A Constructive Neural-Network Approach to Modeling Psychological Development

ERIC Educational Resources Information Center

Shultz, Thomas R.

2012-01-01

This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept…

Python scripting in the nengo simulator.

PubMed

Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

2009-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

Python Scripting in the Nengo Simulator

PubMed Central

Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective.

PubMed

Krystal, John H; Anticevic, Alan; Yang, Genevieve J; Dragoi, George; Driesen, Naomi R; Wang, Xiao-Jing; Murray, John D

2017-05-15

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders. Published by Elsevier Inc.

Should I stay or should I go? Cadherin function and regulation in the neural crest

PubMed Central

Taneyhill, Lisa A.; Schiffmacher, Andrew T.

2017-01-01

Our increasing comprehension of neural crest cell development has reciprocally advanced our understanding of cadherin expression, regulation, and function. As a transient population of multipotent stem cells that significantly contribute to the vertebrate body plan, neural crest cells undergo a variety of transformative processes and exhibit many cellular behaviors, including epithelial-to-mesenchymal-transition (EMT), motility, collective cell migration, and differentiation. Multiple studies have elucidated regulatory and mechanistic details of specific cadherins during neural crest cell development in a highly contextual manner. Collectively, these results reveal that gradual changes within neural crest cells are accompanied by often times subtle, yet important, alterations in cadherin expression and function. The primary focus of this review is to coalesce recent data on cadherins in neural crest cells, from their specification to their emergence as motile cells soon after EMT, and to highlight the complexities of cadherin expression beyond our current perceptions, including the hypothesis that the neural crest EMT is a transition involving a predominantly singular cadherin switch. Further advancements in genetic approaches and molecular techniques will provide greater opportunities to integrate data from various model systems in order to distinguish unique or overlapping functions of cadherins expressed at any point throughout the ontogeny of the neural crest. PMID:28253541

Synaptic Inputs Compete during Rapid Formation of the Calyx of Held: A New Model System for Neural Development

PubMed Central

Holcomb, Paul S.; Hoffpauir, Brian K.; Hoyson, Mitchell C.; Jackson, Dakota R.; Deerinck, Thomas J.; Marrs, Glenn S.; Dehoff, Marlin; Wu, Jonathan; Ellisman, Mark H.

2013-01-01

Hallmark features of neural circuit development include early exuberant innervation followed by competition and pruning to mature innervation topography. Several neural systems, including the neuromuscular junction and climbing fiber innervation of Purkinje cells, are models to study neural development in part because they establish a recognizable endpoint of monoinnervation of their targets and because the presynaptic terminals are large and easily monitored. We demonstrate here that calyx of Held (CH) innervation of its target, which forms a key element of auditory brainstem binaural circuitry, exhibits all of these characteristics. To investigate CH development, we made the first application of serial block-face scanning electron microscopy to neural development with fine temporal resolution and thereby accomplished the first time series for 3D ultrastructural analysis of neural circuit formation. This approach revealed a growth spurt of added apposed surface area (ASA) >200 μm2/d centered on a single age at postnatal day 3 in mice and an initial rapid phase of growth and competition that resolved to monoinnervation in two-thirds of cells within 3 d. This rapid growth occurred in parallel with an increase in action potential threshold, which may mediate selection of the strongest input as the winning competitor. ASAs of competing inputs were segregated on the cell body surface. These data suggest mechanisms to select “winning” inputs by regional reinforcement of postsynaptic membrane to mediate size and strength of competing synaptic inputs. PMID:23926251

Neural Networks for Flight Control

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1996-01-01

Neural networks are being developed at NASA Ames Research Center to permit real-time adaptive control of time varying nonlinear systems, enhance the fault-tolerance of mission hardware, and permit online system reconfiguration. In general, the problem of controlling time varying nonlinear systems with unknown structures has not been solved. Adaptive neural control techniques show considerable promise and are being applied to technical challenges including automated docking of spacecraft, dynamic balancing of the space station centrifuge, online reconfiguration of damaged aircraft, and reducing cost of new air and spacecraft designs. Our experiences have shown that neural network algorithms solved certain problems that conventional control methods have been unable to effectively address. These include damage mitigation in nonlinear reconfiguration flight control, early performance estimation of new aircraft designs, compensation for damaged planetary mission hardware by using redundant manipulator capability, and space sensor platform stabilization. This presentation explored these developments in the context of neural network control theory. The discussion began with an overview of why neural control has proven attractive for NASA application domains. The more important issues in control system development were then discussed with references to significant technical advances in the literature. Examples of how these methods have been applied were given, followed by projections of emerging application needs and directions.

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

PubMed

Hall, Brian K

2018-04-10

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

Meninges harbor cells expressing neural precursor markers during development and adulthood.

PubMed

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood.

Meninges harbor cells expressing neural precursor markers during development and adulthood

PubMed Central

Bifari, Francesco; Berton, Valeria; Pino, Annachiara; Kusalo, Marijana; Malpeli, Giorgio; Di Chio, Marzia; Bersan, Emanuela; Amato, Eliana; Scarpa, Aldo; Krampera, Mauro; Fumagalli, Guido; Decimo, Ilaria

2015-01-01

Brain and skull developments are tightly synchronized, allowing the cranial bones to dynamically adapt to the brain shape. At the brain-skull interface, meninges produce the trophic signals necessary for normal corticogenesis and bone development. Meninges harbor different cell populations, including cells forming the endosteum of the cranial vault. Recently, we and other groups have described the presence in meninges of a cell population endowed with neural differentiation potential in vitro and, after transplantation, in vivo. However, whether meninges may be a niche for neural progenitor cells during embryonic development and in adulthood remains to be determined. In this work we provide the first description of the distribution of neural precursor markers in rat meninges during development up to adulthood. We conclude that meninges share common properties with the classical neural stem cell niche, as they: (i) are a highly proliferating tissue; (ii) host cells expressing neural precursor markers such as nestin, vimentin, Sox2 and doublecortin; and (iii) are enriched in extracellular matrix components (e.g., fractones) known to bind and concentrate growth factors. This study underlines the importance of meninges as a potential niche for endogenous precursor cells during development and in adulthood. PMID:26483637

Fgfr1 regulates patterning of the pharyngeal region

PubMed Central

Trokovic, Nina; Trokovic, Ras; Mai, Petra; Partanen, Juha

2003-01-01

Development of the pharyngeal region depends on the interaction and integration of different cell populations, including surface ectoderm, foregut endoderm, paraxial mesoderm, and neural crest. Mice homozygous for a hypomorphic allele of Fgfr1 have craniofacial defects, some of which appeared to result from a failure in the early development of the second branchial arch. A stream of neural crest cells was found to originate from the rhombomere 4 region and migrate toward the second branchial arch in the mutants. Neural crest cells mostly failed to enter the second arch, however, but accumulated in a region proximal to it. Both rescue of the hypomorphic Fgfr1 allele and inactivation of a conditional Fgfr1 allele specifically in neural crest cells indicated that Fgfr1 regulates the entry of neural crest cells into the second branchial arch non-cell-autonomously. Gene expression in the pharyngeal ectoderm overlying the developing second branchial arch was affected in the hypomorphic Fgfr1 mutants at a stage prior to neural crest entry. Our results indicate that Fgfr1 patterns the pharyngeal region to create a permissive environment for neural crest cell migration. PMID:12514106

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

PubMed

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

2012-04-01

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

Medical image analysis with artificial neural networks.

PubMed

Jiang, J; Trundle, P; Ren, J

2010-12-01

Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multipotent Caudal Neural Progenitors Derived from Human Pluripotent Stem Cells That Give Rise to Lineages of the Central and Peripheral Nervous System

PubMed Central

Hasegawa, Kouichi; Menheniott, Trevelyan; Rollo, Ben; Zhang, Dongcheng; Hough, Shelley; Alshawaf, Abdullah; Febbraro, Fabia; Ighaniyan, Samiramis; Leung, Jessie; Elliott, David A.; Newgreen, Donald F.; Pera, Martin F.

2015-01-01

Abstract The caudal neural plate is a distinct region of the embryo that gives rise to major progenitor lineages of the developing central and peripheral nervous system, including neural crest and floor plate cells. We show that dual inhibition of the glycogen synthase kinase 3β and activin/nodal pathways by small molecules differentiate human pluripotent stem cells (hPSCs) directly into a preneuroepithelial progenitor population we named “caudal neural progenitors” (CNPs). CNPs coexpress caudal neural plate and mesoderm markers, and, share high similarities to embryonic caudal neural plate cells in their lineage differentiation potential. Exposure of CNPs to BMP2/4, sonic hedgehog, or FGF2 signaling efficiently directs their fate to neural crest/roof plate cells, floor plate cells, and caudally specified neuroepithelial cells, respectively. Neural crest derived from CNPs differentiated to neural crest derivatives and demonstrated extensive migratory properties in vivo. Importantly, we also determined the key extrinsic factors specifying CNPs from human embryonic stem cell include FGF8, canonical WNT, and IGF1. Our studies are the first to identify a multipotent neural progenitor derived from hPSCs, that is the precursor for major neural lineages of the embryonic caudal neural tube. Stem Cells 2015;33:1759–1770 PMID:25753817

The Effects of GABAergic Polarity Changes on Episodic Neural Network Activity in Developing Neural Systems.

PubMed

Blanco, Wilfredo; Bertram, Richard; Tabak, Joël

2017-01-01

Early in development, neural systems have primarily excitatory coupling, where even GABAergic synapses are excitatory. Many of these systems exhibit spontaneous episodes of activity that have been characterized through both experimental and computational studies. As development progress the neural system goes through many changes, including synaptic remodeling, intrinsic plasticity in the ion channel expression, and a transformation of GABAergic synapses from excitatory to inhibitory. What effect each of these, and other, changes have on the network behavior is hard to know from experimental studies since they all happen in parallel. One advantage of a computational approach is that one has the ability to study developmental changes in isolation. Here, we examine the effects of GABAergic synapse polarity change on the spontaneous activity of both a mean field and a neural network model that has both glutamatergic and GABAergic coupling, representative of a developing neural network. We find some intuitive behavioral changes as the GABAergic neurons go from excitatory to inhibitory, shared by both models, such as a decrease in the duration of episodes. We also find some paradoxical changes in the activity that are only present in the neural network model. In particular, we find that during early development the inter-episode durations become longer on average, while later in development they become shorter. In addressing this unexpected finding, we uncover a priming effect that is particularly important for a small subset of neurons, called the "intermediate neurons." We characterize these neurons and demonstrate why they are crucial to episode initiation, and why the paradoxical behavioral change result from priming of these neurons. The study illustrates how even arguably the simplest of developmental changes that occurs in neural systems can present non-intuitive behaviors. It also makes predictions about neural network behavioral changes that occur during development that may be observable even in actual neural systems where these changes are convoluted with changes in synaptic connectivity and intrinsic neural plasticity.

Anomalous Development of Brain Structure and Function in Spina Bifida Myelomeningocele

ERIC Educational Resources Information Center

Juranek, Jenifer; Salman, Michael S.

2010-01-01

Spina bifida myelomeningocele (SBM) is a specific type of neural tube defect whereby the open neural tube at the level of the spinal cord alters brain development during early stages of gestation. Some structural anomalies are virtually unique to individuals with SBM, including a complex pattern of cerebellar dysplasia known as the Chiari II…

Learning and adaptation: neural and behavioural mechanisms behind behaviour change

NASA Astrophysics Data System (ADS)

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.

Enteric nervous system specific deletion of Foxd3 disrupts glial cell differentiation and activates compensatory enteric progenitors.

PubMed

Mundell, Nathan A; Plank, Jennifer L; LeGrone, Alison W; Frist, Audrey Y; Zhu, Lei; Shin, Myung K; Southard-Smith, E Michelle; Labosky, Patricia A

2012-03-15

The enteric nervous system (ENS) arises from the coordinated migration, expansion and differentiation of vagal and sacral neural crest progenitor cells. During development, vagal neural crest cells enter the foregut and migrate in a rostro-to-caudal direction, colonizing the entire gastrointestinal tract and generating the majority of the ENS. Sacral neural crest contributes to a subset of enteric ganglia in the hindgut, colonizing the colon in a caudal-to-rostral wave. During this process, enteric neural crest-derived progenitors (ENPs) self-renew and begin expressing markers of neural and glial lineages as they populate the intestine. Our earlier work demonstrated that the transcription factor Foxd3 is required early in neural crest-derived progenitors for self-renewal, multipotency and establishment of multiple neural crest-derived cells and structures including the ENS. Here, we describe Foxd3 expression within the fetal and postnatal intestine: Foxd3 was strongly expressed in ENPs as they colonize the gastrointestinal tract and was progressively restricted to enteric glial cells. Using a novel Ednrb-iCre transgene to delete Foxd3 after vagal neural crest cells migrate into the midgut, we demonstrated a late temporal requirement for Foxd3 during ENS development. Lineage labeling of Ednrb-iCre expressing cells in Foxd3 mutant embryos revealed a reduction of ENPs throughout the gut and loss of Ednrb-iCre lineage cells in the distal colon. Although mutant mice were viable, defects in patterning and distribution of ENPs were associated with reduced proliferation and severe reduction of glial cells derived from the Ednrb-iCre lineage. Analyses of ENS-lineage and differentiation in mutant embryos suggested activation of a compensatory population of Foxd3-positive ENPs that did not express the Ednrb-iCre transgene. Our findings highlight the crucial roles played by Foxd3 during ENS development including progenitor proliferation, neural patterning, and glial differentiation and may help delineate distinct molecular programs controlling vagal versus sacral neural crest development. Copyright © 2012 Elsevier Inc. All rights reserved.

Neural Tuning to Numerosity Relates to Perceptual Tuning in 3-6-Year-Old Children.

PubMed

Kersey, Alyssa J; Cantlon, Jessica F

2017-01-18

Neural representations of approximate numerical value, or numerosity, have been observed in the intraparietal sulcus (IPS) in monkeys and humans, including children. Using functional magnetic resonance imaging, we show that children as young as 3-4 years old exhibit neural tuning to cardinal numerosities in the IPS and that their neural responses are accounted for by a model of numerosity coding that has been used to explain neural responses in the adult IPS. We also found that the sensitivity of children's neural tuning to number in the right IPS was comparable to their numerical discrimination sensitivity observed behaviorally, outside of the scanner. Children's neural tuning curves in the right IPS were significantly sharper than in the left IPS, indicating that numerical representations are more precise and mature more rapidly in the right hemisphere than in the left. Further, we show that children's perceptual sensitivity to numerosity can be predicted by the development of their neural sensitivity to numerosity. This research provides novel evidence of developmental continuity in the neural code underlying numerical representation and demonstrates that children's neural sensitivity to numerosity is related to their cognitive development. Here we test for the existence of neural tuning to numerosity in the developing brain in the youngest sample of children tested with fMRI to date. Although previous research shows evidence of numerical distance effects in the intraparietal sulcus of the developing brain, those effects could be explained by patterns of neural activity that do not represent neural tuning to numerosity. These data provide the first robust evidence that from as early as 3-4 years of age there is developmental continuity in how the intraparietal sulcus represents the values of numerosities. Moreover, the study goes beyond previous research by examining the relation between neural tuning and perceptual tuning in children. Copyright © 2017 the authors 0270-6474/17/370512-11$15.00/0.

Rapid Postnatal Expansion of Neural Networks Occurs in an Environment of Altered Neurovascular and Neurometabolic Coupling.

PubMed

Kozberg, Mariel G; Ma, Ying; Shaik, Mohammed A; Kim, Sharon H; Hillman, Elizabeth M C

2016-06-22

In the adult brain, increases in neural activity lead to increases in local blood flow. However, many prior measurements of functional hemodynamics in the neonatal brain, including functional magnetic resonance imaging (fMRI) in human infants, have noted altered and even inverted hemodynamic responses to stimuli. Here, we demonstrate that localized neural activity in early postnatal mice does not evoke blood flow increases as in the adult brain, and elucidate the neural and metabolic correlates of these altered functional hemodynamics as a function of developmental age. Using wide-field GCaMP imaging, the development of neural responses to somatosensory stimulus is visualized over the entire bilaterally exposed cortex. Neural responses are observed to progress from tightly localized, unilateral maps to bilateral responses as interhemispheric connectivity becomes established. Simultaneous hemodynamic imaging confirms that spatiotemporally coupled functional hyperemia is not present during these early stages of postnatal brain development, and develops gradually as cortical connectivity is established. Exploring the consequences of this lack of functional hyperemia, measurements of oxidative metabolism via flavoprotein fluorescence suggest that neural activity depletes local oxygen to below baseline levels at early developmental stages. Analysis of hemoglobin oxygenation dynamics at the same age confirms oxygen depletion for both stimulus-evoked and resting-state neural activity. This state of unmet metabolic demand during neural network development poses new questions about the mechanisms of neurovascular development and its role in both normal and abnormal brain development. These results also provide important insights for the interpretation of fMRI studies of the developing brain. This work demonstrates that the postnatal development of neuronal connectivity is accompanied by development of the mechanisms that regulate local blood flow in response to neural activity. Novel in vivo imaging reveals that, in the developing mouse brain, strong and localized GCaMP neural responses to stimulus fail to evoke local blood flow increases, leading to a state in which oxygen levels become locally depleted. These results demonstrate that the development of cortical connectivity occurs in an environment of altered energy availability that itself may play a role in shaping normal brain development. These findings have important implications for understanding the pathophysiology of abnormal developmental trajectories, and for the interpretation of functional magnetic resonance imaging data acquired in the developing brain. Copyright © 2016 the authors 0270-6474/16/366704-14$15.00/0.

Development of human nervous tissue upon differentiation of embryonic stem cells in three-dimensional culture.

PubMed

Preynat-Seauve, Olivier; Suter, David M; Tirefort, Diderik; Turchi, Laurent; Virolle, Thierry; Chneiweiss, Herve; Foti, Michelangelo; Lobrinus, Johannes-Alexander; Stoppini, Luc; Feki, Anis; Dubois-Dauphin, Michel; Krause, Karl Heinz

2009-03-01

Researches on neural differentiation using embryonic stem cells (ESC) require analysis of neurogenesis in conditions mimicking physiological cellular interactions as closely as possible. In this study, we report an air-liquid interface-based culture of human ESC. This culture system allows three-dimensional cell expansion and neural differentiation in the absence of added growth factors. Over a 3-month period, a macroscopically visible, compact tissue developed. Histological coloration revealed a dense neural-like neural tissue including immature tubular structures. Electron microscopy, immunochemistry, and electrophysiological recordings demonstrated a dense network of neurons, astrocytes, and oligodendrocytes able to propagate signals. Within this tissue, tubular structures were niches of cells resembling germinal layers of human fetal brain. Indeed, the tissue contained abundant proliferating cells expressing markers of neural progenitors. Finally, the capacity to generate neural tissues on air-liquid interface differed for different ESC lines, confirming variations of their neurogenic potential. In conclusion, this study demonstrates in vitro engineering of a human neural-like tissue with an organization that bears resemblance to early developing brain. As opposed to previously described methods, this differentiation (a) allows three-dimensional organization, (b) yields dense interconnected neural tissue with structurally and functionally distinct areas, and (c) is spontaneously guided by endogenous developmental cues.

Emergence and migration of trunk neural crest cells in a snake, the California Kingsnake (Lampropeltis getula californiae)

PubMed Central

2010-01-01

Background The neural crest is a group of multipotent cells that emerges after an epithelial-to-mesenchymal transition from the dorsal neural tube early during development. These cells then migrate throughout the embryo, giving rise to a wide variety derivatives including the peripheral nervous system, craniofacial skeleton, pigment cells, and endocrine organs. While much is known about neural crest cells in mammals, birds, amphibians and fish, relatively little is known about their development in non-avian reptiles like snakes and lizards. Results In this study, we show for the first time ever trunk neural crest migration in a snake by labeling it with DiI and immunofluorescence. As in birds and mammals, we find that early migrating trunk neural crest cells use both a ventromedial pathway and an inter-somitic pathway in the snake. However, unlike birds and mammals, we also observed large numbers of late migrating neural crest cells utilizing the inter-somitic pathway in snake. Conclusions We found that while trunk neural crest migration in snakes is very similar to that of other amniotes, the inter-somitic pathway is used more extensively by late-migrating trunk neural crest cells in snake. PMID:20482793

Emergence and migration of trunk neural crest cells in a snake, the California Kingsnake (Lampropeltis getula californiae).

PubMed

Reyes, Michelle; Zandberg, Katrina; Desmawati, Iska; de Bellard, Maria E

2010-05-18

The neural crest is a group of multipotent cells that emerges after an epithelial-to-mesenchymal transition from the dorsal neural tube early during development. These cells then migrate throughout the embryo, giving rise to a wide variety derivatives including the peripheral nervous system, craniofacial skeleton, pigment cells, and endocrine organs. While much is known about neural crest cells in mammals, birds, amphibians and fish, relatively little is known about their development in non-avian reptiles like snakes and lizards. In this study, we show for the first time ever trunk neural crest migration in a snake by labeling it with DiI and immunofluorescence. As in birds and mammals, we find that early migrating trunk neural crest cells use both a ventromedial pathway and an inter-somitic pathway in the snake. However, unlike birds and mammals, we also observed large numbers of late migrating neural crest cells utilizing the inter-somitic pathway in snake. We found that while trunk neural crest migration in snakes is very similar to that of other amniotes, the inter-somitic pathway is used more extensively by late-migrating trunk neural crest cells in snake.

Interaction between DISC1 and CHL1 in regulation of neurite outgrowth.

PubMed

Ren, Jun; Zhao, Tian; Xu, Yiliang; Ye, Haihong

2016-10-01

Disrupted-in-schizophrenia 1 (DISC1), a gene susceptible for major mental illnesses, including schizophrenia, plays multiple roles in neural development, including neuronal proliferation, maturation, migration and neurite outgrowth. DISC1 regulates neurite length via interaction with several intracellular proteins, such as NDEL1, FEZ1 and dysbindin. However, the signal transduction mechanism upstream of DISC1 in regulating neurite outgrowth remains to be elucidated. Here we show that DISC1 interacts with the intracellular domain of close homolog of L1 (CHL1), a member of the L1 family of neural cell adhesion molecules. DISC1 and CHL1 proteins co-localize in growth cones of cortical neurons. Moreover, in neurite outgrowth assay, CHL1 rescues the inhibitory effect of DISC1 on the initial phase of neurite outgrowth. Considering the fact that CHL1 also plays crucial roles in neural development, and its coding gene is associated with schizophrenia, our findings indicate that DISC1 and CHL1 may engage in physical and functional interaction in neural development, supporting the notion that DISC1 regulates neurite outgrowth with a receptor belonging to the neural cell adhesion molecules, and disruption of such interaction may contribute to increased risk for schizophrenia. Copyright © 2016. Published by Elsevier B.V.

Mitochondrial metabolism in early neural fate and its relevance for neuronal disease modeling.

PubMed

Lorenz, Carmen; Prigione, Alessandro

2017-12-01

Modulation of energy metabolism is emerging as a key aspect associated with cell fate transition. The establishment of a correct metabolic program is particularly relevant for neural cells given their high bioenergetic requirements. Accordingly, diseases of the nervous system commonly involve mitochondrial impairment. Recent studies in animals and in neural derivatives of human pluripotent stem cells (PSCs) highlighted the importance of mitochondrial metabolism for neural fate decisions in health and disease. The mitochondria-based metabolic program of early neurogenesis suggests that PSC-derived neural stem cells (NSCs) may be used for modeling neurological disorders. Understanding how metabolic programming is orchestrated during neural commitment may provide important information for the development of therapies against conditions affecting neural functions, including aging and mitochondrial disorders. Copyright © 2017. Published by Elsevier Ltd.

Neural networks: Application to medical imaging

NASA Technical Reports Server (NTRS)

Clarke, Laurence P.

1994-01-01

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Neural Tube Defects

PubMed Central

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

2015-01-01

Neural tube defects (NTDs), including spina bifida and anencephaly, are severe birth defects of the central nervous system that originate during embryonic development when the neural tube fails to close completely. Human NTDs are multifactorial, with contributions from both genetic and environmental factors. The genetic basis is not yet well understood, but several nongenetic risk factors have been identified as have possibilities for prevention by maternal folic acid supplementation. Mechanisms underlying neural tube closure and NTDs may be informed by experimental models, which have revealed numerous genes whose abnormal function causes NTDs and have provided details of critical cellular and morphological events whose regulation is essential for closure. Such models also provide an opportunity to investigate potential risk factors and to develop novel preventive therapies. PMID:25032496

Establishing neural crest identity: a gene regulatory recipe

PubMed Central

Simões-Costa, Marcos; Bronner, Marianne E.

2015-01-01

The neural crest is a stem/progenitor cell population that contributes to a wide variety of derivatives, including sensory and autonomic ganglia, cartilage and bone of the face and pigment cells of the skin. Unique to vertebrate embryos, it has served as an excellent model system for the study of cell behavior and identity owing to its multipotency, motility and ability to form a broad array of cell types. Neural crest development is thought to be controlled by a suite of transcriptional and epigenetic inputs arranged hierarchically in a gene regulatory network. Here, we examine neural crest development from a gene regulatory perspective and discuss how the underlying genetic circuitry results in the features that define this unique cell population. PMID:25564621

New genes in the evolution of the neural crest differentiation program

PubMed Central

2007-01-01

Background Development of the vertebrate head depends on the multipotency and migratory behavior of neural crest derivatives. This cell population is considered a vertebrate innovation and, accordingly, chordate ancestors lacked neural crest counterparts. The identification of neural crest specification genes expressed in the neural plate of basal chordates, in addition to the discovery of pigmented migratory cells in ascidians, has challenged this hypothesis. These new findings revive the debate on what is new and what is ancient in the genetic program that controls neural crest formation. Results To determine the origin of neural crest genes, we analyzed Phenotype Ontology annotations to select genes that control the development of this tissue. Using a sequential blast pipeline, we phylogenetically classified these genes, as well as those associated with other tissues, in order to define tissue-specific profiles of gene emergence. Of neural crest genes, 9% are vertebrate innovations. Our comparative analyses show that, among different tissues, the neural crest exhibits a particularly high rate of gene emergence during vertebrate evolution. A remarkable proportion of the new neural crest genes encode soluble ligands that control neural crest precursor specification into each cell lineage, including pigmented, neural, glial, and skeletal derivatives. Conclusion We propose that the evolution of the neural crest is linked not only to the recruitment of ancestral regulatory genes but also to the emergence of signaling peptides that control the increasingly complex lineage diversification of this plastic cell population. PMID:17352807

The development of neural stimulators: a review of preclinical safety and efficacy studies.

PubMed

Shepherd, Robert K; Villalobos, Joel; Burns, Owen; Nayagam, David

2018-05-14

Given the rapid expansion of the field of neural stimulation and the rigorous regulatory approval requirements required before these devices can be applied clinically, it is important that there is clarity around conducting preclinical safety and efficacy studies required for the development of this technology. The present review examines basic design principles associated with the development of a safe neural stimulator and describes the suite of preclinical safety studies that need to be considered when taking a device to clinical trial. Neural stimulators are active implantable devices that provide therapeutic intervention, sensory feedback or improved motor control via electrical stimulation of neural or neuro-muscular tissue in response to trauma or disease. Because of their complexity, regulatory bodies classify these devices in the highest risk category (Class III), and they are therefore required to go through a rigorous regulatory approval process before progressing to market. The successful development of these devices is achieved through close collaboration across disciplines including engineers, scientists and a surgical/clinical team, and the adherence to clear design principles. Preclinical studies form one of several key components in the development pathway from concept to product release of neural stimulators. Importantly, these studies provide iterative feedback in order to optimise the final design of the device. Key components of any preclinical evaluation include: in vitro studies that are focussed on device reliability and include accelerated testing under highly controlled environments; in vivo studies using animal models of the disease or injury in order to assess safety and, given an appropriate animal model, the efficacy of the technology under both passive and electrically active conditions; and human cadaver and ex vivo studies designed to ensure the device's form factor conforms to human anatomy, to optimise the surgical approach and to develop any specialist surgical tooling required. The pipeline from concept to commercialisation of these devices is long and expensive; careful attention to both device design and its preclinical evaluation will have significant impact on the duration and cost associated with taking a device through to commercialisation. Carefully controlled in vitro and in vivo studies together with ex vivo and human cadaver trials are key components of a thorough preclinical evaluation of any new neural stimulator. © 2018 IOP Publishing Ltd.

The Nedd4 binding protein 3 is required for anterior neural development in Xenopus laevis.

PubMed

Kiem, Lena-Maria; Dietmann, Petra; Linnemann, Alexander; Schmeisser, Michael J; Kühl, Susanne J

2017-03-01

The Fezzin family member Nedd4-binding protein 3 (N4BP3) is known to regulate axonal and dendritic branching. Here, we show that n4bp3 is expressed in the neural tissue of the early Xenopus laevis embryo including the eye, the brain and neural crest cells. Knockdown of N4bp3 in the Xenopus anterior neural tissue results in severe developmental impairment of the eye, the brain and neural crest derived cranial cartilage structures. Moreover, we demonstrate that N4bp3 depletion leads to a significant reduction of both eye and brain specific marker genes and reduced neural crest cell migration. Finally, we demonstrate an impact of N4bp3 deficiency on cell apoptosis and proliferation. Our studies indicate that N4bp3 is required for early anterior neural development of vertebrates. This is in line with a study implicating that genetic disruption of N4BP3 in humans might be related to neurodevelopmental disease. Copyright © 2017 Elsevier Inc. All rights reserved.

Recent advances in neural dust: towards a neural interface platform.

PubMed

Neely, Ryan M; Piech, David K; Santacruz, Samantha R; Maharbiz, Michel M; Carmena, Jose M

2018-06-01

The neural dust platform uses ultrasonic power and communication to enable a scalable, wireless, and batteryless system for interfacing with the nervous system. Ultrasound offers several advantages over alternative wireless approaches, including a safe method for powering and communicating with sub mm-sized devices implanted deep in tissue. Early studies demonstrated that neural dust motes could wirelessly transmit high-fidelity electrophysiological data in vivo, and that theoretically, this system could be miniaturized well below the mm-scale. Future developments are focused on further minimization of the platform, better encapsulation methods as a path towards truly chronic neural interfaces, improved delivery mechanisms, stimulation capabilities, and finally refinements to enable deployment of neural dust in the central nervous system. Copyright © 2017. Published by Elsevier Ltd.

A computational model of conditioning inspired by Drosophila olfactory system.

PubMed

Faghihi, Faramarz; Moustafa, Ahmed A; Heinrich, Ralf; Wörgötter, Florentin

2017-03-01

Recent studies have demonstrated that Drosophila melanogaster (briefly Drosophila) can successfully perform higher cognitive processes including second order olfactory conditioning. Understanding the neural mechanism of this behavior can help neuroscientists to unravel the principles of information processing in complex neural systems (e.g. the human brain) and to create efficient and robust robotic systems. In this work, we have developed a biologically-inspired spiking neural network which is able to execute both first and second order conditioning. Experimental studies demonstrated that volume signaling (e.g. by the gaseous transmitter nitric oxide) contributes to memory formation in vertebrates and invertebrates including insects. Based on the existing knowledge of odor encoding in Drosophila, the role of retrograde signaling in memory function, and the integration of synaptic and non-synaptic neural signaling, a neural system is implemented as Simulated fly. Simulated fly navigates in a two-dimensional environment in which it receives odors and electric shocks as sensory stimuli. The model suggests some experimental research on retrograde signaling to investigate neural mechanisms of conditioning in insects and other animals. Moreover, it illustrates a simple strategy to implement higher cognitive capabilities in machines including robots. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social Influences on Neurobiology and Behavior: Epigenetic Effects During Development

PubMed Central

Curley, JP; Jensen, CL; Mashoodh, R; Champagne, FA

2010-01-01

The quality of the social environment can have profound influences on the development and activity of neural systems with implications for numerous behavioral and physiological responses, including the expression of emotionality. Though social experiences occurring early in development may be particularly influential on the developing brain, there is continued plasticity within these neural circuits amongst juveniles and into early adulthood. In this review, we explore the evidence derived from studies in rodents which illustrates the social modulation during development of neural systems, with a particular emphasis on those systems in which a long-term effect is observed. One possible explanation for the persistence of dynamic changes in these systems in response to the environment is the involvement of epigenetic mechanisms, and here we discuss recent studies which support the role of these mechanisms in mediating the link between social experiences, gene expression, neurobiological changes, and behavioral variation. This literature raises critical questions about the interaction between neural systems, the concordance between neural and behavioral changes, sexual dimorphism in effects, the importance of considering individual differences in response to the social environment, and the potential of an epigenetic perspective in advancing our understanding of the pathways leading to variations in mental health. PMID:20650569

Electrophysiological Repetition Effects in Persons with Mild Cognitive Impairment depend upon Working Memory Demand.

PubMed

Broster, Lucas S; Jenkins, Shonna L; Holmes, Sarah D; Edwards, Matthew G; Jicha, Gregory A; Jiang, Yang

2018-05-07

Forms of implicit memory, including repetition effects, are preserved relative to explicit memory in clinical Alzheimer's disease. Consequently, cognitive interventions for persons with Alzheimer's disease have been developed that leverage this fact. However, despite the clinical robustness of behavioral repetition effects, altered neural mechanisms of repetition effects are studied as biomarkers of both clinical Alzheimer's disease and pre-morbid Alzheimer's changes in the brain. We hypothesized that the clinical preservation of behavioral repetition effects results in part from concurrent operation of discrete memory systems. We developed two experiments that included probes of emotional repetition effects differing in that one included an embedded working memory task. We found that neural repetition effects manifested in patients with amnestic mild cognitive impairment, the earliest form of clinical Alzheimer's disease, during emotional working memory tasks, but they did not manifest during the task that lacked the embedded working memory manipulation. Specifically, the working memory task evoked neural repetition effects in the P600 time-window, but the same neural mechanism was only minimally implicated in the task without a working memory component. We also found that group differences in behavioral repetition effects were smaller in the experiment with a working memory task. We suggest that cross-domain cognitive challenge can expose "defunct" neural capabilities of individuals with amnestic mild cognitive impairment. Copyright © 2018. Published by Elsevier Ltd.

Mammalian brain development and our grandmothering life history.

PubMed

Hawkes, Kristen; Finlay, Barbara L

2018-05-02

Among mammals, including humans, adult brain size and the relative size of brain components depend precisely on the duration of a highly regular process of neural development. Much wider variation is seen in rates of body growth and the state of neural maturation at life history events like birth and weaning. Large brains result from slow maturation, which in humans is accompanied by weaning early with respect to both neural maturation and longevity. The grandmother hypothesis proposes this distinctive combination of life history features evolved as ancestral populations began to depend on foods that just weaned juveniles couldn't handle. Here we trace possible reciprocal connections between brain development and life history, highlighting the resulting extended neural plasticity in a wider cognitive ecology of allomaternal care that distinguishes human ontogeny with consequences for other peculiarities of our lineage. Copyright © 2018 Elsevier Inc. All rights reserved.

Assessment of the developmental totipotency of neural cells in the cerebral cortex of mouse embryo by nuclear transfer

PubMed Central

Yamazaki, Yukiko; Makino, Hatsune; Hamaguchi-Hamada, Kayoko; Hamada, Shun; Sugino, Hidehiko; Kawase, Eihachiro; Miyata, Takaki; Ogawa, Masaharu; Yanagimachi, Ryuzo; Yagi, Takeshi

2001-01-01

When neural cells were collected from the entire cerebral cortex of developing mouse fetuses (15.5–17.5 days postcoitum) and their nuclei were transferred into enucleated oocytes, 5.5% of the reconstructed oocytes developed into normal offspring. This success rate was the highest among all previous mouse cloning experiments that used somatic cells. Forty-four percent of live embryos at 10.5 days postcoitum were morphologically normal when premature and early-postmitotic neural cells from the ventricular side of the cortex were used. In contrast, the majority (95%) of embryos were morphologically abnormal (including structural abnormalities in the neural tube) when postmitotic-differentiated neurons from the pial side of the cortex were used for cloning. Whereas 4.3% of embryos cloned with ventricular-side cells developed into healthy offspring, only 0.5% of those cloned with differentiated neurons in the pial side did so. These facts seem to suggest that the nuclei of neural cells in advanced stages of differentiation had lost their developmental totipotency. The underlying mechanism for this developmental limitation could be somatic DNA rearrangements in differentiating neural cells. PMID:11698647

A biologically inspired neural network for dynamic programming.

PubMed

Francelin Romero, R A; Kacpryzk, J; Gomide, F

2001-12-01

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Novel Roles for Immune Molecules in Neural Development: Implications for Neurodevelopmental Disorders

PubMed Central

Garay, Paula A.; McAllister, A. Kimberley

2010-01-01

Although the brain has classically been considered “immune-privileged”, current research suggests an extensive communication between the immune and nervous systems in both health and disease. Recent studies demonstrate that immune molecules are present at the right place and time to modulate the development and function of the healthy and diseased central nervous system (CNS). Indeed, immune molecules play integral roles in the CNS throughout neural development, including affecting neurogenesis, neuronal migration, axon guidance, synapse formation, activity-dependent refinement of circuits, and synaptic plasticity. Moreover, the roles of individual immune molecules in the nervous system may change over development. This review focuses on the effects of immune molecules on neuronal connections in the mammalian central nervous system – specifically the roles for MHCI and its receptors, complement, and cytokines on the function, refinement, and plasticity of geniculate, cortical and hippocampal synapses, and their relationship to neurodevelopmental disorders. These functions for immune molecules during neural development suggest that they could also mediate pathological responses to chronic elevations of cytokines in neurodevelopmental disorders, including autism spectrum disorders (ASD) and schizophrenia. PMID:21423522

Live imaging of mitosis in the developing mouse embryonic cortex.

PubMed

Pilaz, Louis-Jan; Silver, Debra L

2014-06-04

Although of short duration, mitosis is a complex and dynamic multi-step process fundamental for development of organs including the brain. In the developing cerebral cortex, abnormal mitosis of neural progenitors can cause defects in brain size and function. Hence, there is a critical need for tools to understand the mechanisms of neural progenitor mitosis. Cortical development in rodents is an outstanding model for studying this process. Neural progenitor mitosis is commonly examined in fixed brain sections. This protocol will describe in detail an approach for live imaging of mitosis in ex vivo embryonic brain slices. We will describe the critical steps for this procedure, which include: brain extraction, brain embedding, vibratome sectioning of brain slices, staining and culturing of slices, and time-lapse imaging. We will then demonstrate and describe in detail how to perform post-acquisition analysis of mitosis. We include representative results from this assay using the vital dye Syto11, transgenic mice (histone H2B-EGFP and centrin-EGFP), and in utero electroporation (mCherry-α-tubulin). We will discuss how this procedure can be best optimized and how it can be modified for study of genetic regulation of mitosis. Live imaging of mitosis in brain slices is a flexible approach to assess the impact of age, anatomy, and genetic perturbation in a controlled environment, and to generate a large amount of data with high temporal and spatial resolution. Hence this protocol will complement existing tools for analysis of neural progenitor mitosis.

Engineering platform and experimental protocol for design and evaluation of a neurally-controlled powered transfemoral prosthesis.

PubMed

Zhang, Fan; Liu, Ming; Harper, Stephen; Lee, Michael; Huang, He

2014-07-22

To enable intuitive operation of powered artificial legs, an interface between user and prosthesis that can recognize the user's movement intent is desired. A novel neural-machine interface (NMI) based on neuromuscular-mechanical fusion developed in our previous study has demonstrated a great potential to accurately identify the intended movement of transfemoral amputees. However, this interface has not yet been integrated with a powered prosthetic leg for true neural control. This study aimed to report (1) a flexible platform to implement and optimize neural control of powered lower limb prosthesis and (2) an experimental setup and protocol to evaluate neural prosthesis control on patients with lower limb amputations. First a platform based on a PC and a visual programming environment were developed to implement the prosthesis control algorithms, including NMI training algorithm, NMI online testing algorithm, and intrinsic control algorithm. To demonstrate the function of this platform, in this study the NMI based on neuromuscular-mechanical fusion was hierarchically integrated with intrinsic control of a prototypical transfemoral prosthesis. One patient with a unilateral transfemoral amputation was recruited to evaluate our implemented neural controller when performing activities, such as standing, level-ground walking, ramp ascent, and ramp descent continuously in the laboratory. A novel experimental setup and protocol were developed in order to test the new prosthesis control safely and efficiently. The presented proof-of-concept platform and experimental setup and protocol could aid the future development and application of neurally-controlled powered artificial legs.

At the interface: convergence of neural regeneration and neural prostheses for restoration of function.

PubMed

Grill, W M; McDonald, J W; Peckham, P H; Heetderks, W; Kocsis, J; Weinrich, M

2001-01-01

The rapid pace of recent advances in development and application of electrical stimulation of the nervous system and in neural regeneration has created opportunities to combine these two approaches to restoration of function. This paper relates the discussion on this topic from a workshop at the International Functional Electrical Stimulation Society. The goals of this workshop were to discuss the current state of interaction between the fields of neural regeneration and neural prostheses and to identify potential areas of future research that would have the greatest impact on achieving the common goal of restoring function after neurological damage. Identified areas include enhancement of axonal regeneration with applied electric fields, development of hybrid neural interfaces combining synthetic silicon and biologically derived elements, and investigation of the role of patterned neural activity in regulating various neuronal processes and neurorehabilitation. Increased communication and cooperation between the two communities and recognition by each field that the other has something to contribute to their efforts are needed to take advantage of these opportunities. In addition, creative grants combining the two approaches and more flexible funding mechanisms to support the convergence of their perspectives are necessary to achieve common objectives.

Modeling Aircraft Wing Loads from Flight Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Allen, Michael J.; Dibley, Ryan P.

2003-01-01

Neural networks were used to model wing bending-moment loads, torsion loads, and control surface hinge-moments of the Active Aeroelastic Wing (AAW) aircraft. Accurate loads models are required for the development of control laws designed to increase roll performance through wing twist while not exceeding load limits. Inputs to the model include aircraft rates, accelerations, and control surface positions. Neural networks were chosen to model aircraft loads because they can account for uncharacterized nonlinear effects while retaining the capability to generalize. The accuracy of the neural network models was improved by first developing linear loads models to use as starting points for network training. Neural networks were then trained with flight data for rolls, loaded reversals, wind-up-turns, and individual control surface doublets for load excitation. Generalization was improved by using gain weighting and early stopping. Results are presented for neural network loads models of four wing loads and four control surface hinge moments at Mach 0.90 and an altitude of 15,000 ft. An average model prediction error reduction of 18.6 percent was calculated for the neural network models when compared to the linear models. This paper documents the input data conditioning, input parameter selection, structure, training, and validation of the neural network models.

An Initial Investigation of the Neural Correlates of Word Processing in Preschoolers with Specific Language Impairment

ERIC Educational Resources Information Center

Haebig, Eileen; Leonard, Laurence; Usler, Evan; Deevy, Patricia; Weber, Christine

2018-01-01

Purpose: Previous behavioral studies have found deficits in lexical--semantic abilities in children with specific language impairment (SLI), including reduced depth and breadth of word knowledge. This study explored the neural correlates of early emerging familiar word processing in preschoolers with SLI and typical development. Method: Fifteen…

Vertically aligned carbon nanofiber as nano-neuron interface for monitoring neural function.

PubMed

Yu, Zhe; McKnight, Timothy E; Ericson, M Nance; Melechko, Anatoli V; Simpson, Michael L; Morrison, Barclay

2012-05-01

Neural chips, which are capable of simultaneous multisite neural recording and stimulation, have been used to detect and modulate neural activity for almost thirty years. As neural interfaces, neural chips provide dynamic functional information for neural decoding and neural control. By improving sensitivity and spatial resolution, nano-scale electrodes may revolutionize neural detection and modulation at cellular and molecular levels as nano-neuron interfaces. We developed a carbon-nanofiber neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes and demonstrated its capability of both stimulating and monitoring electrophysiological signals from brain tissues in vitro and monitoring dynamic information of neuroplasticity. This novel nano-neuron interface may potentially serve as a precise, informative, biocompatible, and dual-mode neural interface for monitoring of both neuroelectrical and neurochemical activity at the single-cell level and even inside the cell. The authors demonstrate the utility of a neural chip with lithographically defined arrays of vertically aligned carbon nanofiber electrodes. The new device can be used to stimulate and/or monitor signals from brain tissue in vitro and for monitoring dynamic information of neuroplasticity both intracellularly and at the single cell level including neuroelectrical and neurochemical activities. Copyright © 2012 Elsevier Inc. All rights reserved.

Male Killing Spiroplasma Preferentially Disrupts Neural Development in the Drosophila melanogaster Embryo

PubMed Central

Martin, Jennifer; Chong, Trisha; Ferree, Patrick M.

