortic endothelial cells (pAEC) were investigated. The expression of swine leukocyte antigen (SLA) class II (SLA II) was tested. Costimulatory molecules CD80 and CD86 mRNA levels were measured. Human T-cell proliferation and the production of pro-inflammatory cytokines in response to GTKO and GTKO/CD46 pMSC in comparison with human MSC (hMSC) were evaluated. α1,3-galactosyltransferase gene knockout and GTKO/CD46 pMSC isolation and differentiation were achieved in vitro. Binding of human antibodies and T-cell responses were lower to GTKO than those to WT pMSC. Human and baboon (naïve and sensitized) antibody binding were significantly lower to GTKO pMSC than to GTKO pAEC. Before activation, human CD4(+) T-cell response to GTKO pMSC was significantly weaker than that to GTKO pAEC, even after pIFN-γ activation. More than 99% of GTKO/CD46 pMSC expressed hCD46. Human peripheral blood mononuclear cells and CD4(+) T-cell responses to GTKO and GTKO/CD46 pMSC were comparable with those to hMSC, and all were significantly lower than to GTKO pAEC. GTKO/CD46 pMSC downregulated human T-cell proliferation as efficiently as hMSC. The level of proinflammatory cytokines IL-2, IFN-γ, TNF-α, and sCD40L correlated with the downregulation of T-cell proliferation by all types of MSC. Genetically modified pMSC is significantly less

Decreased neural precursor cell pool in NADPH oxidase 2-deficiency: From mouse brain to neural differentiation of patient derived iPSC

Directory of Open Access Journals (Sweden)

Zeynab Nayernia

2017-10-01

Full Text Available There is emerging evidence for the involvement of reactive oxygen species (ROS in the regulation of stem cells and cellular differentiation. Absence of the ROS-generating NADPH oxidase NOX2 in chronic granulomatous disease (CGD patients, predominantly manifests as immune deficiency, but has also been associated with decreased cognition. Here, we investigate the role of NOX enzymes in neuronal homeostasis in adult mouse brain and in neural cells derived from human induced pluripotent stem cells (iPSC. High levels of NOX2 were found in mouse adult neurogenic regions. In NOX2-deficient mice, neurogenic regions showed diminished redox modifications, as well as decrease in neuroprecursor numbers and in expression of genes involved in neural differentiation including NES, BDNF and OTX2. iPSC from healthy subjects and patients with CGD were used to study the role of NOX2 in human in vitro neuronal development. Expression of NOX2 was low in undifferentiated iPSC, upregulated upon neural induction, and disappeared during neuronal differentiation. In human neurospheres, NOX2 protein and ROS generation were polarized within the inner cell layer of rosette structures. NOX2 deficiency in CGD-iPSCs resulted in an abnormal neural induction in vitro, as revealed by a reduced expression of neuroprogenitor markers (NES, BDNF, OTX2, NRSF/REST, and a decreased generation of mature neurons. Vector-mediated NOX2 expression in NOX2-deficient iPSCs rescued neurogenesis. Taken together, our study provides novel evidence for a regulatory role of NOX2 during early stages of neurogenesis in mouse and human.

Analysis of neural activity in human motor cortex -- Towards brain machine interface system

Science.gov (United States)

Secundo, Lavi

, the correlation of ECoG activity to kinematic parameters of arm movement is context-dependent, an important constraint to consider in future development of BMI systems. The third chapter delves into a fundamental organizational principle of the primate motor system---cortical control of contralateral limb movements. However, ipsilateral motor areas also appear to play a role in the control of ipsilateral limb movements. Several studies in monkeys have shown that individual neurons in ipsilateral primary motor cortex (M1) may represent, on average, the direction of movements of the ipsilateral arm. Given the increasing body of evidence demonstrating that neural ensembles can reliably represent information with a high temporal resolution, here we characterize the distributed neural representation of ipsilateral upper limb kinematics in both monkey and man. In two macaque monkeys trained to perform center-out reaching movements, we found that the ensemble spiking activity in M1 could continuously represent ipsilateral limb position. We also recorded cortical field potentials from three human subjects and also consistently found evidence of a neural representation for ipsilateral movement parameters. Together, our results demonstrate the presence of a high-fidelity neural representation for ipsilateral movement and illustrates that it can be successfully incorporated into a brain-machine interface.

Integration of Neural Networks and Cellular Automata for Urban Planning

Institute of Scientific and Technical Information of China (English)

Anthony Gar-on Yeh; LI Xia

2004-01-01

This paper presents a new type of cellular automata (CA) model for the simulation of alternative land development using neural networks for urban planning. CA models can be regarded as a planning tool because they can generate alternative urban growth. Alternative development patterns can be formed by using different sets of parameter values in CA simulation. A critical issue is how to define parameter values for realistic and idealized simulation. This paper demonstrates that neural networks can simplify CA models but generate more plausible results. The simulation is based on a simple three-layer network with an output neuron to generate conversion probability. No transition rules are required for the simulation. Parameter values are automatically obtained from the training of network by using satellite remote sensing data. Original training data can be assessed and modified according to planning objectives. Alternative urban patterns can be easily formulated by using the modified training data sets rather than changing the model.

Neuronal regeneration in injured rat spinal cord after human dental pulp derived neural crest stem cell transplantation.

Science.gov (United States)

Kabatas, S; Demir, C S; Civelek, E; Yilmaz, I; Kircelli, A; Yilmaz, C; Akyuva, Y; Karaoz, E

2018-01-01

This study aimed to analyze the effect of human Dental Pulp-Neural Crest Stem Cells (hDP-NCSCs) delivery on lesion site after spinal cord injury (SCI), and to observe the functional recovery after transplantation. Neural Crest Stem Cells (NCSCs) were isolated from human Dental Pulp (hDP). The experimental rat population was divided into four groups (n = 6/24). Their behavioral motility was scored regularly. After 4-weeks, rats were sacrificed, and their spinal cords were examined for Green Fluorescent Protein (GFP) labeled hDP-NCSCs by immunofluorescence (IF) staining. In early post-injury (p.i) period, the ultrastructure of spinal cord tissue was preserved in Group 4. The majority of cells forming the ependymal region around the central canal were found to be hDP-NCSCs. While the grey-and-white-matter around the ependymal region was composed of e.g. GFP cells, with astrocytic-like appearance. The scores showed significant motor recovery in hind limb functions in Group 4. However, no obvious change was observed in other groups. Cells e.g., mesenchymal (Vimentin+) which express GFP+ cells in the gray-and-white-matter around the ependymal region could indicate the potential to self-renewal and plasticity. Thus, transplantation of hDP-NCSCs might be an effective strategy to improve functional recovery following spinal cord trauma (Fig. 10, Ref. 32).

Cross-Linguistic Differences in the Neural Representation of Human Language: Evidence from Users of Signed Languages

Science.gov (United States)

Corina, David P.; Lawyer, Laurel A.; Cates, Deborah

2013-01-01

Studies of deaf individuals who are users of signed languages have provided profound insight into the neural representation of human language. Case studies of deaf signers who have incurred left- and right-hemisphere damage have shown that left-hemisphere resources are a necessary component of sign language processing. These data suggest that, despite frank differences in the input and output modality of language, core left perisylvian regions universally serve linguistic function. Neuroimaging studies of deaf signers have generally provided support for this claim. However, more fine-tuned studies of linguistic processing in deaf signers are beginning to show evidence of important differences in the representation of signed and spoken languages. In this paper, we provide a critical review of this literature and present compelling evidence for language-specific cortical representations in deaf signers. These data lend support to the claim that the neural representation of language may show substantive cross-linguistic differences. We discuss the theoretical implications of these findings with respect to an emerging understanding of the neurobiology of language. PMID:23293624

In vitro culture and characterization of enteric neural precursor cells from human gut biopsy specimens using polymer scaffold.

Science.gov (United States)

Krishnamohan, Janardhanam; Senthilnathan, Venugopal S; Vaikundaraman, Tirunelveli Muthiah; Srinivasan, Thangavelu; Balamurugan, Madasamy; Iwasaki, Masaru; Preethy, Senthilkumar; Abraham, Samuel Jk

2013-08-01

In vitro expansion and characterization of neural precursor cells from human gut biopsy specimens with or without Hirschsprung's disease using a novel thermoreversible gelation polymer (TGP) is reported aiming at a possible future treatment. Gut biopsy samples were obtained from five patients undergoing gut resection for Hirschsprung's disease (n = 1) or gastrointestinal disorders (n = 4). Cells isolated from the smooth muscle layer and the myenteric plexus were cultured in two groups for 18 to 28 days; Group I: conventional culture as earlier reported and Group II: using TGP scaffold. Neurosphere like bodies (NLBs) were observed in the cultures between 8th to 12th day and H & E staining was positive for neural cells in both groups including aganglionic gut portion from the Hirschsprung's disease patient. Immunohistochemistry using S-100 and neuron specific enolase (NSE) was positive in both groups but the TGP group (Group II) showed more number of cells with intense cytoplasmic granular positivity for both NSE and S-100 compared to Group I. TGP supports the in vitro expansion of human gut derived neuronal cells with seemingly better quality NLBs. Animal Studies can be tried to validate their functional outcome by transplanting the NLBs with TGP scaffolds to see whether this can enhance the outcome of cell based therapies for Hirschsprung's disease.

Empirical modeling of nuclear power plants using neural networks

International Nuclear Information System (INIS)

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

1991-01-01

A summary of a procedure for nonlinear identification of process dynamics encountered in nuclear power plant components is presented in this paper using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the nonlinear structure for system identification. In the overall identification process, 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 time-dependent system nonlinearities. The standard backpropagation learning algorithm is modified and is used to train the proposed hybrid network in a supervised manner. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The nonlinear response of a representative steam generator is predicted using a neural network and is compared to the response obtained from a sophisticated physical model during both high- and low-power operation. The transient responses compare well, though further research is warranted for training and testing of recurrent neural networks during more severe operational transients and accident scenarios

Leukemia inhibitory factor (LIF) enhances MAP2 + and HUC/D + neurons and influences neurite extension during differentiation of neural progenitors derived from human embryonic stem cells.

Science.gov (United States)

Leukemia Inhibitory Factor (L1F), a member of the Interleukin 6 cytokine family, has a role in differentiation of Human Neural Progenitor (hNP) cells in vitro. hNP cells, derived from Human Embryonic Stem (hES) cells, have an unlimited capacity for self-renewal in monolayer cultu...

Updating Procedures Can Reorganize the Neural Circuit Supporting a Fear Memory.

Science.gov (United States)

Kwapis, Janine L; Jarome, Timothy J; Ferrara, Nicole C; Helmstetter, Fred J

2017-07-01

Established memories undergo a period of vulnerability following retrieval, a process termed 'reconsolidation.' Recent work has shown that the hypothetical process of reconsolidation is only triggered when new information is presented during retrieval, suggesting that this process may allow existing memories to be modified. Reconsolidation has received increasing attention as a possible therapeutic target for treating disorders that stem from traumatic memories, yet little is known about how this process changes the original memory. In particular, it is unknown whether reconsolidation can reorganize the neural circuit supporting an existing memory after that memory is modified with new information. Here, we show that trace fear memory undergoes a protein synthesis-dependent reconsolidation process following exposure to a single updating trial of delay conditioning. Further, this reconsolidation-dependent updating process appears to reorganize the neural circuit supporting the trace-trained memory, so that it better reflects the circuit supporting delay fear. Specifically, after a trace-to-delay update session, the amygdala is now required for extinction of the updated memory but the retrosplenial cortex is no longer required for retrieval. These results suggest that updating procedures could be used to force a complex, poorly defined memory circuit to rely on a better-defined neural circuit that may be more amenable to behavioral or pharmacological manipulation. This is the first evidence that exposure to new information can fundamentally reorganize the neural circuit supporting an existing memory.

Effects of topography on the functional development of human neural progenitor cells.

Science.gov (United States)

Wu, Ze-Zhi; Kisaalita, William S; Wang, Lina; Zachman, Angela L; Zhao, Yiping; Hasneen, Kowser; Machacek, Dave; Stice, Steven L

2010-07-01

We have fabricated a topographical substrate with a packed polystyrene bead array for the development of cell-based assay systems targeting voltage-gated calcium channels (VGCCs). Human neural progenitor cells (H945RB.3) cultured on both flat and topographical substrates were analyzed in terms of morphological spreading, neuronal commitment, resting membrane potential (V(m)) establishment and VGCC function development. We found, by SEM imaging, that arrayed substrates, formed with both sub-micrometer (of 0.51 microm in mean diameter) and micrometer (of 1.98 microm in mean diameter) beads, were capable of promoting the spreading of the progenitor cells as compared with the flat polystyrene surfaces. With the micrometer beads, it was found that arrayed substrates facilitated the neural progenitor cells' maintenance of less negative V(m) values upon differentiation with bFGF starvation, which favored predominant neuronal commitment. Almost all the progenitor cells were responsive to 50 mM K(+) depolarization with an increase in [Ca(2+)](i) either before or upon differentiation, suggesting the expression of functional VGCCs. Compared to the flat polystyrene surfaces, microbead arrayed substrates facilitated the development of higher VGCC responsiveness by the progenitor cells upon differentiation. The enhancement of both VGCC responsiveness and cell spreading by arrays of micrometer beads was most significant on day 14 into differentiation, which was the latest time point of measurement in this study. This study thus rationalized the possibility for future substrate topography engineering to manipulate ion channel function and to meet the challenge of low VGCC responsiveness found in early drug discovery.