2013-01-01

Male killing bacteria such as Spiroplasma are widespread pathogens of numerous arthropods including Drosophila melanogaster. These maternally transmitted bacteria can bias host sex ratios toward the female sex in order to ‘selfishly’ enhance bacterial transmission. However, little is known about the specific means by which these pathogens disrupt host development in order to kill males. Here we show that a male-killing Spiroplasma strain severely disrupts nervous tissue development in male but not female D. melanogaster embryos. The neuroblasts, or neuron progenitors, form properly and their daughter cells differentiate into neurons of the ventral nerve chord. However, the neurons fail to pack together properly and they produce highly abnormal axons. In contrast, non-neural tissue, such as mesoderm, and body segmentation appear normal during this time, although the entire male embryo becomes highly abnormal during later stages. Finally, we found that Spiroplasma is altogether absent from the neural tissue but localizes within the gut and the epithelium immediately surrounding the neural tissue, suggesting that the bacterium secretes a toxin that affects neural tissue development across tissue boundaries. Together these findings demonstrate the unique ability of this insect pathogen to preferentially affect development of a specific embryonic tissue to induce male killing. PMID:24236124

Neural Crossroads in the Hematopoietic Stem Cell Niche.

PubMed

Agarwala, Sobhika; Tamplin, Owen J

2018-05-29

The hematopoietic stem cell (HSC) niche supports steady-state hematopoiesis and responds to changing needs during stress and disease. The nervous system is an important regulator of the niche, and its influence is established early in development when stem cells are specified. Most research has focused on direct innervation of the niche, however recent findings show there are different modes of neural control, including globally by the central nervous system (CNS) and hormone release, locally by neural crest-derived mesenchymal stem cells, and intrinsically by hematopoietic cells that express neural receptors and neurotransmitters. Dysregulation between neural and hematopoietic systems can contribute to disease, however new therapeutic opportunities may be found among neuroregulator drugs repurposed to support hematopoiesis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Method and system for determining induction motor speed

DOEpatents

Parlos, Alexander G.; Bharadwaj, Raj M.

2004-03-30

A non-linear, semi-parametric neural network-based adaptive filter is utilized to determine the dynamic speed of a rotating rotor within an induction motor, without the explicit use of a speed sensor, such as a tachometer, is disclosed. The neural network-based filter is developed using actual motor current measurements, voltage measurements, and nameplate information. The neural network-based adaptive filter is trained using an estimated speed calculator derived from the actual current and voltage measurements. The neural network-based adaptive filter uses voltage and current measurements to determine the instantaneous speed of a rotating rotor. The neural network-based adaptive filter also includes an on-line adaptation scheme that permits the filter to be readily adapted for new operating conditions during operations.

Enhanced expression of FNDC5 in human embryonic stem cell-derived neural cells along with relevant embryonic neural tissues.

PubMed

Ghahrizjani, Fatemeh Ahmadi; Ghaedi, Kamran; Salamian, Ahmad; Tanhaei, Somayeh; Nejati, Alireza Shoaraye; Salehi, Hossein; Nabiuni, Mohammad; Baharvand, Hossein; Nasr-Esfahani, Mohammad Hossein

2015-02-25

Availability of human embryonic stem cells (hESCs) has enhanced the capability of basic and clinical research in the context of human neural differentiation. Derivation of neural progenitor (NP) cells from hESCs facilitates the process of human embryonic development through the generation of neuronal subtypes. We have recently indicated that fibronectin type III domain containing 5 protein (FNDC5) expression is required for appropriate neural differentiation of mouse embryonic stem cells (mESCs). Bioinformatics analyses have shown the presence of three isoforms for human FNDC5 mRNA. To differentiate which isoform of FNDC5 is involved in the process of human neural differentiation, we have used hESCs as an in vitro model for neural differentiation by retinoic acid (RA) induction. The hESC line, Royan H5, was differentiated into a neural lineage in defined adherent culture treated by RA and basic fibroblast growth factor (bFGF). We collected all cell types that included hESCs, rosette structures, and neural cells in an attempt to assess the expression of FNDC5 isoforms. There was a contiguous increase in all three FNDC5 isoforms during the neural differentiation process. Furthermore, the highest level of expression of the isoforms was significantly observed in neural cells compared to hESCs and the rosette structures known as neural precursor cells (NPCs). High expression levels of FNDC5 in human fetal brain and spinal cord tissues have suggested the involvement of this gene in neural tube development. Additional research is necessary to determine the major function of FDNC5 in this process. Copyright © 2014 Elsevier B.V. All rights reserved.

Natural and Artificial Intelligence, Language, Consciousness, Emotion, and Anticipation

NASA Astrophysics Data System (ADS)

Dubois, Daniel M.

2010-11-01

The classical paradigm of the neural brain as the seat of human natural intelligence is too restrictive. This paper defends the idea that the neural ectoderm is the actual brain, based on the development of the human embryo. Indeed, the neural ectoderm includes the neural crest, given by pigment cells in the skin and ganglia of the autonomic nervous system, and the neural tube, given by the brain, the spinal cord, and motor neurons. So the brain is completely integrated in the ectoderm, and cannot work alone. The paper presents fundamental properties of the brain as follows. Firstly, Paul D. MacLean proposed the triune human brain, which consists to three brains in one, following the species evolution, given by the reptilian complex, the limbic system, and the neo-cortex. Secondly, the consciousness and conscious awareness are analysed. Thirdly, the anticipatory unconscious free will and conscious free veto are described in agreement with the experiments of Benjamin Libet. Fourthly, the main section explains the development of the human embryo and shows that the neural ectoderm is the whole neural brain. Fifthly, a conjecture is proposed that the neural brain is completely programmed with scripts written in biological low-level and high-level languages, in a manner similar to the programmed cells by the genetic code. Finally, it is concluded that the proposition of the neural ectoderm as the whole neural brain is a breakthrough in the understanding of the natural intelligence, and also in the future design of robots with artificial intelligence.

Fuzzy logic and neural network technologies

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Lea, Robert N.; Savely, Robert T.

1992-01-01

Applications of fuzzy logic technologies in NASA projects are reviewed to examine their advantages in the development of neural networks for aerospace and commercial expert systems and control. Examples of fuzzy-logic applications include a 6-DOF spacecraft controller, collision-avoidance systems, and reinforcement-learning techniques. The commercial applications examined include a fuzzy autofocusing system, an air conditioning system, and an automobile transmission application. The practical use of fuzzy logic is set in the theoretical context of artificial neural systems (ANSs) to give the background for an overview of ANS research programs at NASA. The research and application programs include the Network Execution and Training Simulator and faster training algorithms such as the Difference Optimized Training Scheme. The networks are well suited for pattern-recognition applications such as predicting sunspots, controlling posture maintenance, and conducting adaptive diagnoses.

Sex differences in the development of brain mechanisms for processing biological motion.

PubMed

Anderson, L C; Bolling, D Z; Schelinski, S; Coffman, M C; Pelphrey, K A; Kaiser, M D

2013-12-01

Disorders related to social functioning including autism and schizophrenia differ drastically in incidence and severity between males and females. Little is known about the neural systems underlying these sex-linked differences in risk and resiliency. Using functional magnetic resonance imaging and a task involving the visual perception of point-light displays of coherent and scrambled biological motion, we discovered sex differences in the development of neural systems for basic social perception. In adults, we identified enhanced activity during coherent biological motion perception in females relative to males in a network of brain regions previously implicated in social perception including amygdala, medial temporal gyrus, and temporal pole. These sex differences were less pronounced in our sample of school-age youth. We hypothesize that the robust neural circuitry supporting social perception in females, which diverges from males beginning in childhood, may underlie sex differences in disorders related to social processing. © 2013 Elsevier Inc. All rights reserved.

Sex Differences in the Development of Brain Mechanisms for Processing Biological Motion

PubMed Central

Anderson, L.C.; Bolling, D.Z.; Schelinski, S.; Coffman, M.C.; Pelphrey, K.A.; Kaiser, M.D.

2013-01-01

Disorders related to social functioning including autism and schizophrenia differ drastically in incidence and severity between males and females. Little is known about the neural systems underlying these sex-linked differences in risk and resiliency. Using functional magnetic resonance imaging and a task involving the visual perception of point-light displays of coherent and scrambled biological motion, we discovered sex differences in the development of neural systems for basic social perception. In adults, we identified enhanced activity during coherent biological motion perception in females relative to males in a network of brain regions previously implicated in social perception including amygdala, medial temporal gyrus, and temporal pole. These sex differences were less pronounced in our sample of school-age youth. We hypothesize that the robust neural circuitry supporting social perception in females, which diverges from males beginning in childhood, may underlie sex differences in disorders related to social processing. PMID:23876243

Recent Advances in Neural Electrode-Tissue Interfaces.

PubMed

Woeppel, Kevin; Yang, Qianru; Cui, Xinyan Tracy

2017-12-01

Neurotechnology is facing an exponential growth in the recent decades. Neural electrode-tissue interface research has been well recognized as an instrumental component of neurotechnology development. While satisfactory long-term performance was demonstrated in some applications, such as cochlear implants and deep brain stimulators, more advanced neural electrode devices requiring higher resolution for single unit recording or microstimulation still face significant challenges in reliability and longevity. In this article, we review the most recent findings that contribute to our current understanding of the sources of poor reliability and longevity in neural recording or stimulation, including the material failure, biological tissue response and the interplay between the two. The newly developed characterization tools are introduced from electrophysiology models, molecular and biochemical analysis, material characterization to live imaging. The effective strategies that have been applied to improve the interface are also highlighted. Finally, we discuss the challenges and opportunities in improving the interface and achieving seamless integration between the implanted electrodes and neural tissue both anatomically and functionally.

Regulation of cell protrusions by small GTPases during fusion of the neural folds

PubMed Central

Rolo, Ana; Savery, Dawn; Escuin, Sarah; de Castro, Sandra C; Armer, Hannah EJ; Munro, Peter MG; Molè, Matteo A; Greene, Nicholas DE; Copp, Andrew J

2016-01-01

Epithelial fusion is a crucial process in embryonic development, and its failure underlies several clinically important birth defects. For example, failure of neural fold fusion during neurulation leads to open neural tube defects including spina bifida. Using mouse embryos, we show that cell protrusions emanating from the apposed neural fold tips, at the interface between the neuroepithelium and the surface ectoderm, are required for completion of neural tube closure. By genetically ablating the cytoskeletal regulators Rac1 or Cdc42 in the dorsal neuroepithelium, or in the surface ectoderm, we show that these protrusions originate from surface ectodermal cells and that Rac1 is necessary for the formation of membrane ruffles which typify late closure stages, whereas Cdc42 is required for the predominance of filopodia in early neurulation. This study provides evidence for the essential role and molecular regulation of membrane protrusions prior to fusion of a key organ primordium in mammalian development. DOI: http://dx.doi.org/10.7554/eLife.13273.001 PMID:27114066

Evolvable synthetic neural system

NASA Technical Reports Server (NTRS)

Curtis, Steven A. (Inventor)

2009-01-01

An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

NASA Technical Reports Server (NTRS)

Broderick, Ron

1997-01-01

The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network development. The changes were to include evaluation tools that can be applied to neural networks at each phase of the software engineering life cycle. The result was a formal evaluation approach to increase the product quality of systems that use neural networks for their implementation.

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

PubMed Central

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

2015-01-01

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 (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>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. PMID:26395144

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

PubMed

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 (<10) of presynaptic inputs, whereas a small set of hub-like neurons have large numbers of synaptic connections (>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.

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

PubMed

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

2015-01-01

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

A heuristic neural network initialization scheme for modeling nonlinear functions in engineering mechanics: continuous development

NASA Astrophysics Data System (ADS)

Pei, Jin-Song; Mai, Eric C.

2007-04-01

This paper introduces a continuous effort towards the development of a heuristic initialization methodology for constructing multilayer feedforward neural networks to model nonlinear functions. In this and previous studies that this work is built upon, including the one presented at SPIE 2006, the authors do not presume to provide a universal method to approximate arbitrary functions, rather the focus is given to the development of a rational and unambiguous initialization procedure that applies to the approximation of nonlinear functions in the specific domain of engineering mechanics. The applications of this exploratory work can be numerous including those associated with potential correlation and interpretation of the inner workings of neural networks, such as damage detection. The goal of this study is fulfilled by utilizing the governing physics and mathematics of nonlinear functions and the strength of the sigmoidal basis function. A step-by-step graphical procedure utilizing a few neural network prototypes as "templates" to approximate commonly seen memoryless nonlinear functions of one or two variables is further developed in this study. Decomposition of complex nonlinear functions into a summation of some simpler nonlinear functions is utilized to exploit this prototype-based initialization methodology. Training examples are presented to demonstrate the rationality and effciency of the proposed methodology when compared with the popular Nguyen-Widrow initialization algorithm. Future work is also identfied.

Hippocampal and posterior parietal contributions to developmental increases in visual short-term memory capacity.

PubMed

von Allmen, David Yoh; Wurmitzer, Karoline; Klaver, Peter

2014-10-01

Developmental increases in visual short-term memory (VSTM) capacity have been associated with changes in attention processing limitations and changes in neural activity within neural networks including the posterior parietal cortex (PPC). A growing body of evidence suggests that the hippocampus plays a role in VSTM, but it is unknown whether the hippocampus contributes to the capacity increase across development. We investigated the functional development of the hippocampus and PPC in 57 children, adolescents and adults (age 8-27 years) who performed a visuo-spatial change detection task. A negative relationship between age and VSTM related activity was found in the right posterior hippocampus that was paralleled by a positive age-activity relationship in the right PPC. In the posterior hippocampus, VSTM related activity predicted individual capacity in children, whereas neural activity in the right anterior hippocampus predicted individual capacity in adults. The findings provide first evidence that VSTM development is supported by an integrated neural network that involves hippocampal and posterior parietal regions.

Asymmetric segregation of the double-stranded RNA binding protein Staufen2 during mammalian neural stem cell divisions promotes lineage progression.

PubMed

Kusek, Gretchen; Campbell, Melissa; Doyle, Frank; Tenenbaum, Scott A; Kiebler, Michael; Temple, Sally

2012-10-05

Asymmetric cell divisions are a fundamental feature of neural development, and misregulation can lead to brain abnormalities or tumor formation. During an asymmetric cell division, molecular determinants are segregated preferentially into one daughter cell to specify its fate. An important goal is to identify the asymmetric determinants in neural progenitor cells, which could be tumor suppressors or inducers of specific neural fates. Here, we show that the double-stranded RNA-binding protein Stau2 is distributed asymmetrically during progenitor divisions in the developing mouse cortex, preferentially segregating into the Tbr2(+) neuroblast daughter, taking with it a subset of RNAs. Knockdown of Stau2 stimulates differentiation and overexpression produces periventricular neuronal masses, demonstrating its functional importance for normal cortical development. We immunoprecipitated Stau2 to examine its cargo mRNAs, and found enrichment for known asymmetric and basal cell determinants, such as Trim32, and identified candidates, including a subset involved in primary cilium function. Copyright © 2012 Elsevier Inc. All rights reserved.

Asymmetric Segregation of the Double-Stranded RNA Binding Protein Staufen2 during Mammalian Neural Stem Cell Divisions Promotes Lineage Progression

PubMed Central

Kusek, Gretchen; Campbell, Melissa; Doyle, Frank; Tenenbaum, Scott A.; Kiebler, Michael; Temple, Sally

2012-01-01

Summary Asymmetric cell divisions are a fundamental feature of neural development, and misregulation can lead to brain abnormalities or tumor formation. During an asymmetric cell division, molecular determinants are segregated preferentially into one daughter cell to specify its fate. An important goal is to identify the asymmetric determinants in neural progenitor cells, which could be tumor suppressors or inducers of specific neural fates. Here we show that the double-stranded RNA-binding protein Stau2 is distributed asymmetrically during progenitor divisions in the developing mouse cortex, preferentially segregating into the Tbr2+ neuroblast daughter, taking with it a sub-set of RNAs. Knockdown of Stau2 stimulates differentiation and over-expression produces periventricular neuronal masses, demonstrating its functional importance for normal cortical development. We immunoprecipitated Stau2 to examine its cargo mRNAs, and found enrichment for known asymmetric and basal cell determinants, such as Trim32, and identified novel candidates, including a subset involved in primary cilium function. PMID:22902295

A quantitative framework to evaluate modeling of cortical development by neural stem cells

PubMed Central

Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.

2014-01-01

Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955

FINAL REPORT ON HEAD START EVALUATION AND RESEARCH--1966-67 TO THE INSTITUTE FOR EDUCATIONAL DEVELOPMENT. SECTION VII, SENSORY AND PERCEPTUAL STUDIES.

ERIC Educational Resources Information Center

HOLMES, DAVID S.; AND OTHERS

THREE STUDIES OF PRESCHOOL CHILDREN ARE INCLUDED IN THIS EVALUATION REPORT. (1) "'NEURAL CONDUCTIVITY' AND ACHIEVEMENT IN CULTURALLY DEPRIVED STUDENTS." NEURAL CONDUCTIVITY WAS INFERRED FROM A CORRELATION BETWEEN PUPILLARY RESPONSE AND CHILDREN'S PRESCHOOL PERFORMANCE. COMPLICATIONS IN ACQUIRING AND USING THE NECESSARY EQUIPMENT RESULTED…

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

The neural correlates of reciprocity are sensitive to prior experience of reciprocity.

PubMed

Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew

2017-08-14

Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.

Sox5 is a DNA binding co-factor for BMP R-Smads that directs target specificity during patterning of the early ectoderm

PubMed Central

Nordin, Kara; LaBonne, Carole

2014-01-01

SUMMARY The SoxD factor, Sox5, is expressed in ectodermal cells at times and places where BMP signaling is active, including the cells of the animal hemisphere at blastula stages, and the neural plate border (NPB) and neural crest (NC) at neurula stages. Sox5 is required for proper ectoderm development, and deficient embryos display patterning defects characteristic of perturbations of BMP signaling, including loss of neural crest and epidermis and expansion of the neural plate. We show that Sox5 is essential for activation of BMP target genes in embryos and explants, that it physically interacts with BMP R-Smads, and that it is essential for recruitment of Smad1/4 to BMP regulatory elements. Our findings identify Sox5 as the long sought DNA binding partner for BMP R-Smads essential to plasticity and pattern in the early ectoderm. PMID:25453832

Retinoic acid-induced lumbosacral neural tube defects: myeloschisis and hamartoma.

PubMed

Cai, WeiSong; Zhao, HongYu; Guo, JunBin; Li, Yong; Yuan, ZhengWei; Wang, WeiLin

2007-05-01

To observe the morphological features of the lumbosacral neural tube defects (NTDs) induced by all-trans retinoic acid (atRA) and to explore the pathogenesis of these defects. Rat embryos with lumbosacral NTDs were obtained by treating pregnant rats with administration of atRA. Rat embryos were obtained by cesarean. Fetuses were sectioned and stained with hematoxylin-eosin (H&E). Relevant structures including caudal neural tube were examined. In the atRA-treated rats, about 48% embryos showed lumbosacral NTDs. There appeared a dorsally and rostrally situated, neural-plate-like structure (myeloschisis) and a ventrally and caudally located cell mass containing multiple canals (hamartoma) in the lumbosacral NTDs induced by atRA. Retinoic acid could disturb the notochord and tail bud development in the process of primary and secondary neurulation in rat embryos, which cause lumbosacral NTDs including myeloschisis and hamartoma. The morphology is very similar to that happens in humans.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Long, Theresa W.

1995-01-01

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.

Positive mood enhances reward-related neural activity

PubMed Central

Nusslock, Robin

2016-01-01

Although behavioral research has shown that positive mood leads to desired outcomes in nearly every major life domain, no studies have directly examined the effects of positive mood on the neural processes underlying reward-related affect and goal-directed behavior. To address this gap, participants in the present fMRI study experienced either a positive (n = 20) or neutral (n = 20) mood induction and subsequently completed a monetary incentive delay task that assessed reward and loss processing. Consistent with prediction, positive mood elevated activity specifically during reward anticipation in corticostriatal neural regions that have been implicated in reward processing and goal-directed behavior, including the nucleus accumbens, caudate, lateral orbitofrontal cortex and putamen, as well as related paralimbic regions, including the anterior insula and ventromedial prefrontal cortex. These effects were not observed during reward outcome, loss anticipation or loss outcome. Critically, this is the first study to report that positive mood enhances reward-related neural activity. Our findings have implications for uncovering the neural mechanisms by which positive mood enhances goal-directed behavior, understanding the malleability of reward-related neural activity, and developing targeted treatments for psychiatric disorders characterized by deficits in reward processing. PMID:26833919

Neural Differentiation of Embryonic Stem Cells In Vitro: A Road Map to Neurogenesis in the Embryo

PubMed Central

Abranches, Elsa; Silva, Margarida; Pradier, Laurent; Schulz, Herbert; Hummel, Oliver; Henrique, Domingos; Bekman, Evguenia

2009-01-01

Background The in vitro generation of neurons from embryonic stem (ES) cells is a promising approach to produce cells suitable for neural tissue repair and cell-based replacement therapies of the nervous system. Available methods to promote ES cell differentiation towards neural lineages attempt to replicate, in different ways, the multistep process of embryonic neural development. However, to achieve this aim in an efficient and reproducible way, a better knowledge of the cellular and molecular events that are involved in the process, from the initial specification of neuroepithelial progenitors to their terminal differentiation into neurons and glial cells, is required. Methodology/Principal Findings In this work, we characterize the main stages and transitions that occur when ES cells are driven into a neural fate, using an adherent monolayer culture system. We established improved conditions to routinely produce highly homogeneous cultures of neuroepithelial progenitors, which organize into neural tube-like rosettes when they acquire competence for neuronal production. Within rosettes, neuroepithelial progenitors display morphological and functional characteristics of their embryonic counterparts, namely, apico-basal polarity, active Notch signalling, and proper timing of production of neurons and glia. In order to characterize the global gene activity correlated with each particular stage of neural development, the full transcriptome of different cell populations that arise during the in vitro differentiation protocol was determined by microarray analysis. By using embryo-oriented criteria to cluster the differentially expressed genes, we define five gene expression signatures that correlate with successive stages in the path from ES cells to neurons. These include a gene signature for a primitive ectoderm-like stage that appears after ES cells enter differentiation, and three gene signatures for subsequent stages of neural progenitor development, from an early stage that follows neural induction to a final stage preceding terminal differentiation. Conclusions/Significance Overall, our work confirms and extends the cellular and molecular parallels between monolayer ES cell neural differentiation and embryonic neural development, revealing in addition novel aspects of the genetic network underlying the multistep process that leads from uncommitted cells to differentiated neurons. PMID:19621087

Hard to Swallow: Developmental Biological Insights into Pediatric Dysphagia

PubMed Central

LaMantia, Anthony-Samuel; Moody, Sally A.; Maynard, Thomas M.; Karpinski, Beverly A.; Zohn, Irene E.; Mendelowitz, David; Lee, Norman H.; Popratiloff, Anastas

2015-01-01

Pediatric dysphagia—feeding and swallowing difficulties that begin at birth, last throughout childhood, and continue into maturity—is one of the most common, least understood complications in children with developmental disorders. We argue that a major cause of pediatric dysphagia is altered hindbrain patterning during pre-natal development. Such changes can compromise craniofacial structures including oropharyngeal muscles and skeletal elements as well as motor and sensory circuits necessary for normal feeding and swallowing. Animal models of developmental disorders that include pediatric dysphagia in their phenotypic spectrum can provide mechanistic insight into pathogenesis of feeding and swallowing difficulties. A fairly common human genetic developmental disorder, DiGeorge/22q11.2 Deletion Syndrome (22q11DS) includes a substantial incidence of pediatric dysphagia in its phenotypic spectrum. Infant mice carrying a parallel deletion to 22q11DS patients have feeding and swallowing difficulties. Altered hindbrain patterning, neural crest migration, craniofacial malformations, and changes in cranial nerve growth prefigure these difficulties. Thus, in addition to craniofacial and pharyngeal anomalies that arise independently of altered neural development, pediatric dysphagia may reflect disrupted hindbrain patterning and its impact on neural circuit development critical for feeding and swallowing. The mechanisms that disrupt hindbrain patterning and circuitry may provide a foundation to develop novel therapeutic approaches for improved clinical management of pediatric dysphagia. PMID:26554723

Insights into Metabolic Mechanisms Underlying Folate-Responsive Neural Tube Defects: A Minireview

PubMed Central

Beaudin, Anna E.; Stover, Patrick J.

2015-01-01

Neural tube defects (NTDs), including anencephaly and spina bifida, arise from the failure of neurulation during early embryonic development. Neural tube defects are common birth defects with a heterogenous and multifactorial etiology with interacting genetic and environmental risk factors. Although the mechanisms resulting in failure of neural tube closure are unknown, up to 70% of NTDs can be prevented by maternal folic acid supplementation. However, the metabolic mechanisms underlying the association between folic acid and NTD pathogenesis have not been identified. This review summarizes our current understanding of the mechanisms by which impairments in folate metabolism might ultimately lead to failure of neural tube closure, with an emphasis on untangling the relative contributions of nutritional deficiency and genetic risk factors to NTD pathogenesis. PMID:19180567

Integration of perception and reasoning in fast neural modules

NASA Technical Reports Server (NTRS)

Fritz, David G.

1989-01-01

Artificial neural systems promise to integrate symbolic and sub-symbolic processing to achieve real time control of physical systems. Two potential alternatives exist. In one, neural nets can be used to front-end expert systems. The expert systems, in turn, are developed with varying degrees of parallelism, including their implementation in neural nets. In the other, rule-based reasoning and sensor data can be integrated within a single hybrid neural system. The hybrid system reacts as a unit to provide decisions (problem solutions) based on the simultaneous evaluation of data and rules. Discussed here is a model hybrid system based on the fuzzy cognitive map (FCM). The operation of the model is illustrated with the control of a hypothetical satellite that intelligently alters its attitude in space in response to an intersecting micrometeorite shower.

5-Mehtyltetrahydrofolate rescues alcohol-induced neural crest cell migration abnormalities.

PubMed

Shi, Yu; Li, Jiejing; Chen, Chunjiang; Gong, Manzi; Chen, Yuan; Liu, Youxue; Chen, Jie; Li, Tingyu; Song, Weihong

2014-09-16

Alcohol is detrimental to early development. Fetal alcohol spectrum disorders (FASD) due to maternal alcohol abuse results in a series of developmental abnormalities including cranial facial dysmorphology, ocular anomalies, congenital heart defects, microcephaly and intellectual disabilities. Previous studies have been shown that ethanol exposure causes neural crest (NC) apoptosis and perturbation of neural crest migration. However, the underlying mechanism remains elusive. In this report we investigated the fetal effect of alcohol on the process of neural crest development in the Xenopus leavis. Pre-gastrulation exposure of 2-4% alcohol induces apoptosis in Xenopus embryo whereas 1% alcohol specifically impairs neural crest migration without observing discernible apoptosis. Additionally, 1% alcohol treatment considerably increased the phenotype of small head (43.4% ± 4.4%, total embryo n = 234), and 1.5% and 2.0% dramatically augment the deformation to 81.2% ± 6.5% (n = 205) and 91.6% ± 3.0% (n = 235), respectively (P < 0.05). Significant accumulation of Homocysteine was caused by alcohol treatment in embryos and 5-mehtyltetrahydrofolate restores neural crest migration and alleviates homocysteine accumulation, resulting in inhibition of the alcohol-induced neurocristopathies. Our study demonstrates that prenatal alcohol exposure causes neural crest cell migration abnormality and 5-mehtyltetrahydrofolate could be beneficial for treating FASD.

Cre-driver lines used for genetic fate mapping of neural crest cells in the mouse: An overview.

PubMed

Debbache, Julien; Parfejevs, Vadims; Sommer, Lukas

2018-04-19

The neural crest is one of the embryonic structures with the broadest developmental potential in vertebrates. Morphologically, neural crest cells emerge during neurulation in the dorsal folds of the neural tube before undergoing an epithelial-to-mesenchymal transition (EMT), delaminating from the neural tube, and migrating to multiple sites in the growing embryo. Neural crest cells generate cell types as diverse as peripheral neurons and glia, melanocytes, and so-called mesectodermal derivatives that include craniofacial bone and cartilage and smooth muscle cells in cardiovascular structures. In mice, the fate of neural crest cells has been determined mainly by means of transgenesis and genome editing technologies. The most frequently used method relies on the Cre-loxP system, in which expression of Cre-recombinase in neural crest cells or their derivatives genetically enables the expression of a Cre-reporter allele, thus permanently marking neural crest-derived cells. Here, we provide an overview of the Cre-driver lines used in the field and discuss to what extent these lines allow precise neural crest stage and lineage-specific fate mapping. © 2018 The Authors Genesis: The Journal of Genetics and Development Published by Wiley Periodicals, Inc.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, B.; Wood, R.T.

1997-04-22

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.

Automated method for the systematic interpretation of resonance peaks in spectrum data

DOEpatents

Damiano, Brian; Wood, Richard T.

1997-01-01

A method for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system.

HMMR acts in the PLK1-dependent spindle positioning pathway and supports neural development

PubMed Central

Jiang, Jihong; Kuan, Chia-Wei; Fotovati, Abbas; Chu, Tony LH; He, Zhengcheng; Lengyell, Tess C; Li, Huaibiao; Kroll, Torsten; Li, Amanda M; Goldowitz, Daniel; Frappart, Lucien; Ploubidou, Aspasia; Patel, Millan S; Pilarski, Linda M; Simpson, Elizabeth M; Lange, Philipp F; Allan, Douglas W

2017-01-01

Oriented cell division is one mechanism progenitor cells use during development and to maintain tissue homeostasis. Common to most cell types is the asymmetric establishment and regulation of cortical NuMA-dynein complexes that position the mitotic spindle. Here, we discover that HMMR acts at centrosomes in a PLK1-dependent pathway that locates active Ran and modulates the cortical localization of NuMA-dynein complexes to correct mispositioned spindles. This pathway was discovered through the creation and analysis of Hmmr-knockout mice, which suffer neonatal lethality with defective neural development and pleiotropic phenotypes in multiple tissues. HMMR over-expression in immortalized cancer cells induces phenotypes consistent with an increase in active Ran including defects in spindle orientation. These data identify an essential role for HMMR in the PLK1-dependent regulatory pathway that orients progenitor cell division and supports neural development. PMID:28994651

Gender development and the human brain.

PubMed

Hines, Melissa

2011-01-01

Convincing evidence indicates that prenatal exposure to the gonadal hormone, testosterone, influences the development of children's sex-typical toy and activity interests. In addition, growing evidence shows that testosterone exposure contributes similarly to the development of other human behaviors that show sex differences, including sexual orientation, core gender identity, and some, though not all, sex-related cognitive and personality characteristics. In addition to these prenatal hormonal influences, early infancy and puberty may provide additional critical periods when hormones influence human neurobehavioral organization. Sex-linked genes could also contribute to human gender development, and most sex-related characteristics are influenced by socialization and other aspects of postnatal experience, as well. Neural mechanisms underlying the influences of gonadal hormones on human behavior are beginning to be identified. Although the neural mechanisms underlying experiential influences remain largely uninvestigated, they could involve the same neural circuitry as that affected by hormones.

Fetal Alcohol Spectrum Disorder (FASD) Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets

PubMed Central

Muralidharan, Pooja; Sarmah, Swapnalee; Zhou, Feng C.; Marrs, James A.

2013-01-01

Fetal alcohol spectrum disorder (FASD), caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection. PMID:24961433

Fetal Alcohol Spectrum Disorder (FASD) Associated Neural Defects: Complex Mechanisms and Potential Therapeutic Targets.

PubMed

Muralidharan, Pooja; Sarmah, Swapnalee; Zhou, Feng C; Marrs, James A

2013-06-19

Fetal alcohol spectrum disorder (FASD), caused by prenatal alcohol exposure, can result in craniofacial dysmorphism, cognitive impairment, sensory and motor disabilities among other defects. FASD incidences are as high as 2% to 5 % children born in the US, and prevalence is higher in low socioeconomic populations. Despite various mechanisms being proposed to explain the etiology of FASD, the molecular targets of ethanol toxicity during development are unknown. Proposed mechanisms include cell death, cell signaling defects and gene expression changes. More recently, the involvement of several other molecular pathways was explored, including non-coding RNA, epigenetic changes and specific vitamin deficiencies. These various pathways may interact, producing a wide spectrum of consequences. Detailed understanding of these various pathways and their interactions will facilitate the therapeutic target identification, leading to new clinical intervention, which may reduce the incidence and severity of these highly prevalent preventable birth defects. This review discusses manifestations of alcohol exposure on the developing central nervous system, including the neural crest cells and sensory neural placodes, focusing on molecular neurodevelopmental pathways as possible therapeutic targets for prevention or protection.

Neonatal ghrelin programs development of hypothalamic feeding circuits

PubMed Central

Steculorum, Sophie M.; Collden, Gustav; Coupe, Berengere; Croizier, Sophie; Lockie, Sarah; Andrews, Zane B.; Jarosch, Florian; Klussmann, Sven; Bouret, Sebastien G.

2015-01-01

A complex neural network regulates body weight and energy balance, and dysfunction in the communication between the gut and this neural network is associated with metabolic diseases, such as obesity. The stomach-derived hormone ghrelin stimulates appetite through interactions with neurons in the arcuate nucleus of the hypothalamus (ARH). Here, we evaluated the physiological and neurobiological contribution of ghrelin during development by specifically blocking ghrelin action during early postnatal development in mice. Ghrelin blockade in neonatal mice resulted in enhanced ARH neural projections and long-term metabolic effects, including increased body weight, visceral fat, and blood glucose levels and decreased leptin sensitivity. In addition, chronic administration of ghrelin during postnatal life impaired the normal development of ARH projections and caused metabolic dysfunction. Consistent with these observations, direct exposure of postnatal ARH neuronal explants to ghrelin blunted axonal growth and blocked the neurotrophic effect of the adipocyte-derived hormone leptin. Moreover, chronic ghrelin exposure in neonatal mice also attenuated leptin-induced STAT3 signaling in ARH neurons. Collectively, these data reveal that ghrelin plays an inhibitory role in the development of hypothalamic neural circuits and suggest that proper expression of ghrelin during neonatal life is pivotal for lifelong metabolic regulation. PMID:25607843

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

Characterization of axon formation in the embryonic stem cell-derived motoneuron.

PubMed

Pan, Hung-Chuan; Wu, Ya-Ting; Shen, Shih-Cheng; Wang, Chi-Chung; Tsai, Ming-Shiun; Cheng, Fu-Chou; Lin, Shinn-Zong; Chen, Ching-Wen; Liu, Ching-San; Su, Hong-Lin

2011-01-01

The developing neural cell must form a highly organized architecture to properly receive and transmit nerve signals. Neural formation from embryonic stem (ES) cells provides a novel system for studying axonogenesis, which are orchestrated by polarity-regulating molecules. Here the ES-derived motoneurons, identified by HB9 promoter-driven green fluorescent protein (GFP) expression, showed characteristics of motoneuron-specific gene expression. In the majority of motoneurons, one of the bilateral neurites developed into an axon that featured with axonal markers, including Tau1, vesicle acetylcholine transporter, and synaptophysin. Interestingly, one third of the motoneurons developed bi-axonal processes but no multiple axonal GFP cell was found. The neuronal polarity-regulating proteins, including the phosphorylated AKT and ERK, were compartmentalized into both of the bilateral axonal tips. Importantly, this aberrant axon morphology was still present after the engraftment of GFP(+) neurons into the spinal cord, suggesting that even a mature neural environment fails to provide a proper niche to guide normal axon formation. These findings underscore the necessity for evaluating the morphogenesis and functionality of neurons before the clinical trials using ES or somatic stem cells.

Predictive and Neural Predictive Control of Uncertain Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.

2000-01-01

Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

Roles of mTOR Signaling in Brain Development.

PubMed

Lee, Da Yong

2015-09-01

mTOR is a serine/threonine kinase composed of multiple protein components. Intracellular signaling of mTOR complexes is involved in many of physiological functions including cell survival, proliferation and differentiation through the regulation of protein synthesis in multiple cell types. During brain development, mTOR-mediated signaling pathway plays a crucial role in the process of neuronal and glial differentiation and the maintenance of the stemness of neural stem cells. The abnormalities in the activity of mTOR and its downstream signaling molecules in neural stem cells result in severe defects of brain developmental processes causing a significant number of brain disorders, such as pediatric brain tumors, autism, seizure, learning disability and mental retardation. Understanding the implication of mTOR activity in neural stem cells would be able to provide an important clue in the development of future brain developmental disorder therapies.

A multivariate extension of mutual information for growing neural networks.

PubMed

Ball, Kenneth R; Grant, Christopher; Mundy, William R; Shafer, Timothy J

2017-11-01

Recordings of neural network activity in vitro are increasingly being used to assess the development of neural network activity and the effects of drugs, chemicals and disease states on neural network function. The high-content nature of the data derived from such recordings can be used to infer effects of compounds or disease states on a variety of important neural functions, including network synchrony. Historically, synchrony of networks in vitro has been assessed either by determination of correlation coefficients (e.g. Pearson's correlation), by statistics estimated from cross-correlation histograms between pairs of active electrodes, and/or by pairwise mutual information and related measures. The present study examines the application of Normalized Multiinformation (NMI) as a scalar measure of shared information content in a multivariate network that is robust with respect to changes in network size. Theoretical simulations are designed to investigate NMI as a measure of complexity and synchrony in a developing network relative to several alternative approaches. The NMI approach is applied to these simulations and also to data collected during exposure of in vitro neural networks to neuroactive compounds during the first 12 days in vitro, and compared to other common measures, including correlation coefficients and mean firing rates of neurons. NMI is shown to be more sensitive to developmental effects than first order synchronous and nonsynchronous measures of network complexity. Finally, NMI is a scalar measure of global (rather than pairwise) mutual information in a multivariate network, and hence relies on less assumptions for cross-network comparisons than historical approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

Review: the role of neural crest cells in the endocrine system.

PubMed

Adams, Meghan Sara; Bronner-Fraser, Marianne

2009-01-01

The neural crest is a pluripotent population of cells that arises at the junction of the neural tube and the dorsal ectoderm. These highly migratory cells form diverse derivatives including neurons and glia of the sensory, sympathetic, and enteric nervous systems, melanocytes, and the bones, cartilage, and connective tissues of the face. The neural crest has long been associated with the endocrine system, although not always correctly. According to current understanding, neural crest cells give rise to the chromaffin cells of the adrenal medulla, chief cells of the extra-adrenal paraganglia, and thyroid C cells. The endocrine tumors that correspond to these cell types are pheochromocytomas, extra-adrenal paragangliomas, and medullary thyroid carcinomas. Although controversies concerning embryological origin appear to have mostly been resolved, questions persist concerning the pathobiology of each tumor type and its basis in neural crest embryology. Here we present a brief history of the work on neural crest development, both in general and in application to the endocrine system. In particular, we present findings related to the plasticity and pluripotency of neural crest cells as well as a discussion of several different neural crest tumors in the endocrine system.

Deletion of OTX2 in neural ectoderm delays anterior pituitary development

PubMed Central

Mortensen, Amanda H.; Schade, Vanessa; Lamonerie, Thomas; Camper, Sally A.

2015-01-01

OTX2 is a homeodomain transcription factor that is necessary for normal head development in mouse and man. Heterozygosity for loss-of-function alleles causes an incompletely penetrant, haploinsufficiency disorder. Affected individuals exhibit a spectrum of features that range from developmental defects in eye and/or pituitary development to acephaly. To investigate the mechanism underlying the pituitary defects, we used different cre lines to inactivate Otx2 in early head development and in the prospective anterior and posterior lobes. Mice homozygous for Otx2 deficiency in early head development and pituitary oral ectoderm exhibit craniofacial defects and pituitary gland dysmorphology, but normal pituitary cell specification. The morphological defects mimic those observed in humans and mice with OTX2 heterozygous mutations. Mice homozygous for Otx2 deficiency in the pituitary neural ectoderm exhibited altered patterning of gene expression and ablation of FGF signaling. The posterior pituitary lobe and stalk, which normally arise from neural ectoderm, were extremely hypoplastic. Otx2 expression was intact in Rathke's pouch, the precursor to the anterior lobe, but the anterior lobe was hypoplastic. The lack of FGF signaling from the neural ectoderm was sufficient to impair anterior lobe growth, but not the differentiation of hormone-producing cells. This study demonstrates that Otx2 expression in the neural ectoderm is important intrinsically for the development of the posterior lobe and pituitary stalk, and it has significant extrinsic effects on anterior pituitary growth. Otx2 expression early in head development is important for establishing normal craniofacial features including development of the brain, eyes and pituitary gland. PMID:25315894

The impact of cultural differences in self-representation on the neural substrates of posttraumatic stress disorder

PubMed Central

Liddell, Belinda J.; Jobson, Laura

2016-01-01

A significant body of literature documents the neural mechanisms involved in the development and maintenance of posttraumatic stress disorder (PTSD). However, there is very little empirical work considering the influence of culture on these underlying mechanisms. Accumulating cultural neuroscience research clearly indicates that cultural differences in self-representation modulate many of the same neural processes proposed to be aberrant in PTSD. The objective of this review paper is to consider how culture may impact on the neural mechanisms underlying PTSD. We first outline five key affective and cognitive functions and their underlying neural correlates that have been identified as being disrupted in PTSD: (1) fear dysregulation; (2) attentional biases to threat; (3) emotion and autobiographical memory; (4) self-referential processing; and (5) attachment and interpersonal processing. Second, we consider prominent cultural theories and review the empirical research that has demonstrated the influence of cultural variations in self-representation on the neural substrates of these same five affective and cognitive functions. Finally, we propose a conceptual model that suggests that these five processes have major relevance to considering how culture may influence the neural processes underpinning PTSD. Highlights of the article Cultural variations in individualistic-collectivistic self-representation modulate many of the same neural and psychological processes disrupted in PTSD. These commonly affected processes include fear perception and regulation mechanisms, attentional biases (to threat), emotional and autobiographical memory systems, self-referential processing and attachment systems. A conceptual model is proposed whereby culture is considered integral to the development and maintenance of PTSD and its neural substrates. PMID:27302635

Listening to Brain Microcircuits for Interfacing With External World—Progress in Wireless Implantable Microelectronic Neuroengineering Devices

PubMed Central

Nurmikko, Arto V.; Donoghue, John P.; Hochberg, Leigh R.; Patterson, William R.; Song, Yoon-Kyu; Bull, Christopher W.; Borton, David A.; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2011-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature’s amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic “brain-interfaces” within the body, a point of special emphasis of this paper. PMID:21654935

Synchronization in a noise-driven developing neural network

NASA Astrophysics Data System (ADS)

Lin, I.-H.; Wu, R.-K.; Chen, C.-M.

2011-11-01

We use computer simulations to investigate the structural and dynamical properties of a developing neural network whose activity is driven by noise. Structurally, the constructed neural networks in our simulations exhibit the small-world properties that have been observed in several neural networks. The dynamical change of neuronal membrane potential is described by the Hodgkin-Huxley model, and two types of learning rules, including spike-timing-dependent plasticity (STDP) and inverse STDP, are considered to restructure the synaptic strength between neurons. Clustered synchronized firing (SF) of the network is observed when the network connectivity (number of connections/maximal connections) is about 0.75, in which the firing rate of neurons is only half of the network frequency. At the connectivity of 0.86, all neurons fire synchronously at the network frequency. The network SF frequency increases logarithmically with the culturing time of a growing network and decreases exponentially with the delay time in signal transmission. These conclusions are consistent with experimental observations. The phase diagrams of SF in a developing network are investigated for both learning rules.

The neural network to determine the mechanical properties of the steels

NASA Astrophysics Data System (ADS)

Yemelyanov, Vitaliy; Yemelyanova, Nataliya; Safonova, Marina; Nedelkin, Aleksey

2018-04-01

The authors describe the neural network structure and software that is designed and developed to determine the mechanical properties of steels. The neural network is developed to refine upon the values of the steels properties. The results of simulations of the developed neural network are shown. The authors note the low standard error of the proposed neural network. To realize the proposed neural network the specialized software has been developed.

Modeling level of urban taxi services using neural network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, J.; Wong, S.C.; Tong, C.O.

1999-05-01

This paper is concerned with the modeling of the complex demand-supply relationship in urban taxi services. A neural network model is developed, based on a taxi service situation observed in the urban area of Hong Kong. The input consists of several exogenous variables including number of licensed taxis, incremental charge of taxi fare, average occupied taxi journey time, average disposable income, and population and customer price index; the output consists of a set of endogenous variables including daily taxi passenger demand, passenger waiting time, vacant taxi headway, average percentage of occupied taxis, taxi utilization, and average taxi waiting time. Comparisonsmore » of the estimation accuracy are made between the neural network model and the simultaneous equations model. The results show that the neural network-based macro taxi model can obtain much more accurate information of the taxi services than the simultaneous equations model does. Although the data set used for training the neural network is small, the results obtained thus far are very encouraging. The neural network model can be used as a policy tool by regulator to assist with the decisions concerning the restriction over the number of taxi licenses and the fixing of the taxi fare structure as well as a range of service quality control.« less

Simulator for neural networks and action potentials.