Neural Basis of Intrinsic Motivation: Evidence from Event-Related Potentials.

Science.gov (United States)

Jin, Jia; Yu, Liping; Ma, Qingguo

2015-01-01

Human intrinsic motivation is of great importance in human behavior. However, although researchers have focused on this topic for decades, its neural basis was still unclear. The current study employed event-related potentials to investigate the neural disparity between an interesting stop-watch (SW) task and a boring watch-stop task (WS) to understand the neural mechanisms of intrinsic motivation. Our data showed that, in the cue priming stage, the cue of the SW task elicited smaller N2 amplitude than that of the WS task. Furthermore, in the outcome feedback stage, the outcome of the SW task induced smaller FRN amplitude and larger P300 amplitude than that of the WS task. These results suggested that human intrinsic motivation did exist and that it can be detected at the neural level. Furthermore, intrinsic motivation could be quantitatively indexed by the amplitude of ERP components, such as N2, FRN, and P300, in the cue priming stage or feedback stage. Quantitative measurements would also be convenient for intrinsic motivation to be added as a candidate social factor in the construction of a machine learning model.

Visual attentional load influences plasticity in the human motor cortex.

Science.gov (United States)

Kamke, Marc R; Hall, Michelle G; Lye, Hayley F; Sale, Martin V; Fenlon, Laura R; Carroll, Timothy J; Riek, Stephan; Mattingley, Jason B

2012-05-16

Neural plasticity plays a critical role in learning, memory, and recovery from injury to the nervous system. Although much is known about the physical and physiological determinants of plasticity, little is known about the influence of cognitive factors. In this study, we investigated whether selective attention plays a role in modifying changes in neural excitability reflecting long-term potentiation (LTP)-like plasticity. We induced LTP-like effects in the hand area of the human motor cortex using transcranial magnetic stimulation (TMS). During the induction of plasticity, participants engaged in a visual detection task with either low or high attentional demands. Changes in neural excitability were assessed by measuring motor-evoked potentials in a small hand muscle before and after the TMS procedures. In separate experiments plasticity was induced either by paired associative stimulation (PAS) or intermittent theta-burst stimulation (iTBS). Because these procedures induce different forms of LTP-like effects, they allowed us to investigate the generality of any attentional influence on plasticity. In both experiments reliable changes in motor cortex excitability were evident under low-load conditions, but this effect was eliminated under high-attentional load. In a third experiment we investigated whether the attentional task was associated with ongoing changes in the excitability of motor cortex, but found no difference in evoked potentials across the levels of attentional load. Our findings indicate that in addition to their role in modifying sensory processing, mechanisms of attention can also be a potent modulator of cortical plasticity.

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

Science.gov (United States)

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.

Enteric neurospheres are not specific to neural crest cultures : Implications for neural stem cell therapies

NARCIS (Netherlands)

Binder, E. (Ellen); D. Natarajan (Dipa); J.E. Cooper (Julie E.); Kronfli, R. (Rania); Cananzi, M. (Mara); J.-M. Delalande (Jean-Marie); C. Mccann; A.J. Burns (Alan); N. Thapar (Nikhil)

2015-01-01

textabstractObjectives Enteric neural stem cells provide hope of curative treatment for enteric neuropathies. Current protocols for their harvesting from humans focus on the generation of 'neurospheres' from cultures of dissociated gut tissue. The study aims to better understand the derivation,

On the Same Wavelength: Face-to-Face Communication Increases Interpersonal Neural Synchronization

OpenAIRE

Yun, Kyongsik

2013-01-01

Understanding neural mechanisms of social interaction is important for understanding human social nature and for developing treatments for social deficits related to disorders such as autism. However, conventional cognitive and behavioral neuroscience has concentrated on developing novel experimental paradigms and investigating human–computer interactions, rather than studying interpersonal interaction per se. To fully understand neural mechanisms of human interpersonal interaction, we will l...

Do neural tube defects lead to structural alterations in the human bladder?

Science.gov (United States)

Pazos, Helena M F; Lobo, Márcio Luiz de P; Costa, Waldemar S; Sampaio, Francisco J B; Cardoso, Luis Eduardo M; Favorito, Luciano Alves

2011-05-01

Anencephaly is the most severe neural tube defect in human fetuses. The objective of this paper is to analyze the structure of the bladder in anencephalic human fetuses. We studied 40 bladders of normal human fetuses (20 male and 20 female, aged 14 to 23 WPC) and 12 bladders of anencephalic fetuses (5 male and 7 female, aged 18 to 22 WPC). The bladders were removed and processed by routine histological techniques. Stereological analysis of collagen, elastic system fibers and smooth muscle was performed in sections. Data were expressed as volumetric density (Vv-%). The images were captured with Olympus BX51 microscopy and Olympus DP70 camera. The stereological analysis was done using the software Image Pro and Image J. For biochemical analysis, samples were fixed in acetone, and collagen concentrations were expressed as micrograms of hydroxyproline per mg of dry tissue. Means were statistically compared using the unpaired t-test (p<0.05). We observed a significant increase (p<0.0001) in the Vv of collagen in the bladders of anencephalic fetuses (69.71%) when compared to normal fetuses (52.74%), and a significant decrease (p<0.0001) in the Vv of smooth muscle cells in the bladders of anencephalic fetuses (23.96%) when compared to normal fetuses (38.35%). The biochemical analyses showed a higher concentration of total collagen in the bladders of anencephalic fetuses (37354 µg/mg) when compared to normal fetuses (48117 µg/mg, p<0.02). The structural alterations of the bladder found in this study may suggest the existence of functional alterations in the bladder of anencephalic human fetuses.

Neural networks dynamic hysteresis model for piezoceramic actuator based on hysteresis operator of first-order differential equation

International Nuclear Information System (INIS)

Dang Xuanju; Tan Yonghong

2005-01-01

A new neural networks dynamic hysteresis model for piezoceramic actuator is proposed by combining the Preisach model with diagonal recurrent neural networks. The Preisach model is based on elementary rate-independent operators and is not suitable for modeling piezoceramic actuator across a wide frequency band because of the rate-dependent hysteresis characteristic of the piezoceramic actuator. The structure of the developed model is based on the structure of the Preisach model, in which the rate-independent relay hysteresis operators (cells) are replaced by the rate-dependent hysteresis operators of first-order differential equation. The diagonal recurrent neural networks being modified by an adjustable factor can be used to model the hysteresis behavior of the pizeoceramic actuator because its structure is similar to the structure of the modified Preisach model. Therefore, the proposed model not only possesses that of the Preisach model, but also can be used for describing its dynamic hysteresis behavior. Through the experimental results of both the approximation and the prediction, the effectiveness of the neural networks dynamic hysteresis model for the piezoceramic actuator is demonstrated

The Neural Correlates of Chronic Symptoms of Vertigo Proneness in Humans.

Directory of Open Access Journals (Sweden)

Ola Alsalman

Full Text Available Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic

The Neural Correlates of Chronic Symptoms of Vertigo Proneness in Humans.

Science.gov (United States)

Alsalman, Ola; Ost, Jan; Vanspauwen, Robby; Blaivie, Catherine; De Ridder, Dirk; Vanneste, Sven

2016-01-01

Vestibular signals are of significant importance for variable functions including gaze stabilization, spatial perception, navigation, cognition, and bodily self-consciousness. The vestibular network governs functions that might be impaired in patients affected with vestibular dysfunction. It is currently unclear how different brain regions/networks process vestibular information and integrate the information into a unified spatial percept related to somatosensory awareness and whether people with recurrent balance complaints have a neural signature as a trait affecting their development of chronic symptoms of vertigo. Pivotal evidence points to a vestibular-related brain network in humans that is widely distributed in nature. By using resting state source localized electroencephalography in non-vertiginous state, electrophysiological changes in activity and functional connectivity of 23 patients with balance complaints where chronic symptoms of vertigo and dizziness are among the most common reported complaints are analyzed and compared to healthy subjects. The analyses showed increased alpha2 activity within the posterior cingulate cortex and the precuneues/cuneus and reduced beta3 and gamma activity within the pregenual and subgenual anterior cingulate cortex for the subjects with balance complaints. These electrophysiological variations were correlated with reported chronic symptoms of vertigo intensity. A region of interest analysis found reduced functional connectivity for gamma activity within the vestibular cortex, precuneus, frontal eye field, intra-parietal sulcus, orbitofrontal cortex, and the dorsal anterior cingulate cortex. In addition, there was a positive correlation between chronic symptoms of vertigo intensity and increased alpha-gamma nesting in the left frontal eye field. When compared to healthy subjects, there is evidence of electrophysiological changes in the brain of patients with balance complaints even outside chronic symptoms of vertigo

Neural synchronization during face-to-face communication

OpenAIRE

Jiang, J.; Dai, B.; Peng, D.; Zhu, C.; Liu, L.; Lu, C.

2012-01-01

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-...

Collagen-coated polylactic-glycolic acid (PLGA) seeded with neural-differentiated human mesenchymal stem cells as a potential nerve conduit.

Science.gov (United States)

Sulong, Ahmad Fadzli; Hassan, Nur Hidayah; Hwei, Ng Min; Lokanathan, Yogeswaran; Naicker, Amaramalar Selvi; Abdullah, Shalimar; Yusof, Mohd Reusmaazran; Htwe, Ohnmar; Idrus, Ruszymah Bt Hj; Haflah, Nor Hazla Mohamed

2014-01-01

Autologous nerve grafts to bridge nerve gaps pose various drawbacks. Nerve tissue engineering to promote nerve regeneration using artificial neural conduits has emerged as a promising alternative. To develop an artificial nerve conduit using collagen-coated polylactic-glycolic acid (PLGA) and to analyse the survivability and propagating ability of the neuro-differentiated human mesenchymal stem cells in this conduit. The PLGA conduit was constructed by dip-molding method and coated with collagen by immersing the conduit in collagen bath. The ultra structure of the conduits were examined before they were seeded with neural-differentiated human mesenchymal stem cells (nMSC) and implanted sub-muscularly on nude mice thighs. The non-collagen-coated PLGA conduit seeded with nMSC and non-seeded non-collagen-coated PLGA conduit were also implanted for comparison purposes. The survivability and propagation ability of nMSC was studied by histological and immunohistochemical analysis. The collagen-coated conduits had a smooth inner wall and a highly porous outer wall. Conduits coated with collagen and seeded with nMSCs produced the most number of cells after 3 weeks. The best conduit based on the number of cells contained within it after 3 weeks was the collagen-coated PLGA conduit seeded with neuro-transdifferentiated cells. The collagen-coated PLGA conduit found to be suitable for attachment, survival and proliferation of the nMSC. Minimal cell infiltration was found in the implanted conduits where nearly all of the cells found in the cell seeded conduits are non-mouse origin and have neural cell markers, which exhibit the biocompatibility of the conduits. The collagen-coated PLGA conduit is biocompatible, non-cytotoxic and suitable for use as artificial nerve conduits.

Numerical Solution of Fuzzy Differential Equations with Z-numbers Using Bernstein Neural Networks

Directory of Open Access Journals (Sweden)

Raheleh Jafari

2017-01-01

Full Text Available The uncertain nonlinear systems can be modeled with fuzzy equations or fuzzy differential equations (FDEs by incorporating the fuzzy set theory. The solutions of them are applied to analyze many engineering problems. However, it is very difficult to obtain solutions of FDEs. In this paper, the solutions of FDEs are approximated by two types of Bernstein neural networks. Here, the uncertainties are in the sense of Z-numbers. Initially the FDE is transformed into four ordinary differential equations (ODEs with Hukuhara differentiability. Then neural models are constructed with the structure of ODEs. With modified back propagation method for Z- number variables, the neural networks are trained. The theory analysis and simulation results show that these new models, Bernstein neural networks, are effective to estimate the solutions of FDEs based on Z-numbers.

Surface and protein analyses of normal human cell attachment on PIII-modified chitosan membranes

International Nuclear Information System (INIS)

Saranwong, N.; Inthanon, K.; Wongkham, W.; Wanichapichart, P.; Suwannakachorn, D.; Yu, L.D.

2012-01-01

Surface of chitosan membrane was modified with argon (Ar) and nitrogen (N) plasma immersion ion implantation (PIII) for human skin fibroblasts F1544 cell attachment. The modified surfaces were characterized by Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM). Cell attachment patterns were evaluated by scanning electron microscopy (SEM). The enzyme-linked immunosorbent assay (ELISA) was used to quantify levels of focal adhesion kinase (FAK). The results showed that Ar PIII had an enhancement effect on the cell attachment while N-PIII had an inhibition effect. Filopodial analysis revealed more microfilament cytoplasmic spreading on the edge of cells attached on the Ar-treated membranes than N-treated membranes. Higher level FAK was found in Ar-treated membranes than that in N-treated membranes.

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

Science.gov (United States)

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.

Neural correlates for perception of companion animal photographs.

Science.gov (United States)

Hayama, Sara; Chang, Linda; Gumus, Kazim; King, George R; Ernst, Thomas

2016-05-01

Anthrozoological neuroscience, which we propose as the use of neuroscience techniques to study human-animal interaction, may help to elucidate mechanisms underlying the associated psychological, physiological, and other purported health effects. This preliminary study investigates the neural response to animal photographs in pet owners and non-pet owners, and both attraction and attachment to companion animals as modulators of human perception of companion animal photographs. Thirty male participants, 15 "Pet Owners" (PO) and 15 "Non-Pet Owners" (NPO), viewed photographs of companion animals during functional MRI (fMRI) scans at 3 T and provided ratings of attraction to the animal species represented in the photographs. Fourteen subjects additionally submitted and viewed personal pet photographs during fMRI scans, and completed the Lexington Attachment to Pets Scale (LAPS). PO exhibited greater activation than NPO during the viewing of animal photographs in areas of the insula, and frontal and occipital cortices. Moreover, ratings of attraction to animals correlated positively with neural activation in the cingulate gyrus, precentral gyrus, inferior parietal lobule, and superior temporal gyrus during the viewing of representative photographs. For subjects with household pets, scores on the LAPS correlated positively with neural activation during the viewing of owned pet photographs in the precuneus, cuneus, and superior parietal lobule. Our preliminary findings suggest that human perception of companion animals involve the visual attention network, which may be modulated at the neural level by subjective experiences of attraction or attachment to animals. Our understanding of human-animal interactions through anthrozoological neuroscience may better direct therapeutic applications, such as animal-assisted therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Willingness to purchase Genetically Modified food: an analysis applying artificial Neural Networks

OpenAIRE

Salazar-Ordóñez, M.; Rodríguez-Entrena, M.; Becerra-Alonso, D.

2014-01-01

Findings about consumer decision-making process regarding GM food purchase remain mixed and are inconclusive. This paper offers a model which classifies willingness to purchase GM food, using data from 399 surveys in Southern Spain. Willingness to purchase has been measured using three dichotomous questions and classification, based on attitudinal, cognitive and socio-demographic factors, has been made by an artificial neural network model. The results show 74% accuracy to forecast the willin...

Understanding the Implications of Neural Population Activity on Behavior

Science.gov (United States)

Briguglio, John

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

Evolutionary Algorithms For Neural Networks Binary And Real Data Classification

Directory of Open Access Journals (Sweden)

Dr. Hanan A.R. Akkar

2015-08-01

Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.

Artificial neural network-based predictive model for bacterial growth in a simulated medium of modified-atmosphere-packed cooked meat products.

Science.gov (United States)

Lou, W; Nakai, S

2001-04-01

The data of Devilieghere et al. (Int. J. Food Microbiol. 1999, 46, 57--70) on bacterial growth in a simulated medium of modified-atmosphere-packed cooked meat products was processed for estimating maximum specific growth rate mu(max) and lag phase lambda of Lactobacillus sake using artificial neural networks-based model (ANNM) computation. The comparison between ANNM and response surface methodology (RSM) model showed that the accuracy of ANNM prediction was higher than that of RSM. Two-dimensional and three-dimensional plots of the response surfaces revealed that the relationships of water activity a(w), temperature T, and dissolved CO(2) concentration with mu(max) and lambda were complicated, not just linear or second-order relations. Furthermore, it was possible to compute the sensitivity of the model outputs against each input parameter by using ANNM. The results showed that mu(max) was most sensitive to a(w), T, and dissolved CO(2) in this order; whereas lambda was sensitive to T the most, followed by a(w), and dissolved CO(2) concentrations.

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

Science.gov (United States)

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

Sex differences in the neural and behavioral response to intranasal oxytocin and vasopressin during human social interaction.

Science.gov (United States)

Rilling, James K; Demarco, Ashley C; Hackett, Patrick D; Chen, Xu; Gautam, Pritam; Stair, Sabrina; Haroon, Ebrahim; Thompson, Richmond; Ditzen, Beate; Patel, Rajan; Pagnoni, Giuseppe

2014-01-01

Both oxytocin (OT) and vasopressin (AVP) are known to modulate social behavior, and dysfunction in both systems has been postulated as a potential cause of certain psychiatric disorders that involve social behavioral deficits. In particular, there is growing interest in intranasal OT as a potential treatment for certain psychiatric disorders, and preliminary pre-clinical and clinical studies suggest efficacy in alleviating some of the associated symptoms. However, the vast majority of research participants in these studies have been male, and there is evidence for sexually differentiated effects of nonapeptides in both humans and non-human animals. To date, no study has investigated the effect of intranasal OT on brain function in human males and females within the same paradigm. Previously, in a randomized, placebo-controlled, double-blind fMRI study, we reported effects of intranasal OT and AVP on behavior and brain activity of human males as they played an interactive social game known as the Prisoner's Dilemma Game. Here, we present findings from an identical study in human females, and compare these with our findings from males. Overall, we find that both behavioral and neural responses to intranasal OT and AVP are highly sexually differentiated. In women, AVP increased conciliatory behavior, and both OT and AVP caused women to treat computer partners more like humans. In men, AVP increased reciprocation of cooperation from both human and computer partners. However, no specific drug effects on behavior were shared between men and women. During cooperative interactions, both OT and AVP increased brain activity in men within areas rich in OT and AVP receptors and in areas playing a key role in reward, social bonding, arousal and memory (e.g., the striatum, basal forebrain, insula, amygdala and hippocampus), whereas OT and AVP either had no effect or in some cases actually decreased brain activity in these regions in women. OT treatment rendered neural responses

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

Directory of Open Access Journals (Sweden)

W. L. C. Rutten

2006-01-01

Full Text Available One type of future, improved neural interface is the “cultured probe”. It is a hybrid type of neural information transducer or prosthesis, for stimulation and/or recording of neural activity. It would consist of a microelectrode array (MEA on a planar substrate, each electrode being covered and surrounded by a local circularly confined network (“island” of cultured neurons. The main purpose of the local networks is that they act as biofriendly intermediates for collateral sprouts from the in vivo system, thus allowing for an effective and selective neuron–electrode interface. As a secondary purpose, one may envisage future information processing applications of these intermediary networks. In this paper, first, progress is shown on how substrates can be chemically modified to confine developing networks, cultured from dissociated rat cortex cells, to “islands” surrounding an electrode site. Additional coating of neurophobic, polyimide-coated substrate by triblock-copolymer coating enhances neurophilic-neurophobic adhesion contrast. Secondly, results are given on neuronal activity in patterned, unconnected and connected, circular “island” networks. For connected islands, the larger the island diameter (50, 100 or 150 μm, the more spontaneous activity is seen. Also, activity may show a very high degree of synchronization between two islands. For unconnected islands, activity may start at 22 days in vitro (DIV, which is two weeks later than in unpatterned networks.

MR-based imaging of neural stem cells

Energy Technology Data Exchange (ETDEWEB)

Politi, Letterio S. [San Raffaele Scientific Institute, Neuroradiology Department, Milano (Italy)

2007-06-15

The efficacy of therapies based on neural stem cells (NSC) has been demonstrated in preclinical models of several central nervous system (CNS) diseases. Before any potential human application of such promising therapies can be envisaged, there are some important issues that need to be solved. The most relevant one is the requirement for a noninvasive technique capable of monitoring NSC delivery, homing to target sites and trafficking. Knowledge of the location and temporospatial migration of either transplanted or genetically modified NSC is of the utmost importance in analyzing mechanisms of correction and cell distribution. Further, such a technique may represent a crucial step toward clinical application of NSC-based approaches in humans, for both designing successful protocols and monitoring their outcome. Among the diverse imaging approaches available for noninvasive cell tracking, such as nuclear medicine techniques, fluorescence and bioluminescence, magnetic resonance imaging (MRI) has unique advantages. Its high temporospatial resolution, high sensitivity and specificity render MRI one of the most promising imaging modalities available, since it allows dynamic visualization of migration of transplanted cells in animal models and patients during clinically useful time periods. Different cellular and molecular labeling approaches for MRI depiction of NSC are described and discussed in this review, as well as the most relevant issues to be considered in optimizing molecular imaging techniques for clinical application. (orig.)

MR-based imaging of neural stem cells

International Nuclear Information System (INIS)

Politi, Letterio S.

2007-01-01

The efficacy of therapies based on neural stem cells (NSC) has been demonstrated in preclinical models of several central nervous system (CNS) diseases. Before any potential human application of such promising therapies can be envisaged, there are some important issues that need to be solved. The most relevant one is the requirement for a noninvasive technique capable of monitoring NSC delivery, homing to target sites and trafficking. Knowledge of the location and temporospatial migration of either transplanted or genetically modified NSC is of the utmost importance in analyzing mechanisms of correction and cell distribution. Further, such a technique may represent a crucial step toward clinical application of NSC-based approaches in humans, for both designing successful protocols and monitoring their outcome. Among the diverse imaging approaches available for noninvasive cell tracking, such as nuclear medicine techniques, fluorescence and bioluminescence, magnetic resonance imaging (MRI) has unique advantages. Its high temporospatial resolution, high sensitivity and specificity render MRI one of the most promising imaging modalities available, since it allows dynamic visualization of migration of transplanted cells in animal models and patients during clinically useful time periods. Different cellular and molecular labeling approaches for MRI depiction of NSC are described and discussed in this review, as well as the most relevant issues to be considered in optimizing molecular imaging techniques for clinical application. (orig.)

Human olfactory bulb neural stem cells mitigate movement disorders in a rat model of Parkinson's disease.

Science.gov (United States)

Marei, Hany E S; Lashen, Samah; Farag, Amany; Althani, Asmaa; Afifi, Nahla; A, Abd-Elmaksoud; Rezk, Shaymaa; Pallini, Roberto; Casalbore, Patrizia; Cenciarelli, Carlo

2015-07-01

Parkinson's disease (PD) is a neurological disorder characterized by the loss of midbrain dopaminergic (DA) neurons. Neural stem cells (NSCs) are multipotent stem cells that are capable of differentiating into different neuronal and glial elements. The production of DA neurons from NSCs could potentially alleviate behavioral deficits in Parkinsonian patients; timely intervention with NSCs might provide a therapeutic strategy for PD. We have isolated and generated highly enriched cultures of neural stem/progenitor cells from the human olfactory bulb (OB). If NSCs can be obtained from OB, it would alleviate ethical concerns associated with the use of embryonic tissue, and provide an easily accessible cell source that would preclude the need for invasive brain surgery. Following isolation and culture, olfactory bulb neural stem cells (OBNSCs) were genetically engineered to express hNGF and GFP. The hNFG-GFP-OBNSCs were transplanted into the striatum of 6-hydroxydopamin (6-OHDA) Parkinsonian rats. The grafted cells survived in the lesion environment for more than eight weeks after implantation with no tumor formation. The grafted cells differentiated in vivo into oligodendrocyte-like (25 ± 2.88%), neuron-like (52.63 ± 4.16%), and astrocyte -like (22.36 ± 1.56%) lineages, which we differentiated based on morphological and immunohistochemical criteria. Transplanted rats exhibited a significant partial correction in stepping and placing in non-pharmacological behavioral tests, pole and rotarod tests. Taken together, our data encourage further investigations of the possible use of OBNSCs as a promising cell-based therapeutic strategy for Parkinson's disease. © 2014 Wiley Periodicals, Inc.

Human Neural Stem Cell Aging Is Counteracted by α-Glycerylphosphorylethanolamine.

Science.gov (United States)

Daniele, Simona; Da Pozzo, Eleonora; Iofrida, Caterina; Martini, Claudia

2016-07-20

Neural stem cells (NSCs) represent a subpopulation of cells, located in specific regions of the adult mammalian brain, with the ability of self-renewing and generating neurons and glia. In aged NSCs, modifications in the amount and composition of membrane proteins/lipids, which lead to a reduction in membrane fluidity and cholinergic activities, have been reported. In this respect, molecules that are effective at normalizing the membrane composition and cholinergic signaling could counteract stem cell aging. α-Glycerylphosphorylethanolamine (GPE), a nootropic drug, plays a role in phospholipid biosynthesis and acetylcholine release. Herein, GPE was assayed on human NSC cultures and on hydroxyurea-aged cells. Using cell counting, colorimetric, and fluorimetric analyses, immunoenzymatic assays, and real time PCR experiments, NSC culture proliferation, senescence, reactive oxygen species, and ADP/ATP levels were assessed. Aged NSCs exhibited cellular senescence, decreased proliferation, and an impairment in mitochondrial metabolism. These changes included a substantial induction in the nuclear factor NF-κB, a key inflammatory mediator. GPE cell treatment significantly protected the redox state and functional integrity of mitochondria, and counteracted senescence and NF-κB activation. In conclusion, our data show the beneficial properties of GPE in this model of stem cell aging.