PubMed

Baxter, Douglas A; Byrne, John H

2007-01-01

A key challenge for neuroinformatics is to devise methods for representing, accessing, and integrating vast amounts of diverse and complex data. A useful approach to represent and integrate complex data sets is to develop mathematical models [Arbib (The Handbook of Brain Theory and Neural Networks, pp. 741-745, 2003); Arbib and Grethe (Computing the Brain: A Guide to Neuroinformatics, 2001); Ascoli (Computational Neuroanatomy: Principles and Methods, 2002); Bower and Bolouri (Computational Modeling of Genetic and Biochemical Networks, 2001); Hines et al. (J. Comput. Neurosci. 17, 7-11, 2004); Shepherd et al. (Trends Neurosci. 21, 460-468, 1998); Sivakumaran et al. (Bioinformatics 19, 408-415, 2003); Smolen et al. (Neuron 26, 567-580, 2000); Vadigepalli et al. (OMICS 7, 235-252, 2003)]. Models of neural systems provide quantitative and modifiable frameworks for representing data and analyzing neural function. These models can be developed and solved using neurosimulators. One such neurosimulator is simulator for neural networks and action potentials (SNNAP) [Ziv (J. Neurophysiol. 71, 294-308, 1994)]. SNNAP is a versatile and user-friendly tool for developing and simulating models of neurons and neural networks. SNNAP simulates many features of neuronal function, including ionic currents and their modulation by intracellular ions and/or second messengers, and synaptic transmission and synaptic plasticity. SNNAP is written in Java and runs on most computers. Moreover, SNNAP provides a graphical user interface (GUI) and does not require programming skills. This chapter describes several capabilities of SNNAP and illustrates methods for simulating neurons and neural networks. SNNAP is available at http://snnap.uth.tmc.edu .

Face off against ROS: Tcof1/Treacle safeguards neuroepithelial cells and progenitor neural crest cells from oxidative stress during craniofacial development.

PubMed

Sakai, Daisuke; Trainor, Paul A

2016-09-01

One-third of all congenital birth defects affect the head and face, and most craniofacial anomalies are considered to arise through defects in the development of cranial neural crest cells. Cranial neural crest cells give rise to the majority of craniofacial bones, cartilages and connective tissues. Therefore, understanding the events that control normal cranial neural crest and subsequent craniofacial development is important for elucidating the pathogenetic mechanisms of craniofacial anomalies and for the exploring potential therapeutic avenues for their prevention. Treacher Collins syndrome (TCS) is a congenital disorder characterized by severe craniofacial anomalies. An animal model of TCS, generated through mutation of Tcof1, the mouse (Mus musculus) homologue of the gene primarily mutated in association with TCS in humans, has recently revealed significant insights into the pathogenesis of TCS. Apoptotic elimination of neuroepithelial cells including neural crest cells is the primary cause of craniofacial defects in Tcof1 mutant embryos. However, our understanding of the mechanisms that induce tissue-specific apoptosis remains incomplete. In this review, we describe recent advances in our understanding of the pathogenesis TCS. Furthermore, we discuss the role of Tcof1 in normal embryonic development, the correlation between genetic and environmental factors on the severity of craniofacial abnormalities, and the prospect for prenatal prevention of craniofacial anomalies. © 2016 Japanese Society of Developmental Biologists.

Face off against ROS: Tcof1/Treacle safeguards neuroepithelial cells and progenitor neural crest cells from oxidative stress during craniofacial development

PubMed Central

Sakai, Daisuke; Trainor, Paul A.

2016-01-01

One-third of all congenital birth defects affect the head and face, and most craniofacial anomalies are considered to arise through defects in the development of cranial neural crest cells. Cranial neural crest cells give rise to the majority of craniofacial bones, cartilages and connective tissues. Therefore understanding the events that control normal cranial neural crest and subsequent craniofacial development is important for elucidating the pathogenetic mechanisms of craniofacial anomalies and for the exploring potential therapeutic avenues for their prevention. Treacher Collins syndrome (TCS) is a congenital disorder characterized by severe craniofacial anomalies. An animal model of TCS, generated through mutation of Tcof1, the mouse (Mus musculus) homologue of the gene primarily mutated in association with TCS in humans, has recently revealed significant insights into the pathogenesis of TCS. Apoptotic elimination of neuroepithelial cells including neural crest cells is the primary cause of craniofacial defects in Tcof1 mutant embryos. However our understanding of the mechanisms that induce tissue-specific apoptosis remains incomplete. In this review, we describe recent advances in our understanding of the pathogenesis TCS. Furthermore, we discuss the role of Tcof1 in normal embryonic development, the correlation between genetic and environmental factors on the severity of craniofacial abnormalities, and the prospect for prenatal prevention of craniofacial anomalies. PMID:27481486

Limited receptive area neural classifier for recognition of swallowing sounds using continuous wavelet transform.

PubMed

Makeyev, Oleksandr; Sazonov, Edward; Schuckers, Stephanie; Lopez-Meyer, Paulo; Melanson, Ed; Neuman, Michael

2007-01-01

In this paper we propose a sound recognition technique based on the limited receptive area (LIRA) neural classifier and continuous wavelet transform (CWT). LIRA neural classifier was developed as a multipurpose image recognition system. Previous tests of LIRA demonstrated good results in different image recognition tasks including: handwritten digit recognition, face recognition, metal surface texture recognition, and micro work piece shape recognition. We propose a sound recognition technique where scalograms of sound instances serve as inputs of the LIRA neural classifier. The methodology was tested in recognition of swallowing sounds. Swallowing sound recognition may be employed in systems for automated swallowing assessment and diagnosis of swallowing disorders. The experimental results suggest high efficiency and reliability of the proposed approach.

The biometric-based module of smart grid system

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Ermoshkina, A.

2015-10-01

Within Smart Grid concept the flexible biometric-based module base on Principal Component Analysis (PCA) and selective Neural Network is developed. The formation of the selective Neural Network the biometric-based module uses the method which includes three main stages: preliminary processing of the image, face localization and face recognition. Experiments on the Yale face database show that (i) selective Neural Network exhibits promising classification capability for face detection, recognition problems; and (ii) the proposed biometric-based module achieves near real-time face detection, recognition speed and the competitive performance, as compared to some existing subspaces-based methods.

Pdgfrα functions in endothelial-derived cells to regulate neural crest cells and the development of the great arteries.

PubMed

Aghajanian, Haig; Cho, Young Kuk; Rizer, Nicholas W; Wang, Qiaohong; Li, Li; Degenhardt, Karl; Jain, Rajan

2017-09-01

Originating as a single vessel emerging from the embryonic heart, the truncus arteriosus must septate and remodel into the aorta and pulmonary artery to support postnatal life. Defective remodeling or septation leads to abnormalities collectively known as conotruncal defects, which are associated with significant mortality and morbidity. Multiple populations of cells must interact to coordinate outflow tract remodeling, and the cardiac neural crest has emerged as particularly important during this process. Abnormalities in the cardiac neural crest have been implicated in the pathogenesis of multiple conotruncal defects, including persistent truncus arteriosus, double outlet right ventricle and tetralogy of Fallot. However, the role of the neural crest in the pathogenesis of another conotruncal abnormality, transposition of the great arteries, is less well understood. In this report, we demonstrate an unexpected role of Pdgfra in endothelial cells and their derivatives during outflow tract development. Loss of Pdgfra in endothelium and endothelial-derived cells results in double outlet right ventricle and transposition of the great arteries. Our data suggest that loss of Pdgfra in endothelial-derived mesenchyme in the outflow tract endocardial cushions leads to a secondary defect in neural crest migration during development. © 2017. Published by The Company of Biologists Ltd.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

The brain as a dynamic physical system.

PubMed

McKenna, T M; McMullen, T A; Shlesinger, M F

1994-06-01

The brain is a dynamic system that is non-linear at multiple levels of analysis. Characterization of its non-linear dynamics is fundamental to our understanding of brain function. Identifying families of attractors in phase space analysis, an approach which has proven valuable in describing non-linear mechanical and electrical systems, can prove valuable in describing a range of behaviors and associated neural activity including sensory and motor repertoires. Additionally, transitions between attractors may serve as useful descriptors for analysing state changes in neurons and neural ensembles. Recent observations of synchronous neural activity, and the emerging capability to record the spatiotemporal dynamics of neural activity by voltage-sensitive dyes and electrode arrays, provide opportunities for observing the population dynamics of neural ensembles within a dynamic systems context. New developments in the experimental physics of complex systems, such as the control of chaotic systems, selection of attractors, attractor switching and transient states, can be a source of powerful new analytical tools and insights into the dynamics of neural systems.

Tutorial: Neural networks and their potential application in nuclear power plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uhrig, R.E.

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 Kanjimore » 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 modelled 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.« less

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Extracellular matrix and its receptors in Drosophila neural development

PubMed Central

Broadie, Kendal; Baumgartner, Stefan; Prokop, Andreas

2011-01-01

Extracellular matrix (ECM) and matrix receptors are intimately involved in most biological processes. The ECM plays fundamental developmental and physiological roles in health and disease, including processes underlying the development, maintenance and regeneration of the nervous system. To understand the principles of ECM-mediated functions in the nervous system, genetic model organisms like Drosophila provide simple, malleable and powerful experimental platforms. This article provides an overview of ECM proteins and receptors in Drosophila. It then focuses on their roles during three progressive phases of neural development: 1) neural progenitor proliferation, 2) axonal growth and pathfinding and 3) synapse formation and function. Each section highlights known ECM and ECM-receptor components and recent studies done in mutant conditions to reveal their in vivo functions, all illustrating the enormous opportunities provided when merging work on the nervous system with systematic research into ECM-related gene functions. PMID:21688401

Quantitative Analysis of Human Pluripotency and Neural Specification by In-Depth (Phospho)Proteomic Profiling.

PubMed

Singec, Ilyas; Crain, Andrew M; Hou, Junjie; Tobe, Brian T D; Talantova, Maria; Winquist, Alicia A; Doctor, Kutbuddin S; Choy, Jennifer; Huang, Xiayu; La Monaca, Esther; Horn, David M; Wolf, Dieter A; Lipton, Stuart A; Gutierrez, Gustavo J; Brill, Laurence M; Snyder, Evan Y

2016-09-13

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. Published by Elsevier Inc.

Ultrasmall implantable composite microelectrodes with bioactive surfaces for chronic neural interfaces

PubMed Central

Kozai, Takashi D. Yoshida; Langhals, Nicholas B.; Patel, Paras R.; Deng, Xiaopei; Zhang, Huanan; Smith, Karen L.; Lahann, Joerg; Kotov, Nicholas A.; Kipke, Daryl R.

2012-01-01

Implantable neural microelectrodes that can record extracellular biopotentials from small, targeted groups of neurons are critical for neuroscience research and emerging clinical applications including brain-controlled prosthetic devices. The crucial material-dependent problem is developing microelectrodes that record neural activity from the same neurons for years with high fidelity and reliability. Here, we report the development of an integrated composite electrode consisting of a carbon-fibre core, a poly(p-xylylene)-based thin-film coating that acts as a dielectric barrier and that is functionalized to control intrinsic biological processes, and a poly(thiophene)-based recording pad. The resulting implants are an order of magnitude smaller than traditional recording electrodes, and more mechanically compliant with brain tissue. They were found to elicit much reduced chronic reactive tissue responses and enabled single-neuron recording in acute and early chronic experiments in rats. This technology, taking advantage of new composites, makes possible highly selective and stealthy neural interface devices towards realizing long-lasting implants. PMID:23142839

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

PubMed

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

A renaissance of neural networks in drug discovery.

PubMed

Baskin, Igor I; Winkler, David; Tetko, Igor V

2016-08-01

Neural networks are becoming a very popular method for solving machine learning and artificial intelligence problems. The variety of neural network types and their application to drug discovery requires expert knowledge to choose the most appropriate approach. In this review, the authors discuss traditional and newly emerging neural network approaches to drug discovery. Their focus is on backpropagation neural networks and their variants, self-organizing maps and associated methods, and a relatively new technique, deep learning. The most important technical issues are discussed including overfitting and its prevention through regularization, ensemble and multitask modeling, model interpretation, and estimation of applicability domain. Different aspects of using neural networks in drug discovery are considered: building structure-activity models with respect to various targets; predicting drug selectivity, toxicity profiles, ADMET and physicochemical properties; characteristics of drug-delivery systems and virtual screening. Neural networks continue to grow in importance for drug discovery. Recent developments in deep learning suggests further improvements may be gained in the analysis of large chemical data sets. It's anticipated that neural networks will be more widely used in drug discovery in the future, and applied in non-traditional areas such as drug delivery systems, biologically compatible materials, and regenerative medicine.

How age of bilingual exposure can change the neural systems for language in the developing brain: a functional near infrared spectroscopy investigation of syntactic processing in monolingual and bilingual children.

PubMed

Jasinska, K K; Petitto, L A

2013-10-01

Is the developing bilingual brain fundamentally similar to the monolingual brain (e.g., neural resources supporting language and cognition)? Or, does early-life bilingual language experience change the brain? If so, how does age of first bilingual exposure impact neural activation for language? We compared how typically-developing bilingual and monolingual children (ages 7-10) and adults recruit brain areas during sentence processing using functional Near Infrared Spectroscopy (fNIRS) brain imaging. Bilingual participants included early-exposed (bilingual exposure from birth) and later-exposed individuals (bilingual exposure between ages 4-6). Both bilingual children and adults showed greater neural activation in left-hemisphere classic language areas, and additionally, right-hemisphere homologues (Right Superior Temporal Gyrus, Right Inferior Frontal Gyrus). However, important differences were observed between early-exposed and later-exposed bilinguals in their earliest-exposed language. Early bilingual exposure imparts fundamental changes to classic language areas instead of alterations to brain regions governing higher cognitive executive functions. However, age of first bilingual exposure does matter. Later-exposed bilinguals showed greater recruitment of the prefrontal cortex relative to early-exposed bilinguals and monolinguals. The findings provide fascinating insight into the neural resources that facilitate bilingual language use and are discussed in terms of how early-life language experiences can modify the neural systems underlying human language processing. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

PubMed

Peters, Sabine; Koolschijn, P Cédric M P; Crone, Eveline A; Van Duijvenvoorde, Anna C K; Raijmakers, Maartje E J

2014-09-01

Learning from feedback is an important aspect of executive functioning that shows profound improvements during childhood and adolescence. This is accompanied by neural changes in the feedback-learning network, which includes pre-supplementary motor area (pre- SMA)/anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC), superior parietal cortex (SPC), and the basal ganglia. However, there can be considerable differences within age ranges in performance that are ascribed to differences in strategy use. This is problematic for traditional approaches of analyzing developmental data, in which age groups are assumed to be homogenous in strategy use. In this study, we used latent variable models to investigate if underlying strategy groups could be detected for a feedback-learning task and whether there were differences in neural activation patterns between strategies. In a sample of 268 participants between ages 8 to 25 years, we observed four underlying strategy groups, which were cut across age groups and varied in the optimality of executive functioning. These strategy groups also differed in neural activity during learning; especially the most optimal performing group showed more activity in DLPFC, SPC and pre-SMA/ACC compared to the other groups. However, age differences remained an important contributor to neural activation, even when correcting for strategy. These findings contribute to the debate of age versus performance predictors of neural development, and highlight the importance of studying individual differences in strategy use when studying development. Copyright © 2014 Elsevier Ltd. All rights reserved.

In vivo performance of a microelectrode neural probe with integrated drug delivery

PubMed Central

Rohatgi, Pratik; Langhals, Nicholas B.; Kipke, Daryl R.; Patil, Parag G.

2014-01-01

Object The availability of sophisticated neural probes is a key prerequisite in the development of future brain machine interfaces (BMI). In this study, we developed and validated a neural probe design capable of simultaneous drug delivery and electrophysiology recordings in vivo. Focal drug delivery has promise to dramatically extend the recording lives of neural probes, a limiting factor to clinical adoption of BMI technology. Methods To form the multifunctional neural probe, we affixed a 16-channel microfabricated silicon electrode array to a fused silica catheter. Three experiments were conducted to characterize the performance of the device. Experiment 1 examines cellular damage from probe insertion and the drug distribution in tissue. Experiment 2 measures the effects of saline infusions delivered through the probe on concurrent electrophysiology. Experiment 3 demonstrates that a physiologically relevant amount of drug can be delivered in a controlled fashion. For these experiments, Hoechst and propidium iodide were used to assess insertion trauma and the tissue distribution of the infusate. Artificial cerebral spinal fluid and tetrodotoxin were injected to determine the efficacy of drug delivery. Results The newly developed multifunctional neural probes were successfully inserted into rat cortex and were able to deliver fluids and drugs that resulted in the expected electrophysiological and histological responses. The damage from insertion of the device into brain tissue was substantially less than the volume of drug dispersion in tissue. Electrophysiological activity, including both individual spikes as well as local field potentials, was successfully recorded with this device during real-time drug delivery. No significant changes were seen in response to delivery of artificial cerebral spinal fluid as a control experiment, whereas delivery of tetrodotoxin produced the expected result of suppressing all spiking activity in the vicinity of the catheter outlet. Conclusions Multifunctional neural probes such as the ones developed and validated within this study have great potential to help further understand the design space and criteria for the next generation of neural probe technology. By incorporating integrated drug delivery functionality into the probes, new treatment options for neurological disorders and regenerative neural interfaces utilizing localized and feedback controlled delivery of drugs can be realized in the near future. PMID:19569896

A Physiological Neural Controller of a Muscle Fiber Oculomotor Plant in Horizontal Monkey Saccades

PubMed Central

Enderle, John D.

2014-01-01

A neural network model of biophysical neurons in the midbrain is presented to drive a muscle fiber oculomotor plant during horizontal monkey saccades. Neural circuitry, including omnipause neuron, premotor excitatory and inhibitory burst neurons, long lead burst neuron, tonic neuron, interneuron, abducens nucleus, and oculomotor nucleus, is developed to examine saccade dynamics. The time-optimal control strategy by realization of agonist and antagonist controller models is investigated. In consequence, each agonist muscle fiber is stimulated by an agonist neuron, while an antagonist muscle fiber is unstimulated by a pause and step from the antagonist neuron. It is concluded that the neural network is constrained by a minimum duration of the agonist pulse and that the most dominant factor in determining the saccade magnitude is the number of active neurons for the small saccades. For the large saccades, however, the duration of agonist burst firing significantly affects the control of saccades. The proposed saccadic circuitry establishes a complete model of saccade generation since it not only includes the neural circuits at both the premotor and motor stages of the saccade generator, but also uses a time-optimal controller to yield the desired saccade magnitude. PMID:24944832

Optogenetics and the future of neuroscience.

PubMed

Boyden, Edward S

2015-09-01

Over the last 10 years, optogenetics has become widespread in neuroscience for the study of how specific cell types contribute to brain functions and brain disorder states. The full impact of optogenetics will emerge only when other toolsets mature, including neural connectivity and cell phenotyping tools and neural recording and imaging tools. The latter tools are rapidly improving, in part because optogenetics has helped galvanize broad interest in neurotechnology development.

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

A behavioral framework to guide research on central auditory development and plasticity

PubMed Central

Sanes, Dan H.; Woolley, Sarah M. N.

2011-01-01

The auditory CNS is influenced profoundly by sounds heard during development. Auditory deprivation and augmented sound exposure can each perturb the maturation of neural computations as well as their underlying synaptic properties. However, we have learned little about the emergence of perceptual skills in these same model systems, and especially how perception is influenced by early acoustic experience. Here, we argue that developmental studies must take greater advantage of behavioral benchmarks. We discuss quantitative measures of perceptual development, and suggest how they can play a much larger role in guiding experimental design. Most importantly, including behavioral measures will allow us to establish empirical connections among environment, neural development, and perception. PMID:22196328

Emerging technologies with potential for objectively evaluating speech recognition skills.

PubMed

Rawool, Vishakha Waman

2016-01-01

Work-related exposure to noise and other ototoxins can cause damage to the cochlea, synapses between the inner hair cells, the auditory nerve fibers, and higher auditory pathways, leading to difficulties in recognizing speech. Procedures designed to determine speech recognition scores (SRS) in an objective manner can be helpful in disability compensation cases where the worker claims to have poor speech perception due to exposure to noise or ototoxins. Such measures can also be helpful in determining SRS in individuals who cannot provide reliable responses to speech stimuli, including patients with Alzheimer's disease, traumatic brain injuries, and infants with and without hearing loss. Cost-effective neural monitoring hardware and software is being rapidly refined due to the high demand for neurogaming (games involving the use of brain-computer interfaces), health, and other applications. More specifically, two related advances in neuro-technology include relative ease in recording neural activity and availability of sophisticated analysing techniques. These techniques are reviewed in the current article and their applications for developing objective SRS procedures are proposed. Issues related to neuroaudioethics (ethics related to collection of neural data evoked by auditory stimuli including speech) and neurosecurity (preservation of a person's neural mechanisms and free will) are also discussed.

Psychological and neural contributions to appetite self-regulation.

PubMed

Stoeckel, Luke E; Birch, Leann L; Heatherton, Todd; Mann, Traci; Hunter, Christine; Czajkowski, Susan; Onken, Lisa; Berger, Paige K; Savage, Cary R

2017-03-01

This paper reviews the state of the science on psychological and neural contributions to appetite self-regulation in the context of obesity. Three content areas (neural systems and cognitive functions; parenting and early childhood development; and goal setting and goal striving) served to illustrate different perspectives on the psychological and neural factors that contribute to appetite dysregulation in the context of obesity. Talks were initially delivered at an NIH workshop consisting of experts in these three content areas, and then content areas were further developed through a review of the literature. Self-regulation of appetite involves a complex interaction between multiple domains, including cognitive, neural, social, and goal-directed behaviors and decision-making. Self-regulation failures can arise from any of these factors, and the resulting implications for obesity should be considered in light of each domain. In some cases, self-regulation is amenable to intervention; however, this does not appear to be universally true, which has implications for both prevention and intervention efforts. Appetite regulation is a complex, multifactorial construct. When considering its role in the obesity epidemic, it is advisable to consider its various dimensions together to best inform prevention and treatment efforts. © 2017 The Obesity Society.

The lamprey: a jawless vertebrate model system for examining origin of the neural crest and other vertebrate traits.

PubMed

Green, Stephen A; Bronner, Marianne E

2014-01-01

Lampreys are a group of jawless fishes that serve as an important point of comparison for studies of vertebrate evolution. Lampreys and hagfishes are agnathan fishes, the cyclostomes, which sit at a crucial phylogenetic position as the only living sister group of the jawed vertebrates. Comparisons between cyclostomes and jawed vertebrates can help identify shared derived (i.e. synapomorphic) traits that might have been inherited from ancestral early vertebrates, if unlikely to have arisen convergently by chance. One example of a uniquely vertebrate trait is the neural crest, an embryonic tissue that produces many cell types crucial to vertebrate features, such as the craniofacial skeleton, pigmentation of the skin, and much of the peripheral nervous system (Gans and Northcutt, 1983). Invertebrate chordates arguably lack unambiguous neural crest homologs, yet have cells with some similarities, making comparisons with lampreys and jawed vertebrates essential for inferring characteristics of development in early vertebrates, and how they may have evolved from nonvertebrate chordates. Here we review recent research on cyclostome neural crest development, including research on lamprey gene regulatory networks and differentiated neural crest fates. Copyright © 2014 International Society of Differentiation. Published by Elsevier B.V. All rights reserved.

Psychological and Neural Contributions to Appetite Self-Regulation

PubMed Central

Stoeckel, Luke E.; Birch, Leann L.; Heatherton, Todd; Mann, Traci; Hunter, Christine; Czajkowski, Susan; Onken, Lisa; Berger, Paige K.; Savage, Cary R.

2017-01-01

Objective Review the state-of-the-science on psychological and neural contributions to appetite self-regulation in the context of obesity. Methods Three content areas (neural systems and cognitive functions; parenting and early childhood development; and goal setting and goal striving) served as examples of different perspectives on the psychological and neural factors that contribute to appetite dysregulation in the context of obesity. Talks were initially delivered at a workshop consisting of experts in these three content areas and then content areas were further developed through a review of the literature. Results Self-regulation of appetite involves a complex interaction between multiple domains, including cognitive, neural, social, and goal-directed behaviors and decision-making. Self-regulation failures can results from any of these factors, and the resulting implications for obesity should be considered in light of each domain. In some cases, self-regulation appears to be amenable to intervention; however, this does not appear to be universally true, which has implications for both prevention and intervention efforts. Conclusions Appetite regulation is a complex, multi-factorial construct. When considering its role in the obesity epidemic, it is advisable to consider these various contributions together to best inform prevention and treatment efforts. PMID:28229541

Listening to Brain Microcircuits for Interfacing With External World-Progress in Wireless Implantable Microelectronic Neuroengineering Devices: Experimental systems are described for electrical recording in the brain using multiple microelectrodes and short range implantable or wearable broadcasting units.

PubMed

Nurmikko, Arto V; Donoghue, John P; Hochberg, Leigh R; Patterson, William R; Song, Yoon-Kyu; Bull, Christopher W; Borton, David A; Laiwalla, Farah; Park, Sunmee; Ming, Yin; Aceros, Juan

2010-01-01

Acquiring neural signals at high spatial and temporal resolution directly from brain microcircuits and decoding their activity to interpret commands and/or prior planning activity, such as motion of an arm or a leg, is a prime goal of modern neurotechnology. Its practical aims include assistive devices for subjects whose normal neural information pathways are not functioning due to physical damage or disease. On the fundamental side, researchers are striving to decipher the code of multiple neural microcircuits which collectively make up nature's amazing computing machine, the brain. By implanting biocompatible neural sensor probes directly into the brain, in the form of microelectrode arrays, it is now possible to extract information from interacting populations of neural cells with spatial and temporal resolution at the single cell level. With parallel advances in application of statistical and mathematical techniques tools for deciphering the neural code, extracted populations or correlated neurons, significant understanding has been achieved of those brain commands that control, e.g., the motion of an arm in a primate (monkey or a human subject). These developments are accelerating the work on neural prosthetics where brain derived signals may be employed to bypass, e.g., an injured spinal cord. One key element in achieving the goals for practical and versatile neural prostheses is the development of fully implantable wireless microelectronic "brain-interfaces" within the body, a point of special emphasis of this paper.

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

PubMed

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

2015-08-01

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

The involvement of heparan sulfate proteoglycans in stem cell differentiation and in malignant glioma

NASA Astrophysics Data System (ADS)

Kundu, Soumi; Xiong, Anqi; Forsberg-Nilsson, Karin

2016-04-01

Heparan sulfate (HS) proteoglycans (HSPG) are major components of the extracellular matrix. They interact with a plethora of macromolecules that are of physiological importance. The pattern of sulfation of the HS chain determines the specificity of these interactions. The enzymes that synthesize and degrade HS are thus key regulators of processes ranging from embryonic development to tissue homeostasis and tumor development. Formation of the nervous system is also critically dependent on appropriate HSPGs as shown by several studies on the role of HS in neural induction from embryonic stem cells. High-grade glioma is the most common primary malignant brain tumor among adults, and the prognosis is poor. Neural and glioma stem cells share several traits, including sustained proliferation and highly efficient migration in the brain. There are also similarities between the neurogenic niche where adult neural stem cells reside and the tumorigenic niche, including their interactions with components of the extracellular matrix (ECM). The levels of many of these components, for example HSPGs and enzymes involved in the biosynthesis and modification of HS are attenuated in gliomas. In this paper, HS regulation of pathways involved in neural differentiation and how these may be of importance for brain development are discussed. The literature suggesting that modifications of HS could regulate glioma growth and invasion is reviewed. Targeting the invasiveness of glioma cells by modulating HS may improve upon present therapeutic options, which only marginally enhance the survival of glioma patients.

Neural dynamic optimization for control systems. I. Background.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the background and motivations for the development of NDO, while the two other subsequent papers of this topic present the theory of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Neural dynamic optimization for control systems.III. Applications.

PubMed

Seong, C Y; Widrow, B

2001-01-01

For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively.

Neural dynamic optimization for control systems.II. Theory.

PubMed

Seong, C Y; Widrow, B

2001-01-01

The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper mainly describes the theory of NDO, while the two other companion papers of this topic explain the background for the development of NDO and demonstrate the method with several applications including control of autonomous vehicles and of a robot arm, respectively.

Photopolymerized materials and patterning for improved performance of neural prosthetics

NASA Astrophysics Data System (ADS)

Tuft, Bradley William

Neural prosthetics are used to replace or substantially augment remaining motor and sensory functions of neural pathways that were lost or damaged due to physical trauma, disease, or genetics. However, due to poor spatial signal resolution, neural prostheses fail to recapitulate the intimate, precise interactions inherent to neural networks. Designing materials and interfaces that direct de novo nerve growth to spatially specific stimulating elements is, therefore, a promising method to enhance signal specificity and performance of prostheses such as the successful cochlear implant (CI) and the developing retinal implant. In this work, the spatial and temporal reaction control inherent to photopolymerization was used to develop methods to generate micro and nanopatterned materials that direct neurite growth from prosthesis relevant neurons. In particular, neurite growth and directionality has been investigated in response to physical, mechanical, and chemical cues on photopolymerized surfaces. Spiral ganglion neurons (SGNs) serve as the primary neuronal model as they are the principal target for CI stimulation. The objective of the research is to rationally design materials that spatially direct neurite growth and to translate fundamental understanding of nerve cell-material interactions into methods of nerve regeneration that improve neural prosthetic performance. A rapid, single-step photopolymerization method was developed to fabricate micro and nanopatterned physical cues on methacrylate surfaces by selectively blocking light with photomasks. Feature height is readily tuned by modulating parameters of the photopolymerizaiton including initiator concentration and species, light intensity, separation distance from the photomask, and radiation exposure time. Alignment of neural elements increases significantly with increasing feature amplitude and constant periodicity, as well as with decreasing periodicity and constant amplitude. SGN neurite alignment strongly correlates with the maximum feature slope. Neurite alignment is compared on unpatterned, unidirectional, and multidirectional photopolymerized micropatterns. The effect of substrate rigidity on neurite alignment to physical cues was determined by maintaining equivalent pattern microfeatures, afforded by the reaction control of photopolymerization, while concomitantly altering the composition of several copolymer platforms to tune matrix stiffness. For each platform, neurite alignment to unidirectional patterns increases with increasing substrate rigidity. Interestingly, SGN neurites respond to material stiffness cues that are orders of magnitude higher (GPa) than what is typically ascribed to neural environments (kPa). Finally, neurite behavior at bioactive borders of various adhesion modulating molecules was evaluated on micropatterned materials to determine which cues took precedence in establishing neurite directionality. At low microfeatures aspect ratios, neurites align to the pattern direction but are then caused to turn and repel from or turn and align to bioactive borders. Conversely, physical cues dominate neurite path-finding as pattern feature slope increases, i.e. aspect ratio of sloping photopolymerized features increases, causing neurites to readily cross bioactive borders. The photopolymerization method developed in this work to generate micro and nanopatterned materials serves as an additional surface engineering tool that enables investigation of cell-material interactions including directed de novo neurite growth. The results of this interdisciplinary effort contribute substantially to polymer neural regeneration technology and will lead to development of advanced biomaterials that improve neural prosthetic tissue integration and performance by spatially directing nerve growth.

The development of the neural crest in the human

PubMed Central

O’Rahilly, Ronan; Müller, Fabiola

2007-01-01

The first systematic account of the neural crest in the human has been prepared after an investigation of 185 serially sectioned staged embryos, aided by graphic reconstructions. As many as fourteen named topographical subdivisions of the crest were identified and eight of them give origin to ganglia (Table 2). Significant findings in the human include the following. (1) An indication of mesencephalic neural crest is discernible already at stage 9, and trigeminal, facial, and postotic components can be detected at stage 10. (2) Crest was not observed at the level of diencephalon 2. Although pre-otic crest from the neural folds is at first continuous (stage 10), crest-free zones are soon observable (stage 11) in Rh.1, 3, and 5. (3) Emigration of cranial neural crest from the neural folds at the neurosomatic junction begins before closure of the rostral neuropore, and later crest cells do not accumulate above the neural tube. (4) The trigeminal, facial, glossopharyngeal and vagal ganglia, which develop from crest that emigrates before the neural folds have fused, continue to receive contributions from the roof plate of the neural tube after fusion of the folds. (5) The nasal crest and the terminalis-vomeronasal complex are the last components of the cranial crest to appear (at stage 13) and they persist longer. (6) The optic, mesencephalic, isthmic, accessory, and hypoglossal crest do not form ganglia. Cervical ganglion 1 is separated early from the neural crest and is not a Froriep ganglion. (7) The cranial ganglia derived from neural crest show a specific relationship to individual neuromeres, and rhombomeres are better landmarks than the otic primordium, which descends during stages 9–14. (8) Epipharyngeal placodes of the pharyngeal arches contribute to cranial ganglia, although that of arch 1 is not typical. (9) The neural crest from rhombomeres 6 and 7 that migrates to pharyngeal arch 3 and from there rostrad to the truncus arteriosus at stage 12 is identified here, for the first time in the human, as the cardiac crest. (10) The hypoglossal crest provides cells that accompany those of myotomes 1–4 and form the hypoglossal cell cord at stages 13 and 14. (11) The occipital crest, which is related to somites 1–4 in the human, differs from the spinal mainly in that it does not develop ganglia. (12) The occipital and spinal portions of the crest migrate dorsoventrad and appear to traverse the sclerotomes before the differentiation into loose and dense zones in the latter. (13) Embryonic examples of synophthalmia and anencephaly are cited to emphasize the role of the neural crest in the development of cranial ganglia and the skull. PMID:17848161

Development switch in neural circuitry underlying odor-malaise learning.

PubMed

Shionoya, Kiseko; Moriceau, Stephanie; Lunday, Lauren; Miner, Cathrine; Roth, Tania L; Sullivan, Regina M

2006-01-01

Fetal and infant rats can learn to avoid odors paired with illness before development of brain areas supporting this learning in adults, suggesting an alternate learning circuit. Here we begin to document the transition from the infant to adult neural circuit underlying odor-malaise avoidance learning using LiCl (0.3 M; 1% of body weight, ip) and a 30-min peppermint-odor exposure. Conditioning groups included: Paired odor-LiCl, Paired odor-LiCl-Nursing, LiCl, and odor-saline. Results showed that Paired LiCl-odor conditioning induced a learned odor aversion in postnatal day (PN) 7, 12, and 23 pups. Odor-LiCl Paired Nursing induced a learned odor preference in PN7 and PN12 pups but blocked learning in PN23 pups. 14C 2-deoxyglucose (2-DG) autoradiography indicated enhanced olfactory bulb activity in PN7 and PN12 pups with odor preference and avoidance learning. The odor aversion in weanling aged (PN23) pups resulted in enhanced amygdala activity in Paired odor-LiCl pups, but not if they were nursing. Thus, the neural circuit supporting malaise-induced aversions changes over development, indicating that similar infant and adult-learned behaviors may have distinct neural circuits.

Integrative approaches for modeling regulation and function of the respiratory system.

PubMed

Ben-Tal, Alona; Tawhai, Merryn H

2013-01-01

Mathematical models have been central to understanding the interaction between neural control and breathing. Models of the entire respiratory system-which comprises the lungs and the neural circuitry that controls their ventilation-have been derived using simplifying assumptions to compartmentalize each component of the system and to define the interactions between components. These full system models often rely-through necessity-on empirically derived relationships or parameters, in addition to physiological values. In parallel with the development of whole respiratory system models are mathematical models that focus on furthering a detailed understanding of the neural control network, or of the several functions that contribute to gas exchange within the lung. These models are biophysically based, and rely on physiological parameters. They include single-unit models for a breathing lung or neural circuit, through to spatially distributed models of ventilation and perfusion, or multicircuit models for neural control. The challenge is to bring together these more recent advances in models of neural control with models of lung function, into a full simulation for the respiratory system that builds upon the more detailed models but remains computationally tractable. This requires first understanding the mathematical models that have been developed for the respiratory system at different levels, and which could be used to study how physiological levels of O2 and CO2 in the blood are maintained. Copyright © 2013 Wiley Periodicals, Inc.

The coxsackievirus-adenovirus receptor reveals complex homophilic and heterophilic interactions on neural cells.

PubMed

Patzke, Christopher; Max, Klaas E A; Behlke, Joachim; Schreiber, Jadwiga; Schmidt, Hannes; Dorner, Armin A; Kröger, Stephan; Henning, Mechthild; Otto, Albrecht; Heinemann, Udo; Rathjen, Fritz G

2010-02-24

The coxsackievirus-adenovirus receptor (CAR) is a member of the Ig superfamily strongly expressed in the developing nervous system. Our histological investigations during development reveal an initial uniform distribution of CAR on all neural cells with a concentration on membranes that face the margins of the nervous system (e.g., the basal laminae and the ventricular side). At more advanced stages, CAR becomes downregulated and restricted to specific regions including areas rich in axonal and dendritic surfaces. To study the function of CAR on neural cells, we used the fiber knob of the adenovirus, extracellular CAR domains, blocking antibodies to CAR, as well as CAR-deficient neural cells. Blocking antibodies were found to inhibit neurite extension in retina organ and retinal explant cultures, whereas the application of the recombinant fiber knob of the adenovirus subtype Ad2 or extracellular CAR domains promoted neurite extension and adhesion to extracellular matrices. We observed a promiscuous interaction of CAR with extracellular matrix glycoproteins, which was deduced from analytical ultracentrifugation experiments, affinity chromatography, and adhesion assays. The membrane proximal Ig domain of CAR, termed D2, was found to bind to a fibronectin fragment, including the heparin-binding domain 2, which promotes neurite extension of wild type, but not of CAR-deficient neural cells. In contrast to heterophilic interactions, homophilic association of CAR involves both Ig domains, as was revealed by ultracentrifugation, chemical cross-linking, and adhesion studies. The results of these functional and binding studies are correlated to a U-shaped homodimer of the complete extracellular domains of CAR detected by x-ray crystallography.

Detection of Oil Chestnuts Infected by Blue Mold Using Near-Infrared Hyperspectral Imaging Combined with Artificial Neural Networks.

PubMed

Feng, Lei; Zhu, Susu; Lin, Fucheng; Su, Zhenzhu; Yuan, Kangpei; Zhao, Yiying; He, Yong; Zhang, Chu

2018-06-15

Mildew damage is a major reason for chestnut poor quality and yield loss. In this study, a near-infrared hyperspectral imaging system in the 874⁻1734 nm spectral range was applied to detect the mildew damage to chestnuts caused by blue mold. Principal component analysis (PCA) scored images were firstly employed to qualitatively and intuitively distinguish moldy chestnuts from healthy chestnuts. Spectral data were extracted from the hyperspectral images. A successive projections algorithm (SPA) was used to select 12 optimal wavelengths. Artificial neural networks, including back propagation neural network (BPNN), evolutionary neural network (ENN), extreme learning machine (ELM), general regression neural network (GRNN) and radial basis neural network (RBNN) were used to build models using the full spectra and optimal wavelengths to distinguish moldy chestnuts. BPNN and ENN models using full spectra and optimal wavelengths obtained satisfactory performances, with classification accuracies all surpassing 99%. The results indicate the potential for the rapid and non-destructive detection of moldy chestnuts by hyperspectral imaging, which would help to develop online detection system for healthy and blue mold infected chestnuts.

Linking structure and activity in nonlinear spiking networks

PubMed Central

Josić, Krešimir; Shea-Brown, Eric

2017-01-01

Recent experimental advances are producing an avalanche of data on both neural connectivity and neural activity. To take full advantage of these two emerging datasets we need a framework that links them, revealing how collective neural activity arises from the structure of neural connectivity and intrinsic neural dynamics. This problem of structure-driven activity has drawn major interest in computational neuroscience. Existing methods for relating activity and architecture in spiking networks rely on linearizing activity around a central operating point and thus fail to capture the nonlinear responses of individual neurons that are the hallmark of neural information processing. Here, we overcome this limitation and present a new relationship between connectivity and activity in networks of nonlinear spiking neurons by developing a diagrammatic fluctuation expansion based on statistical field theory. We explicitly show how recurrent network structure produces pairwise and higher-order correlated activity, and how nonlinearities impact the networks’ spiking activity. Our findings open new avenues to investigating how single-neuron nonlinearities—including those of different cell types—combine with connectivity to shape population activity and function. PMID:28644840

Neural plasticity of development and learning.

PubMed

Galván, Adriana

2010-06-01

Development and learning are powerful agents of change across the lifespan that induce robust structural and functional plasticity in neural systems. An unresolved question in developmental cognitive neuroscience is whether development and learning share the same neural mechanisms associated with experience-related neural plasticity. In this article, I outline the conceptual and practical challenges of this question, review insights gleaned from adult studies, and describe recent strides toward examining this topic across development using neuroimaging methods. I suggest that development and learning are not two completely separate constructs and instead, that they exist on a continuum. While progressive and regressive changes are central to both, the behavioral consequences associated with these changes are closely tied to the existing neural architecture of maturity of the system. Eventually, a deeper, more mechanistic understanding of neural plasticity will shed light on behavioral changes across development and, more broadly, about the underlying neural basis of cognition. (c) 2010 Wiley-Liss, Inc.

Research In Nonlinear Flight Control for Tiltrotor Aircraft Operating in the Terminal Area

NASA Technical Reports Server (NTRS)

Calise, A. J.; Rysdyk, R.

1996-01-01

The research during the first year of the effort focused on the implementation of the recently developed combination of neural net work adaptive control and feedback linearization. At the core of this research is the comprehensive simulation code Generic Tiltrotor Simulator (GTRS) of the XV-15 tilt rotor aircraft. For this research the GTRS code has been ported to a Fortran environment for use on PC. The emphasis of the research is on terminal area approach procedures, including conversion from aircraft to helicopter configuration. This report focuses on the longitudinal control which is the more challenging case for augmentation. Therefore, an attitude command attitude hold (ACAH) control augmentation is considered which is typically used for the pitch channel during approach procedures. To evaluate the performance of the neural network adaptive control architecture it was necessary to develop a set of low order pilot models capable of performing such tasks as, follow desired altitude profiles, follow desired speed profiles, operate on both sides of powercurve, convert, including flaps as well as mastangle changes, operate with different stability and control augmentation system (SCAS) modes. The pilot models are divided in two sets, one for the backside of the powercurve and one for the frontside. These two sets are linearly blended with speed. The mastangle is also scheduled with speed. Different aspects of the proposed architecture for the neural network (NNW) augmented model inversion were also demonstrated. The demonstration involved implementation of a NNW architecture using linearized models from GTRS, including rotor states, to represent the XV-15 at various operating points. The dynamics used for the model inversion were based on the XV-15 operating at 30 Kts, with residualized rotor dynamics, and not including cross coupling between translational and rotational states. The neural network demonstrated ACAH control under various circumstances. Future efforts will include the implementation into the Fortran environment of GTRS, including pilot modeling and NNW augmentation for the lateral channels. These efforts should lead to the development of architectures that will provide for fully automated approach, using similar strategies.

Evidence that the notochord may be pivotal in the development of sacral and anorectal malformations.

PubMed

Qi, Bao Quan; Beasley, Spencer W; Frizelle, Francis A

2003-09-01

The notochord is known to organize normal development of central axial structures, such as the spinal cord, vertebral column, and anorectum, but its role in abnormal development of these organs has not been well documented. The current study has used Ethylenethiourea to induce anorectal malformations in fetal rats, allowing investigation of abnormalities of the notochord and their relationship to the axial structural abnormalities that occur. Timed-mated pregnant rats were fed Ethylenethiourea by gavage on gestational day 10. Their embryos were harvested on gestational days 13 to 16 and sectioned in either the transverse or sagittal plane. Sections were stained with H and E and examined serially. Anorectal malformations were identified in 29 of 34 embryos and neural tube defects in 24, ranging from an accessory neural tube to lumbo-sacral rachischisis. There was no tail or only a rudimentary tail in the majority of embryos. Abnormalities of the notochord in the lumbo-sacral area included ventro-dorsal branching, ventral deviation, and ectopic notochordal tissue. Most abnormal notochord branches and ectopic notochordal tissue were abnormally close to or in contact with the wall of the cloaca or neural tube. Given the known role of the notochord in controlling normal development, this study would suggest that abnormal notochord development may be pivotal in producing neural tube defects and anorectal malformations, possibly by altering sonic hedgehog signalling.

New views on the neural crest epithelial-mesenchymal transition and neuroepithelial interkinetic nuclear migration

PubMed Central

Erickson, Carol A

2009-01-01

By developing a technique for imaging the avian neural crest epithelial-mesenchymal transition (EMT), we have discovered cellular behaviors that challenge current thinking on this important developmental event, including the probability that complete disassembly of the adherens junctions may not control whether or not a neural epithelial cell undergoes an EMT. Further, neural crest cells can adopt multiple modes of cell motility in order to emigrate from the neuroepithelium. We also gained insights into interkinetic nuclear migration (INM). For example, the movement of the nucleus from the basal to apical domain may not require microtubule motors nor an intact nuclear envelope, and the nucleus does not always need to reach the apical surface in order for cytokinesis to occur. These studies illustrate the value of live-cell imaging to elucidate cellular processes. PMID:20195454

Normalization as a canonical neural computation

PubMed Central

Carandini, Matteo; Heeger, David J.