Distorted Character Recognition Via An Associative Neural Network

Science.gov (United States)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

Neural networks for genetic epidemiology: past, present, and future

Directory of Open Access Journals (Sweden)

Motsinger-Reif Alison A

2008-07-01

Full Text Available Abstract During the past two decades, the field of human genetics has experienced an information explosion. The completion of the human genome project and the development of high throughput SNP technologies have created a wealth of data; however, the analysis and interpretation of these data have created a research bottleneck. While technology facilitates the measurement of hundreds or thousands of genes, statistical and computational methodologies are lacking for the analysis of these data. New statistical methods and variable selection strategies must be explored for identifying disease susceptibility genes for common, complex diseases. Neural networks (NN are a class of pattern recognition methods that have been successfully implemented for data mining and prediction in a variety of fields. The application of NN for statistical genetics studies is an active area of research. Neural networks have been applied in both linkage and association analysis for the identification of disease susceptibility genes. In the current review, we consider how NN have been used for both linkage and association analyses in genetic epidemiology. We discuss both the successes of these initial NN applications, and the questions that arose during the previous studies. Finally, we introduce evolutionary computing strategies, Genetic Programming Neural Networks (GPNN and Grammatical Evolution Neural Networks (GENN, for using NN in association studies of complex human diseases that address some of the caveats illuminated by previous work.

Effective long-term immunosuppression in rats by subcutaneously implanted sustained-release tacrolimus pellet: Effect on spinally grafted human neural precursor survival

Czech Academy of Sciences Publication Activity Database

Ševc, J.; Goldberg, D.; van Gorp, S.; Leerink, M.; Juhás, Štefan; Juhásová, Jana; Marsala, S.; Hruška-Plocháň, Marian; Hefferan, M. P.; Motlík, Jan; Rypáček, František; Machová, Luďka; Kakinohana, O.; Santucci, C.; Johe, K.; Lukáčová, N.; Yamada, K.; Bui, J. D.; Marsala, M.

2013-01-01

Roč. 248, October (2013), s. 85-99 ISSN 0014-4886 R&D Projects: GA TA ČR TA01011466; GA MŠk ED2.1.00/03.0124 Institutional support: RVO:67985904 ; RVO:61389013 Keywords : immunosuppression * xenograft * human neural precursors Subject RIV: FH - Neurology; CD - Macromolecular Chemistry (UMCH-V) Impact factor: 4.617, year: 2013

A neural network approach to the orienteering problem

Energy Technology Data Exchange (ETDEWEB)

Golden, B.; Wang, Q.; Sun, X.; Jia, J.

1994-12-31

In the orienteering problem, we are given a transportation network in which a start point and an end point are specified. Other points have associated scores. Given a fixed amount of time, the goal is to determine a path from start to end through a subset of locations in order to maximize the total path score. This problem has received a considerable amount of attention in the last ten years. The TSP is a variant of the orienteering problem. This paper applies a modified, continuous Hopfield neural network to attack this NP-hard optimization problem. In it, we design an effective energy function and learning algorithm. Unlike some applications of neural networks to optimization problems, this approach is shown to perform quite well.

High-frequency oscillations in distributed neural networks reveal the dynamics of human decision making

Directory of Open Access Journals (Sweden)

Adrian G Guggisberg

2008-03-01

Full Text Available We examine the relative timing of numerous brain regions involved in human decisions that are based on external criteria, learned information, personal preferences, or unconstrained internal considerations. Using magnetoencephalography (MEG and advanced signal analysis techniques, we were able to non-invasively reconstruct oscillations of distributed neural networks in the high-gamma frequency band (60–150 Hz. The time course of the observed neural activity suggested that two-alternative forced choice tasks are processed in four overlapping stages: processing of sensory input, option evaluation, intention formation, and action execution. Visual areas are activated fi rst, and show recurring activations throughout the entire decision process. The temporo-occipital junction and the intraparietal sulcus are active during evaluation of external values of the options, 250–500 ms after stimulus presentation. Simultaneously, personal preference is mediated by cortical midline structures. Subsequently, the posterior parietal and superior occipital cortices appear to encode intention, with different subregions being responsible for different types of choice. The cerebellum and inferior parietal cortex are recruited for internal generation of decisions and actions, when all options have the same value. Action execution was accompanied by activation peaks in the contralateral motor cortex. These results suggest that high-gamma oscillations as recorded by MEG allow a reliable reconstruction of decision processes with excellent spatiotemporal resolution.

Application of neural networks to signal prediction in nuclear power plant

International Nuclear Information System (INIS)

Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

1993-01-01

This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

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

Science.gov (United States)

Sameiro-Barbosa, Catia M; Geiser, Eveline

2016-01-01

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

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

Science.gov (United States)

Sameiro-Barbosa, Catia M.; Geiser, Eveline

2016-01-01

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

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography

Directory of Open Access Journals (Sweden)

Murilo Coutinho

2018-04-01

Full Text Available Researches in Artificial Intelligence (AI have achieved many important breakthroughs, especially in recent years. In some cases, AI learns alone from scratch and performs human tasks faster and better than humans. With the recent advances in AI, it is natural to wonder whether Artificial Neural Networks will be used to successfully create or break cryptographic algorithms. Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC. Using the proposed network, we show limitations and directions to improve the current approach of ANC. Training the proposed Artificial Neural Network with the improved model of ANC, we show that artificially intelligent agents can learn the unbreakable One-Time Pad (OTP algorithm, without human knowledge, to communicate securely through an insecure communication channel. This paper shows in which conditions an AI agent can learn a secure encryption scheme. However, it also shows that, without a stronger adversary, it is more likely to obtain an insecure one.

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography.

Science.gov (United States)

Coutinho, Murilo; de Oliveira Albuquerque, Robson; Borges, Fábio; García Villalba, Luis Javier; Kim, Tai-Hoon

2018-04-24

Researches in Artificial Intelligence (AI) have achieved many important breakthroughs, especially in recent years. In some cases, AI learns alone from scratch and performs human tasks faster and better than humans. With the recent advances in AI, it is natural to wonder whether Artificial Neural Networks will be used to successfully create or break cryptographic algorithms. Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC). Using the proposed network, we show limitations and directions to improve the current approach of ANC. Training the proposed Artificial Neural Network with the improved model of ANC, we show that artificially intelligent agents can learn the unbreakable One-Time Pad (OTP) algorithm, without human knowledge, to communicate securely through an insecure communication channel. This paper shows in which conditions an AI agent can learn a secure encryption scheme. However, it also shows that, without a stronger adversary, it is more likely to obtain an insecure one.

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

Science.gov (United States)

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

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

OpenAIRE

Francisco Javier Ordóñez; Daniel Roggen

2016-01-01

Human activity recognition (HAR) tasks have traditionally been solved using engineered features obtained by heuristic processes. Current research suggests that deep convolutional neural networks are suited to automate feature extraction from raw sensor inputs. However, human activities are made of complex sequences of motor movements, and capturing this temporal dynamics is fundamental for successful HAR. Based on the recent success of recurrent neural networks for time series domains, we pro...

Neural networks and their potential application to nuclear power plants

International Nuclear Information System (INIS)

Uhrig, R.E.

1991-01-01

A network of artificial neurons, usually called an artificial neural network is a data processing system consisting of a number of highly interconnected processing elements in an architecture inspired by the structure of the cerebral cortex portion of the brain. Hence, neural networks are often capable of doing things which humans or animals do well but which conventional computers often do poorly. Neural networks exhibit characteristics and capabilities not provided by any other technology. Neural networks may be designed so as to classify an input pattern as one of several predefined types or to create, as needed, categories or classes of system states which can be interpreted by a human operator. Neural networks have the ability to recognize patterns, even when the information comprising these patterns is noisy, sparse, or incomplete. Thus, systems of artificial neural networks show great promise for use in environments in which robust, fault-tolerant pattern recognition is necessary in a real-time mode, and in which the incoming data may be distorted or noisy. The application of neural networks, a rapidly evolving technology used extensively in defense applications, alone or in conjunction with other advanced technologies, to some of the problems of operating nuclear power plants has the potential to enhance the safety, reliability and operability of nuclear power plants. The potential applications of neural networking include, but are not limited to diagnosing specific abnormal conditions, identification of nonlinear dynamics and transients, detection of the change of mode of operation, control of temperature and pressure during start-up, signal validation, plant-wide monitoring using autoassociative neural networks, monitoring of check valves, modeling of the plant thermodynamics, emulation of core reload calculations, analysis of temporal sequences in NRC's ''licensee event reports,'' and monitoring of plant parameters

Supervised Learning with Complex-valued Neural Networks

CERN Document Server

Suresh, Sundaram; Savitha, Ramasamy

2013-01-01

Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.  Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...

Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors.

Science.gov (United States)

Kim, Jong Hyun; Hong, Hyung Gil; Park, Kang Ryoung

2017-05-08

Because intelligent surveillance systems have recently undergone rapid growth, research on accurately detecting humans in videos captured at a long distance is growing in importance. The existing research using visible light cameras has mainly focused on methods of human detection for daytime hours when there is outside light, but human detection during nighttime hours when there is no outside light is difficult. Thus, methods that employ additional near-infrared (NIR) illuminators and NIR cameras or thermal cameras have been used. However, in the case of NIR illuminators, there are limitations in terms of the illumination angle and distance. There are also difficulties because the illuminator power must be adaptively adjusted depending on whether the object is close or far away. In the case of thermal cameras, their cost is still high, which makes it difficult to install and use them in a variety of places. Because of this, research has been conducted on nighttime human detection using visible light cameras, but this has focused on objects at a short distance in an indoor environment or the use of video-based methods to capture multiple images and process them, which causes problems related to the increase in the processing time. To resolve these problems, this paper presents a method that uses a single image captured at night on a visible light camera to detect humans in a variety of environments based on a convolutional neural network. Experimental results using a self-constructed Dongguk night-time human detection database (DNHD-DB1) and two open databases (Korea advanced institute of science and technology (KAIST) and computer vision center (CVC) databases), as well as high-accuracy human detection in a variety of environments, show that the method has excellent performance compared to existing methods.

Convolutional Neural Network-Based Human Detection in Nighttime Images Using Visible Light Camera Sensors

Directory of Open Access Journals (Sweden)

Jong Hyun Kim

2017-05-01

Full Text Available Because intelligent surveillance systems have recently undergone rapid growth, research on accurately detecting humans in videos captured at a long distance is growing in importance. The existing research using visible light cameras has mainly focused on methods of human detection for daytime hours when there is outside light, but human detection during nighttime hours when there is no outside light is difficult. Thus, methods that employ additional near-infrared (NIR illuminators and NIR cameras or thermal cameras have been used. However, in the case of NIR illuminators, there are limitations in terms of the illumination angle and distance. There are also difficulties because the illuminator power must be adaptively adjusted depending on whether the object is close or far away. In the case of thermal cameras, their cost is still high, which makes it difficult to install and use them in a variety of places. Because of this, research has been conducted on nighttime human detection using visible light cameras, but this has focused on objects at a short distance in an indoor environment or the use of video-based methods to capture multiple images and process them, which causes problems related to the increase in the processing time. To resolve these problems, this paper presents a method that uses a single image captured at night on a visible light camera to detect humans in a variety of environments based on a convolutional neural network. Experimental results using a self-constructed Dongguk night-time human detection database (DNHD-DB1 and two open databases (Korea advanced institute of science and technology (KAIST and computer vision center (CVC databases, as well as high-accuracy human detection in a variety of environments, show that the method has excellent performance compared to existing methods.

Vestibular hearing and neural synchronization.

Science.gov (United States)

Emami, Seyede Faranak; Daneshi, Ahmad

2012-01-01

Objectives. Vestibular hearing as an auditory sensitivity of the saccule in the human ear is revealed by cervical vestibular evoked myogenic potentials (cVEMPs). The range of the vestibular hearing lies in the low frequency. Also, the amplitude of an auditory brainstem response component depends on the amount of synchronized neural activity, and the auditory nerve fibers' responses have the best synchronization with the low frequency. Thus, the aim of this study was to investigate correlation between vestibular hearing using cVEMPs and neural synchronization via slow wave Auditory Brainstem Responses (sABR). Study Design. This case-control survey was consisted of twenty-two dizzy patients, compared to twenty healthy controls. Methods. Intervention comprised of Pure Tone Audiometry (PTA), Impedance acoustic metry (IA), Videonystagmography (VNG), fast wave ABR (fABR), sABR, and cVEMPs. Results. The affected ears of the dizzy patients had the abnormal findings of cVEMPs (insecure vestibular hearing) and the abnormal findings of sABR (decreased neural synchronization). Comparison of the cVEMPs at affected ears versus unaffected ears and the normal persons revealed significant differences (P < 0.05). Conclusion. Safe vestibular hearing was effective in the improvement of the neural synchronization.

mRNA transfection of mouse and human neural stem cell cultures.

Directory of Open Access Journals (Sweden)

Samuel McLenachan

Full Text Available The use of synthetic mRNA as an alternative gene delivery vector to traditional DNA-based constructs provides an effective method for inducing transient gene expression in cell cultures without genetic modification. Delivery of mRNA has been proposed as a safer alternative to viral vectors in the induction of pluripotent cells for regenerative therapies. Although mRNA transfection of fibroblasts, dendritic and embryonic stem cells has been described, mRNA delivery to neurosphere cultures has not been previously reported. Here we sought to establish an efficient method for delivering mRNA to primary neurosphere cultures. Neurospheres derived from the subventricular zone of adult mice or from human embryonic stem cells were transfected with EGFP mRNA by lipofection and electroporation. Transfection efficiency and expression levels were monitored by flow cytometry. Cell survival following transfection was examined using live cell counting and the MTT assay. Both lipofection and electroporation provided high efficiency transfection of neurospheres. In comparison with lipofection, electroporation resulted in increased transfection efficiencies, but lower expression per cell and shorter durations of expression. Additional rounds of lipofection renewed EGFP expression in neurospheres, suggesting this method may be suitable for reprogramming applications. In summary, we have developed a protocol for achieving high efficiency transfection rates in mouse and human neurosphere cell culture that can be applied for future studies of gene function studies in neural stem cells, such as defining efficient differentiation protocols for glial and neuronal linages.

mRNA Transfection of Mouse and Human Neural Stem Cell Cultures

Science.gov (United States)

McLenachan, Samuel; Zhang, Dan; Palomo, Ana Belén Alvarez; Edel, Michael J.; Chen, Fred K.

2013-01-01

The use of synthetic mRNA as an alternative gene delivery vector to traditional DNA-based constructs provides an effective method for inducing transient gene expression in cell cultures without genetic modification. Delivery of mRNA has been proposed as a safer alternative to viral vectors in the induction of pluripotent cells for regenerative therapies. Although mRNA transfection of fibroblasts, dendritic and embryonic stem cells has been described, mRNA delivery to neurosphere cultures has not been previously reported. Here we sought to establish an efficient method for delivering mRNA to primary neurosphere cultures. Neurospheres derived from the subventricular zone of adult mice or from human embryonic stem cells were transfected with EGFP mRNA by lipofection and electroporation. Transfection efficiency and expression levels were monitored by flow cytometry. Cell survival following transfection was examined using live cell counting and the MTT assay. Both lipofection and electroporation provided high efficiency transfection of neurospheres. In comparison with lipofection, electroporation resulted in increased transfection efficiencies, but lower expression per cell and shorter durations of expression. Additional rounds of lipofection renewed EGFP expression in neurospheres, suggesting this method may be suitable for reprogramming applications. In summary, we have developed a protocol for achieving high efficiency transfection rates in mouse and human neurosphere cell culture that can be applied for future studies of gene function studies in neural stem cells, such as defining efficient differentiation protocols for glial and neuronal linages. PMID:24386231

mRNA transfection of mouse and human neural stem cell cultures.

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McLenachan, Samuel; Zhang, Dan; Palomo, Ana Belén Alvarez; Edel, Michael J; Chen, Fred K

2013-01-01

The use of synthetic mRNA as an alternative gene delivery vector to traditional DNA-based constructs provides an effective method for inducing transient gene expression in cell cultures without genetic modification. Delivery of mRNA has been proposed as a safer alternative to viral vectors in the induction of pluripotent cells for regenerative therapies. Although mRNA transfection of fibroblasts, dendritic and embryonic stem cells has been described, mRNA delivery to neurosphere cultures has not been previously reported. Here we sought to establish an efficient method for delivering mRNA to primary neurosphere cultures. Neurospheres derived from the subventricular zone of adult mice or from human embryonic stem cells were transfected with EGFP mRNA by lipofection and electroporation. Transfection efficiency and expression levels were monitored by flow cytometry. Cell survival following transfection was examined using live cell counting and the MTT assay. Both lipofection and electroporation provided high efficiency transfection of neurospheres. In comparison with lipofection, electroporation resulted in increased transfection efficiencies, but lower expression per cell and shorter durations of expression. Additional rounds of lipofection renewed EGFP expression in neurospheres, suggesting this method may be suitable for reprogramming applications. In summary, we have developed a protocol for achieving high efficiency transfection rates in mouse and human neurosphere cell culture that can be applied for future studies of gene function studies in neural stem cells, such as defining efficient differentiation protocols for glial and neuronal linages.

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

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Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

Evolving RBF neural networks for adaptive soft-sensor design.

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Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Periconceptional Folate Deficiency and Implications in Neural Tube Defects

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J. Safi

2012-01-01

Full Text Available Nutritional deficiencies are preventable etiological and epigenetic factors causing congenital abnormalities, first cause of infant mortality. Folate deficiency has a well-established teratogenic effect, leading to an increasing risk of neural tube defects. This paper highlights the most recent medical literature about folate deficiency, be it maternal or paternal. It then focuses on associated deficiencies as nutritional deficiencies are multiple and interrelated. Observational and interventional studies have all been consistent with a 50–70% protective effect of adequate women consumption of folates on neural tube defects. Since strategies to modify women’s dietary habits and vitamin use have achieved little progress, scientific as well as political effort is mandatory in order to implement global preventive public health strategies aimed at improving the alimentation of women in reproductive age, especially folic acid supplementation. Even with the recent breakthrough of fetal surgery for myelomeningocele, the emphasis should still be on prevention as the best practice rather than treatment of neural tube defects.

Cryopreservation of human blood for alkaline and Fpg-modified comet assay.

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Pu, Xinzhu; Wang, Zemin; Klaunig, James E

2016-01-01

The Comet assay is a reproducible and sensitive assay for the detection of DNA damage in eukaryotic cells and tissues. Incorporation of lesion specific, oxidative DNA damage repair enzymes (for example, Fpg, OGG1 and EndoIII) in the standard alkaline Comet assay procedure allows for the detection and measurement of oxidative DNA damage. The Comet assay using white blood cells (WBC) has proven useful in monitoring DNA damage from environmental agents in humans. However, it is often impractical to performance Comet assay immediately after blood sampling. Thus, storage of blood sample is required. In this study, we developed and tested a simple storage method for very small amount of whole blood for standard and Fpg-modified modified Comet assay. Whole blood was stored in RPMI 1640 media containing 10% FBS, 10% DMSO and 1 mM deferoxamine at a sample to media ratio of 1:50. Samples were stored at -20 °C and -80 °C for 1, 7, 14 and 28 days. Isolated lymphocytes from the same subjects were also stored under the same conditions for comparison. Direct DNA strand breakage and oxidative DNA damage in WBC and lymphocytes were analyzed using standard and Fpg-modified alkaline Comet assay and compared with freshly analyzed samples. No significant changes in either direct DNA strand breakage or oxidative DNA damage was seen in WBC and lymphocytes stored at -20 °C for 1 and 7 days compared to fresh samples. However, significant increases in both direct and oxidative DNA damage were seen in samples stored at -20 °C for 14 and 28 days. No changes in direct and oxidative DNA damage were observed in WBC and lymphocytes stored at -80 °C for up to 28 days. These results identified the proper storage conditions for storing whole blood or isolated lymphocytes to evaluate direct and oxidative DNA damage using standard and Fpg-modified alkaline Comet assay.

Acute opioid withdrawal is associated with increased neural activity in reward-processing centers in healthy men: A functional magnetic resonance imaging study.

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Chu, Larry F; Lin, Joanne C; Clemenson, Anna; Encisco, Ellen; Sun, John; Hoang, Dan; Alva, Heather; Erlendson, Matthew; Clark, J David; Younger, Jarred W

2015-08-01

Opioid analgesics are frequently prescribed for chronic pain. One expected consequence of long-term opioid use is the development of physical dependence. Although previous resting state functional magnetic resonance imaging (fMRI) studies have demonstrated signal changes in reward-associated areas following morphine administration, the effects of acute withdrawal on the human brain have been less well-investigated. In an earlier study by our laboratory, ondansetron was shown to be effective in preventing symptoms associated with opioid withdrawal. The purpose of this current study was to characterize neural activity associated with acute opioid withdrawal and examine whether these changes are modified by ondansetron. Ten participants were enrolled in this placebo-controlled, randomized, double-blind, crossover study and attended three acute opioid withdrawal sessions. Participants received either placebo or ondansetron (8Ymg IV) before morphine administration (10Ymg/70Ykg IV). Participants then underwent acute naloxone-precipitated withdrawal during a resting state fMRI scan. Objective and subjective opioid withdrawal symptoms were assessed. Imaging results showed that naloxone-precipitated opioid withdrawal was associated with increased neural activity in several reward processing regions, including the right pregenual cingulate, putamen, and bilateral caudate, and decreased neural activity in networks involved in sensorimotor integration. Ondansetron pretreatment did not have a significant effect on the imaging correlates of opioid withdrawal. This study presents a preliminary investigation of the regional changes in neural activity during acute opioid withdrawal. The fMRI acute opioid withdrawal model may serve as a tool for studying opioid dependence and withdrawal in human participants. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Migratory capabilities of human umbilical cord blood-derived neural stem cells (HUCB-NSC) in vitro.

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Janowski, Miroslaw; Lukomska, Barbara; Domanska-Janik, Krystyna

2011-01-01

Many types of neural progenitors from various sources have been evaluated for therapy of CNS disorders. Prerequisite for success in cell therapy is the ability for transplanted cells to reach appropriate target such as stroke lesion. We have established neural stem cell line from human umbilical cord blood neural stem (HUCB-NSC). In the present study we evaluated migratory capabilities of cells (HUCB-NSC) and the presence of various migration-related receptors. Immunocytochemical analysis revealed abundant expression of CXCR4, PDGFR-alpha, PDGFR-beta, c-Met, VEGFR, IGF-1R and PSA-NCAM receptors in non-adherent population of HUCB-NSC cultured in serum free (SF) conditions (SF cells). Biological activity of selected receptors was confirmed by HUCB-NSC in vitro migration towards SDF-1 and IGF-1 ligands. Additionally, rat brain-derived homogenates have been assessed for their chemoattractive activity of HUCB-NSC. Our experiments unveiled that brain tissue was more attracted for HUCB-NSC than single ligands with higher potency of injured than intact brain. Moreover, adherent HUCB-NSC cultured in low serum (LS) conditions (LS cells) were employed to investigate an impact of different extracellular matrix (ECM) proteins on cell motility. It turned out that laminin provided most permissive microenvironment for cell migration, followed by fibronectin and gelatin. Unexpected nuclear localization of CXCR4 in SF cells prompted us to characterize intracellular pattern of this expression in relation to developmental stage of cells cultured in different conditions. Continuous culture of LS cells revealed cytoplasmatic pattern of CXCR4 expression while HUCB-NSC cultured in high serum conditions (HS cells) resulted in gradual translocation of CXCR4 from nucleus to cytoplasm and then to arising processes. Terminal differentiation of HUCB-NSC was followed by CXCR4 expression decline.

Overlapping neural response to the pain or harm of people, animals, and nature.

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Mathur, Vani A; Cheon, Bobby K; Harada, Tokiko; Scimeca, Jason M; Chiao, Joan Y

2016-01-29

Interpersonal pain perception is a fundamental and evolutionarily beneficial social process. While critical for navigating the social world, whether or not people rely on similar processes to perceive and respond to the harm of the non-human biological world remains largely unknown. Here we investigate whether neural reactivity toward the suffering of other people is distinct from or overlapping with the neural response to pain and harm inflicted upon non-human entities, specifically animals and nature. We used fMRI to measure neural activity while participants (n=15) perceived and reported how badly they felt for the pain or harm of humans, animals, and nature, relative to neutral situations. Neural regions associated with perceiving the pain of other people (e.g. dorsal anterior cingulate cortex, bilateral anterior insula) were similarly recruited when perceiving and responding to painful scenes across people, animals, and nature. These results suggest that similar brain responses are relied upon when perceiving the harm of social and non-social biological entities, broadly construed, and that activity within the dorsal anterior cingulate cortex and bilateral anterior insula in response to pain-relevant stimuli is not uniquely specific to humans. Copyright © 2016 Elsevier Ltd. All rights reserved.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording.