2012-01-01

There is increasing evidence that the brain relies on a set of canonical neural computations, repeating them across brain regions and modalities to apply similar operations to different problems. A promising candidate for such a computation is normalization, in which the responses of neurons are divided by a common factor that typically includes the summed activity of a pool of neurons. Normalization was developed to explain responses in the primary visual cortex and is now thought to operate throughout the visual system, and in many other sensory modalities and brain regions. Normalization may underlie operations such as the representation of odours, the modulatory effects of visual attention, the encoding of value and the integration of multisensory information. Its presence in such a diversity of neural systems in multiple species, from invertebrates to mammals, suggests that it serves as a canonical neural computation. PMID:22108672

Transcriptome analysis reveals determinant stages controlling human embryonic stem cell commitment to neuronal cells.

PubMed

Li, Yuanyuan; Wang, Ran; Qiao, Nan; Peng, Guangdun; Zhang, Ke; Tang, Ke; Han, Jing-Dong J; Jing, Naihe

2017-12-01

Proper neural commitment is essential for ensuring the appropriate development of the human brain and for preventing neurodevelopmental diseases such as autism spectrum disorders, schizophrenia, and intellectual disorders. However, the molecular mechanisms underlying the neural commitment in humans remain elusive. Here, we report the establishment of a neural differentiation system based on human embryonic stem cells (hESCs) and on comprehensive RNA sequencing analysis of transcriptome dynamics during early hESC differentiation. Using weighted gene co-expression network analysis, we reveal that the hESC neurodevelopmental trajectory has five stages: pluripotency (day 0); differentiation initiation (days 2, 4, and 6); neural commitment (days 8-10); neural progenitor cell proliferation (days 12, 14, and 16); and neuronal differentiation (days 18, 20, and 22). These stages were characterized by unique module genes, which may recapitulate the early human cortical development. Moreover, a comparison of our RNA-sequencing data with several other transcriptome profiling datasets from mice and humans indicated that Module 3 associated with the day 8-10 stage is a critical window of fate switch from the pluripotency to the neural lineage. Interestingly, at this stage, no key extrinsic signals were activated. In contrast, using CRISPR/Cas9-mediated gene knockouts, we also found that intrinsic hub transcription factors, including the schizophrenia-associated SIX3 gene and septo-optic dysplasia-related HESX1 gene, are required to program hESC neural determination. Our results improve the understanding of the mechanism of neural commitment in the human brain and may help elucidate the etiology of human mental disorders and advance therapies for managing these conditions. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Transcranial Alternating Current Stimulation (tACS) Mechanisms and Protocols

PubMed Central

Tavakoli, Amir V.; Yun, Kyongsik

2017-01-01

Perception, cognition and consciousness can be modulated as a function of oscillating neural activity, while ongoing neuronal dynamics are influenced by synaptic activity and membrane potential. Consequently, transcranial alternating current stimulation (tACS) may be used for neurological intervention. The advantageous features of tACS include the biphasic and sinusoidal tACS currents, the ability to entrain large neuronal populations, and subtle control over somatic effects. Through neuromodulation of phasic, neural activity, tACS is a powerful tool to investigate the neural correlates of cognition. The rapid development in this area requires clarity about best practices. Here we briefly introduce tACS and review the most compelling findings in the literature to provide a starting point for using tACS. We suggest that tACS protocols be based on functional brain mechanisms and appropriate control experiments, including active sham and condition blinding. PMID:28928634

LavaNet—Neural network development environment in a general mine planning package

NASA Astrophysics Data System (ADS)

Kapageridis, Ioannis Konstantinou; Triantafyllou, A. G.

2011-04-01

LavaNet is a series of scripts written in Perl that gives access to a neural network simulation environment inside a general mine planning package. A well known and a very popular neural network development environment, the Stuttgart Neural Network Simulator, is used as the base for the development of neural networks. LavaNet runs inside VULCAN™—a complete mine planning package with advanced database, modelling and visualisation capabilities. LavaNet is taking advantage of VULCAN's Perl based scripting environment, Lava, to bring all the benefits of neural network development and application to geologists, mining engineers and other users of the specific mine planning package. LavaNet enables easy development of neural network training data sets using information from any of the data and model structures available, such as block models and drillhole databases. Neural networks can be trained inside VULCAN™ and the results be used to generate new models that can be visualised in 3D. Direct comparison of developed neural network models with conventional and geostatistical techniques is now possible within the same mine planning software package. LavaNet supports Radial Basis Function networks, Multi-Layer Perceptrons and Self-Organised Maps.

Organotypic three-dimensional culture model of mesenchymal and epithelial cells to examine tissue fusion events.

EPA Science Inventory

Tissue fusion during early mammalian development requires coordination of multiple cell types, the extracellular matrix, and complex signaling pathways. Fusion events during processes including heart development, neural tube closure, and palatal fusion are dependent on signaling ...

Neural networks for sign language translation

NASA Astrophysics Data System (ADS)

Wilson, Beth J.; Anspach, Gretel

1993-09-01

A neural network is used to extract relevant features of sign language from video images of a person communicating in American Sign Language or Signed English. The key features are hand motion, hand location with respect to the body, and handshape. A modular hybrid design is under way to apply various techniques, including neural networks, in the development of a translation system that will facilitate communication between deaf and hearing people. One of the neural networks described here is used to classify video images of handshapes into their linguistic counterpart in American Sign Language. The video image is preprocessed to yield Fourier descriptors that encode the shape of the hand silhouette. These descriptors are then used as inputs to a neural network that classifies their shapes. The network is trained with various examples from different signers and is tested with new images from new signers. The results have shown that for coarse handshape classes, the network is invariant to the type of camera used to film the various signers and to the segmentation technique.

How Early Hormones Shape Gender Development

PubMed Central

Berenbaum, Sheri A.; Beltz, Adriene M.

2015-01-01

Many important psychological characteristics show sex differences, and are influenced by sex hormones at different developmental periods. We focus on the role of sex hormones in early development, particularly the differential effects of prenatal androgens on aspects of gender development. Increasing evidence confirms that prenatal androgens have facilitative effects on male-typed activity interests and engagement (including child toy preferences and adult careers), and spatial abilities, but relatively minimal effects on gender identity. Recent emphasis has been directed to the psychological mechanisms underlying these effects (including sex differences in propulsive movement, and androgen effects on interest in people versus things), and neural substrates of androgen effects (including regional brain volumes, and neural responses to mental rotation, sexually arousing stimuli, emotion, and reward). Ongoing and planned work is focused on understanding the ways in which hormones act jointly with the social environment across time to produce varying trajectories of gender development, and clarifying mechanisms by which androgens affect behaviors. Such work will be facilitated by applying lessons from other species, and by expanding methodology. Understanding hormonal influences on gender development enhances knowledge of psychological development generally, and has important implications for basic and applied questions, including sex differences in psychopathology, women’s underrepresentation in science and math, and clinical care of individuals with variations in gender expression. PMID:26688827

Cortical Development and Neuroplasticity in Auditory Neuropathy Spectrum Disorder

PubMed Central

Sharma, Anu; Cardon, Garrett

2015-01-01

Cortical development is dependent to a large extent on stimulus-driven input. Auditory Neuropathy Spectrum Disorder (ANSD) is a recently described form of hearing impairment where neural dys-synchrony is the predominant characteristic. Children with ANSD provide a unique platform to examine the effects of asynchronous and degraded afferent stimulation on cortical auditory neuroplasticity and behavioral processing of sound. In this review, we describe patterns of auditory cortical maturation in children with ANSD. The disruption of cortical maturation that leads to these various patterns includes high levels of intra-individual cortical variability and deficits in cortical phase synchronization of oscillatory neural responses. These neurodevelopmental changes, which are constrained by sensitive periods for central auditory maturation, are correlated with behavioral outcomes for children with ANSD. Overall, we hypothesize that patterns of cortical development in children with ANSD appear to be markers of the severity of the underlying neural dys-synchrony, providing prognostic indicators of success of clinical intervention with amplification and/or electrical stimulation. PMID:26070426

Neural correlates of socioeconomic status in the developing human brain.

PubMed

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

2012-07-01

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

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

PubMed

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

PubMed Central

Manoonpong, Poramate; Parlitz, Ulrich; Wörgötter, Florentin

2013-01-01

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines. PMID:23408775

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

NASA Technical Reports Server (NTRS)

Burken, John J.; Larson, Richard R.

2009-01-01

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-09-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

PubMed

Yamazaki, Tadashi; Ikeno, Hidetoshi; Okumura, Yoshihiro; Satoh, Shunji; Kamiyama, Yoshimi; Hirata, Yutaka; Inagaki, Keiichiro; Ishihara, Akito; Kannon, Takayuki; Usui, Shiro

2011-11-01

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them. In this paper, we report our on-going project to develop a cloud-based web service for online simulation called "Simulation Platform". Simulation Platform is a cloud of virtual machines running GNU/Linux. On a virtual machine, various software including developer tools such as compilers and libraries, popular neural simulators such as GENESIS, NEURON and NEST, and scientific software such as Gnuplot, R and Octave, are pre-installed. When a user posts a request, a virtual machine is assigned to the user, and the simulation starts on that machine. The user remotely accesses to the machine through a web browser and carries out the simulation, without the need to install any software but a web browser on the user's own computer. Therefore, Simulation Platform is expected to eliminate impediments to handle multiple neural models that require multiple software. Copyright © 2011 Elsevier Ltd. All rights reserved.

Modification of a neuronal network direction using stepwise photo-thermal etching of an agarose architecture.

PubMed

Suzuki, Ikurou; Sugio, Yoshihiro; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Yasuda, Kenji

2004-07-01

Control over spatial distribution of individual neurons and the pattern of neural network provides an important tool for studying information processing pathways during neural network formation. Moreover, the knowledge of the direction of synaptic connections between cells in each neural network can provide detailed information on the relationship between the forward and feedback signaling. We have developed a method for topographical control of the direction of synaptic connections within a living neuronal network using a new type of individual-cell-based on-chip cell-cultivation system with an agarose microchamber array (AMCA). The advantages of this system include the possibility to control positions and number of cultured cells as well as flexible control of the direction of elongation of axons through stepwise melting of narrow grooves. Such micrometer-order microchannels are obtained by photo-thermal etching of agarose where a portion of the gel is melted with a 1064-nm infrared laser beam. Using this system, we created neural network from individual Rat hippocampal cells. We were able to control elongation of individual axons during cultivation (from cells contained within the AMCA) by non-destructive stepwise photo-thermal etching. We have demonstrated the potential of our on-chip AMCA cell cultivation system for the controlled development of individual cell-based neural networks.

Neural data science: accelerating the experiment-analysis-theory cycle in large-scale neuroscience.

PubMed

Paninski, L; Cunningham, J P

2018-06-01

Modern large-scale multineuronal recording methodologies, including multielectrode arrays, calcium imaging, and optogenetic techniques, produce single-neuron resolution data of a magnitude and precision that were the realm of science fiction twenty years ago. The major bottlenecks in systems and circuit neuroscience no longer lie in simply collecting data from large neural populations, but also in understanding this data: developing novel scientific questions, with corresponding analysis techniques and experimental designs to fully harness these new capabilities and meaningfully interrogate these questions. Advances in methods for signal processing, network analysis, dimensionality reduction, and optimal control-developed in lockstep with advances in experimental neurotechnology-promise major breakthroughs in multiple fundamental neuroscience problems. These trends are clear in a broad array of subfields of modern neuroscience; this review focuses on recent advances in methods for analyzing neural time-series data with single-neuronal precision. Copyright © 2018 Elsevier Ltd. All rights reserved.

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System

PubMed Central

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms. PMID:22408487

Vehicle Signal Analysis Using Artificial Neural Networks for a Bridge Weigh-in-Motion System.

PubMed

Kim, Sungkon; Lee, Jungwhee; Park, Min-Seok; Jo, Byung-Wan

2009-01-01

This paper describes the procedures for development of signal analysis algorithms using artificial neural networks for Bridge Weigh-in-Motion (B-WIM) systems. Through the analysis procedure, the extraction of information concerning heavy traffic vehicles such as weight, speed, and number of axles from the time domain strain data of the B-WIM system was attempted. As one of the several possible pattern recognition techniques, an Artificial Neural Network (ANN) was employed since it could effectively include dynamic effects and bridge-vehicle interactions. A number of vehicle traveling experiments with sufficient load cases were executed on two different types of bridges, a simply supported pre-stressed concrete girder bridge and a cable-stayed bridge. Different types of WIM systems such as high-speed WIM or low-speed WIM were also utilized during the experiments for cross-checking and to validate the performance of the developed algorithms.

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data.

PubMed

Ching, Travers; Zhu, Xun; Garmire, Lana X

2018-04-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet.

The Relationship of Aluminium and Silver to Neural Tube Defects; a Case Control

PubMed Central

Ramírez-Altamirano, María de Jesús; Fenton-Navarro, Patricia; Sivet-Chiñas, Elvira; Harp-Iturribarria, Flor de María; Martínez-Cruz, Ruth; Cruz, Pedro Hernández; Cruz, Margarito Martínez; Pérez-Campos, Eduardo

2012-01-01

Objective The purpose of this study was to identify the relationship of neurotoxic inorganic elements in the hair of patients with the diagnosis of Neural Tube Defects. Our initial hypothesis was that neurotoxic inorganic elements were associated with Neural Tube Defects. Methods Twenty-three samples of hair from newborns were obtained from the General Hospital, “Aurelio Valdivieso” in the city of Oaxaca, Mexico. The study group included 8 newborn infants with neural tube pathology. The control group was composed of 15 newborns without this pathology. The presence of inorganic elements in the hair samples was determined by inductively-coupled plasma spectroscopy (spectroscopic emission of the plasma). Findings The population of newborns with Neural Tube Defects showed significantly higher values of the following elements than the control group: Aluminium, Neural Tube Defects 152.77±51.06 µg/g, control group 76.24±27.89 µg/g; Silver, Neural Tube Defects 1.45±0.76, control group 0.25±0.53 µg/g; Potassium, Neural Tube Defects 553.87±77.91 µg/g, control group 341.13±205.90 µg/g. Association was found at 75 percentile between aluminium plus silver, aluminium plus potassium, silver plus potassium, and potassium plus sodium. Conclusion In the hair of newborns with Neural Tube Defects, the following metals were increased: aluminium, silver. Given the neurotoxicity of the same, and association of Neural Tube Defects with aluminum and silver, one may infer that they may be participating as factors in the development of Neural Tube Defects. PMID:23400307

A Spiking Neural Simulator Integrating Event-Driven and Time-Driven Computation Schemes Using Parallel CPU-GPU Co-Processing: A Case Study.

PubMed

Naveros, Francisco; Luque, Niceto R; Garrido, Jesús A; Carrillo, Richard R; Anguita, Mancia; Ros, Eduardo

2015-07-01

Time-driven simulation methods in traditional CPU architectures perform well and precisely when simulating small-scale spiking neural networks. Nevertheless, they still have drawbacks when simulating large-scale systems. Conversely, event-driven simulation methods in CPUs and time-driven simulation methods in graphic processing units (GPUs) can outperform CPU time-driven methods under certain conditions. With this performance improvement in mind, we have developed an event-and-time-driven spiking neural network simulator suitable for a hybrid CPU-GPU platform. Our neural simulator is able to efficiently simulate bio-inspired spiking neural networks consisting of different neural models, which can be distributed heterogeneously in both small layers and large layers or subsystems. For the sake of efficiency, the low-activity parts of the neural network can be simulated in CPU using event-driven methods while the high-activity subsystems can be simulated in either CPU (a few neurons) or GPU (thousands or millions of neurons) using time-driven methods. In this brief, we have undertaken a comparative study of these different simulation methods. For benchmarking the different simulation methods and platforms, we have used a cerebellar-inspired neural-network model consisting of a very dense granular layer and a Purkinje layer with a smaller number of cells (according to biological ratios). Thus, this cerebellar-like network includes a dense diverging neural layer (increasing the dimensionality of its internal representation and sparse coding) and a converging neural layer (integration) similar to many other biologically inspired and also artificial neural networks.

Function of FEZF1 during early neural differentiation of human embryonic stem cells.

PubMed

Liu, Xin; Su, Pei; Lu, Lisha; Feng, Zicen; Wang, Hongtao; Zhou, Jiaxi

2018-01-01

The understanding of the mechanism underlying human neural development has been hampered due to lack of a cellular system and complicated ethical issues. Human embryonic stem cells (hESCs) provide an invaluable model for dissecting human development because of unlimited self-renewal and the capacity to differentiate into nearly all cell types in the human body. In this study, using a chemical defined neural induction protocol and molecular profiling, we identified Fez family zinc finger 1 (FEZF1) as a potential regulator of early human neural development. FEZF1 is rapidly up-regulated during neural differentiation in hESCs and expressed before PAX6, a well-established marker of early human neural induction. We generated FEZF1-knockout H1 hESC lines using CRISPR-CAS9 technology and found that depletion of FEZF1 abrogates neural differentiation of hESCs. Moreover, loss of FEZF1 impairs the pluripotency exit of hESCs during neural specification, which partially explains the neural induction defect caused by FEZF1 deletion. However, enforced expression of FEZF1 itself fails to drive neural differentiation in hESCs, suggesting that FEZF1 is necessary but not sufficient for neural differentiation from hESCs. Taken together, our findings identify one of the earliest regulators expressed upon neural induction and provide insight into early neural development in human.

Biphasic influence of Miz1 on neural crest development by regulating cell survival and apical adhesion complex formation in the developing neural tube

PubMed Central

Kerosuo, Laura; Bronner, Marianne E.

2014-01-01

Myc interacting zinc finger protein-1 (Miz1) is a transcription factor known to regulate cell cycle– and cell adhesion–related genes in cancer. Here we show that Miz1 also plays a critical role in neural crest development. In the chick, Miz1 is expressed throughout the neural plate and closing neural tube. Its morpholino-mediated knockdown affects neural crest precursor survival, leading to reduction of neural plate border and neural crest specifier genes Msx-1, Pax7, FoxD3, and Sox10. Of interest, Miz1 loss also causes marked reduction of adhesion molecules (N-cadherin, cadherin6B, and α1-catenin) with a concomitant increase of E-cadherin in the neural folds, likely leading to delayed and decreased neural crest emigration. Conversely, Miz1 overexpression results in up-regulation of cadherin6B and FoxD3 expression in the neural folds/neural tube, leading to premature neural crest emigration and increased number of migratory crest cells. Although Miz1 loss effects cell survival and proliferation throughout the neural plate, the neural progenitor marker Sox2 was unaffected, suggesting a neural crest–selective effect. The results suggest that Miz1 is important not only for survival of neural crest precursors, but also for maintenance of integrity of the neural folds and tube, via correct formation of the apical adhesion complex therein. PMID:24307680

Neural Response to Reward as a Predictor of Rise in Depressive Symptoms in Adolescence

PubMed Central

Morgan, Judith K.; Olino, Thomas M.; McMakin, Dana L.; Ryan, Neal D.; Forbes, Erika E.

2012-01-01

Adolescence is a developmental period characterized by significant increases in the onset of depression, but also by increases in depressive symptoms, even among psychiatrically healthy youth. Disrupted reward function has been postulated as a critical factor in the development of depression, but it is still unclear which adolescents are particularly at risk for rising depressive symptoms. We provide a conceptual stance on gender, pubertal development, and reward type as potential moderators of the association between neural response to reward and rises in depressive symptoms. In addition, we describe preliminary findings that support claims of this conceptual stance. We propose that (1) status-related rewards may be particularly salient for eliciting neural response relevant to depressive symptoms in boys, whereas social rewards may be more salient for eliciting neural response relevant to depressive symptoms in girls and (2) the pattern of reduced striatal response and enhanced medial prefrontal response to reward may be particularly predictive of depressive symptoms in pubertal adolescents. We found that greater vmPFC activation when winning rewards predicted greater increases in depressive symptoms over two years, for boys only, and less striatal activation when anticipating rewards predicted greater increases in depressive symptoms over two years, for adolescents in mid to late pubertal stages but not those in pre to early puberty. We also propose directions for future studies, including the investigation of social vs. monetary reward directly and the longitudinal assessment of parallel changes in pubertal development, neural response to reward, and depressive symptoms. PMID:22521464

A chemical screen in zebrafish embryonic cells establishes that Akt activation is required for neural crest development

PubMed Central

Ciarlo, Christie; Kaufman, Charles K; Kinikoglu, Beste; Michael, Jonathan; Yang, Song; D′Amato, Christopher; Blokzijl-Franke, Sasja; den Hertog, Jeroen; Schlaeger, Thorsten M; Zhou, Yi; Liao, Eric

2017-01-01

The neural crest is a dynamic progenitor cell population that arises at the border of neural and non-neural ectoderm. The inductive roles of FGF, Wnt, and BMP at the neural plate border are well established, but the signals required for subsequent neural crest development remain poorly characterized. Here, we conducted a screen in primary zebrafish embryo cultures for chemicals that disrupt neural crest development, as read out by crestin:EGFP expression. We found that the natural product caffeic acid phenethyl ester (CAPE) disrupts neural crest gene expression, migration, and melanocytic differentiation by reducing Sox10 activity. CAPE inhibits FGF-stimulated PI3K/Akt signaling, and neural crest defects in CAPE-treated embryos are suppressed by constitutively active Akt1. Inhibition of Akt activity by constitutively active PTEN similarly decreases crestin expression and Sox10 activity. Our study has identified Akt as a novel intracellular pathway required for neural crest differentiation. PMID:28832322

Neural network expert system for X-ray analysis of welded joints

NASA Astrophysics Data System (ADS)

Kozlov, V. V.; Lapik, N. V.; Popova, N. V.

2018-03-01

The use of intelligent technologies for the automated analysis of product quality is one of the main trends in modern machine building. At the same time, rapid development in various spheres of human activity is experienced by methods associated with the use of artificial neural networks, as the basis for building automated intelligent diagnostic systems. Technologies of machine vision allow one to effectively detect the presence of certain regularities in the analyzed designation, including defects of welded joints according to radiography data.

A novel, immortal, and multipotent human neural stem cell line generating functional neurons and oligodendrocytes.

PubMed

De Filippis, Lidia; Lamorte, Giuseppe; Snyder, Evan Y; Malgaroli, Antonio; Vescovi, Angelo L

2007-09-01

The discovery and study of neural stem cells have revolutionized our understanding of the neurogenetic process, and their inherent ability to adopt expansive growth behavior in vitro is of paramount importance for the development of novel therapeutics based on neural cell replacement. Recent advances in high-throughput assays for drug development and gene discovery dictate the need for rapid, reproducible, long-term expansion of human neural stem cells (hNSCs). In this view, the complement of wild-type cell lines currently available is insufficient. Here we report the establishment of a stable human neural stem cell line (immortalized human NSCs [IhNSCs]) by v-myc-mediated immortalization of previously derived wild-type hNSCs. These cells demonstrate three- to fourfold faster proliferation than wild-type cells in response to growth factors but retain rather similar properties, including multipotentiality. By molecular biology, biochemistry, immunocytochemistry, fluorescence microscopy, and electrophysiology, we show that upon growth factor removal, IhNSCs completely downregulate v-myc expression, cease proliferation, and differentiate terminally into three major neural lineages: astrocytes, oligodendrocytes, and neurons. The latter are functional, mature cells displaying clear-cut morphological and physiological features of terminally differentiated neurons, encompassing mostly the GABAergic, glutamatergic, and cholinergic phenotypes. Finally, IhNSCs produce bona fide oligodendrocytes in fractions up to 20% of total cell number. This is in contrast to the negligible propensity of hNSCs to generate oligodendroglia reported so far. Thus, we describe an immortalized hNSC line endowed with the properties of normal hNSCs and suitable for developing the novel, reliable assays and reproducible high-throughput gene and drug screening that are essential in both diagnostics and cell therapy studies.

What is CAR doing in the middle of the adult neurogenic road?

PubMed Central

Junyent, Felix; Coré, Nathalie; Cremer, Harold

2017-01-01

ABSTRACT The molecular and cellular basis of adult neurogenesis has attracted considerable attention for fundamental and clinical applications because neural stem cells and newborn neurons may, one day, be harnessed to replace neurons and allow cognitive improvement in the diseased brain. In rodents, neural progenitors are located in the dentate gyrus and the sub/periventricular zone. In the dentate gyrus the generation of newborn neurons is associated with plasticity, including regulation of memory. The role of subventricular zone neural precursors that migrate to the olfactory bulb is less characterized. Identifying factors that impact neural stem cell proliferation, migration and differentiation is therefore sine qua non before we can harness their potential. Here, we expand upon our recent results showing that CAR, the coxsackievirus and adenovirus receptor, is among the developing list of key players when it comes to the complex process of integrating newborn neurons into existing circuits in the mature brain. PMID:28516108

Estimation of locomotion speed and directions changes to control a vehicle using neural signals from the motor cortex of rat.

PubMed

Fukayama, Osamu; Taniguchi, Noriyuki; Suzuki, Takafumi; Mabuchi, Kunihiko

2006-01-01

We have developed a brain-machine interface (BMI) in the form of a small vehicle, which we call the RatCar. In this system, we implanted wire electrodes in the motor cortices of rat's brain to continuously record neural signals. We applied a linear model to estimate the locomotion state (e.g., speed and directions) of a rat using a weighted summation model for the neural firing rates. With this information, we then determined the approximate movement of a rat. Although the estimation is still imprecise, results suggest that our model is able to control the system to some degree. In this paper, we give an overview of our system and describe the methods used, which include continuous neural recording, spike detection and a discrimination algorithm, and a locomotion estimation model minimizes the square error of the locomotion speed and changes in direction.

Deep learning with coherent nanophotonic circuits

NASA Astrophysics Data System (ADS)

Shen, Yichen; Harris, Nicholas C.; Skirlo, Scott; Prabhu, Mihika; Baehr-Jones, Tom; Hochberg, Michael; Sun, Xin; Zhao, Shijie; Larochelle, Hugo; Englund, Dirk; Soljačić, Marin

2017-07-01

Artificial neural networks are computational network models inspired by signal processing in the brain. These models have dramatically improved performance for many machine-learning tasks, including speech and image recognition. However, today's computing hardware is inefficient at implementing neural networks, in large part because much of it was designed for von Neumann computing schemes. Significant effort has been made towards developing electronic architectures tuned to implement artificial neural networks that exhibit improved computational speed and accuracy. Here, we propose a new architecture for a fully optical neural network that, in principle, could offer an enhancement in computational speed and power efficiency over state-of-the-art electronics for conventional inference tasks. We experimentally demonstrate the essential part of the concept using a programmable nanophotonic processor featuring a cascaded array of 56 programmable Mach-Zehnder interferometers in a silicon photonic integrated circuit and show its utility for vowel recognition.

Evaluation of a parallel implementation of the learning portion of the backward error propagation neural network: experiments in artifact identification.

PubMed Central

Sittig, D. F.; Orr, J. A.

1991-01-01

Various methods have been proposed in an attempt to solve problems in artifact and/or alarm identification including expert systems, statistical signal processing techniques, and artificial neural networks (ANN). ANNs consist of a large number of simple processing units connected by weighted links. To develop truly robust ANNs, investigators are required to train their networks on huge training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from approximately 6.4 hours to 1.5 hours. We conclude that use of the master-worker model of parallel computation is an excellent method for obtaining speedups in the backward error propagation neural network training algorithm. PMID:1807607

Calcium signaling mediates five types of cell morphological changes to form neural rosettes.

PubMed

Hříbková, Hana; Grabiec, Marta; Klemová, Dobromila; Slaninová, Iva; Sun, Yuh-Man

2018-02-12

Neural rosette formation is a critical morphogenetic process during neural development, whereby neural stem cells are enclosed in rosette niches to equipoise proliferation and differentiation. How neural rosettes form and provide a regulatory micro-environment remains to be elucidated. We employed the human embryonic stem cell-based neural rosette system to investigate the structural development and function of neural rosettes. Our study shows that neural rosette formation consists of five types of morphological change: intercalation, constriction, polarization, elongation and lumen formation. Ca 2+ signaling plays a pivotal role in the five steps by regulating the actions of the cytoskeletal complexes, actin, myosin II and tubulin during intercalation, constriction and elongation. These, in turn, control the polarizing elements, ZO-1, PARD3 and β-catenin during polarization and lumen production for neural rosette formation. We further demonstrate that the dismantlement of neural rosettes, mediated by the destruction of cytoskeletal elements, promotes neurogenesis and astrogenesis prematurely, indicating that an intact rosette structure is essential for orderly neural development. © 2018. Published by The Company of Biologists Ltd.

Journal of Gravitational Physiology. Volume 10, No. 1

NASA Technical Reports Server (NTRS)

Fuller, Charles (Editor); Cogoli, Augusto (Editor); Hargens, Alan R. (Editor); Smith, Arthur H. (Editor); Alberts, Jeffrey (Editor); Baldwin, Kenneth (Editor); Bjurstedt, Hilding (Editor); Blomqvist, C. Gunnar (Editor); Burton, Russell (Editor); Cardus, David (Editor)

2003-01-01

The topics addressed in this issue include: 1) Biosatellites: Past, Present, and Future; 2) Plant Physiology; 3) Neural/Sensory; 4) Musculoskeletal; 5) Endocrinology/Immunology; 6) Development; 7) Cardiovascular; 8) Countermeasures/Applied; 9) Technical.

Neuronal activity during development: permissive or instructive?

PubMed

Crair, M C

1999-02-01

Experimental studies over the past year have shown that neural activity has a range of effects on the development of neural pathways. Although activity appears unimportant for establishing many aspects of the gross morphology and topology of the brain, there are many cases where the presence of neural activity is essential for the formation of a mature system of neural connections; in some instances, the pattern of neural activity actually orchestrates the final arrangement of neural connections.

Acf7 (MACF) is an actin and microtubule linker protein whose expression predominates in neural, muscle, and lung development.

PubMed

Bernier, G; Pool, M; Kilcup, M; Alfoldi, J; De Repentigny, Y; Kothary, R

2000-10-01

Several proteins belonging to the plakin family of cytoskeletal linker proteins have recently been identified, including dystonin/Bpag1 and plectin. These proteins are unique in their abilities to form bridges between different cytoskeletal elements through specialized modular domains. We have previously reported the cloning and partial characterization of Acf7, a novel member of the plakin family. More recently, the full-length cDNA for mouse Acf7 has been reported. Acf7 has a hybrid composition, with extended homology to dystonin/Bpag1 and plectin in the N-terminal half, and to dystrophin in the central and C-terminal half. Recent studies have demonstrated that Acf7 has functional actin and microtubule binding domains. Here, we describe the developmental expression profile for mouse Acf7. RNA in situ hybridization experiments revealed Acf7 transcripts in the dermomyotome and neural fold of day 8.5 mouse embryos. Later in development, Acf7 expression was predominant in neural and muscle tissues and was strongly up-regulated just before birth in type II alveolar cells of the lung. Altogether, our results suggest that Acf7 functions as a versatile cytoskeletal linker protein and plays an important role in neural, muscle, and lung development. Copyright 2000 Wiley-Liss, Inc.

Intelligence Applied to Air Vehicles

NASA Technical Reports Server (NTRS)

Rosen, Robert; Gross, Anthony R.; Fletcher, L. Skip; Zornetzer, Steven (Technical Monitor)

2000-01-01

The exponential growth in information technology has provided the potential for air vehicle capabilities that were previously unavailable to mission and vehicle designers. The increasing capabilities of computer hardware and software, including new developments such as neural networks, provide a new balance of work between humans and machines. This paper will describe several NASA projects, and review results and conclusions from ground and flight investigations where vehicle intelligence was developed and applied to aeronautical and space systems. In the first example, flight results from a neural network flight control demonstration will be reviewed. Using, a highly-modified F-15 aircraft, a NASA/Dryden experimental flight test program has demonstrated how the neural network software can correctly identify and respond to changes in aircraft stability and control characteristics. Using its on-line learning capability, the neural net software would identify that something in the vehicle has changed, then reconfigure the flight control computer system to adapt to those changes. The results of the Remote Agent software project will be presented. This capability will reduce the cost of future spacecraft operations as computers become "thinking" partners along with humans. In addition, the paper will describe the objectives and plans for the autonomous airplane program and the autonomous rotorcraft project. Technologies will also be developed.

Gross anatomy and development of the peripheral nervous system.

PubMed

Catala, Martin; Kubis, Nathalie

2013-01-01

The nervous system is divided into the central nervous system (CNS) composed of the brain, the brainstem, the cerebellum, and the spinal cord and the peripheral nervous system (PNS) made up of the different nerves arising from the CNS. The PNS is divided into the cranial nerves III to XII supplying the head and the spinal nerves that supply the upper and lower limbs. The general anatomy of the PNS is organized according to the arrangement of the fibers along the rostro-caudal axis. The control of the development of the PNS has been unravelled during the last 30 years. Motor nerves arise from the ventral neural tube. This ventralization is induced by morphogenetic molecules such as sonic hedgehog. In contrast, the sensory elements of the PNS arise from a specific population of cells originating from the roof of the neural tube, namely the neural crest. These cells give rise to the neurons of the dorsal root ganglia, the autonomic ganglia and the paraganglia including the adrenergic neurons of the adrenals. Furthermore, the supportive glial Schwann cells of the PNS originate from the neural crest cells. Growth factors as well as myelinating proteins are involved in the development of the PNS. Copyright © 2013 Elsevier B.V. All rights reserved.

White spotting phenotype induced by targeted REST disruption during neural crest specification to a melanocyte cell lineage.

PubMed

Aoki, Hitomi; Hara, Akira; Kunisada, Takahiro

2015-05-01

Neural crest cells (NCCs) emerge from the dorsal region of the neural tube of vertebrate embryos and have the pluripotency to differentiate into both neuronal and non-neuronal lineages including melanocytes. Rest, also known as NRSF (neuro-restrictive silencer factor), is a regulator of neuronal development and function and suggested to be involved in the lineage specification of NCCs. However, further investigations of Rest gene functions in vivo have been hampered by the fact that Rest null mice show early embryonic lethality. To investigate the function of Rest in NCC development, we recently established NCC-specific Rest conditional knockout (CKO) mice and observed their neonatal death. Here, we have established viable heterozygous NCC-specific Rest CKO mice to analyze the function of Rest in an NCC-derived melanocyte cell lineage and found that the white spotting phenotype was associated with the reduction in the number of melanoblasts in the embryonic skin. The Rest deletion induced after the specification to melanocytes did not reduce the number of melanoblasts; therefore, the expression of REST during the early neural crest specification stage was necessary for the normal development of melanoblasts to cover all of the skin. © 2015 The Molecular Biology Society of Japan and Wiley Publishing Asia Pty Ltd.

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

PubMed

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

2017-01-01

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

Artificial neural network modeling of dissolved oxygen in reservoir.

PubMed

Chen, Wei-Bo; Liu, Wen-Cheng

2014-02-01

The water quality of reservoirs is one of the key factors in the operation and water quality management of reservoirs. Dissolved oxygen (DO) in water column is essential for microorganisms and a significant indicator of the state of aquatic ecosystems. In this study, two artificial neural network (ANN) models including back propagation neural network (BPNN) and adaptive neural-based fuzzy inference system (ANFIS) approaches and multilinear regression (MLR) model were developed to estimate the DO concentration in the Feitsui Reservoir of northern Taiwan. The input variables of the neural network are determined as water temperature, pH, conductivity, turbidity, suspended solids, total hardness, total alkalinity, and ammonium nitrogen. The performance of the ANN models and MLR model was assessed through the mean absolute error, root mean square error, and correlation coefficient computed from the measured and model-simulated DO values. The results reveal that ANN estimation performances were superior to those of MLR. Comparing to the BPNN and ANFIS models through the performance criteria, the ANFIS model is better than the BPNN model for predicting the DO values. Study results show that the neural network particularly using ANFIS model is able to predict the DO concentrations with reasonable accuracy, suggesting that the neural network is a valuable tool for reservoir management in Taiwan.

SpikingLab: modelling agents controlled by Spiking Neural Networks in Netlogo.

PubMed

Jimenez-Romero, Cristian; Johnson, Jeffrey

2017-01-01

The scientific interest attracted by Spiking Neural Networks (SNN) has lead to the development of tools for the simulation and study of neuronal dynamics ranging from phenomenological models to the more sophisticated and biologically accurate Hodgkin-and-Huxley-based and multi-compartmental models. However, despite the multiple features offered by neural modelling tools, their integration with environments for the simulation of robots and agents can be challenging and time consuming. The implementation of artificial neural circuits to control robots generally involves the following tasks: (1) understanding the simulation tools, (2) creating the neural circuit in the neural simulator, (3) linking the simulated neural circuit with the environment of the agent and (4) programming the appropriate interface in the robot or agent to use the neural controller. The accomplishment of the above-mentioned tasks can be challenging, especially for undergraduate students or novice researchers. This paper presents an alternative tool which facilitates the simulation of simple SNN circuits using the multi-agent simulation and the programming environment Netlogo (educational software that simplifies the study and experimentation of complex systems). The engine proposed and implemented in Netlogo for the simulation of a functional model of SNN is a simplification of integrate and fire (I&F) models. The characteristics of the engine (including neuronal dynamics, STDP learning and synaptic delay) are demonstrated through the implementation of an agent representing an artificial insect controlled by a simple neural circuit. The setup of the experiment and its outcomes are described in this work.

Conserved gene regulatory module specifies lateral neural borders across bilaterians

PubMed Central

Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua

2017-01-01

The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans. Second, orthologs of the vertebrate NPB specification module (Msx/vab-15, Pax3/7/pax-3, and Zic/ref-2) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref-2 in C. elegans. Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans, Drosophila melanogaster, and Ciona intestinalis. We also identify a novel lateral neural border specifier, ZNF703/tlp-1, which functions synergistically with Msx/vab-15 in both C. elegans and Xenopus laevis. These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians. PMID:28716930

Conserved gene regulatory module specifies lateral neural borders across bilaterians.

PubMed

Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao

2017-08-01

The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.

Implications of newborn amygdala connectivity for fear and cognitive development at 6-months-of-age

PubMed Central

Graham, Alice M.; Buss, Claudia; Rasmussen, Jerod M.; Rudolph, Marc D.; Demeter, Damion V.; Gilmore, John H.; Styner, Martin; Entringer, Sonja; Wadhwa, Pathik D.; Fair, Damien A.

2015-01-01

The first year of life is an important period for emergence of fear in humans. While animal models have revealed developmental changes in amygdala circuitry accompanying emerging fear, human neural systems involved in early fear development remain poorly understood. To increase understanding of the neural foundations of human fear, it is important to consider parallel cognitive development, which may modulate associations between typical development of early fear and subsequent risk for fear-related psychopathology. We, therefore, examined amygdala functional connectivity with rs-fcMRI in 48 neonates (M=3.65 weeks, SD=1.72), and measured fear and cognitive development at 6-months-of-age. Stronger, positive neonatal amygdala connectivity to several regions, including bilateral anterior insula and ventral striatum, was prospectively associated with higher fear at 6-months. Stronger amygdala connectivity to ventral anterior cingulate/anterior medial prefrontal cortex predicted a specific phenotype of higher fear combined with more advanced cognitive development. Overall, findings demonstrate unique profiles of neonatal amygdala functional connectivity related to emerging fear and cognitive development, which may have implications for normative and pathological fear in later years. Consideration of infant fear in the context of cognitive development will likely contribute to a more nuanced understanding of fear, its neural bases, and its implications for future mental health. PMID:26499255

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain

PubMed Central

Matthes, Michaela; Preusse, Martin; Zhang, Jingzhong; Schechter, Julia; Mayer, Daniela; Lentes, Bernd; Theis, Fabian; Prakash, Nilima; Wurst, Wolfgang; Trümbach, Dietrich

2014-01-01

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior–posterior, dorsal–ventral and medial– lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson’s disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. Database URL: http://mouseidgenes.helmholtz-muenchen.de. PMID:25145340

Mouse IDGenes: a reference database for genetic interactions in the developing mouse brain.

PubMed

Matthes, Michaela; Preusse, Martin; Zhang, Jingzhong; Schechter, Julia; Mayer, Daniela; Lentes, Bernd; Theis, Fabian; Prakash, Nilima; Wurst, Wolfgang; Trümbach, Dietrich

2014-01-01

The study of developmental processes in the mouse and other vertebrates includes the understanding of patterning along the anterior-posterior, dorsal-ventral and medial- lateral axis. Specifically, neural development is also of great clinical relevance because several human neuropsychiatric disorders such as schizophrenia, autism disorders or drug addiction and also brain malformations are thought to have neurodevelopmental origins, i.e. pathogenesis initiates during childhood and adolescence. Impacts during early neurodevelopment might also predispose to late-onset neurodegenerative disorders, such as Parkinson's disease. The neural tube develops from its precursor tissue, the neural plate, in a patterning process that is determined by compartmentalization into morphogenetic units, the action of local signaling centers and a well-defined and locally restricted expression of genes and their interactions. While public databases provide gene expression data with spatio-temporal resolution, they usually neglect the genetic interactions that govern neural development. Here, we introduce Mouse IDGenes, a reference database for genetic interactions in the developing mouse brain. The database is highly curated and offers detailed information about gene expressions and the genetic interactions at the developing mid-/hindbrain boundary. To showcase the predictive power of interaction data, we infer new Wnt/β-catenin target genes by machine learning and validate one of them experimentally. The database is updated regularly. Moreover, it can easily be extended by the research community. Mouse IDGenes will contribute as an important resource to the research on mouse brain development, not exclusively by offering data retrieval, but also by allowing data input. http://mouseidgenes.helmholtz-muenchen.de. © The Author(s) 2014. Published by Oxford University Press.

Neural network hardware and software solutions for sorting of waste plastics for recycling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanton, S.L.; Alam, M.K.; Hebner, G.A.

1992-12-31

While plastic recycling efforts have expanded during the past several years, the cost of recovering plastics is still a major impediment for recyclers. Several factors contribute to the prohibitive cost of recycled resins, including the present low marketability of products made with mixed recycled materials, and costs of collecting, sorting and reprocessing plastic materials. A method for automatic sorting of post-consumer plastics into pure polymer streams is needed to overcome the inaccuracies and low product throughput of the currently used method of hand sorting of waste plastics for recycling. The Society of Plastics has designated seven categories as recyclable: Polyethylenemore » terephthalate (PET); High Density Polyethylene (HDPE); Polyvinyl Chloride (PVC); Low Density Polyethylene (LDPE); Polypropylene (PP); Polystyrene (PS); and Other (mixtures, layered items, etc.). With these categories in mind, a system for sorting of waste plastics using near-infrared reflectance spectra and a backpropagation neural network classifier has been developed. A solution has been demonstrated in the laboratory using a high resolution, and relatively slow instrument. A faster instrument is being developed at this time. Neural network hardware options have been evaluated for use in a real-time industrial system. In the lab, a Fourier transform Near Infrared (FT-NIR) scanning spectrometer was used to gather reflectance data from various locations on samples of actual waste plastics. Neural networks were trained off-line with this data using the NeuralWorks Professional II Plus software package on a SparcStation 2. One of the successfully trained networks was used to compare the neural accelerator hardware options available. The results of running this ``worst case`` network on the neural network hardware will be presented. The AT&T ANNA chip and the Intel 80170NX chip development system were used to determine the ease of implementation and accuracies for this network.« less

Neural network hardware and software solutions for sorting of waste plastics for recycling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stanton, S.L.; Alam, M.K.; Hebner, G.A.

1992-01-01

While plastic recycling efforts have expanded during the past several years, the cost of recovering plastics is still a major impediment for recyclers. Several factors contribute to the prohibitive cost of recycled resins, including the present low marketability of products made with mixed recycled materials, and costs of collecting, sorting and reprocessing plastic materials. A method for automatic sorting of post-consumer plastics into pure polymer streams is needed to overcome the inaccuracies and low product throughput of the currently used method of hand sorting of waste plastics for recycling. The Society of Plastics has designated seven categories as recyclable: Polyethylenemore » terephthalate (PET); High Density Polyethylene (HDPE); Polyvinyl Chloride (PVC); Low Density Polyethylene (LDPE); Polypropylene (PP); Polystyrene (PS); and Other (mixtures, layered items, etc.). With these categories in mind, a system for sorting of waste plastics using near-infrared reflectance spectra and a backpropagation neural network classifier has been developed. A solution has been demonstrated in the laboratory using a high resolution, and relatively slow instrument. A faster instrument is being developed at this time. Neural network hardware options have been evaluated for use in a real-time industrial system. In the lab, a Fourier transform Near Infrared (FT-NIR) scanning spectrometer was used to gather reflectance data from various locations on samples of actual waste plastics. Neural networks were trained off-line with this data using the NeuralWorks Professional II Plus software package on a SparcStation 2. One of the successfully trained networks was used to compare the neural accelerator hardware options available. The results of running this worst case'' network on the neural network hardware will be presented. The AT T ANNA chip and the Intel 80170NX chip development system were used to determine the ease of implementation and accuracies for this network.« less

Six degree of freedom active vibration damping for space application

NASA Technical Reports Server (NTRS)

Haynes, Leonard S.

1993-01-01

Work performed during the period 1 Jan. - 31 Mar. 1993 on six degree of freedom active vibration damping for space application is presented. A performance and cost report is included. Topics covered include: actuator testing; mechanical amplifier design; and neural network control system development and experimental evaluation.

Neuromechanic: a computational platform for simulation and analysis of the neural control of movement

PubMed Central

Bunderson, Nathan E.; Bingham, Jeffrey T.; Sohn, M. Hongchul; Ting, Lena H.; Burkholder, Thomas J.

2015-01-01

Neuromusculoskeletal models solve the basic problem of determining how the body moves under the influence of external and internal forces. Existing biomechanical modeling programs often emphasize dynamics with the goal of finding a feed-forward neural program to replicate experimental data or of estimating force contributions or individual muscles. The computation of rigid-body dynamics, muscle forces, and activation of the muscles are often performed separately. We have developed an intrinsically forward computational platform (Neuromechanic, www.neuromechanic.com) that explicitly represents the interdependencies among rigid body dynamics, frictional contact, muscle mechanics, and neural control modules. This formulation has significant advantages for optimization and forward simulation, particularly with application to neural controllers with feedback or regulatory features. Explicit inclusion of all state dependencies allows calculation of system derivatives with respect to kinematic states as well as muscle and neural control states, thus affording a wealth of analytical tools, including linearization, stability analyses and calculation of initial conditions for forward simulations. In this review, we describe our algorithm for generating state equations and explain how they may be used in integration, linearization and stability analysis tools to provide structural insights into the neural control of movement. PMID:23027632

Improving the Unsteady Aerodynamic Performance of Transonic Turbines using Neural Networks

NASA Technical Reports Server (NTRS)

Rai, Man Mohan; Madavan, Nateri K.; Huber, Frank W.

1999-01-01

A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The procedure yielded a modified design that improves the aerodynamic performance through small changes to the reference design geometry. These results demonstrate the capabilities of the neural net-based design procedure, and also show the advantages of including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.

Neuromechanic: a computational platform for simulation and analysis of the neural control of movement.

PubMed

Bunderson, Nathan E; Bingham, Jeffrey T; Sohn, M Hongchul; Ting, Lena H; Burkholder, Thomas J

2012-10-01

Neuromusculoskeletal models solve the basic problem of determining how the body moves under the influence of external and internal forces. Existing biomechanical modeling programs often emphasize dynamics with the goal of finding a feed-forward neural program to replicate experimental data or of estimating force contributions or individual muscles. The computation of rigid-body dynamics, muscle forces, and activation of the muscles are often performed separately. We have developed an intrinsically forward computational platform (Neuromechanic, www.neuromechanic.com) that explicitly represents the interdependencies among rigid body dynamics, frictional contact, muscle mechanics, and neural control modules. This formulation has significant advantages for optimization and forward simulation, particularly with application to neural controllers with feedback or regulatory features. Explicit inclusion of all state dependencies allows calculation of system derivatives with respect to kinematic states and muscle and neural control states, thus affording a wealth of analytical tools, including linearization, stability analyses and calculation of initial conditions for forward simulations. In this review, we describe our algorithm for generating state equations and explain how they may be used in integration, linearization, and stability analysis tools to provide structural insights into the neural control of movement. Copyright © 2012 John Wiley & Sons, Ltd.

Neural Net-Based Redesign of Transonic Turbines for Improved Unsteady Aerodynamic Performance

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Rai, Man Mohan; Huber, Frank W.

1998-01-01

A recently developed neural net-based aerodynamic design procedure is used in the redesign of a transonic turbine stage to improve its unsteady aerodynamic performance. The redesign procedure used incorporates the advantages of both traditional response surface methodology (RSM) and neural networks by employing a strategy called parameter-based partitioning of the design space. Starting from the reference design, a sequence of response surfaces based on both neural networks and polynomial fits are constructed to traverse the design space in search of an optimal solution that exhibits improved unsteady performance. The procedure combines the power of neural networks and the economy of low-order polynomials (in terms of number of simulations required and network training requirements). A time-accurate, two-dimensional, Navier-Stokes solver is used to evaluate the various intermediate designs and provide inputs to the optimization procedure. The optimization procedure yields a modified design that improves the aerodynamic performance through small changes to the reference design geometry. The computed results demonstrate the capabilities of the neural net-based design procedure, and also show the tremendous advantages that can be gained by including high-fidelity unsteady simulations that capture the relevant flow physics in the design optimization process.

Copine1 regulates neural stem cell functions during brain development.

PubMed

Kim, Tae Hwan; Sung, Soo-Eun; Cheal Yoo, Jae; Park, Jae-Yong; Yi, Gwan-Su; Heo, Jun Young; Lee, Jae-Ran; Kim, Nam-Soon; Lee, Da Yong

2018-01-01

Copine 1 (CPNE1) is a well-known phospholipid binding protein in plasma membrane of various cell types. In brain cells, CPNE1 is closely associated with AKT signaling pathway, which is important for neural stem cell (NSC) functions during brain development. Here, we investigated the role of CPNE1 in the regulation of brain NSC functions during brain development and determined its underlying mechanism. In this study, abundant expression of CPNE1 was observed in neural lineage cells including NSCs and immature neurons in human. With mouse brain tissues in various developmental stages, we found that CPNE1 expression was higher at early embryonic stages compared to postnatal and adult stages. To model developing brain in vitro, we used primary NSCs derived from mouse embryonic hippocampus. Our in vitro study shows decreased proliferation and multi-lineage differentiation potential in CPNE1 deficient NSCs. Finally, we found that the deficiency of CPNE1 downregulated mTOR signaling in embryonic NSCs. These data demonstrate that CPNE1 plays a key role in the regulation of NSC functions through the activation of AKT-mTOR signaling pathway during brain development. Copyright © 2017 Elsevier Inc. All rights reserved.

Collagen 18 and agrin are secreted by neural crest cells to remodel their microenvironment and regulate their migration during enteric nervous system development.

PubMed

Nagy, Nandor; Barad, Csilla; Hotta, Ryo; Bhave, Sukhada; Arciero, Emily; Dora, David; Goldstein, Allan M

2018-05-08

The enteric nervous system (ENS) arises from neural crest cells that migrate, proliferate, and differentiate into enteric neurons and glia within the intestinal wall. Many extracellular matrix (ECM) components are present in the embryonic gut, but their role in regulating ENS development is largely unknown. Here, we identify heparan sulfate proteoglycan proteins, including collagen XVIII (Col18) and agrin, as important regulators of enteric neural crest-derived cell (ENCDC) development. In developing avian hindgut, Col18 is expressed at the ENCDC wavefront, while agrin expression occurs later. Both proteins are normally present around enteric ganglia, but are absent in aganglionic gut. Using chick-mouse intestinal chimeras and enteric neurospheres, we show that vagal- and sacral-derived ENCDCs from both species secrete Col18 and agrin. Whereas glia express Col18 and agrin, enteric neurons only express the latter. Functional studies demonstrate that Col18 is permissive whereas agrin is strongly inhibitory to ENCDC migration, consistent with the timing of their expression during ENS development. We conclude that ENCDCs govern their own migration by actively remodeling their microenvironment through secretion of ECM proteins. © 2018. Published by The Company of Biologists Ltd.

The relationship of neurogenesis and growth of brain regions to song learning

PubMed Central

Kirn, John R.

2009-01-01

Song learning, maintenance and production require coordinated activity across multiple auditory, sensory-motor, and neuromuscular structures. Telencephalic components of the sensory-motor circuitry are unique to avian species that engage in song learning. The song system shows protracted development that begins prior to hatching but continues well into adulthood. The staggered developmental timetable for construction of the song system provides clues of subsystems involved in specific stages of song learning and maintenance. Progressive events, including neurogenesis and song system growth, as well as regressive events such as apoptosis and synapse elimination, occur during periods of song learning and the transitions between stereotyped and variable song during both development and adulthood. There is clear evidence that gonadal steroids influence the development of song attributes and shape the underlying neural circuitry. Some aspects of song system development are influenced by sensory, motor and social experience, while other aspects of neural development appear to be experience-independent. Although there are species differences in the extent to which song learning continues into adulthood, growing evidence suggests that despite differences in learning trajectories, adult refinement of song motor control and song maintenance can require remarkable behavioral and neural flexibility reminiscent of sensory-motor learning. PMID:19853905

Slit/Robo1 signaling regulates neural tube development by balancing neuroepithelial cell proliferation and differentiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Guang; Li, Yan; Wang, Xiao-yu

2013-05-01

Formation of the neural tube is the morphological hallmark for development of the embryonic central nervous system (CNS). Therefore, neural tube development is a crucial step in the neurulation process. Slit/Robo signaling was initially identified as a chemo-repellent that regulated axon growth cone elongation, but its role in controlling neural tube development is currently unknown. To address this issue, we investigated Slit/Robo1 signaling in the development of chick neCollege of Life Sciences Biocentre, University of Dundee, Dundee DD1 5EH, UKural tube and transgenic mice over-expressing Slit2. We disrupted Slit/Robo1 signaling by injecting R5 monoclonal antibodies into HH10 neural tubes tomore » block the Robo1 receptor. This inhibited the normal development of the ventral body curvature and caused the spinal cord to curl up into a S-shape. Next, Slit/Robo1 signaling on one half-side of the chick embryo neural tube was disturbed by electroporation in ovo. We found that the morphology of the neural tube was dramatically abnormal after we interfered with Slit/Robo1 signaling. Furthermore, we established that silencing Robo1 inhibited cell proliferation while over-expressing Robo1 enhanced cell proliferation. We also investigated the effects of altering Slit/Robo1 expression on Sonic Hedgehog (Shh) and Pax7 expression in the developing neural tube. We demonstrated that over-expressing Robo1 down-regulated Shh expression in the ventral neural tube and resulted in the production of fewer HNK-1{sup +} migrating neural crest cells (NCCs). In addition, Robo1 over-expression enhanced Pax7 expression in the dorsal neural tube and increased the number of Slug{sup +} pre-migratory NCCs. Conversely, silencing Robo1 expression resulted in an enhanced Shh expression and more HNK-1{sup +} migrating NCCs but reduced Pax7 expression and fewer Slug{sup +} pre-migratory NCCs were observed. In conclusion, we propose that Slit/Robo1 signaling is involved in regulating neural tube development by tightly coordinating cell proliferation and differentiation during neurulation. - Highlights: ► The role of Slit/Robo1 signaling was investigated with chick and mouse models. ► Disturbance of Slit/Robo1 signaling resulted in neural tube defects. ► Slit/Robo1 signaling regulated the proliferation of neural tube cells. ► Slit/Robo1 signaling modulated the differentiation of neural tube cells. ► Slit/Robo1 signaling balanced the proliferation and differentiation of neural tube.« less

Quantitative proteomics analysis highlights the role of redox hemostasis and energy metabolism in human embryonic stem cell differentiation to neural cells.

PubMed

Fathi, Ali; Hatami, Maryam; Vakilian, Haghighat; Han, Chia-Li; Chen, Yu-Ju; Baharvand, Hossein; Salekdeh, Ghasem Hosseini

2014-04-14

Neural differentiation of human embryonic stem cells (hESCs) is a unique opportunity for in vitro analyses of neurogenesis in humans. Extrinsic cues through neural plate formation are well described in the hESCs although intracellular mechanisms underlying neural development are largely unknown. Proteome analysis of hESC differentiation to neural cells will help to further define molecular mechanisms involved in neurogenesis in humans. Using a two-dimensional differential gel electrophoresis (2D-DIGE) system, we analyzed the proteome of hESC differentiation to neurons at three stages, early neural differentiation, neural ectoderm and mature neurons. Out of 137 differentially accumulated protein spots, 118 spots were identified using MALDI-TOF/TOF and LC MS/MS. We observed that proteins involved in redox hemostasis, vitamin and energy metabolism and ubiquitin dependent proteolysis were more abundant in differentiated cells, whereas the abundance of proteins associated with RNA processing and protein folding was higher in hESCs. Higher abundance of proteins involved in maintaining cellular redox state suggests the importance of redox hemostasis in neural differentiation. Furthermore, our results support the concept of a coupling mechanism between neuronal activity and glucose utilization. The protein network analysis showed that the majority of the interacting proteins were associated with the cell cycle and cellular proliferation. These results enhanced our understanding of the molecular dynamics that underlie neural commitment and differentiation. In highlighting the role of redox and unique metabolic properties of neuronal cells, the present findings add insight to our understanding of hESC differentiation to neurons. The abundance of fourteen proteins involved in maintaining cellular redox state, including 10 members of peroxiredoxin (Prdx) family, mainly increased during differentiation, thus highlighting a link of neural differentiation to redox. Our results revealed markedly higher expression of genes encoding enzymes involved in the glycolysis and amino acid synthesis during differentiation. Protein network analysis predicted a number of critical mediators in hESC differentiation. These proteins included TP53, CTNNB1, SMARCA4, TNF, TERT, E2F1, MYC, RB1, and AR. Copyright © 2014 Elsevier B.V. All rights reserved.

Neural correlates of heart-focused interoception: a functional magnetic resonance imaging meta-analysis

PubMed Central

2016-01-01

Interoception is the ability to perceive one's internal body state including visceral sensations. Heart-focused interoception has received particular attention, in part due to a readily available task for behavioural assessment, but also due to accumulating evidence for a significant role in emotional experience, decision-making and clinical disorders such as anxiety and depression. Improved understanding of the underlying neural correlates is important to promote development of anatomical-functional models and suitable intervention strategies. In the present meta-analysis, nine studies reporting neural activity associated with interoceptive attentiveness (i.e. focused attention to a particular interoceptive signal for a given time interval) to one's heartbeat were submitted to a multilevel kernel density analysis. The findings corroborated an extended network associated with heart-focused interoceptive attentiveness including the posterior right and left insula, right claustrum, precentral gyrus and medial frontal gyrus. Right-hemispheric dominance emphasizes non-verbal information processing with the posterior insula presumably serving as the major gateway for cardioception. Prefrontal neural activity may reflect both top-down attention deployment and processing of feed-forward cardioceptive information, possibly orchestrated via the claustrum. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’. PMID:28080975

BmprIa is required in mesenchymal tissue and has limited redundant function with BmprIb in tooth and palate development

PubMed Central

Li, Lu; Lin, Minkui; Wang, Ying; Cserjesi, Peter; Chen, Zhi; Chen, YiPing

2010-01-01

The BMP signaling plays a pivotal role in the development of craniofacial organs, including the tooth and palate. BmprIa and BmprIb encode two type I BMP receptors that are primarily responsible for BMP signaling transduction. We investigated mesenchymal tissue-specific requirement of BmprIa and its functional redundancy with BmprIb during the development of mouse tooth and palate. BmprIa and BmprIb exhibit partially overlapping and distinct expression patterns in the developing tooth and palatal shelf. Neural crest specific inactivation of BmprIa leads to formation of an unusual type of anterior clefting of the secondary palate, an arrest of tooth development at the bud/early cap stages, and severe hypoplasia of the mandible. Defective tooth and palate development is accompanied by the down-regulation of BMP responsive genes and reduced cell proliferation levels in the palatal and dental mesenchyme. To determine if BmprIb could substitute for BmprIa during tooth and palate development, we expressed a constitutively active form of BmprIb (caBmprIb) in the neural crest cells in which BmprIa was simultaneously inactivated. We found that substitution of BmprIa by caBmprIb in neural rest cells rescues the development of molars and maxillary incisor, but the rescued teeth exhibit a delayed odontoblast and ameloblast differentiation. In contrast, caBmprIb fails to rescue the palatal and mandibular defects including the lack of lower incisors. Our results demonstrate an essential role for BmprIa in the mesenchymal component and a limited functional redundancy between BmprIa and BmprIb in a tissue specific manner during tooth and palate development. PMID:21034733

AKT signaling displays multifaceted functions in neural crest development.

PubMed

Sittewelle, Méghane; Monsoro-Burq, Anne H

2018-05-31

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

Functional mapping of the neural circuitry of rat maternal motivation: effects of site-specific transient neural inactivation

PubMed Central

Pereira, Mariana; Morrell, Joan I.

2011-01-01

The present review focuses on recent studies from our laboratory examining the neural circuitry subserving rat maternal motivation across postpartum. We employed a site-specific neural inactivation method by infusion of bupivacaine to map the maternal motivation circuitry using two complementary behavioral approaches: unconditioned maternal responsiveness and choice of pup- over cocaine-conditioned incentives in a concurrent pup/cocaine choice conditioned place preference task. Our findings revealed that during the early postpartum period, distinct brain structures, including the medial preoptic area, ventral tegmental area and medial prefrontal cortex infralimbic and anterior cingulate subregions, contribute a pup-specific bias to the motivational circuitry. As the postpartum period progresses and the pups grow older, our findings further revealed that maternal responsiveness becomes progressively less dependent on medial preoptic area and medial prefrontal cortex infralimbic activity, and more distributed in the maternal circuitry, such that additional network components, including the medial prefrontal cortex prelimbic subregion, are recruited with maternal experience, and contribute to the expression of late postpartum maternal behavior. Collectively, our findings provide strong evidence that the remarkable ability of postpartum females to successfully care for their developing infants is subserved by a distributed neural network that carries out efficient and dynamic processing of complex, constantly changing incoming environmental and pup-related stimuli, ultimately allowing the progression of appropriate expression and waning of maternal responsiveness across the postpartum period. PMID:21815954

Hydrological time series modeling: A comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques

NASA Astrophysics Data System (ADS)

Lohani, A. K.; Kumar, Rakesh; Singh, R. D.

2012-06-01

SummaryTime series modeling is necessary for the planning and management of reservoirs. More recently, the soft computing techniques have been used in hydrological modeling and forecasting. In this study, the potential of artificial neural networks and neuro-fuzzy system in monthly reservoir inflow forecasting are examined by developing and comparing monthly reservoir inflow prediction models, based on autoregressive (AR), artificial neural networks (ANNs) and adaptive neural-based fuzzy inference system (ANFIS). To take care the effect of monthly periodicity in the flow data, cyclic terms are also included in the ANN and ANFIS models. Working with time series flow data of the Sutlej River at Bhakra Dam, India, several ANN and adaptive neuro-fuzzy models are trained with different input vectors. To evaluate the performance of the selected ANN and adaptive neural fuzzy inference system (ANFIS) models, comparison is made with the autoregressive (AR) models. The ANFIS model trained with the input data vector including previous inflows and cyclic terms of monthly periodicity has shown a significant improvement in the forecast accuracy in comparison with the ANFIS models trained with the input vectors considering only previous inflows. In all cases ANFIS gives more accurate forecast than the AR and ANN models. The proposed ANFIS model coupled with the cyclic terms is shown to provide better representation of the monthly inflow forecasting for planning and operation of reservoir.

mTOR regulates brain morphogenesis by mediating GSK3 signaling

PubMed Central

Ka, Minhan; Condorelli, Gianluigi; Woodgett, James R.; Kim, Woo-Yang

2014-01-01

Balanced control of neural progenitor maintenance and neuron production is crucial in establishing functional neural circuits during brain development, and abnormalities in this process are implicated in many neurological diseases. However, the regulatory mechanisms of neural progenitor homeostasis remain poorly understood. Here, we show that mammalian target of rapamycin (mTOR) is required for maintaining neural progenitor pools and plays a key role in mediating glycogen synthase kinase 3 (GSK3) signaling during brain development. First, we generated and characterized conditional mutant mice exhibiting deletion of mTOR in neural progenitors and neurons in the developing brain using Nestin-cre and Nex-cre lines, respectively. The elimination of mTOR resulted in abnormal cell cycle progression of neural progenitors in the developing brain and thereby disruption of progenitor self-renewal. Accordingly, production of intermediate progenitors and postmitotic neurons were markedly suppressed. Next, we discovered that GSK3, a master regulator of neural progenitors, interacts with mTOR and controls its activity in cortical progenitors. Finally, we found that inactivation of mTOR activity suppresses the abnormal proliferation of neural progenitors induced by GSK3 deletion. Our findings reveal that the interaction between mTOR and GSK3 signaling plays an essential role in dynamic homeostasis of neural progenitors during brain development. PMID:25273085

High-resolution Imaging of Neural Anatomy and Pathology of the Neck.

PubMed

Lee, Jeong Hyun; Cheng, Kai-Lung; Choi, Young Jun; Baek, Jung Hwan

2017-01-01

The neck has intricately connected neural structures, including cervical and brachial plexi, the sympathetic system, lower cranial nerves, and their branches. Except for brachial plexus, there has been little research regarding the normal imaging appearance or corresponding pathologies of neural structures in the neck. The development in imaging techniques with better spatial resolution and signal-to-noise ratio has made it possible to see many tiny nerves to predict complications related to image-guided procedures and to better assess treatment response, especially in the management of oncology patients. The purposes of this review is to present imaging-based anatomy of major nerves in the neck and explain their relevant clinical significance according to representative pathologies of regarded nerves in the neck.

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

PubMed

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.

Variation in the schedules of somite and neural development in frogs

PubMed Central

Sáenz-Ponce, Natalia; Mitgutsch, Christian; del Pino, Eugenia M.

2012-01-01

The timing of notochord, somite, and neural development was analyzed in the embryos of six different frog species, which have been divided into two groups, according to their developmental speed. Rapid developing species investigated were Xenopus laevis (Pipidae), Engystomops coloradorum, and Engystomops randi (Leiuperidae). The slow developers were Epipedobates machalilla and Epipedobates tricolor (Dendrobatidae) and Gastrotheca riobambae (Hemiphractidae). Blastopore closure, notochord formation, somite development, neural tube closure, and the formation of cranial neural crest cell-streams were detected by light and scanning electron microscopy and by immuno-histochemical detection of somite and neural crest marker proteins. The data were analyzed using event pairing to determine common developmental aspects and their relationship to life-history traits. In embryos of rapidly developing frogs, elongation of the notochord occurred earlier relative to the time point of blastopore closure in comparison with slowly developing species. The development of cranial neural crest cell-streams relative to somite formation is accelerated in rapidly developing frogs, and it is delayed in slowly developing frogs. The timing of neural tube closure seemed to be temporally uncoupled with somite formation. We propose that these changes are achieved through differential timing of developmental modules that begin with the elongation of the notochord during gastrulation in the rapidly developing species. The differences might be related to the necessity of developing a free-living tadpole quickly in rapid developers. PMID:23184997

An avian model for the reversal of neurobehavioral teratogenicity with neural stem cells

PubMed Central

Dotan, Sharon; Pinkas, Adi; Slotkin, Theodore A.; Yanai, Joseph

2010-01-01

A fast and simple model which uses lower animals on the evolutionary scale is beneficial for developing procedures for the reversal of neurobehavioral teratogenicity with neural stem cells. Here, we established a procedure for the derivation of chick neural stem cells, establishing embryonic day (E) 10 as optimal for progression to neuronal phenotypes. Cells were obtained from the embryonic cerebral hemispheres and incubated for 5–7 days in enriched medium containing epidermal growth factor (EGF) and basic fibroblast growth factor (FGF2) according to a procedure originally developed for mice. A small percentage of the cells survived, proliferated and formed nestin-positive neurospheres. After removal of the growth factors to allow differentiation (5 days), 74% of the cells differentiated into all major lineages of the nervous system, including neurons (Beta III tubulin-positive, 54% of the total number of differentiated cells), astrocytes (GFAP-positive, 26%), and oligodendrocytes (O4-positive, 20%). These findings demonstrate that the cells were indeed neural stem cells. Next, the cells were transplanted in two allograft chick models; (1) direct cerebral transplantation to 24-hours-old chicks, followed by post-transplantation cell tracking at 24 hours, 6 days and 14 days, and (2) intravenous transplantation to chick embryos on E13, followed by cell tracking on E19. With both methods, transplanted cells were found in the brain. The chick embryo provides a convenient, precisely-timed and unlimited supply of neural progenitors for therapy by transplantation, as well as constituting a fast and simple model in which to evaluate the ability of neural stem cell transplantation to repair neural damage, steps that are critical for progress toward therapeutic applications. PMID:20211723

Three-Dimensional-Bioprinted Dopamine-Based Matrix for Promoting Neural Regeneration.

PubMed

Zhou, Xuan; Cui, Haitao; Nowicki, Margaret; Miao, Shida; Lee, Se-Jun; Masood, Fahed; Harris, Brent T; Zhang, Lijie Grace

2018-03-14

Central nerve repair and regeneration remain challenging problems worldwide, largely because of the extremely weak inherent regenerative capacity and accompanying fibrosis of native nerves. Inadequate solutions to the unmet needs for clinical therapeutics encourage the development of novel strategies to promote nerve regeneration. Recently, 3D bioprinting techniques, as one of a set of valuable tissue engineering technologies, have shown great promise toward fabricating complex and customizable artificial tissue scaffolds. Gelatin methacrylate (GelMA) possesses excellent biocompatible and biodegradable properties because it contains many arginine-glycine-aspartic acids (RGD) and matrix metalloproteinase sequences. Dopamine (DA), as an essential neurotransmitter, has proven effective in regulating neuronal development and enhancing neurite outgrowth. In this study, GelMA-DA neural scaffolds with hierarchical structures were 3D-fabricated using our custom-designed stereolithography-based printer. DA was functionalized on GelMA to synthesize a biocompatible printable ink (GelMA-DA) for improving neural differentiation. Additionally, neural stem cells (NSCs) were employed as the primary cell source for these scaffolds because of their ability to terminally differentiate into a variety of cell types including neurons, astrocytes, and oligodendrocytes. The resultant GelMA-DA scaffolds exhibited a highly porous and interconnected 3D environment, which is favorable for supporting NSC growth. Confocal microscopy analysis of neural differentiation demonstrated that a distinct neural network was formed on the GelMA-DA scaffolds. In particular, the most significant improvements were the enhanced neuron gene expression of TUJ1 and MAP2. Overall, our results demonstrated that 3D-printed customizable GelMA-DA scaffolds have a positive role in promoting neural differentiation, which is promising for advancing nerve repair and regeneration in the future.

Prenatal Influences on the Brain.

ERIC Educational Resources Information Center

Eliot, Lise

2002-01-01

Gives an overview of embryology and prenatal brain, sensory, and motor development. Includes discussion of maternal nutrition, chemical exposure, prenatal drug and alcohol hazards, cigarette smoking, and some causes of neural tube defects and premature birth. (Author/KB)

Prototype to product—developing a commercially viable neural prosthesis

NASA Astrophysics Data System (ADS)

Seligman, Peter

2009-12-01

The Cochlear implant or 'Bionic ear' is a device that enables people who do not get sufficient benefit from a hearing aid to communicate with the hearing world. The Cochlear implant is not an amplifier, but a device that electrically stimulates the auditory nerve in a way that crudely mimics normal hearing, thus providing a hearing percept. Many recipients are able to understand running speech without the help of lipreading. Cochlear implants have reached a stage of maturity where there are now 170 000 recipients implanted worldwide. The commercial development of these devices has occurred over the last 30 years. This development has been multidisciplinary, including audiologists, engineers, both mechanical and electrical, histologists, materials scientists, physiologists, surgeons and speech pathologists. This paper will trace the development of the device we have today, from the engineering perspective. The special challenges of designing an active device that will work in the human body for a lifetime will be outlined. These challenges include biocompatibility, extreme reliability, safety, patient fitting and surgical issues. It is emphasized that the successful development of a neural prosthesis requires the partnership of academia and industry.

Prototype to product-developing a commercially viable neural prosthesis.

PubMed

Seligman, Peter

2009-12-01

The Cochlear implant or 'Bionic ear' is a device that enables people who do not get sufficient benefit from a hearing aid to communicate with the hearing world. The Cochlear implant is not an amplifier, but a device that electrically stimulates the auditory nerve in a way that crudely mimics normal hearing, thus providing a hearing percept. Many recipients are able to understand running speech without the help of lipreading. Cochlear implants have reached a stage of maturity where there are now 170 000 recipients implanted worldwide. The commercial development of these devices has occurred over the last 30 years. This development has been multidisciplinary, including audiologists, engineers, both mechanical and electrical, histologists, materials scientists, physiologists, surgeons and speech pathologists. This paper will trace the development of the device we have today, from the engineering perspective. The special challenges of designing an active device that will work in the human body for a lifetime will be outlined. These challenges include biocompatibility, extreme reliability, safety, patient fitting and surgical issues. It is emphasized that the successful development of a neural prosthesis requires the partnership of academia and industry.

Blunted Neural Response to Rewards as a Prospective Predictor of the Development of Depression in Adolescent Girls.

PubMed

Nelson, Brady D; Perlman, Greg; Klein, Daniel N; Kotov, Roman; Hajcak, Greg

2016-12-01

A blunted neural response to rewards has recently emerged as a potential mechanistic biomarker of adolescent depression. The reward positivity, an event-related potential elicited by feedback indicating monetary gain relative to loss, has been associated with risk for depression. The authors examined whether the reward positivity prospectively predicted the development of depression 18 months later in a large community sample of adolescent girls. The sample included 444 girls 13.5-15.5 years old with no lifetime history of a depressive disorder, along with a biological parent for each girl. At baseline, the adolescents' reward positivity was measured using a monetary guessing task, their current depressive symptoms were assessed using a self-report questionnaire, and the adolescents' and parents' lifetime psychiatric histories were evaluated with diagnostic interviews. The same interview and questionnaire were administered to the adolescents again approximately 18 months later. A blunted reward positivity at baseline predicted first-onset depressive disorder and greater depressive symptom scores 18 months later. The reward positivity was also a significant predictor independent of other prominent risk factors, including baseline depressive symptoms and adolescent and parental lifetime psychiatric history. The combination of a blunted reward positivity and greater depressive symptom scores at baseline provided the greatest positive predictive value for first-onset depressive disorder. This study provides strong converging evidence that a blunted neural response to rewards precedes adolescent-onset depression and symptom emergence. Blunted neural response may therefore constitute an important target for screening and prevention.

Neurodevelopmental effects of chronic exposure to elevated levels of pro-inflammatory cytokines in a developing visual system

PubMed Central

2010-01-01

Background Imbalances in the regulation of pro-inflammatory cytokines have been increasingly correlated with a number of severe and prevalent neurodevelopmental disorders, including autism spectrum disorder, schizophrenia and Down syndrome. Although several studies have shown that cytokines have potent effects on neural function, their role in neural development is still poorly understood. In this study, we investigated the link between abnormal cytokine levels and neural development using the Xenopus laevis tadpole visual system, a model frequently used to examine the anatomical and functional development of neural circuits. Results Using a test for a visually guided behavior that requires normal visual system development, we examined the long-term effects of prolonged developmental exposure to three pro-inflammatory cytokines with known neural functions: interleukin (IL)-1β, IL-6 and tumor necrosis factor (TNF)-α. We found that all cytokines affected the development of normal visually guided behavior. Neuroanatomical imaging of the visual projection showed that none of the cytokines caused any gross abnormalities in the anatomical organization of this projection, suggesting that they may be acting at the level of neuronal microcircuits. We further tested the effects of TNF-α on the electrophysiological properties of the retinotectal circuit and found that long-term developmental exposure to TNF-α resulted in enhanced spontaneous excitatory synaptic transmission in tectal neurons, increased AMPA/NMDA ratios of retinotectal synapses, and a decrease in the number of immature synapses containing only NMDA receptors, consistent with premature maturation and stabilization of these synapses. Local interconnectivity within the tectum also appeared to remain widespread, as shown by increased recurrent polysynaptic activity, and was similar to what is seen in more immature, less refined tectal circuits. TNF-α treatment also enhanced the overall growth of tectal cell dendrites. Finally, we found that TNF-α-reared tadpoles had increased susceptibility to pentylenetetrazol-induced seizures. Conclusions Taken together our data are consistent with a model in which TNF-α causes premature stabilization of developing synapses within the tectum, therefore preventing normal refinement and synapse elimination that occurs during development, leading to increased local connectivity and epilepsy. This experimental model also provides an integrative approach to understanding the effects of cytokines on the development of neural circuits and may provide novel insights into the etiology underlying some neurodevelopmental disorders. PMID:20067608

Neurodevelopmental effects of chronic exposure to elevated levels of pro-inflammatory cytokines in a developing visual system.

PubMed

Lee, Ryan H; Mills, Elizabeth A; Schwartz, Neil; Bell, Mark R; Deeg, Katherine E; Ruthazer, Edward S; Marsh-Armstrong, Nicholas; Aizenman, Carlos D

2010-01-12

Imbalances in the regulation of pro-inflammatory cytokines have been increasingly correlated with a number of severe and prevalent neurodevelopmental disorders, including autism spectrum disorder, schizophrenia and Down syndrome. Although several studies have shown that cytokines have potent effects on neural function, their role in neural development is still poorly understood. In this study, we investigated the link between abnormal cytokine levels and neural development using the Xenopus laevis tadpole visual system, a model frequently used to examine the anatomical and functional development of neural circuits. Using a test for a visually guided behavior that requires normal visual system development, we examined the long-term effects of prolonged developmental exposure to three pro-inflammatory cytokines with known neural functions: interleukin (IL)-1beta, IL-6 and tumor necrosis factor (TNF)-alpha. We found that all cytokines affected the development of normal visually guided behavior. Neuroanatomical imaging of the visual projection showed that none of the cytokines caused any gross abnormalities in the anatomical organization of this projection, suggesting that they may be acting at the level of neuronal microcircuits. We further tested the effects of TNF-alpha on the electrophysiological properties of the retinotectal circuit and found that long-term developmental exposure to TNF-alpha resulted in enhanced spontaneous excitatory synaptic transmission in tectal neurons, increased AMPA/NMDA ratios of retinotectal synapses, and a decrease in the number of immature synapses containing only NMDA receptors, consistent with premature maturation and stabilization of these synapses. Local interconnectivity within the tectum also appeared to remain widespread, as shown by increased recurrent polysynaptic activity, and was similar to what is seen in more immature, less refined tectal circuits. TNF-alpha treatment also enhanced the overall growth of tectal cell dendrites. Finally, we found that TNF-alpha-reared tadpoles had increased susceptibility to pentylenetetrazol-induced seizures. Taken together our data are consistent with a model in which TNF-alpha causes premature stabilization of developing synapses within the tectum, therefore preventing normal refinement and synapse elimination that occurs during development, leading to increased local connectivity and epilepsy. This experimental model also provides an integrative approach to understanding the effects of cytokines on the development of neural circuits and may provide novel insights into the etiology underlying some neurodevelopmental disorders.

Neuregulin 1 Type II-ErbB Signaling Promotes Cell Divisions Generating Neurons from Neural Progenitor Cells in the Developing Zebrafish Brain.

PubMed

Sato, Tomomi; Sato, Fuminori; Kamezaki, Aosa; Sakaguchi, Kazuya; Tanigome, Ryoma; Kawakami, Koichi; Sehara-Fujisawa, Atsuko

2015-01-01

Post-mitotic neurons are generated from neural progenitor cells (NPCs) at the expense of their proliferation. Molecular and cellular mechanisms that regulate neuron production temporally and spatially should impact on the size and shape of the brain. While transcription factors such as neurogenin1 (neurog1) and neurod govern progression of neurogenesis as cell-intrinsic mechanisms, recent studies show regulatory roles of several cell-extrinsic or intercellular signaling molecules including Notch, FGF and Wnt in production of neurons/neural progenitor cells from neural stem cells/radial glial cells (NSCs/RGCs) in the ventricular zone (VZ). However, it remains elusive how production of post-mitotic neurons from neural progenitor cells is regulated in the sub-ventricular zone (SVZ). Here we show that newborn neurons accumulate in the basal-to-apical direction in the optic tectum (OT) of zebrafish embryos. While neural progenitor cells are amplified by mitoses in the apical ventricular zone, neurons are exclusively produced through mitoses of neural progenitor cells in the sub-basal zone, later in the sub-ventricular zone, and accumulate apically onto older neurons. This neurogenesis depends on Neuregulin 1 type II (NRG1-II)-ErbB signaling. Treatment with an ErbB inhibitor, AG1478 impairs mitoses in the sub-ventricular zone of the optic tectum. Removal of AG1478 resumes sub-ventricular mitoses without precedent mitoses in the apical ventricular zone prior to basal-to-apical accumulation of neurons, suggesting critical roles of ErbB signaling in mitoses for post-mitotic neuron production. Knockdown of NRG1-II impairs both mitoses in the sub-basal/sub-ventricular zone and the ventricular zone. Injection of soluble human NRG1 into the developing brain ameliorates neurogenesis of NRG1-II-knockdown embryos, suggesting a conserved role of NRG1 as a cell-extrinsic signal. From these results, we propose that NRG1-ErbB signaling stimulates cell divisions generating neurons from neural progenitor cells in the developing vertebrate brain.

Femtosecond laser dissection in C. elegans neural circuits

NASA Astrophysics Data System (ADS)

Samuel, Aravinthan D. T.; Chung, Samuel H.; Clark, Damon A.; Gabel, Christopher V.; Chang, Chieh; Murthy, Venkatesh; Mazur, Eric

2006-02-01

The nematode C. elegans, a millimeter-long roundworm, is a well-established model organism for studies of neural development and behavior, however physiological methods to manipulate and monitor the activity of its neural network have lagged behind the development of powerful methods in genetics and molecular biology. The small size and transparency of C. elegans make the worm an ideal test-bed for the development of physiological methods derived from optics and microscopy. We present the development and application of a new physiological tool: femtosecond laser dissection, which allows us to selectively ablate segments of individual neural fibers within live C. elegans. Femtosecond laser dissection provides a scalpel with submicrometer resolution, and we discuss its application in studies of neural growth, regenerative growth, and the neural basis of behavior.

Novel four-sided neural probe fabricated by a thermal lamination process of polymer films.

PubMed

Shin, Soowon; Kim, Jae-Hyun; Jeong, Joonsoo; Gwon, Tae Mok; Lee, Seung-Hee; Kim, Sung June

2017-02-15

Ideally, neural probes should have channels with a three-dimensional (3-D) configuration to record the activities of 3-D neural circuits. Many types of 3-D neural probes have been developed; however, most of them were designed as an array of multiple shanks with electrodes located along one side of the shanks. We developed a novel liquid crystal polymer (LCP)-based neural probe with four-sided electrodes. This probe has electrodes on four sides of the shank, i.e., the front, back and two sidewalls. To generate the proposed configuration of the electrodes, we used a thermal lamination process involving LCP films and laser micromachining. The proposed novel four-sided neural probe, was used to successfully perform in vivo multichannel neural recording in the mouse primary somatosensory cortex. The multichannel neural recording showed that the proposed four-sided neural probe can record spiking activities from a more diverse neuronal population than single-sided probes. This was confirmed by a pairwise Pearson correlation coefficient (Pearson's r) analysis and a cross-correlation analysis. The developed four-sided neural probe can be used to record various signals from a complex neural network. Copyright © 2016 Elsevier B.V. All rights reserved.

Characterization of NvLWamide-like neurons reveals stereotypy in Nematostella nerve net development.

PubMed

Havrilak, Jamie A; Faltine-Gonzalez, Dylan; Wen, Yiling; Fodera, Daniella; Simpson, Ayanna C; Magie, Craig R; Layden, Michael J

2017-11-15

The organization of cnidarian nerve nets is traditionally described as diffuse with randomly arranged neurites that show minimal reproducibility between animals. However, most observations of nerve nets are conducted using cross-reactive antibodies that broadly label neurons, which potentially masks stereotyped patterns produced by individual neuronal subtypes. Additionally, many cnidarians species have overt structures such as a nerve ring, suggesting higher levels of organization and stereotypy exist, but mechanisms that generated that stereotypy are unknown. We previously demonstrated that NvLWamide-like is expressed in a small subset of the Nematostella nerve net and speculated that observing a few neurons within the developing nerve net would provide a better indication of potential stereotypy. Here we document NvLWamide-like expression more systematically. NvLWamide-like is initially expressed in the typical neurogenic salt and pepper pattern within the ectoderm at the gastrula stage, and expression expands to include endodermal salt and pepper expression at the planula larval stage. Expression persists in both ectoderm and endoderm in adults. We characterized our NvLWamide-like::mCherry transgenic reporter line to visualize neural architecture and found that NvLWamide-like is expressed in six neural subtypes identifiable by neural morphology and location. Upon completing development the numbers of neurons in each neural subtype are minimally variable between animals and the projection patterns of each subtype are consistent. Furthermore, between the juvenile polyp and adult stages the number of neurons for each subtype increases. We conclude that development of the Nematostella nerve net is stereotyped between individuals. Our data also imply that one aspect of generating adult cnidarian nervous systems is to modify the basic structural architecture generated in the juvenile by increasing neural number proportionally with size. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Development of Methodologies for IV and V of Neural Networks

NASA Technical Reports Server (NTRS)

Taylor, Brian; Darrah, Marjorie

2003-01-01

Non-deterministic systems often rely upon neural network (NN) technology to "lean" to manage flight systems under controlled conditions using carefully chosen training sets. How can these adaptive systems be certified to ensure that they will become increasingly efficient and behave appropriately in real-time situations? The bulk of Independent Verification and Validation (IV&V) research of non-deterministic software control systems such as Adaptive Flight Controllers (AFC's) addresses NNs in well-behaved and constrained environments such as simulations and strict process control. However, neither substantive research, nor effective IV&V techniques have been found to address AFC's learning in real-time and adapting to live flight conditions. Adaptive flight control systems offer good extensibility into commercial aviation as well as military aviation and transportation. Consequently, this area of IV&V represents an area of growing interest and urgency. ISR proposes to further the current body of knowledge to meet two objectives: Research the current IV&V methods and assess where these methods may be applied toward a methodology for the V&V of Neural Network; and identify effective methods for IV&V of NNs that learn in real-time, including developing a prototype test bed for IV&V of AFC's. Currently. no practical method exists. lSR will meet these objectives through the tasks identified and described below. First, ISR will conduct a literature review of current IV&V technology. TO do this, ISR will collect the existing body of research on IV&V of non-deterministic systems and neural network. ISR will also develop the framework for disseminating this information through specialized training. This effort will focus on developing NASA's capability to conduct IV&V of neural network systems and to provide training to meet the increasing need for IV&V expertise in such systems.

Neural network model for the prediction of PM10 daily concentrations in two sites in the Western Mediterranean.

PubMed

de Gennaro, Gianluigi; Trizio, Livia; Di Gilio, Alessia; Pey, Jorge; Pérez, Noemi; Cusack, Michael; Alastuey, Andrés; Querol, Xavier

2013-10-01

An artificial neural network (ANN) was developed and tested to forecast PM10 daily concentration in two contrasted environments in NE Spain, a regional background site (Montseny), and an urban background site (Barcelona-CSIC), which was highly influenced by vehicular emissions. In order to predict 24-h average PM10 concentrations, the artificial neural network previously developed by Caselli et al. (2009) was improved by using hourly PM concentrations and deterministic factors such as a Saharan dust alert. In particular, the model input data for prediction were the hourly PM10 concentrations 1-day in advance, local meteorological data and information about air masses origin. The forecasted performance indexes for both sites were calculated and they showed better results for the regional background site in Montseny (R(2)=0.86, SI=0.75) than for urban site in Barcelona (R(2)=0.73, SI=0.58), influenced by local and sometimes unexpected sources. Moreover, a sensitivity analysis conducted to understand the importance of the different variables included among the input data, showed that local meteorology and air masses origin are key factors in the model forecasts. This result explains the reason for the improvement of ANN's forecasting performance at the Montseny site with respect to the Barcelona site. Moreover, the artificial neural network developed in this work could prove useful to predict PM10 concentrations, especially, at regional background sites such as those on the Mediterranean Basin which are primarily affected by long-range transports. Hence, the artificial neural network presented here could be a powerful tool for obtaining real time information on air quality status and could aid stakeholders in their development of cost-effective control strategies. © 2013 Elsevier B.V. All rights reserved.

hmmr mediates anterior neural tube closure and morphogenesis in the frog Xenopus.

PubMed

Prager, Angela; Hagenlocher, Cathrin; Ott, Tim; Schambony, Alexandra; Feistel, Kerstin

2017-10-01

Development of the central nervous system requires orchestration of morphogenetic processes which drive elevation and apposition of the neural folds and their fusion into a neural tube. The newly formed tube gives rise to the brain in anterior regions and continues to develop into the spinal cord posteriorly. Conspicuous differences between the anterior and posterior neural tube become visible already during neural tube closure (NTC). Planar cell polarity (PCP)-mediated convergent extension (CE) movements are restricted to the posterior neural plate, i.e. hindbrain and spinal cord, where they propagate neural fold apposition. The lack of CE in the anterior neural plate correlates with a much slower mode of neural fold apposition anteriorly. The morphogenetic processes driving anterior NTC have not been addressed in detail. Here, we report a novel role for the breast cancer susceptibility gene and microtubule (MT) binding protein Hmmr (Hyaluronan-mediated motility receptor, RHAMM) in anterior neurulation and forebrain development in Xenopus laevis. Loss of hmmr function resulted in a lack of telencephalic hemisphere separation, arising from defective roof plate formation, which in turn was caused by impaired neural tissue narrowing. hmmr regulated polarization of neural cells, a function which was dependent on the MT binding domains. hmmr cooperated with the core PCP component vangl2 in regulating cell polarity and neural morphogenesis. Disrupted cell polarization and elongation in hmmr and vangl2 morphants prevented radial intercalation (RI), a cell behavior essential for neural morphogenesis. Our results pinpoint a novel role of hmmr in anterior neural development and support the notion that RI is a major driving force for anterior neurulation and forebrain morphogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction and control of neural responses to pulsatile electrical stimulation

NASA Astrophysics Data System (ADS)

Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

2012-04-01

This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

Novel isoforms of Dlg are fundamental for neuronal development in Drosophila.