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Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Open Ephys electroencephalography (Open Ephys  +  EEG): a modular, low-cost, open-source solution to human neural recording

Science.gov (United States)

Black, Christopher; Voigts, Jakob; Agrawal, Uday; Ladow, Max; Santoyo, Juan; Moore, Christopher; Jones, Stephanie

2017-06-01

Objective. Electroencephalography (EEG) offers a unique opportunity to study human neural activity non-invasively with millisecond resolution using minimal equipment in or outside of a lab setting. EEG can be combined with a number of techniques for closed-loop experiments, where external devices are driven by specific neural signals. However, reliable, commercially available EEG systems are expensive, often making them impractical for individual use and research development. Moreover, by design, a majority of these systems cannot be easily altered to the specification needed by the end user. We focused on mitigating these issues by implementing open-source tools to develop a new EEG platform to drive down research costs and promote collaboration and innovation. Approach. Here, we present methods to expand the open-source electrophysiology system, Open Ephys (www.openephys.org), to include human EEG recordings. We describe the equipment and protocol necessary to interface various EEG caps with the Open Ephys acquisition board, and detail methods for processing data. We present applications of Open Ephys  +  EEG as a research tool and discuss how this innovative EEG technology lays a framework for improved closed-loop paradigms and novel brain-computer interface experiments. Main results. The Open Ephys  +  EEG system can record reliable human EEG data, as well as human EMG data. A side-by-side comparison of eyes closed 8-14 Hz activity between the Open Ephys  +  EEG system and the Brainvision ActiCHamp EEG system showed similar average power and signal to noise. Significance. Open Ephys  +  EEG enables users to acquire high-quality human EEG data comparable to that of commercially available systems, while maintaining the price point and extensibility inherent to open-source systems.

Characterizing low dose and dose rate effects in rodent and human neural stem cells exposed to proton and gamma irradiation

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Bertrand P. Tseng

2013-01-01

Full Text Available Past work has shown that exposure to gamma rays and protons elicit a persistent oxidative stress in rodent and human neural stem cells (hNSCs. We have now adapted these studies to more realistic exposure scenarios in space, using lower doses and dose rates of these radiation modalities, to further elucidate the role of radiation-induced oxidative stress in these cells. Rodent neural stem and precursor cells grown as neurospheres and human neural stem cells grown as monolayers were subjected to acute and multi-dosing paradigms at differing dose rates and analyzed for changes in reactive oxygen species (ROS, reactive nitrogen species (RNS, nitric oxide and superoxide for 2 days after irradiation. While acute exposures led to significant changes in both cell types, hNSCs in particular, exhibited marked and significant elevations in radiation-induced oxidative stress. Elevated oxidative stress was more significant in hNSCs as opposed to their rodent counterparts, and hNSCs were significantly more sensitive to low dose exposures in terms of survival. Combinations of protons and γ-rays delivered as lower priming or higher challenge doses elicited radioadaptive changes that were associated with improved survival, but in general, only under conditions where the levels of reactive species were suppressed compared to cells irradiated acutely. Protective radioadaptive effects on survival were eliminated in the presence of the antioxidant N-acetylcysteine, suggesting further that radiation-induced oxidative stress could activate pro-survival signaling pathways that were sensitive to redox state. Data corroborates much of our past work and shows that low dose and dose rate exposures elicit significant changes in oxidative stress that have functional consequences on survival.

Zika Virus Strains Potentially Display Different Infectious Profiles in Human Neural Cells

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Yannick Simonin

2016-10-01

Full Text Available The recent Zika virus (ZIKV epidemic has highlighted the poor knowledge on its physiopathology. Recent studies showed that ZIKV of the Asian lineage, responsible for this international outbreak, causes neuropathology in vitro and in vivo. However, two African lineages exist and the virus is currently found circulating in Africa. The original African strain was also suggested to be neurovirulent but its laboratory usage has been criticized due to its multiple passages. In this study, we compared the French Polynesian (Asian ZIKV strain to an African strain isolated in Central African Republic and show a difference in infectivity and cellular response between both strains in human neural stem cells and astrocytes. Consistently, this African strain led to a higher infection rate and viral production, as well as stronger cell death and anti-viral response. Our results highlight the need to better characterize the physiopathology and predict neurological impairment associated with African ZIKV.

DeepFix: A Fully Convolutional Neural Network for Predicting Human Eye Fixations.

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Kruthiventi, Srinivas S S; Ayush, Kumar; Babu, R Venkatesh

2017-09-01

Understanding and predicting the human visual attention mechanism is an active area of research in the fields of neuroscience and computer vision. In this paper, we propose DeepFix, a fully convolutional neural network, which models the bottom-up mechanism of visual attention via saliency prediction. Unlike classical works, which characterize the saliency map using various hand-crafted features, our model automatically learns features in a hierarchical fashion and predicts the saliency map in an end-to-end manner. DeepFix is designed to capture semantics at multiple scales while taking global context into account, by using network layers with very large receptive fields. Generally, fully convolutional nets are spatially invariant-this prevents them from modeling location-dependent patterns (e.g., centre-bias). Our network handles this by incorporating a novel location-biased convolutional layer. We evaluate our model on multiple challenging saliency data sets and show that it achieves the state-of-the-art results.

Neural basis of preference for human social hierarchy versus egalitarianism.

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Chiao, Joan Y; Mathur, Vani A; Harada, Tokiko; Lipke, Trixie

2009-06-01

A fundamental way that individuals differ is in the degree to which they prefer social dominance hierarchy over egalitarianism as a guiding principle of societal structure, a phenomenon known as social dominance orientation. Here we show that preference for hierarchical rather than egalitarian social relations varies as a function of neural responses within left anterior insula and anterior cingulate cortices. Our findings provide novel evidence that preference for social dominance hierarchy is associated with neural functioning within brain regions that are associated with the ability to share and feel concern for the pain of others; this suggests a neurobiological basis for social and political attitudes. Implications of these findings for research on the social neuroscience of fairness, justice, and intergroup relations are discussed.

An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

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Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

2013-04-01

Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile

Challenging emotional prejudice by changing self-concept: priming independent self-construal reduces racial in-group bias in neural responses to other's pain.

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Wang, Chenbo; Wu, Bing; Liu, Yi; Wu, Xinhuai; Han, Shihui

2015-09-01

Humans show stronger empathy for in-group compared with out-group members' suffering and help in-group members more than out-group members. Moreover, the in-group bias in empathy and parochial altruism tend to be more salient in collectivistic than individualistic cultures. This work tested the hypothesis that modifying self-construals, which differentiate between collectivistic and individualistic cultural orientations, affects in-group bias in empathy for perceived own-race vs other-race pain. By scanning adults using functional magnetic resonance imaging, we found stronger neural activities in the mid-cingulate, left insula and supplementary motor area (SMA) in response to racial in-group compared with out-group members' pain after participants had been primed with interdependent self-construals. However, the racial in-group bias in neural responses to others' pain in the left SMA, mid-cingulate cortex and insula was significantly reduced by priming independent self-construals. Our findings suggest that shifting an individual's self-construal leads to changes of his/her racial in-group bias in neural responses to others' suffering. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

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

Measuring Customer Behavior with Deep Convolutional Neural Networks

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Veaceslav Albu

2016-03-01

Full Text Available In this paper, we propose a neural network model for human emotion and gesture classification. We demonstrate that the proposed architecture represents an effective tool for real-time processing of customer's behavior for distributed on-land systems, such as information kiosks, automated cashiers and ATMs. The proposed approach combines most recent biometric techniques with the neural network approach for real-time emotion and behavioral analysis. In the series of experiments, emotions of human subjects were recorded, recognized, and analyzed to give statistical feedback of the overall emotions of a number of targets within a certain time frame. The result of the study allows automatic tracking of user’s behavior based on a limited set of observations.

Increasing Human Neural Stem Cell Transplantation Dose Alters Oligodendroglial and Neuronal Differentiation after Spinal Cord Injury

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Katja M. Piltti

2017-06-01

Full Text Available Multipotent human central nervous system-derived neural stem cells transplanted at doses ranging from 10,000 (low to 500,000 (very high cells differentiated predominantly into the oligodendroglial lineage. However, while the number of engrafted cells increased linearly in relationship to increasing dose, the proportion of oligodendrocytic cells declined. Increasing dose resulted in a plateau of engraftment, enhanced neuronal differentiation, and increased distal migration caudal to the transplantation sites. Dose had no effect on terminal sensory recovery or open-field locomotor scores. However, total human cell number and decreased oligodendroglial proportion were correlated with hindlimb girdle coupling errors. Conversely, greater oligodendroglial proportion was correlated with increased Ab step pattern, decreased swing speed, and increased paw intensity, consistent with improved recovery. These data suggest that transplant dose, and/or target niche parameters can regulate donor cell engraftment, differentiation/maturation, and lineage-specific migration profiles.

Revocation of European patent for neural progenitors highlights patent challenges for inventions relating to human embryonic stem cells.

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Rigby, Barbara

2013-11-01

Cells derived from human embryonic stem cells have great therapeutic potential. Patents are key to allowing companies that develop methods of generating such cells to recuperate their investment. However, in Europe, inventions relating to the use of human embryos for commercial purposes are excluded from patentability on moral grounds. The scope of this morality exclusion was recently tested before Germany's highest court and before the European Patent Office (EPO), with diverging results. The decision by the EPO's Opposition Division to revoke EP1040185 relating to neural precursors and methods for their generation has received a mixed reception. The decision has very recently been appealed, and the outcome of this Appeal should provide more definitive guidance on the scope of the morality exclusion.

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

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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.

Pre-evaluated safe human iPSC-derived neural stem cells promote functional recovery after spinal cord injury in common marmoset without tumorigenicity.

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Yoshiomi Kobayashi

Full Text Available Murine and human iPSC-NS/PCs (induced pluripotent stem cell-derived neural stem/progenitor cells promote functional recovery following transplantation into the injured spinal cord in rodents. However, for clinical applicability, it is critical to obtain proof of the concept regarding the efficacy of grafted human iPSC-NS/PCs (hiPSC-NS/PCs for the repair of spinal cord injury (SCI in a non-human primate model. This study used a pre-evaluated "safe" hiPSC-NS/PC clone and an adult common marmoset (Callithrix jacchus model of contusive SCI. SCI was induced at the fifth cervical level (C5, followed by transplantation of hiPSC-NS/PCs at 9 days after injury. Behavioral analyses were performed from the time of the initial injury until 12 weeks after SCI. Grafted hiPSC-NS/PCs survived and differentiated into all three neural lineages. Furthermore, transplantation of hiPSC-NS/PCs enhanced axonal sparing/regrowth and angiogenesis, and prevented the demyelination after SCI compared with that in vehicle control animals. Notably, no tumor formation occurred for at least 12 weeks after transplantation. Quantitative RT-PCR showed that mRNA expression levels of human neurotrophic factors were significantly higher in cultured hiPSC-NS/PCs than in human dermal fibroblasts (hDFs. Finally, behavioral tests showed that hiPSC-NS/PCs promoted functional recovery after SCI in the common marmoset. Taken together, these results indicate that pre-evaluated safe hiPSC-NS/PCs are a potential source of cells for the treatment of SCI in the clinic.

Embedding responses in spontaneous neural activity shaped through sequential learning.

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Tomoki Kurikawa

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

δ-Protocadherins: Organizers of neural circuit assembly.

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Light, Sarah E W; Jontes, James D

2017-09-01

The δ-protocadherins comprise a small family of homophilic cell adhesion molecules within the larger cadherin superfamily. They are essential for neural development as mutations in these molecules give rise to human neurodevelopmental disorders, such as schizophrenia and epilepsy, and result in behavioral defects in animal models. Despite their importance to neural development, a detailed understanding of their mechanisms and the ways in which their loss leads to changes in neural function is lacking. However, recent results have begun to reveal roles for the δ-protocadherins in both regulation of neurogenesis and lineage-dependent circuit assembly, as well as in contact-dependent motility and selective axon fasciculation. These evolutionarily conserved mechanisms could have a profound impact on the robust assembly of the vertebrate nervous system. Future work should be focused on unraveling the molecular mechanisms of the δ-protocadherins and understanding how this family functions broadly to regulate neural development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning from large scale neural simulations

DEFF Research Database (Denmark)

Serban, Maria

2017-01-01

Large-scale neural simulations have the marks of a distinct methodology which can be fruitfully deployed to advance scientific understanding of the human brain. Computer simulation studies can be used to produce surrogate observational data for better conceptual models and new how...

A neural theory of visual attention

DEFF Research Database (Denmark)

Bundesen, Claus; Habekost, Thomas; Kyllingsbæk, Søren

2005-01-01

A neural theory of visual attention (NTVA) is presented. NTVA is a neural interpretation of C. Bundesen's (1990) theory of visual attention (TVA). In NTVA, visual processing capacity is distributed across stimuli by dynamic remapping of receptive fields of cortical cells such that more processing...... resources (cells) are devoted to behaviorally important objects than to less important ones. By use of the same basic equations used in TVA, NTVA accounts for a wide range of known attentional effects in human performance (reaction times and error rates) and a wide range of effects observed in firing rates...

A stochastic learning algorithm for layered neural networks

International Nuclear Information System (INIS)

Bartlett, E.B.; Uhrig, R.E.

1992-01-01

The random optimization method typically uses a Gaussian probability density function (PDF) to generate a random search vector. In this paper the random search technique is applied to the neural network training problem and is modified to dynamically seek out the optimal probability density function (OPDF) from which to select the search vector. The dynamic OPDF search process, combined with an auto-adaptive stratified sampling technique and a dynamic node architecture (DNA) learning scheme, completes the modifications of the basic method. The DNA technique determines the appropriate number of hidden nodes needed for a given training problem. By using DNA, researchers do not have to set the neural network architectures before training is initiated. The approach is applied to networks of generalized, fully interconnected, continuous perceptions. Computer simulation results are given

Human mast cell neutral proteases generate modified LDL particles with increased proteoglycan binding.

Science.gov (United States)

Maaninka, Katariina; Nguyen, Su Duy; Mäyränpää, Mikko I; Plihtari, Riia; Rajamäki, Kristiina; Lindsberg, Perttu J; Kovanen, Petri T; Öörni, Katariina

2018-04-13

Subendothelial interaction of LDL with extracellular matrix drives atherogenesis. This interaction can be strengthened by proteolytic modification of LDL. Mast cells (MCs) are present in atherosclerotic lesions, and upon activation, they degranulate and release a variety of neutral proteases. Here we studied the ability of MC proteases to cleave apoB-100 of LDL and affect the binding of LDL to proteoglycans. Mature human MCs were differentiated from human peripheral blood-derived CD34 + progenitors in vitro and activated with calcium ionophore to generate MC-conditioned medium. LDL was incubated in the MC-conditioned medium or with individual MC proteases, and the binding of native and modified LDL to isolated human aortic proteoglycans or to human atherosclerotic plaques ex vivo was determined. MC proteases in atherosclerotic human coronary artery lesions were detected by immunofluorescence and qPCR. Activated human MCs released the neutral proteases tryptase, chymase, carboxypeptidase A3, cathepsin G, and granzyme B. Of these, cathepsin G degraded most efficiently apoB-100, induced LDL fusion, and enhanced binding of LDL to isolated human aortic proteoglycans and human atherosclerotic lesions ex vivo. Double immunofluoresence staining of human atherosclerotic coronary arteries for tryptase and cathepsin G indicated that lesional MCs contain cathepsin G. In the lesions, expression of cathepsin G correlated with the expression of tryptase and chymase, but not with that of neutrophil proteinase 3. The present study suggests that cathepsin G in human atherosclerotic lesions is largely derived from MCs and that activated MCs may contribute to atherogenesis by enhancing LDL retention. Copyright © 2018 Elsevier B.V. All rights reserved.

Pharmacological characterization of receptor-activity-modifying proteins (RAMPs) and the human calcitonin receptor.

Science.gov (United States)

Armour, S L; Foord, S; Kenakin, T; Chen, W J

1999-12-01

Receptor-activity-modifying proteins (RAMPs) are a family of single transmembrane domain proteins shown to be important for the transport and ligand specificity of the calcitonin gene-related peptide (CGRP) receptor. In this report, we describe the analysis of pharmacological properties of the human calcitonin receptor (hCTR) coexpressed with different RAMPs with the use of the Xenopus laevis melanophore expression system. We show that coexpression of RAMP3 with human calcitonin receptor changed the relative potency of hCTR to human calcitonin (hCAL) and rat amylin. RAMP1 and RAMP2, in contrast, had little effect on the change of hCTR potency to hCAL or rat amylin. When coexpressed with RAMP3, hCTR reversed the relative potency by a 3.5-fold loss in sensitivity to hCAL and a 19-fold increase in sensitivity to rat amylin. AC66, an inverse agonist, produced apparent simple competitive antagonism of hCAL and rat amylin, as indicated by linear Schild regressions. The potency of AC66 was changed in the blockade of rat amylin but not hCAL responses with RAMP3 coexpression. The mean pK(B) for AC66 to hCAL was 9.4 +/- 0.3 without RAMP3 and 9.45 +/- 0.07 with RAMP3. For the antagonism of AC66 to rat amylin, the pK(B) was 9.25 +/- 0.15 without RAMP3 and 8.2 +/- 0.35 with RAMP3. The finding suggests that RAMP3 might modify the active states of calcitonin receptor in such a way as to create a new receptor phenotype that is "amylin-like." Irrespective of the physiological association of the new receptor species, the finding that a coexpressed membrane protein can completely change agonist and antagonist affinities for a receptor raises implications for screening in recombinant receptor systems.

Learning in Artificial Neural Systems

Science.gov (United States)

Matheus, Christopher J.; Hohensee, William E.

1987-01-01

This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

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

Science.gov (United States)

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.

Phytochemicals for taming agitated immune-endocrine-neural axis.

Science.gov (United States)

Patel, Seema

2017-07-01

Homeostasis of immune-endocrine-neural axis is paramount for human health. If this axis gets agitated due to age, genetic variations, environmental exposures or lifestyle assaults, a cascade of adverse reactions occurs in human body. Cytokines, hormones and neurotransmitters, the effector molecules of this axis behave erratically, leading to a gamut of neural, endocrine, autoimmune, and metabolic diseases. Current panel of drugs can tackle some of them but not in a sustainable, benign way as a myriad of side effects, causal of them have been documented. In this context, phytochemicals, the secondary metabolites of plants seem beneficial. These bioactive constituents encompassing polyphenols, alkaloids, flavonoids, terpenoids, tannins, lignans, stilbenoids (resveratrol), saponins, polysaccharides, glycosides, and lectins etc. have been proven to exert antioxidant, anti-inflammatory, hypolipidemic, hypotensive, antidiabetic, anticancer, immunomodulatory, anti-allergic, analgesic, hepatoprotective, neuroprotective, dermatoprotective, and antimicrobial properties, among a litany of other biological effects. This review presents a holistic perspective of common afflictions resultant of immune-endocrine-neural axis disruption, and the phytochemicals capable of restoring their normalcy and mitigating the ailments. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Neural mechanisms underlying catastrophic failure in human-machine interaction during aerial navigation

Science.gov (United States)

Saproo, Sameer; Shih, Victor; Jangraw, David C.; Sajda, Paul

2016-12-01

Objective. We investigated the neural correlates of workload buildup in a fine visuomotor task called the boundary avoidance task (BAT). The BAT has been known to induce naturally occurring failures of human-machine coupling in high performance aircraft that can potentially lead to a crash—these failures are termed pilot induced oscillations (PIOs). Approach. We recorded EEG and pupillometry data from human subjects engaged in a flight BAT simulated within a virtual 3D environment. Main results. We find that workload buildup in a BAT can be successfully decoded from oscillatory features in the electroencephalogram (EEG). Information in delta, theta, alpha, beta, and gamma spectral bands of the EEG all contribute to successful decoding, however gamma band activity with a lateralized somatosensory topography has the highest contribution, while theta band activity with a fronto-central topography has the most robust contribution in terms of real-world usability. We show that the output of the spectral decoder can be used to predict PIO susceptibility. We also find that workload buildup in the task induces pupil dilation, the magnitude of which is significantly correlated with the magnitude of the decoded EEG signals. These results suggest that PIOs may result from the dysregulation of cortical networks such as the locus coeruleus (LC)—anterior cingulate cortex (ACC) circuit. Significance. Our findings may generalize to similar control failures in other cases of tight man-machine coupling where gains and latencies in the control system must be inferred and compensated for by the human operators. A closed-loop intervention using neurophysiological decoding of workload buildup that targets the LC-ACC circuit may positively impact operator performance in such situations.

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

Science.gov (United States)

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Review: the development of neural stem cell biology and technology in regenerative medicine

OpenAIRE

Shanmuganathan, Divyanjali; Sivakumaran, Nivethika

2018-01-01

In the middle of the last century, it has been known that neural stem cells (NSCs) play a key role in regenerative medicine to cure the neurodegenerative disease. This review article covers about the introduction to neural stem cell biology and the isolation, differentiation and transplantation methods/techniques of neural stem cells. The neural stem cells can be transplanted into the human brain in the future to replace the damaged and dead neurons. The highly limited access to embryonic ste...

Lymphotropic Virions Affect Chemokine Receptor-Mediated Neural Signaling and Apoptosis: Implications for Human Immunodeficiency Virus Type 1-Associated Dementia

Science.gov (United States)

Zheng, Jialin; Ghorpade, Anuja; Niemann, Douglas; Cotter, Robin L.; Thylin, Michael R.; Epstein, Leon; Swartz, Jennifer M.; Shepard, Robin B.; Liu, Xiaojuan; Nukuna, Adeline; Gendelman, Howard E.

1999-01-01

Chemokine receptors pivotal for human immunodeficiency virus type 1 (HIV-1) infection in lymphocytes and macrophages (CCR3, CCR5, and CXCR4) are expressed on neural cells (microglia, astrocytes, and/or neurons). It is these cells which are damaged during progressive HIV-1 infection of the central nervous system. We theorize that viral coreceptors could effect neural cell damage during HIV-1-associated dementia (HAD) without simultaneously affecting viral replication. To these ends, we studied the ability of diverse viral strains to affect intracellular signaling and apoptosis of neurons, astrocytes, and monocyte-derived macrophages. Inhibition of cyclic AMP, activation of inositol 1,4,5-trisphosphate, and apoptosis were induced by diverse HIV-1 strains, principally in neurons. Virions from T-cell-tropic (T-tropic) strains (MN, IIIB, and Lai) produced the most significant alterations in signaling of neurons and astrocytes. The HIV-1 envelope glycoprotein, gp120, induced markedly less neural damage than purified virions. Macrophage-tropic (M-tropic) strains (ADA, JR-FL, Bal, MS-CSF, and DJV) produced the least neural damage, while 89.6, a dual-tropic HIV-1 strain, elicited intermediate neural cell damage. All T-tropic strain-mediated neuronal impairments were blocked by the CXCR4 antibody, 12G5. In contrast, the M-tropic strains were only partially blocked by 12G5. CXCR4-mediated neuronal apoptosis was confirmed in pure populations of rat cerebellar granule neurons and was blocked by HA1004, an inhibitor of calcium/calmodulin-dependent protein kinase II, protein kinase A, and protein kinase C. Taken together, these results suggest that progeny HIV-1 virions can influence neuronal signal transduction and apoptosis. This process occurs, in part, through CXCR4 and is independent of CD4 binding. T-tropic viruses that traffic in and out of the brain during progressive HIV-1 disease may play an important role in HAD neuropathogenesis. PMID:10482576

Radioactive fallout and neural tube defects

African Journals Online (AJOL)

Nejat Akar

2015-07-10

Jul 10, 2015 ... It is a prenatal failure of the embryonic neural tube to close over the ... and the ability of radioisotopes to attach to cells, tissues, and ... The Egyptian Journal of Medical Human Genetics .... Stem Cells 1997;15(Suppl 2):255–60.

Therapeutic physical exercise in neural injury: friend or foe?

Science.gov (United States)

Park, Kanghui; Lee, Seunghoon; Hong, Yunkyung; Park, Sookyoung; Choi, Jeonghyun; Chang, Kyu-Tae; Kim, Joo-Heon; Hong, Yonggeun

2015-12-01

[Purpose] The intensity of therapeutic physical exercise is complex and sometimes controversial in patients with neural injuries. This review assessed whether therapeutic physical exercise is beneficial according to the intensity of the physical exercise. [Methods] The authors identified clinically or scientifically relevant articles from PubMed that met the inclusion criteria. [Results] Exercise training can improve body strength and lead to the physiological adaptation of skeletal muscles and the nervous system after neural injuries. Furthermore, neurophysiological and neuropathological studies show differences in the beneficial effects of forced therapeutic exercise in patients with severe or mild neural injuries. Forced exercise alters the distribution of muscle fiber types in patients with neural injuries. Based on several animal studies, forced exercise may promote functional recovery following cerebral ischemia via signaling molecules in ischemic brain regions. [Conclusions] This review describes several types of therapeutic forced exercise and the controversy regarding the therapeutic effects in experimental animals versus humans with neural injuries. This review also provides a therapeutic strategy for physical therapists that grades the intensity of forced exercise according to the level of neural injury.

Sphingosine-1-Phosphate (S1P) Signaling in Neural Progenitors.

Science.gov (United States)

Callihan, Phillip; Alqinyah, Mohammed; Hooks, Shelley B

2018-01-01

Sphingosine-1-phosphate (S1P) and its receptors are important in nervous system development. Reliable in vitro human model systems are needed to further define specific roles for S1P signaling in neural development. We have described S1P-regulated signaling, survival, and differentiation in a human embryonic stem cell-derived neuroepithelial progenitor cell line (hNP1) that expresses functional S1P receptors. These cells can be further differentiated to a neuronal cell type and therefore represent a good model system to study the role of S1P signaling in human neural development. The following sections describe in detail the culture and differentiation of hNP1 cells and two assays to measure S1P signaling in these cells.