PubMed

Mendoza, Carolina; Olguín, Patricio; Lafferte, Gabriela; Thomas, Ulrich; Ebitsch, Susanne; Gundelfinger, Eckart D; Kukuljan, Manuel; Sierralta, Jimena

2003-03-15

Drosophila discs-large (dlg) mutants exhibit multiple developmental abnormalities, including severe defects in neuronal differentiation and synaptic structure and function. These defects have been ascribed to the loss of a single gene product, Dlg-A, a scaffold protein thought to be expressed in many cell types. Here, we describe that additional isoforms arise as a consequence of different transcription start points and alternative splicing of dlg. At least five different dlg gene products are predicted. We identified a subset of dlg-derived cDNAs that include novel exons encoding a peptide homologous to the N terminus of the mammalian protein SAP97/hDLG (S97N). Dlg isoforms containing the S97N domain are expressed at larval neuromuscular junctions and within the CNS of both embryos and larvae but are not detectable in epithelial tissues. Strong hypomorphic dlg alleles exhibit decreased expression of S97N, which may account for neural-specific aspects of the pleiomorphic dlg mutant phenotype. Selective inhibition of the expression of S97N-containing proteins in embryos by double-strand RNA leads to severe defects in neuronal differentiation and axon guidance, without overt perturbations in epithelia. These results indicate that the differential expression of dlg products correlates with distinct functions in non-neural and neural cells. During embryonic development, proteins that include the S97N domain are essential for proper neuronal differentiation and organization, acting through mechanisms that may include the adequate localization of cell fate determinants.

Analysis and classification of normal and pathological skin tissue spectra using neural networks

NASA Astrophysics Data System (ADS)

Bruch, Reinhard F.; Afanasyeva, Natalia I.; Gummuluri, Satyashree

2000-07-01

An innovative spectroscopic diagnostic method has been developed for investigation of different regions of normal human skin tissue, as well as cancerous and precancerous conditions in vivo, ex vivo and in vitro. This new method is a combination of fiber-optical evanescent wave Fourier Transform infrared (FEW-FTIR) spectroscopy and fiber optic techniques using low-loss, highly flexible and nontoxic fiber optical sensors. The FEW-FTIR technique is nondestructive and very sensitive to changes of vibrational spectra in the IR region without heating and staining and thus altering the skin tissue. A special software package was developed for the treatment of the spectra. This package includes a database, programs for data preparation and presentation, and neural networks for classification of disease states. An unsupervised neural competitive learning neural network is implemented for skin cancer diagnosis. In this study, we have investigated and classified skin tissue in the range of 1400 to 1800 cm-1 using these programs. The results of our surface analysis of skin tissue are discussed in terms of molecular structural similarities and differences as well as in terms of different skin states represented by eleven different skin spectra classes.

Classification of neural tumors in laboratory rodents, emphasizing the rat.

PubMed

Weber, Klaus; Garman, Robert H; Germann, Paul-Georg; Hardisty, Jerry F; Krinke, Georg; Millar, Peter; Pardo, Ingrid D

2011-01-01

Neoplasms of the nervous system, whether spontaneous or induced, are infrequent in laboratory rodents and very rare in other laboratory animal species. The morphology of neural tumors depends on the intrinsic functions and properties of the cell type, the interactions between the neoplasm and surrounding normal tissue, and regressive changes. The incidence of neural neoplasms varies with sex, location, and age of tumor onset. Although the onset of spontaneous tumor development cannot be established in routine oncogenicity studies, calculations using the time of diagnosis (day of death) have revealed significant differences in tumor biology among different rat strains. In the central nervous system, granular cell tumors (a meningioma variant), followed by glial tumors, are the most common neoplasms in rats, whereas glial cell tumors are observed most frequently in mice. Central nervous system tumors usually affect the brain rather than the spinal cord. Other than adrenal gland pheochromocytomas, the most common neoplasms of the peripheral nervous system are schwannomas. Neural tumors may develop in the central nervous system and peripheral nervous system from other cell lineages (including extraneural elements like adipose tissue and lymphocytes), but such lesions are very rare in laboratory animals.

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

PubMed Central

Sharifian, Fariba; Heikkinen, Hanna; Vigário, Ricardo

2015-01-01

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

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

PubMed

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

2015-08-01

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals. Copyright © 2015 the American Physiological Society.

Prediction of dissolved oxygen in the Mediterranean Sea along Gaza, Palestine - an artificial neural network approach.

PubMed

Zaqoot, Hossam Adel; Ansari, Abdul Khalique; Unar, Mukhtiar Ali; Khan, Shaukat Hyat

2009-01-01

Artificial Neural Networks (ANNs) are flexible tools which are being used increasingly to predict and forecast water resources variables. The human activities in areas surrounding enclosed and semi-enclosed seas such as the Mediterranean Sea always produce in the long term a strong environmental impact in the form of coastal and marine degradation. The presence of dissolved oxygen is essential for the survival of most organisms in the water bodies. This paper is concerned with the use of ANNs - Multilayer Perceptron (MLP) and Radial Basis Function neural networks for predicting the next fortnight's dissolved oxygen concentrations in the Mediterranean Sea water along Gaza. MLP and Radial Basis Function (RBF) neural networks are trained and developed with reference to five important oceanographic variables including water temperature, wind velocity, turbidity, pH and conductivity. These variables are considered as inputs of the network. The data sets used in this study consist of four years and collected from nine locations along Gaza coast. The network performance has been tested with different data sets and the results show satisfactory performance. Prediction results prove that neural network approach has good adaptability and extensive applicability for modelling the dissolved oxygen in the Mediterranean Sea along Gaza. We hope that the established model will help in assisting the local authorities in developing plans and policies to reduce the pollution along Gaza coastal waters to acceptable levels.

Developing and using expert systems and neural networks in medicine: a review on benefits and challenges.

PubMed

Sheikhtaheri, Abbas; Sadoughi, Farahnaz; Hashemi Dehaghi, Zahra

2014-09-01

Complicacy of clinical decisions justifies utilization of information systems such as artificial intelligence (e.g. expert systems and neural networks) to achieve better decisions, however, application of these systems in the medical domain faces some challenges. We aimed at to review the applications of these systems in the medical domain and discuss about such challenges. Following a brief introduction of expert systems and neural networks by representing few examples, the challenges of these systems in the medical domain are discussed. We found that the applications of expert systems and artificial neural networks have been increased in the medical domain. These systems have shown many advantages such as utilization of experts' knowledge, gaining rare knowledge, more time for assessment of the decision, more consistent decisions, and shorter decision-making process. In spite of all these advantages, there are challenges ahead of developing and using such systems including maintenance, required experts, inputting patients' data into the system, problems for knowledge acquisition, problems in modeling medical knowledge, evaluation and validation of system performance, wrong recommendations and responsibility, limited domains of such systems and necessity of integrating such systems into the routine work flows. We concluded that expert systems and neural networks can be successfully used in medicine; however, there are many concerns and questions to be answered through future studies and discussions.

The murine homeobox gene Msx-3 shows highly restricted expression in the developing neural tube.

PubMed

Shimeld, S M; McKay, I J; Sharpe, P T

1996-04-01

The mouse homeobox-genes Msx-1 and Msx-2 are expressed in several areas of the developing embryo, including the neural tube, neural crest, facial processes and limb buds. Here we report the characterisation of a third mouse Msx gene, which we designate Msx-3. The embryonic expression of Msx-3 was found to differ from that of Msx-1 and -2 in that it was confined to the dorsal neural tube. In embryos with 5-8 somites a segmental pattern of expression was observed in the hindbrain, with rhombomeres 3 and 5 lacking Msx-3 while other rhombomeres expressed Msx-3. This pattern was transient, however, such that in embryos with 18 or more somites expression was continuous throughout the dorsal hindbrain and anterior dorsal spinal cord. Differentiation of dorsal cell types in the neural tube can be induced by addition of members of the Tgf-beta family. Additionally, Msx-1 and -2 have been shown to be activated by addition of the Tgf-beta family member Bmp-4. To determine if Bmp-4 could activate Msx-3, we incubated embryonic hindbrain explants with exogenous Bmp-4. The dorsal expression of Msx-3 was seen to expand into more ventral regions of the neurectoderm in Bmp-4-treated cultures, implying that Bmp-4 may be able to mimic an in vivo signal that induces Msx-3.

Development and application of deep convolutional neural network in target detection

NASA Astrophysics Data System (ADS)

Jiang, Xiaowei; Wang, Chunping; Fu, Qiang

2018-04-01

With the development of big data and algorithms, deep convolution neural networks with more hidden layers have more powerful feature learning and feature expression ability than traditional machine learning methods, making artificial intelligence surpass human level in many fields. This paper first reviews the development and application of deep convolutional neural networks in the field of object detection in recent years, then briefly summarizes and ponders some existing problems in the current research, and the future development of deep convolutional neural network is prospected.

Characterization of the Trunk Neural Crest in the bamboo shark, Chiloscyllium punctatum

PubMed Central

Juarez, Marilyn; Reyes, Michelle; Coleman, Tiffany; Rotenstein, Lisa; Sao, Sothy; Martinez, Darwin; Jones, Matthew; Mackelprang, Rachel; de Bellard, Maria Elena

2013-01-01

The neural crest is a population of mesenchymal cells that after migrating from the neural tube give rise to a structures and cell-types: jaw, part of the peripheral ganglia and melanocytes. Although much is known about neural crest development in jawed vertebrates, a clear picture of trunk neural crest development for elasmobranchs is yet to be developed. Here we present a detailed study of trunk neural crest development in the bamboo shark, Chiloscyllium punctatum. Vital labeling with DiI and in situ hybridization using cloned Sox8 and Sox9 probes demonstrated that trunk neural crest cells follow a pattern similar to the migratory paths already described in zebrafish and amphibians. We found shark trunk neural crest along the rostral side of the somites, the ventromedial pathway, branchial arches, gut, sensory ganglia and nerves. Interestingly, Chiloscyllium punctatum Sox8 and Sox9 sequences aligned with vertebrate SoxE genes, but appeared to be more ancient than the corresponding vertebrate paralogs. The expression of these two SoxE genes in trunk neural crest cells, especially Sox9, matched the Sox10 migratory patterns observed in teleosts. Interestingly, we observed DiI cells and Sox9 labeling along the lateral line, suggesting that in C. punctatum, glial cells in the lateral line are likely of neural crest origin. Though this has been observed in other vertebrates, we are the first to show that the pattern is present in cartilaginous fishes. These findings demonstrate that trunk neural crest cell development in Chiloscyllium punctatum follows the same highly conserved migratory pattern observed in jawed vertebrates PMID:23640803

Shared molecular networks in orofacial and neural tube development.

PubMed

Kousa, Youssef A; Mansour, Tamer A; Seada, Haitham; Matoo, Samaneh; Schutte, Brian C

2017-01-30

Single genetic variants can affect multiple tissues during development. Thus it is possible that disruption of shared gene regulatory networks might underlie syndromic presentations. In this study, we explore this idea through examination of two critical developmental programs that control orofacial and neural tube development and identify shared regulatory factors and networks. Identification of these networks has the potential to yield additional candidate genes for poorly understood developmental disorders and assist in modeling and perhaps managing risk factors to prevent morbidly and mortality. We reviewed the literature to identify genes common between orofacial and neural tube defects and development. We then conducted a bioinformatic analysis to identify shared molecular targets and pathways in the development of these tissues. Finally, we examine publicly available RNA-Seq data to identify which of these genes are expressed in both tissues during development. We identify common regulatory factors in orofacial and neural tube development. Pathway enrichment analysis shows that folate, cancer and hedgehog signaling pathways are shared in neural tube and orofacial development. Developing neural tissues differentially express mouse exencephaly and cleft palate genes, whereas developing orofacial tissues were enriched for both clefting and neural tube defect genes. These data suggest that key developmental factors and pathways are shared between orofacial and neural tube defects. We conclude that it might be most beneficial to focus on common regulatory factors and pathways to better understand pathology and develop preventative measures for these birth defects. Birth Defects Research 109:169-179, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Beyond Fluorescent Proteins: Hybrid and Bioluminescent Indicators for Imaging Neural Activities.

PubMed

Wang, Anqi; Feng, Jiesi; Li, Yulong; Zou, Peng

2018-04-18

Optical biosensors have been invaluable tools in neuroscience research, as they provide the ability to directly visualize neural activity in real time, with high specificity, and with exceptional spatial and temporal resolution. Notably, a majority of these sensors are based on fluorescent protein scaffolds, which offer the ability to target specific cell types or even subcellular compartments. However, fluorescent proteins are intrinsically bulky tags, often insensitive to the environment, and always require excitation light illumination. To address these limitations, there has been a proliferation of alternative sensor scaffolds developed in recent years, including hybrid sensors that combine the advantages of synthetic fluorophores and genetically encoded protein tags, as well as bioluminescent probes. While still in their early stage of development as compared with fluorescent protein-based sensors, these novel probes have offered complementary solutions to interrogate various aspects of neuronal communication, including transmitter release, changes in membrane potential, and the production of second messengers. In this Review, we discuss these important new developments with a particular focus on design strategies.

Increased levels of apoptosis in the prefusion neural folds underlie the craniofacial disorder, Treacher Collins syndrome.

PubMed

Dixon, J; Brakebusch, C; Fässler, R; Dixon, M J

2000-06-12

Treacher Collins syndrome (TCS) is an autosomal dominant disorder of human craniofacial development that results from loss-of-function mutations in the gene TCOF1. Although this gene has been demonstrated to encode the nucleolar phosphoprotein treacle, the developmental mechanism underlying TCS remains elusive, particularly as expression studies have shown that the murine orthologue, Tcof1, is widely expressed. To investigate the molecular pathogenesis of TCS, we replaced exon 1 of Tcof1 with a neomycin-resistance cassette via homologous recombination in embryonic stem cells. Tcof1 heterozygous mice die perinatally as a result of severe craniofacial anomalies that include agenesis of the nasal passages, abnormal development of the maxilla, exencephaly and anophthalmia. These defects arise due to a massive increase in the levels of apoptosis in the prefusion neural folds, which are the site of the highest levels of Tcof1 expression. Our results demonstrate that TCS arises from haploinsufficiency of a protein that plays a crucial role in craniofacial development and indicate that correct dosage of treacle is essential for survival of cephalic neural crest cells.

The Effects of Leptin Replacement on Neural Plasticity

PubMed Central

Paz-Filho, Gilberto J.

2016-01-01

Leptin, an adipokine synthesized and secreted mainly by the adipose tissue, has multiple effects on the regulation of food intake, energy expenditure, and metabolism. Its recently-approved analogue, metreleptin, has been evaluated in clinical trials for the treatment of patients with leptin deficiency due to mutations in the leptin gene, lipodystrophy syndromes, and hypothalamic amenorrhea. In such patients, leptin replacement therapy has led to changes in brain structure and function in intra- and extrahypothalamic areas, including the hippocampus. Furthermore, in one of those patients, improvements in neurocognitive development have been observed. In addition to this evidence linking leptin to neural plasticity and function, observational studies evaluating leptin-sufficient humans have also demonstrated direct correlation between blood leptin levels and brain volume and inverse associations between circulating leptin and risk for the development of dementia. This review summarizes the evidence in the literature on the role of leptin in neural plasticity (in leptin-deficient and in leptin-sufficient individuals) and its effects on synaptic activity, glutamate receptor trafficking, neuronal morphology, neuronal development and survival, and microglial function. PMID:26881138

The Effects of Leptin Replacement on Neural Plasticity.

PubMed

Paz-Filho, Gilberto J

2016-01-01

Leptin, an adipokine synthesized and secreted mainly by the adipose tissue, has multiple effects on the regulation of food intake, energy expenditure, and metabolism. Its recently-approved analogue, metreleptin, has been evaluated in clinical trials for the treatment of patients with leptin deficiency due to mutations in the leptin gene, lipodystrophy syndromes, and hypothalamic amenorrhea. In such patients, leptin replacement therapy has led to changes in brain structure and function in intra- and extrahypothalamic areas, including the hippocampus. Furthermore, in one of those patients, improvements in neurocognitive development have been observed. In addition to this evidence linking leptin to neural plasticity and function, observational studies evaluating leptin-sufficient humans have also demonstrated direct correlation between blood leptin levels and brain volume and inverse associations between circulating leptin and risk for the development of dementia. This review summarizes the evidence in the literature on the role of leptin in neural plasticity (in leptin-deficient and in leptin-sufficient individuals) and its effects on synaptic activity, glutamate receptor trafficking, neuronal morphology, neuronal development and survival, and microglial function.

Development of the posterior neural tube in human embryos.

PubMed

Saitsu, Hirotomo; Yamada, Shigehito; Uwabe, Chigako; Ishibashi, Makoto; Shiota, Kohei

2004-12-01

Development of the posterior neural tube (PNT) in human embryos is a complicated process that involves both primary and secondary neurulation. Because normal development of the PNT is not fully understood, pathogenesis of spinal neural tube defects remains elusive. To clarify the mechanism of PNT development, we histologically examined 20 human embryos around the stage of posterior neuropore closure and found that the developing PNT can be divided into three parts: 1) the most rostral region, which corresponds to the posterior part of the primary neural tube, 2) the junctional region of the primary and secondary neural tubes, and 3) the caudal region, which emerges from the neural cord. In the junctional region, the axially-condensed mesenchyme (AM) intervened between the neural plate/tube and the notochord at the stage of posterior neuropore closure, while the notochord was directly attached to the neural plate/tube in the most rostral region. A single cavity was found to be formed in the AM as the presumptive luminal surface cells were radially aligned in the junctional region prior to the formation of the neural cord. The single cavity was continuous with the central cavity of the primary neural tube. In contrast, multiple or isolated cavities were frequently observed in the caudal region of the PNT. Our observation suggests that the junctional region of the PNT is distinct from other regions in terms of the relationship with the notochord and the mode of cavitation during secondary neurulation.

A 3D human neural cell culture system for modeling Alzheimer’s disease

PubMed Central

Kim, Young Hye; Choi, Se Hoon; D’Avanzo, Carla; Hebisch, Matthias; Sliwinski, Christopher; Bylykbashi, Enjana; Washicosky, Kevin J.; Klee, Justin B.; Brüstle, Oliver; Tanzi, Rudolph E.; Kim, Doo Yeon

2015-01-01

Stem cell technologies have facilitated the development of human cellular disease models that can be used to study pathogenesis and test therapeutic candidates. These models hold promise for complex neurological diseases such as Alzheimer’s disease (AD) because existing animal models have been unable to fully recapitulate all aspects of pathology. We recently reported the characterization of a novel three-dimensional (3D) culture system that exhibits key events in AD pathogenesis, including extracellular aggregation of β-amyloid and accumulation of hyperphosphorylated tau. Here we provide instructions for the generation and analysis of 3D human neural cell cultures, including the production of genetically modified human neural progenitor cells (hNPCs) with familial AD mutations, the differentiation of the hNPCs in a 3D matrix, and the analysis of AD pathogenesis. The 3D culture generation takes 1–2 days. The aggregation of β-amyloid is observed after 6-weeks of differentiation followed by robust tau pathology after 10–14 weeks. PMID:26068894

Classification of ion mobility spectra by functional groups using neural networks

NASA Technical Reports Server (NTRS)

Bell, S.; Nazarov, E.; Wang, Y. F.; Eiceman, G. A.

1999-01-01

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Neural network to diagnose lining condition

NASA Astrophysics Data System (ADS)

Yemelyanov, V. A.; Yemelyanova, N. Y.; Nedelkin, A. A.; Zarudnaya, M. V.

2018-03-01

The paper presents data on the problem of diagnosing the lining condition at the iron and steel works. The authors describe the neural network structure and software that are designed and developed to determine the lining burnout zones. The simulation results of the proposed neural networks are presented. The authors note the low learning and classification errors of the proposed neural networks. To realize the proposed neural network, the specialized software has been developed.

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability

PubMed Central

Barnett, Michael A.; Hartley, Jake; Gomez, Jesse; Stigliani, Anthony; Grill-Spector, Kalanit

2016-01-01

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5–12 years) and adults (ages, 19–34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly. SIGNIFICANCE STATEMENT Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in the brain lead to improved performance. Using fMRI in children and adults, we find that from childhood to adulthood, neural sensitivity to changes in face identity increases in face-selective regions. Critically, subjects' perceptual discriminability among faces is linked to neural sensitivity: participants with higher neural sensitivity in face-selective regions demonstrate higher perceptual discriminability. Thus, our results suggest that developmental increases in face-selective regions' sensitivity to face identity improve perceptual discrimination of faces. These findings significantly advance understanding of the neural mechanisms underlying the development of face perception and have important implications for assessing both typical and atypical development. PMID:27798143

Neural stem cell heterogeneity through time and space in the ventricular-subventricular zone.

PubMed

Rushing, Gabrielle; Ihrie, Rebecca A

2016-08-01

The origin and classification of neural stem cells (NSCs) has been a subject of intense investigation for the past two decades. Efforts to categorize NSCs based on their location, function and expression have established that these cells are a heterogeneous pool in both the embryonic and adult brain. The discovery and additional characterization of adult NSCs has introduced the possibility of using these cells as a source for neuronal and glial replacement following injury or disease. To understand how one could manipulate NSC developmental programs for therapeutic use, additional work is needed to elucidate how NSCs are programmed and how signals during development are interpreted to determine cell fate. This review describes the identification, classification and characterization of NSCs within the large neurogenic niche of the ventricular-subventricular zone (V-SVZ). A literature search was conducted using Pubmed including the keywords "ventricular-subventricular zone," "neural stem cell," "heterogeneity," "identity" and/or "single cell" to find relevant manuscripts to include within the review. A special focus was placed on more recent findings using single-cell level analyses on neural stem cells within their niche(s). This review discusses over 20 research articles detailing findings on V-SVZ NSC heterogeneity, over 25 articles describing fate determinants of NSCs, and focuses on 8 recent publications using distinct single-cell analyses of neural stem cells including flow cytometry and RNA-seq. Additionally, over 60 manuscripts highlighting the markers expressed on cells within the NSC lineage are included in a chart divided by cell type. Investigation of NSC heterogeneity and fate decisions is ongoing. Thus far, much research has been conducted in mice however, findings in human and other mammalian species are also discussed here. Implications of NSC heterogeneity established in the embryo for the properties of NSCs in the adult brain are explored, including how these cells may be redirected after injury or genetic manipulation.

First step in developing SWNT nano-sensor for C17.2 neural stem cells

NASA Astrophysics Data System (ADS)

Ignatova, Tetyana; Pirbhai, Massooma; Chandrasekar, Swetha; Rotkin, Slava V.; Jedlicka, Sabrina

Nanomaterials are widely used for biomedical applications and diagnostics, including as drug and gene delivery agents, imaging objects, and biosensors. As single-wall carbon nanotubes (SWNTs) possess a size similar to intracellular components, including fibrillar proteins and some organelles, the potential for use in a wide variety of intracellular applications is significant. However, implementation of an SWNT based nano-sensor is difficult due to lack of understanding of SWNT-cell interaction on both the cellular and molecular level. In this study, C17.2 neural stem cells have been tested after uptake of SWNTs wrapped with ssDNA over a wide variety of time periods, allowing for broad localization of SWNTs inside of the cells over long time periods. The localization data is being used to develop a predictive model of how, upon uptake of SWNT, the cytoskeleton and other cellular structures of the adherent cells is perturbed.

Modeling Development in Retinal Afferents: Retinotopy, Segregation, and EphrinA/EphA Mutants

PubMed Central

Godfrey, Keith B.; Swindale, Nicholas V.

2014-01-01

During neural development, neurons extend axons to target areas of the brain. Through processes of growth, branching and retraction these axons establish stereotypic patterns of connectivity. In the visual system, these patterns include retinotopic organization and the segregation of individual axons onto different subsets of target neurons based on the eye of origin (ocular dominance) or receptive field type (ON or OFF). Characteristic disruptions to these patterns occur when neural activity or guidance molecule expression is perturbed. In this paper we present a model that explains how these developmental patterns might emerge as a result of the coordinated growth and retraction of individual axons and synapses responding to position-specific markers, trophic factors and spontaneous neural activity. This model derives from one presented earlier (Godfrey et al., 2009) but which is here extended to account for a wider range of phenomena than previously described. These include ocular dominance and ON-OFF segregation and the results of altered ephrinA and EphA guidance molecule expression. The model takes into account molecular guidance factors, realistic patterns of spontaneous retinal wave activity, trophic molecules, homeostatic mechanisms, axon branching and retraction rules and intra-axonal signaling mechanisms that contribute to the survival of nearby synapses on an axon. We show that, collectively, these mechanisms can account for a wider range of phenomena than previous models of retino-tectal development. PMID:25122119

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team is to develop and flight-test control systems that use neural network technology to optimize the performance of the aircraft under nominal conditions as well as stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to the baseline aerodynamic derivatives in flight. This set of open-loop flight tests was performed in preparation for a future phase of flights in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed a pitch frequency sweep and an automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. An examination of flight data shows that addition of the flight-identified aerodynamic derivative increments into the simulation improved the pitch handling qualities of the aircraft.

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

PubMed

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

2018-02-01

Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Cellular basis of neuroepithelial bending during mouse spinal neural tube closure

PubMed Central

McShane, Suzanne G.; Molè, Matteo A.; Savery, Dawn; Greene, Nicholas D. E; Tam, Patrick P.L.; Copp, Andrew J.

2015-01-01

Summary Bending of the neural plate at paired dorsolateral hinge points (DLHPs) is required for neural tube closure in the spinal region of the mouse embryo. As a step towards understanding the morphogenetic mechanism of DLHP development, we examined variations in neural plate cellular architecture and proliferation during closure. Neuroepithelial cells within the median hinge point (MHP) contain nuclei that are mainly basally located and undergo relatively slow proliferation, with a 7 h cell cycle length. In contrast, cells in the dorsolateral neuroepithelium, including the DLHP, exhibit nuclei distributed throughout the apico-basal axis and undergo rapid proliferation, with a 4 h cell cycle length. As the neural folds elevate, cell numbers increase to a greater extent in the dorsolateral neural plate that contacts the surface ectoderm, compared with the more ventromedial neural plate where cells contact paraxial mesoderm and notochord. This marked increase in dorsolateral cell number cannot be accounted for solely on the basis of enhanced cell proliferation in this region. We hypothesised that neuroepithelial cells may translocate in a ventral-to-dorsal direction as DLHP formation occurs, and this was confirmed by vital cell labelling in cultured embryos. The translocation of cells into the neural fold, together with its more rapid cell proliferation, leads to an increase in cell density dorsolaterally compared with the more ventromedial neural plate. These findings suggest a model in which DLHP formation may proceed through ‘buckling’ of the neuroepithelium at a dorso-ventral boundary marked by a change in cell-packing density. PMID:26079577

Angiogenesis in the Developing Spinal Cord: Blood Vessel Exclusion from Neural Progenitor Region Is Mediated by VEGF and Its Antagonists

PubMed Central

Takahashi, Teruaki; Takase, Yuta; Yoshino, Takashi; Saito, Daisuke; Tadokoro, Ryosuke; Takahashi, Yoshiko

2015-01-01

Blood vessels in the central nervous system supply a considerable amount of oxygen via intricate vascular networks. We studied how the initial vasculature of the spinal cord is formed in avian (chicken and quail) embryos. Vascular formation in the spinal cord starts by the ingression of intra-neural vascular plexus (INVP) from the peri-neural vascular plexus (PNVP) that envelops the neural tube. At the ventral region of the PNVP, the INVP grows dorsally in the neural tube, and we observed that these vessels followed the defined path at the interface between the medially positioned and undifferentiated neural progenitor zone and the laterally positioned differentiated zone. When the interface between these two zones was experimentally displaced, INVP faithfully followed a newly formed interface, suggesting that the growth path of the INVP is determined by surrounding neural cells. The progenitor zone expressed mRNA of vascular endothelial growth factor-A whereas its receptor VEGFR2 and FLT-1 (VEGFR1), a decoy for VEGF, were expressed in INVP. By manipulating the neural tube with either VEGF or the soluble form of FLT-1, we found that INVP grew in a VEGF-dependent manner, where VEGF signals appear to be fine-tuned by counteractions with anti-angiogenic activities including FLT-1 and possibly semaphorins. These results suggest that the stereotypic patterning of early INVP is achieved by interactions between these vessels and their surrounding neural cells, where VEGF and its antagonists play important roles. PMID:25585380

A Novel Occulta-Type Spina Bifida Mediated by Murine Double Heterozygotes EphA2 and EphA4 Receptor Tyrosine Kinases.

PubMed

Abdullah, Nor Linda; Mohd-Zin, Siti W; Ahmad-Annuar, Azlina; Abdul-Aziz, Noraishah M

2017-01-01

Members of the Eph receptor tyrosine kinase have previously been implicated in cranial neural tube development. Failure of neural tube closure leads to the devastating conditions known as anencephaly and spina bifida. EphA2 and EphA4 are expressed at the tips of the closing spinal neural folds prior and during neural tube closure. We investigated the possible role of murine EphA2 and EphA4 during the last step of primary neural tube closure, which is adhesion and fusion. The individual mouse knockouts of EphA2 and EphA4 per se do not exhibit neural tube defects (NTDs). The embryos generated by the crossing of double heterozygotes Epha2 tm1Jrui/+ Epha4 rb-2J/+ displayed NTDs with a wide degree of severity including close exencephaly and close spina bifida (spina bifida occulta). Interestingly, mutants displaying NTDs had skin covering the underlying lesion. The tissue sections revealed the elevated neural folds had not adhered and fused. The phenotypes seen in Epha2 tm1Jrui/+ Epha4 rb-2J/+ double heterozygous embryos suggest both genes play a compensatory role with each other in the adhesion and fusion of the neural tube. In this study, there exists a >50% penetrance of NTDs in the mouse mutants, which genetically have a single allele each of EphA2 and EphA4 absent.

A Novel Occulta-Type Spina Bifida Mediated by Murine Double Heterozygotes EphA2 and EphA4 Receptor Tyrosine Kinases

PubMed Central

Abdullah, Nor Linda; Mohd-Zin, Siti W.; Ahmad-Annuar, Azlina; Abdul-Aziz, Noraishah M.

2017-01-01

Members of the Eph receptor tyrosine kinase have previously been implicated in cranial neural tube development. Failure of neural tube closure leads to the devastating conditions known as anencephaly and spina bifida. EphA2 and EphA4 are expressed at the tips of the closing spinal neural folds prior and during neural tube closure. We investigated the possible role of murine EphA2 and EphA4 during the last step of primary neural tube closure, which is adhesion and fusion. The individual mouse knockouts of EphA2 and EphA4 per se do not exhibit neural tube defects (NTDs). The embryos generated by the crossing of double heterozygotes Epha2tm1Jrui/+Epha4rb-2J/+ displayed NTDs with a wide degree of severity including close exencephaly and close spina bifida (spina bifida occulta). Interestingly, mutants displaying NTDs had skin covering the underlying lesion. The tissue sections revealed the elevated neural folds had not adhered and fused. The phenotypes seen in Epha2tm1Jrui/+Epha4rb-2J/+ double heterozygous embryos suggest both genes play a compensatory role with each other in the adhesion and fusion of the neural tube. In this study, there exists a >50% penetrance of NTDs in the mouse mutants, which genetically have a single allele each of EphA2 and EphA4 absent. PMID:29312933

Histone deacetylase 1 and 2 are essential for murine neural crest proliferation, pharyngeal arch development, and craniofacial morphogenesis.

PubMed

Milstone, Zachary J; Lawson, Grace; Trivedi, Chinmay M

2017-12-01

Craniofacial anomalies involve defective pharyngeal arch development and neural crest function. Copy number variation at 1p35, containing histone deacetylase 1 (Hdac1), or 6q21-22, containing Hdac2, are implicated in patients with craniofacial defects, suggesting an important role in guiding neural crest development. However, the roles of Hdac1 and Hdac2 within neural crest cells remain unknown. The neural crest and its derivatives express both Hdac1 and Hdac2 during early murine development. Ablation of Hdac1 and Hdac2 within murine neural crest progenitor cells cause severe hemorrhage, atrophic pharyngeal arches, defective head morphogenesis, and complete embryonic lethality. Embryos lacking Hdac1 and Hdac2 in the neural crest exhibit decreased proliferation and increased apoptosis in both the neural tube and the first pharyngeal arch. Mechanistically, loss of Hdac1 and Hdac2 upregulates cyclin-dependent kinase inhibitors Cdkn1a, Cdkn1b, Cdkn1c, Cdkn2b, Cdkn2c, and Tp53 within the first pharyngeal arch. Our results show that Hdac1 and Hdac2 function redundantly within the neural crest to regulate proliferation and the development of the pharyngeal arches by means of repression of cyclin-dependent kinase inhibitors. Developmental Dynamics 246:1015-1026, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location.

PubMed

Crago, Patrick E; Makowski, Nathaniel S

2014-10-01

Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.

Toward a Unified Sub-symbolic Computational Theory of Cognition

PubMed Central

Butz, Martin V.

2016-01-01

This paper proposes how various disciplinary theories of cognition may be combined into a unifying, sub-symbolic, computational theory of cognition. The following theories are considered for integration: psychological theories, including the theory of event coding, event segmentation theory, the theory of anticipatory behavioral control, and concept development; artificial intelligence and machine learning theories, including reinforcement learning and generative artificial neural networks; and theories from theoretical and computational neuroscience, including predictive coding and free energy-based inference. In the light of such a potential unification, it is discussed how abstract cognitive, conceptualized knowledge and understanding may be learned from actively gathered sensorimotor experiences. The unification rests on the free energy-based inference principle, which essentially implies that the brain builds a predictive, generative model of its environment. Neural activity-oriented inference causes the continuous adaptation of the currently active predictive encodings. Neural structure-oriented inference causes the longer term adaptation of the developing generative model as a whole. Finally, active inference strives for maintaining internal homeostasis, causing goal-directed motor behavior. To learn abstract, hierarchical encodings, however, it is proposed that free energy-based inference needs to be enhanced with structural priors, which bias cognitive development toward the formation of particular, behaviorally suitable encoding structures. As a result, it is hypothesized how abstract concepts can develop from, and thus how they are structured by and grounded in, sensorimotor experiences. Moreover, it is sketched-out how symbol-like thought can be generated by a temporarily active set of predictive encodings, which constitute a distributed neural attractor in the form of an interactive free-energy minimum. The activated, interactive network attractor essentially characterizes the semantics of a concept or a concept composition, such as an actual or imagined situation in our environment. Temporal successions of attractors then encode unfolding semantics, which may be generated by a behavioral or mental interaction with an actual or imagined situation in our environment. Implications, further predictions, possible verification, and falsifications, as well as potential enhancements into a fully spelled-out unified theory of cognition are discussed at the end of the paper. PMID:27445895

Regeneration and maintenance of the planarian midline is regulated by a slit orthologue.

PubMed

Cebrià, Francesc; Guo, Tingxia; Jopek, Jessica; Newmark, Phillip A

2007-07-15

Several families of evolutionarily conserved axon guidance cues orchestrate the precise wiring of the nervous system during embryonic development. The remarkable plasticity of freshwater planarians provides the opportunity to study these molecules in the context of neural regeneration and maintenance. Here we characterize a homologue of the Slit family of guidance cues from the planarian Schmidtea mediterranea. Smed-slit is expressed along the planarian midline, in both dorsal and ventral domains. RNA interference (RNAi) targeting Smed-slit results in the collapse of many newly regenerated tissues at the midline; these include the cephalic ganglia, ventral nerve cords, photoreceptors, and the posterior digestive system. Surprisingly, Smed-slit RNAi knockdown animals also develop morphologically distinguishable, ectopic neural structures near the midline in uninjured regions of intact and regenerating planarians. These results suggest that Smed-slit acts not only as a repulsive cue required for proper midline formation during regeneration but that it may also act to regulate the behavior of neural precursors at the midline in intact planarians.

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models

PubMed Central

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development. PMID:26483621

Development of social skills in children: neural and behavioral evidence for the elaboration of cognitive models.

PubMed

Soto-Icaza, Patricia; Aboitiz, Francisco; Billeke, Pablo

2015-01-01

Social skills refer to a wide group of abilities that allow us to interact and communicate with others. Children learn how to solve social situations by predicting and understanding other's behaviors. The way in which humans learn to interact successfully with others encompasses a complex interaction between neural, behavioral, and environmental elements. These have a role in the accomplishment of positive developmental outcomes, including peer acceptance, academic achievement, and mental health. All these social abilities depend on widespread brain networks that are recently being studied by neuroscience. In this paper, we will first review the studies on this topic, aiming to clarify the behavioral and neural mechanisms related to the acquisition of social skills during infancy and their appearance in time. Second, we will briefly describe how developmental diseases like Autism Spectrum Disorders (ASD) can inform about the neurobiological mechanisms of social skills. We finally sketch a general framework for the elaboration of cognitive models in order to facilitate the comprehension of human social development.

Role of erythropoietin in the brain

PubMed Central

Noguchi, Constance Tom; Asavaritikrai, Pundit; Teng, Ruifeng; Jia, Yi

2007-01-01

Multi-tissue erythropoietin receptor (EPO-R) expression provides for erythropoietin (EPO) activity beyond its known regulation of red blood cell production. This review highlights the role of EPO and EPO-R in brain development and neuroprotection. EPO-R brain expression includes neural progenitor cells (NPC), neurons, glial cells and endothelial cells. EPO is produced in brain in a hypoxia sensitive manner, stimulates NPC proliferation and differentiation, and neuron survival, and contributes to ischemic preconditioning. Mice lacking EPO or EPO-R exhibit increased neural cell apoptosis during development before embryonic death due to severe anemia. EPO administration provides neural protection in animal models of brain ischemia and trauma, reducing the extent of injury and damage. EPO stimulation of endothelial cells contributes to neuroprotection and is of particular importance since only low levels of EPO appear to cross the blood-brain barrier when administered at high dose intravenously. The therapeutic potential of EPO for brain ischemia/trauma and neurodegenerative diseases has shown promise in early clinical trial and awaits further validation. PMID:17482474

Cox-nnet: An artificial neural network method for prognosis prediction of high-throughput omics data

PubMed Central

Ching, Travers; Zhu, Xun

2018-01-01

Artificial neural networks (ANN) are computing architectures with many interconnections of simple neural-inspired computing elements, and have been applied to biomedical fields such as imaging analysis and diagnosis. We have developed a new ANN framework called Cox-nnet to predict patient prognosis from high throughput transcriptomics data. In 10 TCGA RNA-Seq data sets, Cox-nnet achieves the same or better predictive accuracy compared to other methods, including Cox-proportional hazards regression (with LASSO, ridge, and mimimax concave penalty), Random Forests Survival and CoxBoost. Cox-nnet also reveals richer biological information, at both the pathway and gene levels. The outputs from the hidden layer node provide an alternative approach for survival-sensitive dimension reduction. In summary, we have developed a new method for accurate and efficient prognosis prediction on high throughput data, with functional biological insights. The source code is freely available at https://github.com/lanagarmire/cox-nnet. PMID:29634719

The let-7 microRNA target gene, Mlin41/Trim71 is required for mouse embryonic survival and neural tube closure

PubMed Central

Schulman, Betsy R. Maller; Liang, Xianping; Stahlhut, Carlos; DelConte, Casey; Stefani, Giovanni; Slack, Frank J.

2010-01-01

In the nematode Caenorhabditis elegans, the let-7 microRNA (miRNA) controls the timing of key developmental events and terminal differentiation in part by directly regulating lin-41. C. elegans lin-41 mutants display precocious cell cycle exit and terminal differentiation of epidermal skin cells. lin-41 orthologues are found in more complex organisms including both mice and humans, but their roles are not known. We generated Mlin41 mouse mutants to ascertain a functional role for Mlin41. Strong loss of function Mlin41 gene-trap mutants demonstrated a striking neural tube closure defect during development, and embryonic lethality. Like C. elegans lin-41, Mlin41 also appears to be regulated by the let-7 and mir-125 miRNAs. Since Mlin41 is required for neural tube closure and survival it points to human lin-41 (HLIN41/TRIM71) as a potential human development and disease gene. PMID:19098426

Automatic comparison of striation marks and automatic classification of shoe prints

NASA Astrophysics Data System (ADS)

Geradts, Zeno J.; Keijzer, Jan; Keereweer, Isaac

1995-09-01

A database for toolmarks (named TRAX) and a database for footwear outsole designs (named REBEZO) have been developed on a PC. The databases are filled with video-images and administrative data about the toolmarks and the footwear designs. An algorithm for the automatic comparison of the digitized striation patterns has been developed for TRAX. The algorithm appears to work well for deep and complete striation marks and will be implemented in TRAX. For REBEZO some efforts have been made to the automatic classification of outsole patterns. The algorithm first segments the shoeprofile. Fourier-features are selected for the separate elements and are classified with a neural network. In future developments information on invariant moments of the shape and rotation angle will be included in the neural network.

Development of drug-loaded polymer microcapsules for treatment of epilepsy.

PubMed

Chen, Yu; Gu, Qi; Yue, Zhilian; Crook, Jeremy M; Moulton, Simon E; Cook, Mark J; Wallace, Gordon G

2017-09-26

Despite significant progress in developing new drugs for seizure control, epilepsy still affects 1% of the global population and is drug-resistant in more than 30% of cases. To improve the therapeutic efficacy of epilepsy medication, a promising approach is to deliver anti-epilepsy drugs directly to affected brain areas using local drug delivery systems. The drug delivery systems must meet a number of criteria, including high drug loading efficiency, biodegradability, neuro-cytocompatibility and predictable drug release profiles. Here we report the development of fibre- and sphere-based microcapsules that exhibit controllable uniform morphologies and drug release profiles as predicted by mathematical modelling. Importantly, both forms of fabricated microcapsules are compatible with human brain derived neural stem cells and differentiated neurons and neuroglia, indicating clinical compliance for neural implantation and therapeutic drug delivery.

Understanding the Role of Nutrition in the Brain & Behavioral Development of Toddlers and Preschool Children: Identifying and Overcoming Methodological Barriers

PubMed Central

Rosales, Francisco J.; Reznick, J. Steven; Zeisel, Steven H.

2009-01-01

The pre-school years (i.e., 1–5 years of age) is a time of rapid and dramatic postnatal brain development, i.e., neural plasticity, and of fundamental acquisition of cognitive development i.e., working memory, attention and inhibitory control. Also, it is a time of transition from a direct maternal mediation/selection of diet-based nutrition to food selection that is more based on self-selection and self-gratification. However, there have been fewer published studies in pre-school children than in infants or school-aged children that examined the role of nutrition in brain/mental development (i.e., 125 studies vs. 232 and 303 studies, respectively during the last 28 years, Figure 1). This may arise because of age-related variability, in terms of individual differences in temperament, linguistic ability, and patterns of neural activity that may affect assessment of neural and cognitive development in pre-school children. In this review, we suggest several approaches for assessing brain function in children that can be refined. It would be desirable if the discipline developed some common elements to be included in future studies of diet and brain function, with the idea that they would complement more targeted measures based on time of exposure and understanding of data from animal models. Underlining this approach is the concepts of “window of sensitivity” during which nutrients may affect postnatal neural development: investigators and expert panels need to specifically look for region-specific changes and do so with understanding of the likely time window during which the nutrient was, or was not available. (244 words) PMID:19761650

[Voxel-Based Morphometry in Autism Spectrum Disorder].

PubMed

Yamasue, Hidenori

2017-05-01

Autism spectrum disorder shows deficits in social communication and interaction including nonverbal communicative behaviors (e.g., eye contact, gestures, voice prosody, and facial expressions) and restricted and repetitive behaviors as its core symptoms. These core symptoms are emerged as an atypical behavioral development in toddlers with the disorder. Atypical neural development is considered to be a neural underpinning of such behaviorally atypical development. A number of studies using voxel-based morphometry have already been conducted to compare regional brain volumes between individuals with autism spectrum disorder and those with typical development. Furthermore, more than ten papers employing meta-analyses of the comparisons using voxel based morphometry between individuals with autism spectrum disorder and those with typical development have already been published. The current review paper adds some brief discussions about potential factors contributing to the inconsistency observed in the previous findings such as difficulty in controlling the confounding effects of different developmental phases among study participants.

Neural crest contribution to lingual mesenchyme, epithelium and developing taste papillae and taste buds

PubMed Central

Liu, Hong-Xiang; Komatsu, Yoshihiro; Mishina, Yuji; Mistretta, Charlotte M.