Development of a colloidal gold immunochromatographic strip assay for simple and fast detection of human α-lactalbumin in genetically modified cow milk.

Science.gov (United States)

Tao, Chenyu; Zhang, Qingde; Feng, Na; Shi, Deshi; Liu, Bang

2016-03-01

The qualitative and quantitative declaration of food ingredients is important to consumers, especially for genetically modified food as it experiences a rapid increase in sales. In this study, we designed an accurate and rapid detection system using colloidal gold immunochromatographic strip assay (GICA) methods to detect genetically modified cow milk. First, we prepared 2 monoclonal antibodies for human α-lactalbumin (α-LA) and measured their antibody titers; the one with the higher titer was used for further experiments. Then, we found the optimal pH value and protein amount of GICA for detection of pure milk samples. The developed strips successfully detected genetically modified cow milk and non-modified cow milk. To determine the sensitivity of GICA, a quantitative ELISA system was used to determine the exact amount of α-LA, and then genetically modified milk was diluted at different rates to test the sensitivity of GICA; the sensitivity was 10 μg/mL. Our results demonstrated that the applied method was effective to detect human α-LA in cow milk. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Induction of apoptotic death and retardation of neuronal differentiation of human neural stem cells by sodium arsenite treatment

Energy Technology Data Exchange (ETDEWEB)

Ivanov, Vladimir N., E-mail: vni3@columbia.edu [Center for Radiological Research, Department of Radiation Oncology, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, NY 10032 (United States); Hei, Tom K. [Center for Radiological Research, Department of Radiation Oncology, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, NY 10032 (United States)

2013-04-01

Chronic arsenic toxicity is a global health problem that affects more than 100 million people worldwide. Long-term health effects of inorganic sodium arsenite in drinking water may result in skin, lung and liver cancers and in severe neurological abnormalities. We investigated in the present study whether sodium arsenite affects signaling pathways that control cell survival, proliferation and neuronal differentiation of human neural stem cells (NSC). We demonstrated that the critical signaling pathway, which was suppressed by sodium arsenite in NSC, was the protective PI3K–AKT pathway. Sodium arsenite (2–4 μM) also caused down-regulation of Nanog, one of the key transcription factors that control pluripotency and self-renewal of stem cells. Mitochondrial damage and cytochrome-c release induced by sodium arsenite exposure was followed by initiation of the mitochondrial apoptotic pathway in NSC. Beside caspase-9 and caspase-3 inhibitors, suppression of JNK activity decreased levels of arsenite-induced apoptosis in NSC. Neuronal differentiation of NSC was substantially inhibited by sodium arsenite exposure. Overactivation of JNK1 and ERK1/2 and down-regulation of PI3K–AKT activity induced by sodium arsenite were critical factors that strongly affected neuronal differentiation. In conclusion, sodium arsenite exposure of human NSC induces the mitochondrial apoptotic pathway, which is substantially accelerated due to the simultaneous suppression of PI3K–AKT. Sodium arsenite also negatively affects neuronal differentiation of NSC through overactivation of MEK–ERK and suppression of PI3K–AKT. - Highlights: ► Arsenite induces the mitochondrial apoptotic pathway in human neural stem cells. ► Arsenite-induced apoptosis is strongly upregulated by suppression of PI3K–AKT. ► Arsenite-induced apoptosis is strongly down-regulated by inhibition of JNK–cJun. ► Arsenite negatively affects neuronal differentiation by inhibition of PI3K–AKT.

Induction of apoptotic death and retardation of neuronal differentiation of human neural stem cells by sodium arsenite treatment

International Nuclear Information System (INIS)

Ivanov, Vladimir N.; Hei, Tom K.

2013-01-01

Chronic arsenic toxicity is a global health problem that affects more than 100 million people worldwide. Long-term health effects of inorganic sodium arsenite in drinking water may result in skin, lung and liver cancers and in severe neurological abnormalities. We investigated in the present study whether sodium arsenite affects signaling pathways that control cell survival, proliferation and neuronal differentiation of human neural stem cells (NSC). We demonstrated that the critical signaling pathway, which was suppressed by sodium arsenite in NSC, was the protective PI3K–AKT pathway. Sodium arsenite (2–4 μM) also caused down-regulation of Nanog, one of the key transcription factors that control pluripotency and self-renewal of stem cells. Mitochondrial damage and cytochrome-c release induced by sodium arsenite exposure was followed by initiation of the mitochondrial apoptotic pathway in NSC. Beside caspase-9 and caspase-3 inhibitors, suppression of JNK activity decreased levels of arsenite-induced apoptosis in NSC. Neuronal differentiation of NSC was substantially inhibited by sodium arsenite exposure. Overactivation of JNK1 and ERK1/2 and down-regulation of PI3K–AKT activity induced by sodium arsenite were critical factors that strongly affected neuronal differentiation. In conclusion, sodium arsenite exposure of human NSC induces the mitochondrial apoptotic pathway, which is substantially accelerated due to the simultaneous suppression of PI3K–AKT. Sodium arsenite also negatively affects neuronal differentiation of NSC through overactivation of MEK–ERK and suppression of PI3K–AKT. - Highlights: ► Arsenite induces the mitochondrial apoptotic pathway in human neural stem cells. ► Arsenite-induced apoptosis is strongly upregulated by suppression of PI3K–AKT. ► Arsenite-induced apoptosis is strongly down-regulated by inhibition of JNK–cJun. ► Arsenite negatively affects neuronal differentiation by inhibition of PI3K–AKT

Nanoengineered Polystyrene Surfaces with Nanopore Array Pattern Alters Cytoskeleton Organization and Enhances Induction of Neural Differentiation of Human Adipose-Derived Stem Cells.

Science.gov (United States)

Jung, Ae Ryang; Kim, Richard Y; Kim, Hyung Woo; Shrestha, Kshitiz Raj; Jeon, Seung Hwan; Cha, Kyoung Je; Park, Yong Hyun; Kim, Dong Sung; Lee, Ji Youl

2015-07-01

Human adipose-derived stem cells (hADSCs) can differentiate into various cell types depending on chemical and topographical cues. One topographical cue recently noted to be successful in inducing differentiation is the nanoengineered polystyrene surface containing nanopore array-patterned substrate (NP substrate), which is designed to mimic the nanoscale topographical features of the extracellular matrix. In this study, efficacies of NP and flat substrates in inducing neural differentiation of hADSCs were examined by comparing their substrate-cell adhesion rates, filopodia growth, nuclei elongation, and expression of neural-specific markers. The polystyrene nano Petri dishes containing NP substrates were fabricated by a nano injection molding process using a nickel electroformed nano-mold insert (Diameter: 200 nm. Depth of pore: 500 nm. Center-to-center distance: 500 nm). Cytoskeleton and filopodia structures were observed by scanning electron microscopy and F-actin staining, while cell adhesion was tested by vinculin staining after 24 and 48 h of seeding. Expression of neural specific markers was examined by real-time quantitative polymerase chain reaction and immunocytochemistry. Results showed that NP substrates lead to greater substrate-cell adhesion, filopodia growth, nuclei elongation, and expression of neural specific markers compared to flat substrates. These results not only show the advantages of NP substrates, but they also suggest that further study into cell-substrate interactions may yield great benefits for biomaterial engineering.

A model of interval timing by neural integration.

Science.gov (United States)

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Neural Interfaces for Intracortical Recording: Requirements, Fabrication Methods, and Characteristics.

Science.gov (United States)

Szostak, Katarzyna M; Grand, Laszlo; Constandinou, Timothy G

2017-01-01

Implantable neural interfaces for central nervous system research have been designed with wire, polymer, or micromachining technologies over the past 70 years. Research on biocompatible materials, ideal probe shapes, and insertion methods has resulted in building more and more capable neural interfaces. Although the trend is promising, the long-term reliability of such devices has not yet met the required criteria for chronic human application. The performance of neural interfaces in chronic settings often degrades due to foreign body response to the implant that is initiated by the surgical procedure, and related to the probe structure, and material properties used in fabricating the neural interface. In this review, we identify the key requirements for neural interfaces for intracortical recording, describe the three different types of probes-microwire, micromachined, and polymer-based probes; their materials, fabrication methods, and discuss their characteristics and related challenges.

Introduction to neural networks in high energy physics

International Nuclear Information System (INIS)

Therhaag, J.

2013-01-01

Artificial neural networks are a well established tool in high energy physics, playing an important role in both online and offline data analysis. Nevertheless they are often perceived as black boxes which perform obscure operations beyond the control of the user, resulting in a skepticism against any results that may be obtained using them. The situation is not helped by common explanations which try to draw analogies between artificial neural networks and the human brain, for the brain is an even more complex black box itself. In this introductory text, I will take a problem-oriented approach to neural network techniques, showing how the fundamental concepts arise naturally from the demand to solve classification tasks which are frequently encountered in high energy physics. Particular attention is devoted to the question how probability theory can be used to control the complexity of neural networks. (authors)

Unjoined primary and secondary neural tubes: junctional neural tube defect, a new form of spinal dysraphism caused by disturbance of junctional neurulation.

Science.gov (United States)

Eibach, Sebastian; Moes, Greg; Hou, Yong Jin; Zovickian, John; Pang, Dachling

2017-10-01

Primary and secondary neurulation are the two known processes that form the central neuraxis of vertebrates. Human phenotypes of neural tube defects (NTDs) mostly fall into two corresponding categories consistent with the two types of developmental sequence: primary NTD features an open skin defect, an exposed, unclosed neural plate (hence an open neural tube defect, or ONTD), and an unformed or poorly formed secondary neural tube, and secondary NTD with no skin abnormality (hence a closed NTD) and a malformed conus caudal to a well-developed primary neural tube. We encountered three cases of a previously unrecorded form of spinal dysraphism in which the primary and secondary neural tubes are individually formed but are physically separated far apart and functionally disconnected from each other. One patient was operated on, in whom both the lumbosacral spinal cord from primary neurulation and the conus from secondary neurulation are each anatomically complete and endowed with functioning segmental motor roots tested by intraoperative triggered electromyography and direct spinal cord stimulation. The remarkable feature is that the two neural tubes are unjoined except by a functionally inert, probably non-neural band. The developmental error of this peculiar malformation probably occurs during the critical transition between the end of primary and the beginning of secondary neurulation, in a stage aptly called junctional neurulation. We describe the current knowledge concerning junctional neurulation and speculate on the embryogenesis of this new class of spinal dysraphism, which we call junctional neural tube defect.

CD133-enriched Xeno-Free human embryonic-derived neural stem cells expand rapidly in culture and do not form teratomas in immunodeficient mice

Directory of Open Access Journals (Sweden)

Daniel L. Haus

2014-09-01

Full Text Available Common methods for the generation of human embryonic-derived neural stem cells (hNSCs result in cells with potentially compromised safety profiles due to maintenance of cells in conditions containing non-human proteins (e.g. in bovine serum or on mouse fibroblast feeders. Additionally, sufficient expansion of resulting hNSCs for scaling out or up in a clinically relevant time frame has proven to be difficult. Here, we report a strategy that produces hNSCs in completely “Xeno-Free” culture conditions. Furthermore, we have enriched the hNSCs for the cell surface marker CD133 via magnetic sorting, which has led to an increase in the expansion rate and neuronal fate specification of the hNSCs in vitro. Critically, we have also confirmed neural lineage specificity upon sorted hNSC transplantation into the immunodeficient NOD-scid mouse brain. The future use or adaptation of these protocols has the potential to better facilitate the advancement of pre-clinical strategies from the bench to the bedside.

EEG signal classification using PSO trained RBF neural network for epilepsy identification

Directory of Open Access Journals (Sweden)

Sandeep Kumar Satapathy

Full Text Available The electroencephalogram (EEG is a low amplitude signal generated in the brain, as a result of information flow during the communication of several neurons. Hence, careful analysis of these signals could be useful in understanding many human brain disorder diseases. One such disease topic is epileptic seizure identification, which can be identified via a classification process of the EEG signal after preprocessing with the discrete wavelet transform (DWT. To classify the EEG signal, we used a radial basis function neural network (RBFNN. As shown herein, the network can be trained to optimize the mean square error (MSE by using a modified particle swarm optimization (PSO algorithm. The key idea behind the modification of PSO is to introduce a method to overcome the problem of slow searching in and around the global optimum solution. The effectiveness of this procedure was verified by an experimental analysis on a benchmark dataset which is publicly available. The result of our experimental analysis revealed that the improvement in the algorithm is significant with respect to RBF trained by gradient descent and canonical PSO. Here, two classes of EEG signals were considered: the first being an epileptic and the other being non-epileptic. The proposed method produced a maximum accuracy of 99% as compared to the other techniques. Keywords: Electroencephalography, Radial basis function neural network, Particle swarm optimization, Discrete wavelet transform, Machine learning