2012-01-01

The epithelium of mammalian tongue hosts most of the taste buds that transduce gustatory stimuli into neural signals. In the field of taste biology, taste bud cells have been described as arising from “local epithelium”, in distinction from many other receptor organs that are derived from neurogenic ectoderm including neural crest (NC). In fact, contribution of NC to both epithelium and mesenchyme in the developing tongue is not fully understood. In the present study we used two independent, well-characterized mouse lines, Wnt1-Cre and P0-Cre that express Cre recombinase in a NC-specific manner, in combination with two Cre reporter mouse lines, R26R and ZEG, and demonstrate a contribution of NC-derived cells to both tongue mesenchyme and epithelium including taste papillae and taste buds. In tongue mesenchyme, distribution of NC-derived cells is in close association with taste papillae. In tongue epithelium, labeled cells are observed in an initial scattered distribution and progress to a clustered pattern between papillae, and within papillae and early taste buds. This provides evidence for a contribution of NC to lingual epithelium. Together with previous reports for the origin of taste bud cells from local epithelium in postnatal mouse, we propose that NC cells migrate into and reside in the epithelium of the tongue primordium at an early embryonic stage, acquire epithelial cell phenotypes, and undergo cell proliferation and differentiation that is involved in the development of taste papillae and taste buds. Our findings lead to a new concept about derivation of taste bud cells that include a NC origin. PMID:22659543

Time-lapse imaging of neural development: zebrafish lead the way into the fourth dimension.

PubMed

Rieger, Sandra; Wang, Fang; Sagasti, Alvaro

2011-07-01

Time-lapse imaging is often the only way to appreciate fully the many dynamic cell movements critical to neural development. Zebrafish possess many advantages that make them the best vertebrate model organism for live imaging of dynamic development events. This review will discuss technical considerations of time-lapse imaging experiments in zebrafish, describe selected examples of imaging studies in zebrafish that revealed new features or principles of neural development, and consider the promise and challenges of future time-lapse studies of neural development in zebrafish embryos and adults. Copyright © 2011 Wiley-Liss, Inc.

The Roles and Regulation of Polycomb Complexes in Neural Development

PubMed Central

Corley, Matthew; Kroll, Kristen L.

2014-01-01

In the developing mammalian nervous system, common progenitors integrate both cell extrinsic and intrinsic regulatory programs to produce distinct neuronal and glial cell types as development proceeds. This spatiotemporal restriction of neural progenitor differentiation is enforced, in part, by the dynamic reorganization of chromatin into repressive domains by Polycomb Repressive Complexes, effectively limiting the expression of fate-determining genes. Here, we review distinct roles that the Polycomb Repressive Complexes play during neurogenesis and gliogenesis, while also highlighting recent work describing the molecular mechanisms that govern their dynamic activity in neural development. Further investigation of how Polycomb complexes are regulated in neural development will enable more precise manipulation of neural progenitor differentiation, facilitating the efficient generation of specific neuronal and glial cell types for many biological applications. PMID:25367430

Reducing neural network training time with parallel processing

NASA Technical Reports Server (NTRS)

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

1995-01-01

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

Mechanisms of Long Non-Coding RNAs in the Assembly and Plasticity of Neural Circuitry.

PubMed

Wang, Andi; Wang, Junbao; Liu, Ying; Zhou, Yan

2017-01-01

The mechanisms underlying development processes and functional dynamics of neural circuits are far from understood. Long non-coding RNAs (lncRNAs) have emerged as essential players in defining identities of neural cells, and in modulating neural activities. In this review, we summarized latest advances concerning roles and mechanisms of lncRNAs in assembly, maintenance and plasticity of neural circuitry, as well as lncRNAs' implications in neurological disorders. We also discussed technical advances and challenges in studying functions and mechanisms of lncRNAs in neural circuitry. Finally, we proposed that lncRNA studies would advance our understanding on how neural circuits develop and function in physiology and disease conditions.

Fuzzy-neural control of an aircraft tracking camera platform

NASA Technical Reports Server (NTRS)

Mcgrath, Dennis

1994-01-01

A fuzzy-neural control system simulation was developed for the control of a camera platform used to observe aircraft on final approach to an aircraft carrier. The fuzzy-neural approach to control combines the structure of a fuzzy knowledge base with a supervised neural network's ability to adapt and improve. The performance characteristics of this hybrid system were compared to those of a fuzzy system and a neural network system developed independently to determine if the fusion of these two technologies offers any advantage over the use of one or the other. The results of this study indicate that the fuzzy-neural approach to control offers some advantages over either fuzzy or neural control alone.

An ovine model of cerebral catheter venography for implantation of an endovascular neural interface.

PubMed

Oxley, Thomas James; Opie, Nicholas Lachlan; Rind, Gil Simon; Liyanage, Kishan; John, Sam Emmanuel; Ronayne, Stephen; McDonald, Alan James; Dornom, Anthony; Lovell, Timothy John Haynes; Mitchell, Peter John; Bennett, Iwan; Bauquier, Sebastien; Warne, Leon Norris; Steward, Chris; Grayden, David Bruce; Desmond, Patricia; Davis, Stephen M; O'Brien, Terence John; May, Clive N

2018-04-01

OBJECTIVE Neural interface technology may enable the development of novel therapies to treat neurological conditions, including motor prostheses for spinal cord injury. Intracranial neural interfaces currently require a craniotomy to achieve implantation and may result in chronic tissue inflammation. Novel approaches are required that achieve less invasive implantation methods while maintaining high spatial resolution. An endovascular stent electrode array avoids direct brain trauma and is able to record electrocorticography in local cortical tissue from within the venous vasculature. The motor area in sheep runs in a parasagittal plane immediately adjacent to the superior sagittal sinus (SSS). The authors aimed to develop a sheep model of cerebral venography that would enable validation of an endovascular neural interface. METHODS Cerebral catheter venography was performed in 39 consecutive sheep. Contrast-enhanced MRI of the brain was performed on 13 animals. Multiple telescoping coaxial catheter systems were assessed to determine the largest wide-bore delivery catheter that could be delivered into the anterior SSS. Measurements of SSS diameter and distance from the motor area were taken. The location of the motor area was determined in relation to lateral and superior projections of digital subtraction venography images and confirmed on MRI. RESULTS The venous pathway from the common jugular vein (7.4 mm) to the anterior SSS (1.2 mm) was technically challenging to selectively catheterize. The SSS coursed immediately adjacent to the motor cortex (< 1 mm) for a length of 40 mm, or the anterior half of the SSS. Attempted access with 5-Fr and 6-Fr delivery catheters was associated with longer procedure times and higher complication rates. A 4-Fr catheter (internal lumen diameter 1.1 mm) was successful in accessing the SSS in 100% of cases with no associated complications. Complications included procedure-related venous dissection in two major areas: the torcular herophili, and the anterior formation of the SSS. The bifurcation of the cruciate sulcal veins with the SSS was a reliable predictor of the commencement of the motor area. CONCLUSIONS The ovine model for cerebral catheter venography has generalizability to the human cerebral venous system in relation to motor cortex location. This novel model may facilitate the development of the novel field of endovascular neural interfaces that may include preclinical investigations for cortical recording applications such as paralysis and epilepsy, as well as other potential applications in neuromodulation.

Concise review: Pax6 transcription factor contributes to both embryonic and adult neurogenesis as a multifunctional regulator.

PubMed

Osumi, Noriko; Shinohara, Hiroshi; Numayama-Tsuruta, Keiko; Maekawa, Motoko

2008-07-01

Pax6 is a highly conserved transcription factor among vertebrates and is important in various developmental processes in the central nervous system (CNS), including patterning of the neural tube, migration of neurons, and formation of neural circuits. In this review, we focus on the role of Pax6 in embryonic and postnatal neurogenesis, namely, production of new neurons from neural stem/progenitor cells, because Pax6 is intensely expressed in these cells from the initial stage of CNS development and in neurogenic niches (the subgranular zone of the hippocampal dentate gyrus and the subventricular zone of the lateral ventricle) throughout life. Pax6 is a multifunctional player regulating proliferation and differentiation through the control of expression of different downstream molecules in a highly context-dependent manner.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

Robo signaling regulates the production of cranial neural crest cells.

PubMed

Li, Yan; Zhang, Xiao-Tan; Wang, Xiao-Yu; Wang, Guang; Chuai, Manli; Münsterberg, Andrea; Yang, Xuesong

2017-12-01

Slit/Robo signaling plays an important role in the guidance of developing neurons in developing embryos. However, it remains obscure whether and how Slit/Robo signaling is involved in the production of cranial neural crest cells. In this study, we examined Robo1 deficient mice to reveal developmental defects of mouse cranial frontal and parietal bones, which are derivatives of cranial neural crest cells. Therefore, we determined the production of HNK1 + cranial neural crest cells in early chick embryo development after knock-down (KD) of Robo1 expression. Detection of markers for pre-migratory and migratory neural crest cells, PAX7 and AP-2α, showed that production of both was affected by Robo1 KD. In addition, we found that the transcription factor slug is responsible for the aberrant delamination/EMT of cranial neural crest cells induced by Robo1 KD, which also led to elevated expression of E- and N-Cadherin. N-Cadherin expression was enhanced when blocking FGF signaling with dominant-negative FGFR1 in half of the neural tube. Taken together, we show that Slit/Robo signaling influences the delamination/EMT of cranial neural crest cells, which is required for cranial bone development. Copyright © 2017. Published by Elsevier Inc.

The relationship of neurogenesis and growth of brain regions to song learning.

PubMed

Kirn, John R

2010-10-01

Song learning, maintenance and production require coordinated activity across multiple auditory, sensory-motor, and neuromuscular structures. Telencephalic components of the sensory-motor circuitry are unique to avian species that engage in song learning. The song system shows protracted development that begins prior to hatching but continues well into adulthood. The staggered developmental timetable for construction of the song system provides clues of subsystems involved in specific stages of song learning and maintenance. Progressive events, including neurogenesis and song system growth, as well as regressive events such as apoptosis and synapse elimination, occur during periods of song learning and the transitions between variable and stereotyped song during both development and adulthood. There is clear evidence that gonadal steroids influence the development of song attributes and shape the underlying neural circuitry. Some aspects of song system development are influenced by sensory, motor and social experience, while other aspects of neural development appear to be experience-independent. Although there are species differences in the extent to which song learning continues into adulthood, growing evidence suggests that despite differences in learning trajectories, adult refinement of song motor control and song maintenance can require remarkable behavioral and neural flexibility reminiscent of sensory-motor learning. Copyright © 2009 Elsevier Inc. All rights reserved.

Derivation and Expansion Using Only Small Molecules of Human Neural Progenitors for Neurodegenerative Disease Modeling

PubMed Central

Reinhardt, Peter; Glatza, Michael; Hemmer, Kathrin; Tsytsyura, Yaroslav; Thiel, Cora S.; Höing, Susanne; Moritz, Sören; Parga, Juan A.; Wagner, Lydia; Bruder, Jan M.; Wu, Guangming; Schmid, Benjamin; Röpke, Albrecht; Klingauf, Jürgen; Schwamborn, Jens C.; Gasser, Thomas; Schöler, Hans R.; Sterneckert, Jared

2013-01-01

Phenotypic drug discovery requires billions of cells for high-throughput screening (HTS) campaigns. Because up to several million different small molecules will be tested in a single HTS campaign, even small variability within the cell populations for screening could easily invalidate an entire campaign. Neurodegenerative assays are particularly challenging because neurons are post-mitotic and cannot be expanded for implementation in HTS. Therefore, HTS for neuroprotective compounds requires a cell type that is robustly expandable and able to differentiate into all of the neuronal subtypes involved in disease pathogenesis. Here, we report the derivation and propagation using only small molecules of human neural progenitor cells (small molecule neural precursor cells; smNPCs). smNPCs are robust, exhibit immortal expansion, and do not require cumbersome manual culture and selection steps. We demonstrate that smNPCs have the potential to clonally and efficiently differentiate into neural tube lineages, including motor neurons (MNs) and midbrain dopaminergic neurons (mDANs) as well as neural crest lineages, including peripheral neurons and mesenchymal cells. These properties are so far only matched by pluripotent stem cells. Finally, to demonstrate the usefulness of smNPCs we show that mDANs differentiated from smNPCs with LRRK2 G2019S are more susceptible to apoptosis in the presence of oxidative stress compared to wild-type. Therefore, smNPCs are a powerful biological tool with properties that are optimal for large-scale disease modeling, phenotypic screening, and studies of early human development. PMID:23533608

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation

PubMed Central

Sherfey, Jason S.; Soplata, Austin E.; Ardid, Salva; Roberts, Erik A.; Stanley, David A.; Pittman-Polletta, Benjamin R.; Kopell, Nancy J.

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community. PMID:29599715

DynaSim: A MATLAB Toolbox for Neural Modeling and Simulation.

PubMed

Sherfey, Jason S; Soplata, Austin E; Ardid, Salva; Roberts, Erik A; Stanley, David A; Pittman-Polletta, Benjamin R; Kopell, Nancy J

2018-01-01

DynaSim is an open-source MATLAB/GNU Octave toolbox for rapid prototyping of neural models and batch simulation management. It is designed to speed up and simplify the process of generating, sharing, and exploring network models of neurons with one or more compartments. Models can be specified by equations directly (similar to XPP or the Brian simulator) or by lists of predefined or custom model components. The higher-level specification supports arbitrarily complex population models and networks of interconnected populations. DynaSim also includes a large set of features that simplify exploring model dynamics over parameter spaces, running simulations in parallel using both multicore processors and high-performance computer clusters, and analyzing and plotting large numbers of simulated data sets in parallel. It also includes a graphical user interface (DynaSim GUI) that supports full functionality without requiring user programming. The software has been implemented in MATLAB to enable advanced neural modeling using MATLAB, given its popularity and a growing interest in modeling neural systems. The design of DynaSim incorporates a novel schema for model specification to facilitate future interoperability with other specifications (e.g., NeuroML, SBML), simulators (e.g., NEURON, Brian, NEST), and web-based applications (e.g., Geppetto) outside MATLAB. DynaSim is freely available at http://dynasimtoolbox.org. This tool promises to reduce barriers for investigating dynamics in large neural models, facilitate collaborative modeling, and complement other tools being developed in the neuroinformatics community.

Neural responses to maternal criticism in healthy youth

PubMed Central

Siegle, Greg J.; Dahl, Ronald E.; Hooley, Jill M.; Silk, Jennifer S.

2015-01-01

Parental criticism can have positive and negative effects on children’s and adolescents’ behavior; yet, it is unclear how youth react to, understand and process parental criticism. We proposed that youth would engage three sets of neural processes in response to parental criticism including the following: (i) activating emotional reactions, (ii) regulating those reactions and (iii) social cognitive processing (e.g. understanding the parent’s mental state). To examine neural processes associated with both emotional and social processing of parental criticism in personally relevant and ecologically valid social contexts, typically developing youth were scanned while they listened to their mother providing critical, praising and neutral statements. In response to maternal criticism, youth showed increased brain activity in affective networks (e.g. subcortical–limbic regions including lentiform nucleus and posterior insula), but decreased activity in cognitive control networks (e.g. dorsolateral prefrontal cortex and caudal anterior cingulate cortex) and social cognitive networks (e.g. temporoparietal junction and posterior cingulate cortex/precuneus). These results suggest that youth may respond to maternal criticism with increased emotional reactivity but decreased cognitive control and social cognitive processing. A better understanding of children’s responses to parental criticism may provide insights into the ways that parental feedback can be modified to be more helpful to behavior and development in youth. PMID:25338632

A role for chemokine signaling in neural crest cell migration and craniofacial development

PubMed Central

Killian, Eugenia C. Olesnicky; Birkholz, Denise A.; Artinger, Kristin Bruk

2009-01-01

Neural crest cells (NCCs) are a unique population of multipotent cells that migrate along defined pathways throughout the embryo and give rise to many diverse cell types including pigment cells, craniofacial cartilage and the peripheral nervous system (PNS). Aberrant migration of NCCs results in a wide variety of congenital birth defects including craniofacial abnormalities. The chemokine Sdf1 and its receptors, Cxcr4 and Cxcr7, have been identified as key components in the regulation of cell migration in a variety of tissues. Here we describe a novel role for the zebrafish chemokine receptor Cxcr4a in the development and migration of cranial NCCs (CNCCs). We find that loss of Cxcr4a, but not Cxcr7b results in aberrant CNCC migration, defects in the neurocranium, as well as cranial ganglia dismorphogenesis. Moreover, overexpression of either Sdf1b or Cxcr4a causes aberrant CNCC migration and results in ectopic craniofacial cartilages. We propose a model in which Sdf1b signaling from the pharyngeal arch endoderm and optic stalk to Cxcr4a expressing CNCCs is important for both the proper condensation of the CNCCs into pharyngeal arches and the subsequent patterning and morphogenesis of the neural crest derived tissues. PMID:19576198

Role of cranial neural crest cells in visceral arch muscle positioning and morphogenesis in the Mexican axolotl, Ambystoma mexicanum.

PubMed

Ericsson, Rolf; Cerny, Robert; Falck, Pierre; Olsson, Lennart

2004-10-01

The role of cranial neural crest cells in the formation of visceral arch musculature was investigated in the Mexican axolotl, Ambystoma mexicanum. DiI (1,1'-dioctadecyl-3,3,3',3'-tetramethylindocarbocyanine, perchlorate) labeling and green fluorescent protein (GFP) mRNA injections combined with unilateral transplantations of neural folds showed that neural crest cells contribute to the connective tissues but not the myofibers of developing visceral arch muscles in the mandibular, hyoid, and branchial arches. Extirpations of individual cranial neural crest streams demonstrated that neural crest cells are necessary for correct morphogenesis of visceral arch muscles. These do, however, initially develop in their proper positions also in the absence of cranial neural crest. Visceral arch muscles forming in the absence of neural crest cells start to differentiate at their origins but fail to extend toward their insertions and may have a frayed appearance. Our data indicate that visceral arch muscle positioning is controlled by factors that do not have a neural crest origin. We suggest that the cranial neural crest-derived connective tissues provide directional guidance important for the proper extension of the cranial muscles and the subsequent attachment to the insertion on the correct cartilage. In a comparative context, our data from the Mexican axolotl support the view that the cranial neural crest plays a fundamental role in the development of not only the skeleton of the vertebrate head but also in the morphogenesis of the cranial muscles and that this might be a primitive feature of cranial development in vertebrates. 2004 Wiley-Liss, Inc.

Development of Neural Sensitivity to Face Identity Correlates with Perceptual Discriminability.

PubMed

Natu, Vaidehi S; Barnett, Michael A; Hartley, Jake; Gomez, Jesse; Stigliani, Anthony; Grill-Spector, Kalanit

2016-10-19

Face perception is subserved by a series of face-selective regions in the human ventral stream, which undergo prolonged development from childhood to adulthood. However, it is unknown how neural development of these regions relates to the development of face-perception abilities. Here, we used functional magnetic resonance imaging (fMRI) to measure brain responses of ventral occipitotemporal regions in children (ages, 5-12 years) and adults (ages, 19-34 years) when they viewed faces that parametrically varied in dissimilarity. Since similar faces generate lower responses than dissimilar faces due to fMRI adaptation, this design objectively evaluates neural sensitivity to face identity across development. Additionally, a subset of subjects participated in a behavioral experiment to assess perceptual discriminability of face identity. Our data reveal three main findings: (1) neural sensitivity to face identity increases with age in face-selective but not object-selective regions; (2) the amplitude of responses to faces increases with age in both face-selective and object-selective regions; and (3) perceptual discriminability of face identity is correlated with the neural sensitivity to face identity of face-selective regions. In contrast, perceptual discriminability is not correlated with the amplitude of response in face-selective regions or of responses of object-selective regions. These data suggest that developmental increases in neural sensitivity to face identity in face-selective regions improve perceptual discriminability of faces. Our findings significantly advance the understanding of the neural mechanisms of development of face perception and open new avenues for using fMRI adaptation to study the neural development of high-level visual and cognitive functions more broadly. Face perception, which is critical for daily social interactions, develops from childhood to adulthood. However, it is unknown what developmental changes in the brain lead to improved performance. Using fMRI in children and adults, we find that from childhood to adulthood, neural sensitivity to changes in face identity increases in face-selective regions. Critically, subjects' perceptual discriminability among faces is linked to neural sensitivity: participants with higher neural sensitivity in face-selective regions demonstrate higher perceptual discriminability. Thus, our results suggest that developmental increases in face-selective regions' sensitivity to face identity improve perceptual discrimination of faces. These findings significantly advance understanding of the neural mechanisms underlying the development of face perception and have important implications for assessing both typical and atypical development. Copyright © 2016 the authors 0270-6474/16/3610893-15$15.00/0.

Neural Responses to Visual Food Cues According to Weight Status: A Systematic Review of Functional Magnetic Resonance Imaging Studies

PubMed Central

Pursey, Kirrilly M.; Stanwell, Peter; Callister, Robert J.; Brain, Katherine; Collins, Clare E.; Burrows, Tracy L.

2014-01-01

Emerging evidence from recent neuroimaging studies suggests that specific food-related behaviors contribute to the development of obesity. The aim of this review was to report the neural responses to visual food cues, as assessed by functional magnetic resonance imaging (fMRI), in humans of differing weight status. Published studies to 2014 were retrieved and included if they used visual food cues, studied humans >18 years old, reported weight status, and included fMRI outcomes. Sixty studies were identified that investigated the neural responses of healthy weight participants (n = 26), healthy weight compared to obese participants (n = 17), and weight-loss interventions (n = 12). High-calorie food images were used in the majority of studies (n = 36), however, image selection justification was only provided in 19 studies. Obese individuals had increased activation of reward-related brain areas including the insula and orbitofrontal cortex in response to visual food cues compared to healthy weight individuals, and this was particularly evident in response to energy dense cues. Additionally, obese individuals were more responsive to food images when satiated. Meta-analysis of changes in neural activation post-weight loss revealed small areas of convergence across studies in brain areas related to emotion, memory, and learning, including the cingulate gyrus, lentiform nucleus, and precuneus. Differential activation patterns to visual food cues were observed between obese, healthy weight, and weight-loss populations. Future studies require standardization of nutrition variables and fMRI outcomes to enable more direct comparisons between studies. PMID:25988110

Neural responses to visual food cues according to weight status: a systematic review of functional magnetic resonance imaging studies.

PubMed

Pursey, Kirrilly M; Stanwell, Peter; Callister, Robert J; Brain, Katherine; Collins, Clare E; Burrows, Tracy L

2014-01-01

Emerging evidence from recent neuroimaging studies suggests that specific food-related behaviors contribute to the development of obesity. The aim of this review was to report the neural responses to visual food cues, as assessed by functional magnetic resonance imaging (fMRI), in humans of differing weight status. Published studies to 2014 were retrieved and included if they used visual food cues, studied humans >18 years old, reported weight status, and included fMRI outcomes. Sixty studies were identified that investigated the neural responses of healthy weight participants (n = 26), healthy weight compared to obese participants (n = 17), and weight-loss interventions (n = 12). High-calorie food images were used in the majority of studies (n = 36), however, image selection justification was only provided in 19 studies. Obese individuals had increased activation of reward-related brain areas including the insula and orbitofrontal cortex in response to visual food cues compared to healthy weight individuals, and this was particularly evident in response to energy dense cues. Additionally, obese individuals were more responsive to food images when satiated. Meta-analysis of changes in neural activation post-weight loss revealed small areas of convergence across studies in brain areas related to emotion, memory, and learning, including the cingulate gyrus, lentiform nucleus, and precuneus. Differential activation patterns to visual food cues were observed between obese, healthy weight, and weight-loss populations. Future studies require standardization of nutrition variables and fMRI outcomes to enable more direct comparisons between studies.

Near real-time analysis of extrinsic Fabry-Perot interferometric sensors under damped vibration using artificial neural networks

NASA Astrophysics Data System (ADS)

Dua, Rohit; Watkins, Steve E.

2009-03-01

Strain analysis due to vibration can provide insight into structural health. An Extrinsic Fabry-Perot Interferometric (EFPI) sensor under vibrational strain generates a non-linear modulated output. Advanced signal processing techniques, to extract important information such as absolute strain, are required to demodulate this non-linear output. Past research has employed Artificial Neural Networks (ANN) and Fast Fourier Transforms (FFT) to demodulate the EFPI sensor for limited conditions. These demodulation systems could only handle variations in absolute value of strain and frequency of actuation during a vibration event. This project uses an ANN approach to extend the demodulation system to include the variation in the damping coefficient of the actuating vibration, in a near real-time vibration scenario. A computer simulation provides training and testing data for the theoretical output of the EFPI sensor to demonstrate the approaches. FFT needed to be performed on a window of the EFPI output data. A small window of observation is obtained, while maintaining low absolute-strain prediction errors, heuristically. Results are obtained and compared from employing different ANN architectures including multi-layered feedforward ANN trained using Backpropagation Neural Network (BPNN), and Generalized Regression Neural Networks (GRNN). A two-layered algorithm fusion system is developed and tested that yields better results.

How Neural Networks Learn from Experience.

ERIC Educational Resources Information Center

Hinton, Geoffrey E.

1992-01-01

Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…

Misexpression of BRE gene in the developing chick neural tube affects neurulation and somitogenesis

PubMed Central

Wang, Guang; Li, Yan; Wang, Xiao-Yu; Chuai, Manli; Yeuk-Hon Chan, John; Lei, Jian; Münsterberg, Andrea; Lee, Kenneth Ka Ho; Yang, Xuesong

2015-01-01

The brain and reproductive expression (BRE) gene is expressed in numerous adult tissues and especially in the nervous and reproductive systems. However, little is known about BRE expression in the developing embryo or about its role in embryonic development. In this study, we used in situ hybridization to reveal the spatiotemporal expression pattern for BRE in chick embryo during development. To determine the importance of BRE in neurogenesis, we overexpressed BRE and also silenced BRE expression specifically in the neural tube. We established that overexpressing BRE in the neural tube indirectly accelerated Pax7+ somite development and directly increased HNK-1+ neural crest cell (NCC) migration and TuJ-1+ neurite outgrowth. These altered morphogenetic processes were associated with changes in the cell cycle of NCCs and neural tube cells. The inverse effect was obtained when BRE expression was silenced in the neural tube. We also determined that BMP4 and Shh expression in the neural tube was affected by misexpression of BRE. This provides a possible mechanism for how altering BRE expression was able to affect somitogenesis, neurogenesis, and NCC migration. In summary, our results demonstrate that BRE plays an important role in regulating neurogenesis and indirectly somite differentiation during early chick embryo development. PMID:25568339

Autism: Clinical and Research Issues.

ERIC Educational Resources Information Center

Accardo, Pasquale J., Ed.; Magnusen, Christy, Ed.; Capute, Arnold J., Ed.

This text examines the characteristics that define autism: impairments in communication; abnormal social development; and clinically significant odd behaviors. Specific chapters include: (1) Neural Mechanisms in Autism (Andrew W. Zimmerman and Barry Gordon); (2) Epidemiology of Autism and Other Pervasive Developmental Disorders: Current…

Influence and timing of arrival of murine neural crest on pancreatic beta cell development and maturation.

PubMed

Plank, Jennifer L; Mundell, Nathan A; Frist, Audrey Y; LeGrone, Alison W; Kim, Thomas; Musser, Melissa A; Walter, Teagan J; Labosky, Patricia A

2011-01-15

Interactions between cells from the ectoderm and mesoderm influence development of the endodermally-derived pancreas. While much is known about how mesoderm regulates pancreatic development, relatively little is understood about how and when the ectodermally-derived neural crest regulates pancreatic development and specifically, beta cell maturation. A previous study demonstrated that signals from the neural crest regulate beta cell proliferation and ultimately, beta cell mass. Here, we expand on that work to describe timing of neural crest arrival at the developing pancreatic bud and extend our knowledge of the non-cell autonomous role for neural crest derivatives in the process of beta cell maturation. We demonstrated that murine neural crest entered the pancreatic mesenchyme between the 26 and 27 somite stages (approximately 10.0 dpc) and became intermingled with pancreatic progenitors as the epithelium branched into the surrounding mesenchyme. Using a neural crest-specific deletion of the Forkhead transcription factor Foxd3, we ablated neural crest cells that migrate to the pancreatic primordium. Consistent with previous data, in the absence of Foxd3, and therefore the absence of neural crest cells, proliferation of insulin-expressing cells and insulin-positive area are increased. Analysis of endocrine cell gene expression in the absence of neural crest demonstrated that, although the number of insulin-expressing cells was increased, beta cell maturation was significantly impaired. Decreased MafA and Pdx1 expression illustrated the defect in beta cell maturation; we discovered that without neural crest, there was a reduction in the percentage of insulin-positive cells that co-expressed Glut2 and Pdx1 compared to controls. In addition, transmission electron microscopy analyses revealed decreased numbers of characteristic insulin granules and the presence of abnormal granules in insulin-expressing cells from mutant embryos. Together, these data demonstrate that the neural crest is a critical regulator of beta cell development on two levels: by negatively regulating beta cell proliferation and by promoting beta cell maturation. Copyright © 2010 Elsevier Inc. All rights reserved.

Histone modifications controlling native and induced neural stem cell identity.

PubMed

Broccoli, Vania; Colasante, Gaia; Sessa, Alessandro; Rubio, Alicia

2015-10-01

During development, neural progenitor cells (NPCs) that are capable of self-renewing maintain a proliferative cellular pool while generating all differentiated neural cell components. Although the genetic network of transcription factors (TFs) required for neural specification has been well characterized, the unique set of histone modifications that accompanies this process has only recently started to be investigated. In vitro neural differentiation of pluripotent stem cells is emerging as a powerful system to examine epigenetic programs. Deciphering the histone code and how it shapes the chromatin environment will reveal the intimate link between epigenetic changes and mechanisms for neural fate determination in the developing nervous system. Furthermore, it will offer a molecular framework for a stringent comparison between native and induced neural stem cells (iNSCs) generated by direct neural cell conversion. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of Pax3 and Sox10 transgenic Xenopus laevis embryos as tools to study neural crest development.

PubMed

Alkobtawi, Mansour; Ray, Heather; Barriga, Elias H; Moreno, Mauricio; Kerney, Ryan; Monsoro-Burq, Anne-Helene; Saint-Jeannet, Jean-Pierre; Mayor, Roberto

2018-03-06

The neural crest is a multipotent population of cells that originates a variety of cell types. Many animal models are used to study neural crest induction, migration and differentiation, with amphibians and birds being the most widely used systems. A major technological advance to study neural crest development in mouse, chick and zebrafish has been the generation of transgenic animals in which neural crest specific enhancers/promoters drive the expression of either fluorescent proteins for use as lineage tracers, or modified genes for use in functional studies. Unfortunately, no such transgenic animals currently exist for the amphibians Xenopus laevis and tropicalis, key model systems for studying neural crest development. Here we describe the generation and characterization of two transgenic Xenopus laevis lines, Pax3-GFP and Sox10-GFP, in which GFP is expressed in the pre-migratory and migratory neural crest, respectively. We show that Pax3-GFP could be a powerful tool to study neural crest induction, whereas Sox10-GFP could be used in the study of neural crest migration in living embryos. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Elk3 is essential for the progression from progenitor to definitive neural crest cell

PubMed Central

Rogers, Crystal D.; Phillips, Jacquelyn L.; Bronner, Marianne E.

2013-01-01

Elk3/Net/Sap2 (here referred to as Elk3) is an Ets ternary complex transcriptional repressor known for its involvement in angiogenesis during embryonic development. Although Elk3 is expressed in various tissues, additional roles for the protein outside of vasculature development have yet to be reported. Here, we characterize the early spatiotemporal expression pattern of Elk3 in the avian embryo using whole mount in situ hybridization and quantitative RT-PCR and examine the effects of its loss of function on neural crest development. At early stages, Elk3 is expressed in the head folds, head mesenchyme, intersomitic vessels, and migratory cranial neural crest (NC) cells. Loss of the Elk3 protein results in the retention of Pax7+ precursors in the dorsal neural tube that fail to upregulate neural crest specifier genes, FoxD3, Sox10 and Snail2, resulting in embryos with severe migration defects. The results putatively place Elk3 downstream of neural plate border genes, but upstream of neural crest specifier genes in the neural crest gene regulatory network (NC-GRN), suggesting that it is critical for the progression from progenitor to definitive neural crest cell. PMID:23266330

Functional and Histological Effects of Chronic Neural Electrode Implantation.

PubMed

Sahyouni, Ronald; Chang, David T; Moshtaghi, Omid; Mahmoodi, Amin; Djalilian, Hamid R; Lin, Harrison W

2017-04-01

Permanent injury to the cranial nerves can often result in a substantial reduction in quality of life. Novel and innovative interventions can help restore form and function in nerve paralysis, with bioelectric interfaces among the more promising of these approaches. The foreign body response is an important consideration for any bioelectric device as it influences the function and effectiveness of the implant. The purpose of this review is to describe tissue and functional effects of chronic neural implantation among the different categories of neural implants and highlight advances in peripheral and cranial nerve stimulation. Data Sources : PubMed, IEEE, and Web of Science literature search. Review Methods : A review of the current literature was conducted to examine functional and histologic effects of bioelectric interfaces for neural implants. Bioelectric devices can be characterized as intraneural, epineural, perineural, intranuclear, or cortical depending on their placement relative to nerves and neuronal cell bodies. Such devices include nerve-specific stimulators, neuroprosthetics, brainstem implants, and deep brain stimulators. Regardless of electrode location and interface type, acute and chronic histological, macroscopic and functional changes can occur as a result of both passive and active tissue responses to the bioelectric implant. A variety of chronically implantable electrodes have been developed to treat disorders of the peripheral and cranial nerves, to varying degrees of efficacy. Consideration and mitigation of detrimental effects at the neural interface with further optimization of functional nerve stimulation will facilitate the development of these technologies and translation to the clinic. 3.

Zebrafish narrowminded suggests a genetic link between formation of neural crest and primary sensory neurons

PubMed Central

Bruk Artinger, Kristin; Chitnis, Ajay B.; Mercola, Mark; Driever, Wolfgang

2014-01-01

SUMMARY In the developing vertebrate nervous system, both neural crest and sensory neurons form at the boundary between non-neural ectoderm and the neural plate. From an in situ hybridization based expression analysis screen, we have identified a novel zebrafish mutation, narrowminded (nrd), which reduces the number of early neural crest cells and eliminates Rohon-Beard (RB) sensory neurons. Mosaic analysis has shown that the mutation acts cell autonomously suggesting that nrd is involved in either the reception or interpretation of signals at the lateral neural plate boundary. Characterization of the mutant phenotype indicates that nrd is required for a primary wave of neural crest cell formation during which progenitors generate both RB sensory neurons and neural crest cells. Moreover, the early deficit in neural crest cells in nrd homozygotes is compensated later in development. Thus, we propose that a later wave can compensate for the loss of early neural crest cells but, interestingly, not the RB sensory neurons. We discuss the implications of these findings for the possibility that RB sensory neurons and neural crest cells share a common evolutionary origin. PMID:10457007

Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

NASA Astrophysics Data System (ADS)

Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

2018-02-01

Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

Neural Networks for Modeling and Control of Particle Accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Neural Networks for Modeling and Control of Particle Accelerators

NASA Astrophysics Data System (ADS)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Networks for Modeling and Control of Particle Accelerators

DOE PAGES

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

2016-04-01

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

WNT/β-catenin signaling mediates human neural crest induction via a pre-neural border intermediate.

PubMed

Leung, Alan W; Murdoch, Barbara; Salem, Ahmed F; Prasad, Maneeshi S; Gomez, Gustavo A; García-Castro, Martín I

2016-02-01

Neural crest (NC) cells arise early in vertebrate development, migrate extensively and contribute to a diverse array of ectodermal and mesenchymal derivatives. Previous models of NC formation suggested derivation from neuralized ectoderm, via meso-ectodermal, or neural-non-neural ectoderm interactions. Recent studies using bird and amphibian embryos suggest an earlier origin of NC, independent of neural and mesodermal tissues. Here, we set out to generate a model in which to decipher signaling and tissue interactions involved in human NC induction. Our novel human embryonic stem cell (ESC)-based model yields high proportions of multipotent NC cells (expressing SOX10, PAX7 and TFAP2A) in 5 days. We demonstrate a crucial role for WNT/β-catenin signaling in launching NC development, while blocking placodal and surface ectoderm fates. We provide evidence of the delicate temporal effects of BMP and FGF signaling, and find that NC development is separable from neural and/or mesodermal contributions. We further substantiate the notion of a neural-independent origin of NC through PAX6 expression and knockdown studies. Finally, we identify a novel pre-neural border state characterized by early WNT/β-catenin signaling targets that displays distinct responses to BMP and FGF signaling from the traditional neural border genes. In summary, our work provides a fast and efficient protocol for human NC differentiation under signaling constraints similar to those identified in vivo in model organisms, and strengthens a framework for neural crest ontogeny that is separable from neural and mesodermal fates. © 2016. Published by The Company of Biologists Ltd.

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

Neural electrical activity and neural network growth.

PubMed

Gafarov, F M

2018-05-01

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

Attachment in integrative neuroscientific perspective.

PubMed

Hruby, Radovan; Hasto, Jozef; Minarik, Peter

2011-01-01

Attachment theory is a very influential general concept of human social and emotional development, which emphasizes the role of early mother-infant interactions for infant's adaptive behavioural and stress copying strategies, personality organization and mental health. Individuals with disrupted development of secure attachment to mother/primary caregiver are at higher risk of developing mental disorders. This theory consists of the complex developmental psycho-neurobiological model of attachment and emerges from principles of psychoanalysis, evolutionary biology, cognitive-developmental psychology, ethology, physiology and control systems theory. The progress of modern neuroscience enables interpretation of neurobiological aspects of the theory as multi-level neural interactions and functional development of important neural structures, effects of neuromediattors, hormones and essential neurobiological processes including emotional, cognitive, social interactions and the special key role of mentalizing. It has multiple neurobiological, neuroendocrine, neurophysiological, ethological, genetic, developmental, psychological, psychotherapeutic and neuropsychiatric consequences and is a prototype of complex neuroscientific concept as interpretation of modern integrated neuroscience.

Electronic Neural Networks

NASA Technical Reports Server (NTRS)

Thakoor, Anil

1990-01-01

Viewgraphs on electronic neural networks for space station are presented. Topics covered include: electronic neural networks; electronic implementations; VLSI/thin film hybrid hardware for neurocomputing; computations with analog parallel processing; features of neuroprocessors; applications of neuroprocessors; neural network hardware for terrain trafficability determination; a dedicated processor for path planning; neural network system interface; neural network for robotic control; error backpropagation algorithm for learning; resource allocation matrix; global optimization neuroprocessor; and electrically programmable read only thin-film synaptic array.

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

PubMed Central

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

2016-01-01

Study Objectives: Emerging evidence suggests that insomnia may disrupt reward-related brain function—a potentially important factor in the development of depressive disorder. Adolescence may be a period during which such disruption is especially problematic given the rise in the incidence of insomnia and ongoing development of neural systems that support reward processing. The present study uses longitudinal data to test the hypothesis that disruption of neural reward processing is a mechanism by which insomnia symptoms—including nocturnal insomnia symptoms (NIS) and nonrestorative sleep (NRS)—contribute to depressive symptoms in adolescent girls. Method: Participants were 123 adolescent girls and their caregivers from an ongoing longitudinal study of precursors to depression across adolescent development. NIS and NRS were assessed annually from ages 9 to 13 years. Girls completed a monetary reward task during a functional MRI scan at age 16 years. Depressive symptoms were assessed at ages 16 and 17 years. Multivariable regression tested the prospective associations between NIS and NRS, neural response during reward anticipation, and the mean number of depressive symptoms (omitting sleep problems). Results: NRS, but not NIS, during early adolescence was positively associated with late adolescent dorsal medial prefrontal cortex (dmPFC) response to reward anticipation and depressive symptoms. DMPFC response mediated the relationship between early adolescent NRS and late adolescent depressive symptoms. Conclusions: These results suggest that NRS may contribute to depression by disrupting reward processing via altered activity in a region of prefrontal cortex involved in affective control. The results also support the mechanistic differentiation of NIS and NRS. Citation: Casement MD, Keenan KE, Hipwell AE, Guyer AE, Forbes EE. Neural reward processing mediates the relationship between insomnia symptoms and depression in adolescence. SLEEP 2016;39(2):439–447. PMID:26350468

From neural development to cognition: unexpected roles for chromatin

PubMed Central

Ronan, Jehnna L.; Wu, Wei

2014-01-01

Recent genome-sequencing studies in human neurodevelopmental and psychiatric disorders have uncovered mutations in many chromatin regulators. These human genetic studies, along with studies in model organisms, are providing insight into chromatin regulatory mechanisms in neural development and how alterations to these mechanisms can cause cognitive deficits, such as intellectual disability. We discuss several implicated chromatin regulators, including BAF (also known as SWI/SNF) and CHD8 chromatin remodellers, HDAC4 and the Polycomb component EZH2. Interestingly, mutations in EZH2 and certain BAF complex components have roles in both neurodevelopmental disorders and cancer, and overlapping point mutations are suggesting functionally important residues and domains. We speculate on the contribution of these similar mutations to disparate disorders. PMID:23568486

Neural Crest-Derived Mesenchymal Cells Require Wnt Signaling for Their Development and Drive Invagination of the Telencephalic Midline

PubMed Central

Choe, Youngshik; Zarbalis, Konstantinos S.; Pleasure, Samuel J.

2014-01-01

Embryonic neural crest cells contribute to the development of the craniofacial mesenchyme, forebrain meninges and perivascular cells. In this study, we investigated the function of ß-catenin signaling in neural crest cells abutting the dorsal forebrain during development. In the absence of ß-catenin signaling, neural crest cells failed to expand in the interhemispheric region and produced ectopic smooth muscle cells instead of generating dermal and calvarial mesenchyme. In contrast, constitutive expression of stabilized ß-catenin in neural crest cells increased the number of mesenchymal lineage precursors suggesting that ß-catenin signaling is necessary for the expansion of neural crest-derived mesenchymal cells. Interestingly, the loss of neural crest-derived mesenchymal stem cells (MSCs) leads to failure of telencephalic midline invagination and causes ventricular system defects. This study shows that ß-catenin signaling is required for the switch of neural crest cells to MSCs and mediates the expansion of MSCs to drive the formation of mesenchymal structures of the head. Furthermore, loss of these structures causes striking defects in forebrain morphogenesis. PMID:24516524

An Implantable Neural Sensing Microsystem with Fiber-Optic Data Transmission and Power Delivery

PubMed Central

Park, Sunmee; Borton, David A.; Kang, Mingyu; Nurmikko, Arto V.; Song, Yoon-Kyu

2013-01-01

We have developed a prototype cortical neural sensing microsystem for brain implantable neuroengineering applications. Its key feature is that both the transmission of broadband, multichannel neural data and power required for the embedded microelectronics are provided by optical fiber access. The fiber-optic system is aimed at enabling neural recording from rodents and primates by converting cortical signals to a digital stream of infrared light pulses. In the full microsystem whose performance is summarized in this paper, an analog-to-digital converter and a low power digital controller IC have been integrated with a low threshold, semiconductor laser to extract the digitized neural signals optically from the implantable unit. The microsystem also acquires electrical power and synchronization clocks via optical fibers from an external laser by using a highly efficient photovoltaic cell on board. The implantable unit employs a flexible polymer substrate to integrate analog and digital microelectronics and on-chip optoelectronic components, while adapting to the anatomical and physiological constraints of the environment. A low power analog CMOS chip, which includes preamplifier and multiplexing circuitry, is directly flip-chip bonded to the microelectrode array to form the cortical neurosensor device. PMID:23666130

A two-dimensional neuropsychology of defense: fear/anxiety and defensive distance.

PubMed

McNaughton, Neil; Corr, Philip J

2004-05-01

We present in this paper a picture of the neural systems controlling defense that updates and simplifies Gray's "Neuropsychology of Anxiety". It is based on two behavioural dimensions: 'defensive distance' as defined by the Blanchards and 'defensive direction'. Defensive direction is a categorical dimension with avoidance of threat corresponding to fear and approach to threat corresponding to anxiety. These two psychological dimensions are mapped to underlying neural dimensions. Defensive distance is mapped to neural level, with the shortest defensive distances involving the lowest neural level (periaqueductal grey) and the largest defensive distances the highest neural level (prefrontal cortex). Defensive direction is mapped to separate parallel streams that run across these levels. A significant departure from prior models is the proposal that both fear and anxiety are represented at all levels. The theory is presented in a simplified form that does not incorporate the interactions that must occur between non-adjacent levels of the system. It also requires expansion to include the dimension of escapability of threat. Our current development and these proposed future extensions do not change the core concepts originally proposed by Gray and, we argue, demonstrate their enduring value.

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

PubMed Central

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

2014-01-01

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

Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters

PubMed Central

Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

2015-01-01

Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915measuredsamples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rateand heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08. PMID:26624613

Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

PubMed

Liu, Zhijian; Liu, Kejun; Li, Hao; Zhang, Xinyu; Jin, Guangya; Cheng, Kewei

2015-01-01

Measurements of heat collection rate and heat loss coefficient are crucial for the evaluation of in service water-in-glass evacuated tube solar water heaters. However, conventional measurement requires expensive detection devices and undergoes a series of complicated procedures. To simplify the measurement and reduce the cost, software based on artificial neural networks for measuring heat collection rate and heat loss coefficient of water-in-glass evacuated tube solar water heaters was developed. Using multilayer feed-forward neural networks with back-propagation algorithm, we developed and tested our program on the basis of 915 measured samples of water-in-glass evacuated tube solar water heaters. This artificial neural networks-based software program automatically obtained accurate heat collection rate and heat loss coefficient using simply "portable test instruments" acquired parameters, including tube length, number of tubes, tube center distance, heat water mass in tank, collector area, angle between tubes and ground and final temperature. Our results show that this software (on both personal computer and Android platforms) is efficient and convenient to predict the heat collection rate and heat loss coefficient due to it slow root mean square errors in prediction. The software now can be downloaded from http://t.cn/RLPKF08.

Progressive and regressive developmental changes in neural substrates for face processing: Testing specific predictions of the Interactive Specialization account

PubMed Central

Joseph, Jane E.; Gathers, Ann D.; Bhatt, Ramesh S.

2010-01-01

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e., increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of neural development. To differentiate between these accounts, the present study also examined regressive changes (i.e., decreases in specialization in certain regions with age), which is predicted by the IS but not maturational account. The fMRI results show that both progressive and regressive changes occur, consistent with IS. Progressive changes mostly occurred in occipital-fusiform and inferior frontal cortex whereas regressive changes largely emerged in parietal and lateral temporal cortices. Moreover, inconsistent with the maturational account, all of the regions involved in face viewing in adults were active in children, with some regions already specialized for face processing by 5 years of age and other regions activated in children but not specifically for faces. Thus, neurodevelopment of face processing involves dynamic interactions among brain regions including age-related increases and decreases in specialization and the involvement of different regions at different ages. These results are more consistent with IS than maturational models of neural development. PMID:21399706

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

PubMed

Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

2016-07-18

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods

NASA Astrophysics Data System (ADS)

Pham, Binh Thai; Tien Bui, Dieu; Pourghasemi, Hamid Reza; Indra, Prakash; Dholakia, M. B.

2017-04-01

The objective of this study is to make a comparison of the prediction performance of three techniques, Functional Trees (FT), Multilayer Perceptron Neural Networks (MLP Neural Nets), and Naïve Bayes (NB) for landslide susceptibility assessment at the Uttarakhand Area (India). Firstly, a landslide inventory map with 430 landslide locations in the study area was constructed from various sources. Landslide locations were then randomly split into two parts (i) 70 % landslide locations being used for training models (ii) 30 % landslide locations being employed for validation process. Secondly, a total of eleven landslide conditioning factors including slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to lineaments, distance to rivers, and rainfall were used in the analysis to elucidate the spatial relationship between these factors and landslide occurrences. Feature selection of Linear Support Vector Machine (LSVM) algorithm was employed to assess the prediction capability of these conditioning factors on landslide models. Subsequently, the NB, MLP Neural Nets, and FT models were constructed using training dataset. Finally, success rate and predictive rate curves were employed to validate and compare the predictive capability of three used models. Overall, all the three models performed very well for landslide susceptibility assessment. Out of these models, the MLP Neural Nets and the FT models had almost the same predictive capability whereas the MLP Neural Nets (AUC = 0.850) was slightly better than the FT model (AUC = 0.849). The NB model (AUC = 0.838) had the lowest predictive capability compared to other models. Landslide susceptibility maps were final developed using these three models. These maps would be helpful to planners and engineers for the development activities and land-use planning.

Advances in Artificial Neural Networks - Methodological Development and Application

USDA-ARS?s Scientific Manuscript database

Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

Data systems and computer science: Neural networks base R/T program overview

NASA Technical Reports Server (NTRS)

Gulati, Sandeep

1991-01-01

The research base, in the U.S. and abroad, for the development of neural network technology is discussed. The technical objectives are to develop and demonstrate adaptive, neural information processing concepts. The leveraging of external funding is also discussed.

Flight Test of an Intelligent Flight-Control System

NASA Technical Reports Server (NTRS)

Davidson, Ron; Bosworth, John T.; Jacobson, Steven R.; Thomson, Michael Pl; Jorgensen, Charles C.

2003-01-01

The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data inputs with the outputs provided to instrumentation only. The IFCS was not used to control the airplane. In another stage of the flight test, the Phase I pre-trained neural network was integrated into a Phase III version of the flight control system. The Phase I pretrained neural network provided realtime stability and control derivatives to a Phase III controller that was based on a stochastic optimal feedforward and feedback technique (SOFFT). This combined Phase I/III system was operated together with the research flight-control system (RFCS) of the F-15 ACTIVE during the flight test. The RFCS enables the pilot to switch quickly from the experimental- research flight mode back to the safe conventional mode. These initial IFCS ACP flight tests were completed in April 1999. The Phase I/III flight test milestone was to demonstrate, across a range of subsonic and supersonic flight conditions, that the pre-trained neural network could be used to supply real-time aerodynamic stability and control derivatives to the closed-loop optimal SOFFT flight controller. Additional objectives attained in the flight test included (1) flight qualification of a neural-network-based control system; (2) the use of a combined neural-network/closed-loop optimal flight-control system to obtain level-one handling qualities; and (3) demonstration, through variation of control gains, that different handling qualities can be achieved by setting new target parameters. In addition, data for the Phase-II (on-line-learning) neural network were collected, during the use of stacked-frequency- sweep excitation, for post-flight analysis. Initial analysis of these data showed the potential for future flight tests that will incorporate the real-time identification and on-line learning aspects of the IFCS.

The silicon synapse or, neural net computing.

PubMed

Frenger, P

1989-01-01

Recent developments have rekindled interest in the electronic neural network, a form of parallel computer architecture loosely based on the nervous system of living creatures. This paper describes the elements of neural net computers, reviews the historical milestones in their development, and lists the advantages and disadvantages of their use. Methods for software simulation of neural network systems on existing computers, as well as creation of hardware analogues, are given. The most successful applications of these techniques, involving emulation of biological system responses, are presented. The author's experiences with neural net systems are discussed.

A neural network with modular hierarchical learning

NASA Technical Reports Server (NTRS)

Baldi, Pierre F. (Inventor); Toomarian, Nikzad (Inventor)

1994-01-01

This invention provides a new hierarchical approach for supervised neural learning of time dependent trajectories. The modular hierarchical methodology leads to architectures which are more structured than fully interconnected networks. The networks utilize a general feedforward flow of information and sparse recurrent connections to achieve dynamic effects. The advantages include the sparsity of units and connections, the modular organization. A further advantage is that the learning is much more circumscribed learning than in fully interconnected systems. The present invention is embodied by a neural network including a plurality of neural modules each having a pre-established performance capability wherein each neural module has an output outputting present results of the performance capability and an input for changing the present results of the performance capabilitiy. For pattern recognition applications, the performance capability may be an oscillation capability producing a repeating wave pattern as the present results. In the preferred embodiment, each of the plurality of neural modules includes a pre-established capability portion and a performance adjustment portion connected to control the pre-established capability portion.

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

PubMed Central

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

2017-01-01

Cognitive control is related to goal-directed self-regulation abilities, which is fundamental for human development. Conflict control includes the neural processes of conflict monitoring and conflict resolution. Testosterone and cortisol are essential hormones for the development of cognitive functions. However, there are no studies that have investigated the correlation of these two hormones with conflict control in preadolescents. In this study, we aimed to explore whether testosterone, cortisol, and testosterone/cortisol ratio worked differently for preadolescent’s conflict control processes in varied conflict control tasks. Thirty-two 10-year-old children (16 boys and 16 girls) were enrolled. They were instructed to accomplish three conflict control tasks with different conflict dimensions, including the Flanker, Simon, and Stroop tasks, and electrophysiological signals were recorded. Salivary samples were collected from each child. The testosterone and cortisol levels were determined by enzyme-linked immunosorbent assay. The electrophysiological results showed that the incongruent trials induced greater N2/N450 and P3/SP responses than the congruent trials during neural processes of conflict monitoring and conflict resolution in the Flanker and Stroop tasks. The hormonal findings showed that (1) the testosterone/cortisol ratio was correlated with conflict control accuracy and conflict resolution in the Flanker task; (2) the testosterone level was associated with conflict control performance and neural processing of conflict resolution in the Stroop task; (3) the cortisol level was correlated with conflict control performance and neural processing of conflict monitoring in the Simon task. In conclusion, in 10-year-old children, the fewer processes a task needs, the more likely there is an association between the T/C ratios and the behavioral and brain response, and the dual-hormone effects on conflict resolution may be testosterone-driven in the Stroop and Flanker tasks. PMID:28690571

Character Recognition Using Genetically Trained Neural Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diniz, C.; Stantz, K.M.; Trahan, M.W.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfidmore » recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the amount of noise significantly degrades character recognition efficiency, some of which can be overcome by adding noise during training and optimizing the form of the network's activation fimction.« less

Development of a sensor coordinated kinematic model for neural network controller training

NASA Technical Reports Server (NTRS)

Jorgensen, Charles C.

1990-01-01

A robotic benchmark problem useful for evaluating alternative neural network controllers is presented. Specifically, it derives two camera models and the kinematic equations of a multiple degree of freedom manipulator whose end effector is under observation. The mapping developed include forward and inverse translations from binocular images to 3-D target position and the inverse kinematics of mapping point positions into manipulator commands in joint space. Implementation is detailed for a three degree of freedom manipulator with one revolute joint at the base and two prismatic joints on the arms. The example is restricted to operate within a unit cube with arm links of 0.6 and 0.4 units respectively. The development is presented in the context of more complex simulations and a logical path for extension of the benchmark to higher degree of freedom manipulators is presented.

Self-organization of neural tissue architectures from pluripotent stem cells.

PubMed

Karus, Michael; Blaess, Sandra; Brüstle, Oliver

2014-08-15

Despite being a subject of intensive research, the mechanisms underlying the formation of neural tissue architectures during development of the central nervous system remain largely enigmatic. So far, studies into neural pattern formation have been restricted mainly to animal experiments. With the advent of pluripotent stem cells it has become possible to explore early steps of nervous system development in vitro. These studies have unraveled a remarkable propensity of primitive neural cells to self-organize into primitive patterns such as neural tube-like rosettes in vitro. Data from more advanced 3D culture systems indicate that this intrinsic propensity for self-organization can even extend to the formation of complex architectures such as a multilayered cortical neuroepithelium or an entire optic cup. These novel experimental paradigms not only demonstrate the enormous self-organization capacity of neural stem cells, they also provide exciting prospects for studying the earliest steps of human neural tissue development and the pathogenesis of brain malformations in reductionist in vitro paradigms. © 2014 Wiley Periodicals, Inc.

The 3-D image recognition based on fuzzy neural network technology

NASA Technical Reports Server (NTRS)

Hirota, Kaoru; Yamauchi, Kenichi; Murakami, Jun; Tanaka, Kei

1993-01-01

Three dimensional stereoscopic image recognition system based on fuzzy-neural network technology was developed. The system consists of three parts; preprocessing part, feature extraction part, and matching part. Two CCD color camera image are fed to the preprocessing part, where several operations including RGB-HSV transformation are done. A multi-layer perception is used for the line detection in the feature extraction part. Then fuzzy matching technique is introduced in the matching part. The system is realized on SUN spark station and special image input hardware system. An experimental result on bottle images is also presented.

Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts

PubMed Central

2016-01-01

We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available. PMID:27795703

A Regularized Neural Net Approach for Retrieval of Atmospheric and Surface Temperatures with the IASI Instrument

NASA Technical Reports Server (NTRS)

Aires, F.; Chedin, A.; Scott, N. A.; Rossow, W. B.; Hansen, James E. (Technical Monitor)

2001-01-01

Abstract In this paper, a fast atmospheric and surface temperature retrieval algorithm is developed for the high resolution Infrared Atmospheric Sounding Interferometer (IASI) space-borne instrument. This algorithm is constructed on the basis of a neural network technique that has been regularized by introduction of a priori information. The performance of the resulting fast and accurate inverse radiative transfer model is presented for a large divE:rsified dataset of radiosonde atmospheres including rare events. Two configurations are considered: a tropical-airmass specialized scheme and an all-air-masses scheme.

Endpoints for Neural Connectivity Including Neurite Outgrowth, Synapse Formation, and Function

EPA Science Inventory

A strategy for alternative methods for developmental neurotoxicity testing (DNT) focuses on assessment of chemical effects on conserved neurodevelopmental processes. The development of the brain is an integrated series of steps from the commitment of embryonic cells to become neu...

Maladaptive plasticity in tinnitus-triggers, mechanisms and treatment

PubMed Central

Shore, Susan E; Roberts, Larry E.; Langguth, Berthold

2016-01-01

Tinnitus is a phantom auditory sensation that reduces quality of life for millions worldwide and for which there is no medical cure. Most cases are associated with hearing loss caused by the aging process or noise exposure. Because exposure to loud recreational sound is common among youthful populations, young persons are at increasing risk. Head or neck injuries can also trigger the development of tinnitus, as altered somatosensory input can affect auditory pathways and lead to tinnitus or modulate its intensity. Emotional and attentional state may play a role in tinnitus development and maintenance via top-down mechanisms. Thus, military in combat are particularly at risk due to combined hearing loss, somatosensory system disturbances and emotional stress. Neuroscience research has identified neural changes related to tinnitus that commence at the cochlear nucleus and extend to the auditory cortex and brain regions beyond. Maladaptive neural plasticity appears to underlie these neural changes, as it results in increased spontaneous firing rates and synchrony among neurons in central auditory structures that may generate the phantom percept. This review highlights the links between animal and human studies, including several therapeutic approaches that have been developed, which aim to target the neuroplastic changes underlying tinnitus. PMID:26868680

How Tissue Mechanical Properties Affect Enteric Neural Crest Cell Migration

NASA Astrophysics Data System (ADS)

Chevalier, N. R.; Gazguez, E.; Bidault, L.; Guilbert, T.; Vias, C.; Vian, E.; Watanabe, Y.; Muller, L.; Germain, S.; Bondurand, N.; Dufour, S.; Fleury, V.

2016-02-01

Neural crest cells (NCCs) are a population of multipotent cells that migrate extensively during vertebrate development. Alterations to neural crest ontogenesis cause several diseases, including cancers and congenital defects, such as Hirschprung disease, which results from incomplete colonization of the colon by enteric NCCs (ENCCs). We investigated the influence of the stiffness and structure of the environment on ENCC migration in vitro and during colonization of the gastrointestinal tract in chicken and mouse embryos. We showed using tensile stretching and atomic force microscopy (AFM) that the mesenchyme of the gut was initially soft but gradually stiffened during the period of ENCC colonization. Second-harmonic generation (SHG) microscopy revealed that this stiffening was associated with a gradual organization and enrichment of collagen fibers in the developing gut. Ex-vivo 2D cell migration assays showed that ENCCs migrated on substrates with very low levels of stiffness. In 3D collagen gels, the speed of the ENCC migratory front decreased with increasing gel stiffness, whereas no correlation was found between porosity and ENCC migration behavior. Metalloprotease inhibition experiments showed that ENCCs actively degraded collagen in order to progress. These results shed light on the role of the mechanical properties of tissues in ENCC migration during development.

m6A RNA Methylation Controls Neural Development and Is Involved in Human Diseases.

PubMed

Du, Kunzhao; Zhang, Longbin; Lee, Trevor; Sun, Tao

2018-06-16

RNA modifications are involved in many aspects of biological functions. N6-methyladenosine (m 6 A) is one of the most important forms of RNA methylation and plays a vital role in regulating gene expression, protein translation, cell behaviors, and physiological conditions in many species, including humans. The dynamic and reversible modification of m 6 A is conducted by three elements: methyltransferases ("writers"), such as methyltransferase-like protein 3 (METTL3) and METTL14; m 6 A-binding proteins ("readers"), such as the YTH domain family proteins (YTHDFs) and YTH domain-containing protein 1 (YTHDC1); and demethylases ("erasers"), such as fat mass and obesity-associated protein (FTO) and AlkB homolog 5 (ALKBH5). In this review, we summarize the current knowledge on mapping mRNA positions of m 6 A modification and revealing molecular processes of m 6 A. We further highlight the biological significance of m 6 A modification in neural cells during development of the nervous system and its association with human diseases. m 6 A RNA methylation is becoming a new frontier in neuroscience and should help us better understand neural development and neurological diseases from a novel point of view.

Emotion-independent face recognition

NASA Astrophysics Data System (ADS)

De Silva, Liyanage C.; Esther, Kho G. P.

2000-12-01

Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

Neurophysiology and neural engineering: a review.

PubMed

Prochazka, Arthur

2017-08-01

Neurophysiology is the branch of physiology concerned with understanding the function of neural systems. Neural engineering (also known as neuroengineering) is a discipline within biomedical engineering that uses engineering techniques to understand, repair, replace, enhance, or otherwise exploit the properties and functions of neural systems. In most cases neural engineering involves the development of an interface between electronic devices and living neural tissue. This review describes the origins of neural engineering, the explosive development of methods and devices commencing in the late 1950s, and the present-day devices that have resulted. The barriers to interfacing electronic devices with living neural tissues are many and varied, and consequently there have been numerous stops and starts along the way. Representative examples are discussed. None of this could have happened without a basic understanding of the relevant neurophysiology. I also consider examples of how neural engineering is repaying the debt to basic neurophysiology with new knowledge and insight. Copyright © 2017 the American Physiological Society.

Cognitive deficits caused by prefrontal cortical and hippocampal neural disinhibition.

PubMed

Bast, Tobias; Pezze, Marie; McGarrity, Stephanie

2017-10-01

We review recent evidence concerning the significance of inhibitory GABA transmission and of neural disinhibition, that is, deficient GABA transmission, within the prefrontal cortex and the hippocampus, for clinically relevant cognitive functions. Both regions support important cognitive functions, including attention and memory, and their dysfunction has been implicated in cognitive deficits characterizing neuropsychiatric disorders. GABAergic inhibition shapes cortico-hippocampal neural activity, and, recently, prefrontal and hippocampal neural disinhibition has emerged as a pathophysiological feature of major neuropsychiatric disorders, especially schizophrenia and age-related cognitive decline. Regional neural disinhibition, disrupting spatio-temporal control of neural activity and causing aberrant drive of projections, may disrupt processing within the disinhibited region and efferent regions. Recent studies in rats showed that prefrontal and hippocampal neural disinhibition (by local GABA antagonist microinfusion) dysregulates burst firing, which has been associated with important aspects of neural information processing. Using translational tests of clinically relevant cognitive functions, these studies showed that prefrontal and hippocampal neural disinhibition disrupts regional cognitive functions (including prefrontal attention and hippocampal memory function). Moreover, hippocampal neural disinhibition disrupted attentional performance, which does not require the hippocampus but requires prefrontal-striatal circuits modulated by the hippocampus. However, some prefrontal and hippocampal functions (including inhibitory response control) are spared by regional disinhibition. We consider conceptual implications of these findings, regarding the distinct relationships of distinct cognitive functions to prefrontal and hippocampal GABA tone and neural activity. Moreover, the findings support the proposition that prefrontal and hippocampal neural disinhibition contributes to clinically relevant cognitive deficits, and we consider pharmacological strategies for ameliorating cognitive deficits by rebalancing disinhibition-induced aberrant neural activity. Linked Articles This article is part of a themed section on Pharmacology of Cognition: a Panacea for Neuropsychiatric Disease? To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.19/issuetoc. © 2017 The British Pharmacological Society.

Utilising reinforcement learning to develop strategies for driving auditory neural implants.

PubMed

Lee, Geoffrey W; Zambetta, Fabio; Li, Xiaodong; Paolini, Antonio G

2016-08-01

In this paper we propose a novel application of reinforcement learning to the area of auditory neural stimulation. We aim to develop a simulation environment which is based off real neurological responses to auditory and electrical stimulation in the cochlear nucleus (CN) and inferior colliculus (IC) of an animal model. Using this simulator we implement closed loop reinforcement learning algorithms to determine which methods are most effective at learning effective acoustic neural stimulation strategies. By recording a comprehensive set of acoustic frequency presentations and neural responses from a set of animals we created a large database of neural responses to acoustic stimulation. Extensive electrical stimulation in the CN and the recording of neural responses in the IC provides a mapping of how the auditory system responds to electrical stimuli. The combined dataset is used as the foundation for the simulator, which is used to implement and test learning algorithms. Reinforcement learning, utilising a modified n-Armed Bandit solution, is implemented to demonstrate the model's function. We show the ability to effectively learn stimulation patterns which mimic the cochlea's ability to covert acoustic frequencies to neural activity. Time taken to learn effective replication using neural stimulation takes less than 20 min under continuous testing. These results show the utility of reinforcement learning in the field of neural stimulation. These results can be coupled with existing sound processing technologies to develop new auditory prosthetics that are adaptable to the recipients current auditory pathway. The same process can theoretically be abstracted to other sensory and motor systems to develop similar electrical replication of neural signals.

Anosmin-1 is essential for neural crest and cranial placodes formation in Xenopus.

PubMed

Bae, Chang-Joon; Hong, Chang-Soo; Saint-Jeannet, Jean-Pierre

2018-01-15

During embryogenesis vertebrates develop a complex craniofacial skeleton associated with sensory organs. These structures are primarily derived from two embryonic cell populations the neural crest and cranial placodes, respectively. Neural crest cells and cranial placodes are specified through the integrated action of several families of signaling molecules, and the subsequent activation of a complex network of transcription factors. Here we describe the expression and function of Anosmin-1 (Anos1), an extracellular matrix protein, during neural crest and cranial placodes development in Xenopus laevis. Anos1 was identified as a target of Pax3 and Zic1, two transcription factors necessary and sufficient to generate neural crest and cranial placodes. Anos1 is expressed in cranial neural crest progenitors at early neurula stage and in cranial placode derivatives later in development. We show that Anos1 function is required for neural crest and sensory organs development in Xenopus, consistent with the defects observed in Kallmann syndrome patients carrying a mutation in ANOS1. These findings indicate that anos1 has a conserved function in the development of craniofacial structures, and indicate that anos1-depleted Xenopus embryos represent a useful model to analyze the pathogenesis of Kallmann syndrome. Copyright © 2017. Published by Elsevier Inc.

Neural Network Modeling for Gallium Arsenide IC Fabrication Process and Device Characteristics.

NASA Astrophysics Data System (ADS)

Creech, Gregory Lee, I.

This dissertation presents research focused on the utilization of neurocomputing technology to achieve enhanced yield and effective yield prediction in integrated circuit (IC) manufacturing. Artificial neural networks are employed to model complex relationships between material and device characteristics at critical stages of the semiconductor fabrication process. Whole wafer testing was performed on the starting substrate material and during wafer processing at four critical steps: Ohmic or Post-Contact, Post-Recess, Post-Gate and Final, i.e., at completion of fabrication. Measurements taken and subsequently used in modeling include, among others, doping concentrations, layer thicknesses, planar geometries, layer-to-layer alignments, resistivities, device voltages, and currents. The neural network architecture used in this research is the multilayer perceptron neural network (MLPNN). The MLPNN is trained in the supervised mode using the generalized delta learning rule. It has one hidden layer and uses continuous perceptrons. The research focuses on a number of different aspects. First is the development of inter-process stage models. Intermediate process stage models are created in a progressive fashion. Measurements of material and process/device characteristics taken at a specific processing stage and any previous stages are used as input to the model of the next processing stage characteristics. As the wafer moves through the fabrication process, measurements taken at all previous processing stages are used as input to each subsequent process stage model. Secondly, the development of neural network models for the estimation of IC parametric yield is demonstrated. Measurements of material and/or device characteristics taken at earlier fabrication stages are used to develop models of the final DC parameters. These characteristics are computed with the developed models and compared to acceptance windows to estimate the parametric yield. A sensitivity analysis is performed on the models developed during this yield estimation effort. This is accomplished by analyzing the total disturbance of network outputs due to perturbed inputs. When an input characteristic bears no, or little, statistical or deterministic relationship to the output characteristics, it can be removed as an input. Finally, neural network models are developed in the inverse direction. Characteristics measured after the final processing step are used as the input to model critical in-process characteristics. The modeled characteristics are used for whole wafer mapping and its statistical characterization. It is shown that this characterization can be accomplished with minimal in-process testing. The concepts and methodologies used in the development of the neural network models are presented. The modeling results are provided and compared to the actual measured values of each characteristic. An in-depth discussion of these results and ideas for future research are presented.

Translation: screening for novel therapeutics with disease-relevant cell types derived from human stem cell models.

PubMed

Haggarty, Stephen J; Perlis, Roy H

2014-06-15

The advent of somatic cell reprogramming technologies-which enables the generation of patient-specific, induced pluripotent stem cell and other trans-differentiated human neuronal cell models-provides new means of gaining insight into the molecular mechanisms and neural substrates of psychiatric disorders. By allowing a more precise understanding of genotype-phenotype relationship in disease-relevant human cell types, the use of reprogramming technologies in tandem with emerging genome engineering approaches provides a previously "missing link" between basic research and translational efforts. In this review, we summarize advances in applying human pluripotent stem cell and reprogramming technologies to generate specific neural subtypes with a focus on the use of these in vitro systems for the discovery of small molecule-probes and novel therapeutics. Examples are given where human cell models of psychiatric disorders have begun to reveal new mechanistic insight into pathophysiology and simultaneously have provided the foundation for developing disease-relevant, phenotypic assays suitable for both functional genomic and chemical screens. A number of areas for future research are discussed, including the need to develop robust methodology for the reproducible, large-scale production of disease-relevant neural cell types in formats compatible with high-throughput screening modalities, including high-content imaging, multidimensional, signature-based screening, and in vitro network with multielectrode arrays. Limitations, including the challenges in recapitulating neurocircuits and non-cell autonomous phenotypes are discussed. Although these technologies are still in active development, we conclude that, as our understanding of how to efficiently generate and probe the plasticity of patient-specific stem models improves, their utility is likely to advance rapidly. Copyright © 2014 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Neural crest contribution to lingual mesenchyme, epithelium and developing taste papillae and taste buds.

PubMed

Liu, Hong-Xiang; Komatsu, Yoshihiro; Mishina, Yuji; Mistretta, Charlotte M

2012-08-15

The epithelium of mammalian tongue hosts most of the taste buds that transduce gustatory stimuli into neural signals. In the field of taste biology, taste bud cells have been described as arising from "local epithelium", in distinction from many other receptor organs that are derived from neurogenic ectoderm including neural crest (NC). In fact, contribution of NC to both epithelium and mesenchyme in the developing tongue is not fully understood. In the present study we used two independent, well-characterized mouse lines, Wnt1-Cre and P0-Cre that express Cre recombinase in a NC-specific manner, in combination with two Cre reporter mouse lines, R26R and ZEG, and demonstrate a contribution of NC-derived cells to both tongue mesenchyme and epithelium including taste papillae and taste buds. In tongue mesenchyme, distribution of NC-derived cells is in close association with taste papillae. In tongue epithelium, labeled cells are observed in an initial scattered distribution and progress to a clustered pattern between papillae, and within papillae and early taste buds. This provides evidence for a contribution of NC to lingual epithelium. Together with previous reports for the origin of taste bud cells from local epithelium in postnatal mouse, we propose that NC cells migrate into and reside in the epithelium of the tongue primordium at an early embryonic stage, acquire epithelial cell phenotypes, and undergo cell proliferation and differentiation that is involved in the development of taste papillae and taste buds. Our findings lead to a new concept about derivation of taste bud cells that include a NC origin. Copyright © 2012 Elsevier Inc. All rights reserved.

Fibulin-1 Binds to Fibroblast Growth Factor 8 with High Affinity: EFFECTS ON EMBRYO SURVIVAL.

PubMed

Fresco, Victor M; Kern, Christine B; Mohammadi, Moosa; Twal, Waleed O

2016-09-02

Fibulin-1 (FBLN1) is a member of a growing family of extracellular matrix glycoproteins that includes eight members and is involved in cellular functions such as adhesion, migration, and differentiation. FBLN1 has also been implicated in embryonic heart and valve development and in the formation of neural crest-derived structures, including aortic arch, thymus, and cranial nerves. Fibroblast growth factor 8 (FGF8) is a member of a large family of growth factors, and its functions include neural crest cell (NCC) maintenance, specifically NCC migration as well as patterning of structures formed from NCC such as outflow tract and cranial nerves. In this report, we sought to investigate whether FBLN1 and FGF8 have cooperative roles in vivo given their influence on the development of the same NCC-derived structures. Surface plasmon resonance binding data showed that FBLN1 binds tightly to FGF8 and prevents its enzymatic degradation by ADAM17. Moreover, overexpression of FBLN1 up-regulates FGF8 gene expression, and down-regulation of FBLN1 by siRNA inhibits FGF8 expression. The generation of a double mutant Fbln1 and Fgf8 mice (Fbln1(-/-) and Fgf8(-/-)) showed that haplo-insufficiency (Fbln1(+/-) and Fgf8(+/-)) resulted in increased embryonic mortality compared with single heterozygote crosses. The mortality of the FGF8/Fbln1 double heterozygote embryos occurred between 14.5 and 16.5 days post-coitus. In conclusion, FBLN1/FGF8 interaction plays a role in survival of vertebrate embryos, and reduced levels of both proteins resulted in added mortality in utero The FBLN1/FGF8 interaction may also be involved in the survival of neural crest cell population during development. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

Vestigial-like 3 is a novel Ets1 interacting partner and regulates trigeminal nerve formation and cranial neural crest migration

PubMed Central

Simon, Emilie; Thézé, Nadine; Fédou, Sandrine; Thiébaud, Pierre

2017-01-01

ABSTRACT Drosophila Vestigial is the founding member of a protein family containing a highly conserved domain, called Tondu, which mediates their interaction with members of the TEAD family of transcription factors (Scalloped in Drosophila). In Drosophila, the Vestigial/Scalloped complex controls wing development by regulating the expression of target genes through binding to MCAT sequences. In vertebrates, there are four Vestigial-like genes, the functions of which are still not well understood. Here, we describe the regulation and function of vestigial-like 3 (vgll3) during Xenopus early development. A combination of signals, including FGF8, Wnt8a, Hoxa2, Hoxb2 and retinoic acid, limits vgll3 expression to hindbrain rhombomere 2. We show that vgll3 regulates trigeminal placode and nerve formation and is required for normal neural crest development by affecting their migration and adhesion properties. At the molecular level, vgll3 is a potent activator of pax3, zic1, Wnt and FGF, which are important for brain patterning and neural crest cell formation. Vgll3 interacts in the embryo with Tead proteins but unexpectedly with Ets1, with which it is able to stimulate a MCAT driven luciferase reporter gene. Our findings highlight a critical function for vgll3 in vertebrate early development. PMID:28870996

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China.

PubMed

Zhang, Lei; Zou, Zhihong; Shan, Wei

2017-06-01

Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO 4 and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction. Copyright © 2016. Published by Elsevier B.V.

Genetic Removal of Matrix Metalloproteinase 9 Rescues the Symptoms of Fragile X Syndrome in a Mouse Model

PubMed Central

Sidhu, Harpreet; Dansie, Lorraine E.; Hickmott, Peter W.

2014-01-01

Fmr1 knock-out (ko) mice display key features of fragile X syndrome (FXS), including delayed dendritic spine maturation and FXS-associated behaviors, such as poor socialization, obsessive-compulsive behavior, and hyperactivity. Here we provide conclusive evidence that matrix metalloproteinase-9 (MMP-9) is necessary to the development of FXS-associated defects in Fmr1 ko mice. Genetic disruption of Mmp-9 rescued key aspects of Fmr1 deficiency, including dendritic spine abnormalities, abnormal mGluR5-dependent LTD, as well as aberrant behaviors in open field and social novelty tests. Remarkably, MMP-9 deficiency also corrected non-neural features of Fmr1 deficiency—specifically macroorchidism—indicating that MMP-9 dysregulation contributes to FXS-associated abnormalities outside the CNS. Further, MMP-9 deficiency suppressed elevations of Akt, mammalian target of rapamycin, and eukaryotic translation initiation factor 4E phosphorylation seen in Fmr1 ko mice, which are also associated with other autistic spectrum disorders. These findings establish that MMP-9 is critical to the mechanisms responsible for neural and non-neural aspects of the FXS phenotype. PMID:25057190

Hypothalamic neural systems controlling the female reproductive life cycle: Gonadotropin-releasing hormone, glutamate, and GABA

PubMed Central

Maffucci, Jacqueline A.; Gore, Andrea C.

2009-01-01

The hypothalamic-pituitary-gonadal (HPG) axis undergoes a number of changes throughout the reproductive life cycle that are responsible for the development, puberty, adulthood, and senescence of reproductive systems. This natural progression is dictated by the neural network controlling the hypothalamus including the cells that synthesize and release gonadotropin-releasing hormone (GnRH) and their regulatory neurotransmitters. Glutamate and GABA are the primary excitatory and inhibitory neurotransmitters in the central nervous system, and as such contribute a great deal to modulating this axis throughout the lifetime via their actions on receptors in the hypothalamus, both directly on GnRH neurons as well as indirectly though other hypothalamic neural networks. Interactions among GnRH neurons, glutamate, and GABA, including the regulation of GnRH gene and protein expression, hormone release, and modulation by estrogen, are critical to age-appropriate changes in reproductive function. Here, we present evidence for the modulation of GnRH neurosecretory cells by the balance of glutamate and GABA in the hypothalamus, and the functional consequences of these interactions on reproductive physiology across the life cycle. PMID:19349036

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Gao, Rong

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

An amphioxus winged helix/forkhead gene, AmphiFoxD: insights into vertebrate neural crest evolution

NASA Technical Reports Server (NTRS)

Yu, Jr-Kai; Holland, Nicholas D.; Holland, Linda Z.

2002-01-01

During amphioxus development, the neural plate is bordered by cells expressing many genes with homologs involved in vertebrate neural crest induction. However, these amphioxus cells evidently lack additional genetic programs for the cell delaminations, migrations, and differentiations characterizing definitive vertebrate neural crest. We characterize an amphioxus winged helix/forkhead gene (AmphiFoxD) closely related to vertebrate FoxD genes. Phylogenetic analysis indicates that the AmphiFoxD is basal to vertebrate FoxD1, FoxD2, FoxD3, FoxD4, and FoxD5. One of these vertebrate genes (FoxD3) consistently marks neural crest during development. Early in amphioxus development, AmphiFoxD is expressed medially in the anterior neural plate as well as in axial (notochordal) and paraxial mesoderm; later, the gene is expressed in the somites, notochord, cerebral vesicle (diencephalon), and hindgut endoderm. However, there is never any expression in cells bordering the neural plate. We speculate that an AmphiFoxD homolog in the common ancestor of amphioxus and vertebrates was involved in histogenic processes in the mesoderm (evagination and delamination of the somites and notochord); then, in the early vertebrates, descendant paralogs of this gene began functioning in the presumptive neural crest bordering the neural plate to help make possible the delaminations and cell migrations that characterize definitive vertebrate neural crest. Copyright 2002 Wiley-Liss, Inc.

Neural correlates of deception in social contexts in normally developing children

PubMed Central

Yokota, Susumu; Taki, Yasuyuki; Hashizume, Hiroshi; Sassa, Yuko; Thyreau, Benjamin; Tanaka, Mari; Kawashima, Ryuta

2013-01-01

Deception is related to the ability to inhibit prepotent responses and to engage in mental tasks such as anticipating responses and inferring what another person knows, especially in social contexts. However, the neural correlates of deception processing, which requires mentalizing, remain unclear. Using functional magnetic resonance imaging (fMRI), we examined the neural correlates of deception, including mentalization, in social contexts in normally developing children. Healthy right-handed children (aged 8–9 years) were scanned while performing interactive games involving deception. The games varied along two dimensions: the type of reply (deception and truth) and the type of context (social and less social). Participants were instructed to deceive a witch and to tell the truth to a girl. Under the social-context conditions, participants were asked to consider what they inferred about protagonists' preferences from their facial expressions when responding to questions. Under the less-social-context conditions, participants did not need to consider others' preferences. We found a significantly greater response in the right precuneus under the social-context than under less-social-context conditions. Additionally, we found marginally greater activation in the right inferior parietal lobule (IPL) under the deception than under the truth condition. These results suggest that deception in a social context requires not only inhibition of prepotent responses but also engagement in mentalizing processes. This study provides the first evidence of the neural correlates of the mentalizing processes involved in deception in normally developing children. PMID:23730281

Intergenerational neural mediators of early-life anxious temperament.

PubMed

Fox, Andrew S; Oler, Jonathan A; Shackman, Alexander J; Shelton, Steven E; Raveendran, Muthuswamy; McKay, D Reese; Converse, Alexander K; Alexander, Andrew; Davidson, Richard J; Blangero, John; Rogers, Jeffrey; Kalin, Ned H

2015-07-21

Understanding the heritability of neural systems linked to psychopathology is not sufficient to implicate them as intergenerational neural mediators. By closely examining how individual differences in neural phenotypes and psychopathology cosegregate as they fall through the family tree, we can identify the brain systems that underlie the parent-to-child transmission of psychopathology. Although research has identified genes and neural circuits that contribute to the risk of developing anxiety and depression, the specific neural systems that mediate the inborn risk for these debilitating disorders remain unknown. In a sample of 592 young rhesus monkeys that are part of an extended multigenerational pedigree, we demonstrate that metabolism within a tripartite prefrontal-limbic-midbrain circuit mediates some of the inborn risk for developing anxiety and depression. Importantly, although brain volume is highly heritable early in life, it is brain metabolism-not brain structure-that is the critical intermediary between genetics and the childhood risk to develop stress-related psychopathology.

Developing Scene Understanding Neural Software for Realistic Autonomous Outdoor Missions

DTIC Science & Technology

2017-09-01

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

PubMed

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

1999-02-01

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

Molecular parallels between neural and vascular development.

PubMed

Eichmann, Anne; Thomas, Jean-Léon

2013-01-01

The human central nervous system (CNS) features a network of ~400 miles of blood vessels that receives >20% of the body's cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood-brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors.

Innovations in interventional pain management of chronic spinal pain.

PubMed

Manchikanti, Laxmaiah; Boswell, Mark V; Hirsch, Joshua A

2016-09-01

Interventional pain management dates back to 1901, with significant innovations, which include the definition, literature synthesis, pathophysiology, and technical interventions. Interventional pain management and interventional techniques include neural blockade, neural ablative procedures, spinal cord and peripheral nerve stimulation, intrathecal drug delivery systems, minimally invasive lumbar decompression (MILD®), percutaneous endoscopic spinal decompression, and regenerative medicine. In addition, advances are also related to the evidence synthesis of comparative effectiveness research. Expert commentary: Multiple innovations in interventional pain management and potential innovations may reduce costs and improve care and outcomes with proper evidence synthesis and application of principles of evidence-based medicine. Innovations in interventional pain management in managing chronic spinal pain depend on extensive research and appropriate evidence synthesis. Innovations should be developed in conjunction with health care policy based on principles of evidence-based medicine.

Opportunities and questions for the fundamental biological sciences in space

NASA Technical Reports Server (NTRS)

Sharp, Joseph C.; Vernikos, Joan

1992-01-01

The nature of biological issues which can be addressed during long-term space missions is briefly discussed. These issues include structure, from cell to organ to organism; function, the regulation of systems such as immunology, neural sciences, and behavior; and reproduction and development.

Iniencephaly

MedlinePlus

... other neural tube defects. Information from the National Library of Medicine’s MedlinePlus Neural Tube Defects ... by improper closure of the neural tube (the part of a human embryo that becomes the brain and spinal cord) during fetal development. Iniencephaly is in the same family of neural ...

Toward the Development of an Artificial Brain on a Micropatterned and Material-Regulated Biochip by Guiding and Promoting the Differentiation and Neurite Outgrowth of Neural Stem/Progenitor Cells.

PubMed

Liu, Yung-Chiang; Lee, I-Chi; Lei, Kin Fong

2018-02-14

An in vitro model mimicking the in vivo environment of the brain must be developed to study neural communication and regeneration and to obtain an understanding of cellular and molecular responses. In this work, a multilayered neural network was successfully constructed on a biochip by guiding and promoting neural stem/progenitor cell differentiation and network formation. The biochip consisted of 3 × 3 arrays of cultured wells connected with channels. Neurospheroids were cultured on polyelectrolyte multilayer (PEM) films in the culture wells. Neurite outgrowth and neural differentiation were guided and promoted by the micropatterns and the PEM films. After 5 days in culture, a 3 × 3 neural network was constructed on the biochip. The function and the connections of the network were evaluated by immunocytochemistry and impedance measurements. Neurons were generated and produced functional and recyclable synaptic vesicles. Moreover, the electrical connections of the neural network were confirmed by measuring the impedance across the neurospheroids. The current work facilitates the development of an artificial brain on a chip for investigations of electrical stimulations and recordings of multilayered neural communication and regeneration.

Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location

PubMed Central

Crago, Patrick E; Makowski, Nathan S

2014-01-01

Objective Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. Approach We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Main Results Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases.. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. Significance This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation. PMID:25161163

Alteration of neural action potential patterns by axonal stimulation: the importance of stimulus location

NASA Astrophysics Data System (ADS)

Crago, Patrick E.; Makowski, Nathaniel S.

2014-10-01

Objective. Stimulation of peripheral nerves is often superimposed on ongoing motor and sensory activity in the same axons, without a quantitative model of the net action potential train at the axon endpoint. Approach. We develop a model of action potential patterns elicited by superimposing constant frequency axonal stimulation on the action potentials arriving from a physiologically activated neural source. The model includes interactions due to collision block, resetting of the neural impulse generator, and the refractory period of the axon at the point of stimulation. Main results. Both the mean endpoint firing rate and the probability distribution of the action potential firing periods depend strongly on the relative firing rates of the two sources and the intersite conduction time between them. When the stimulus rate exceeds the neural rate, neural action potentials do not reach the endpoint and the rate of endpoint action potentials is the same as the stimulus rate, regardless of the intersite conduction time. However, when the stimulus rate is less than the neural rate, and the intersite conduction time is short, the two rates partially sum. Increases in stimulus rate produce non-monotonic increases in endpoint rate and continuously increasing block of neurally generated action potentials. Rate summation is reduced and more neural action potentials are blocked as the intersite conduction time increases. At long intersite conduction times, the endpoint rate simplifies to being the maximum of either the neural or the stimulus rate. Significance. This study highlights the potential of increasing the endpoint action potential rate and preserving neural information transmission by low rate stimulation with short intersite conduction times. Intersite conduction times can be decreased with proximal stimulation sites for muscles and distal stimulation sites for sensory endings. The model provides a basis for optimizing experiments and designing neuroprosthetic interventions involving motor or sensory stimulation.

[Neurobiology of addictive behavior].

PubMed

Ivlieva, N Iu

2011-01-01

Addictive behavior developes after repeated substance use and it typically include a strong desire to take the drug, difficulties in controlling its use, persisting in its use despite harmful consequences, a higher priority given to the drug use than to other activities. Relapse, the resumption of drug taking after periods of abstinence, remains the major problem for the treatment of addiction. The process of drug addiction shares striking commonalities with neural plasticity associated with natural reward learning and memory and is caused primarily by drug-induced sensitization in the brain mesocorticolimbic systems that attribute incentive salience to reward-associated stimuli. The switch from controlled to compulsive drug seeking represents a transition at the neural level from prefrontal cortical to striatal control. Current neurophysiologic evidence suggests that the development of addiction is to some extent due to neurochemical stimulation of the midbrain dopaminergic system that is traditionally considered as a 'common neural currency' for rewards of most kinds. Addictions are a result of the interplay of multiple genetic and environmental factors. They are characterized by phenotypic and genetic heterogeneity as well as polygenicity. Environmental factors are crucial in addiction vulnerability and resistese too.

Brain-Inspired Constructive Learning Algorithms with Evolutionally Additive Nonlinear Neurons

NASA Astrophysics Data System (ADS)

Fang, Le-Heng; Lin, Wei; Luo, Qiang

In this article, inspired partially by the physiological evidence of brain’s growth and development, we developed a new type of constructive learning algorithm with evolutionally additive nonlinear neurons. The new algorithms have remarkable ability in effective regression and accurate classification. In particular, the algorithms are able to sustain a certain reduction of the loss function when the dynamics of the trained network are bogged down in the vicinity of the local minima. The algorithm augments the neural network by adding only a few connections as well as neurons whose activation functions are nonlinear, nonmonotonic, and self-adapted to the dynamics of the loss functions. Indeed, we analytically demonstrate the reduction dynamics of the algorithm for different problems, and further modify the algorithms so as to obtain an improved generalization capability for the augmented neural networks. Finally, through comparing with the classical algorithm and architecture for neural network construction, we show that our constructive learning algorithms as well as their modified versions have better performances, such as faster training speed and smaller network size, on several representative benchmark datasets including the MNIST dataset for handwriting digits.

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

PubMed Central

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

2012-01-01

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

Skeletogenesis in the swell shark Cephaloscyllium ventriosum.

PubMed

Eames, B Frank; Allen, Nancy; Young, Jonathan; Kaplan, Angelo; Helms, Jill A; Schneider, Richard A

2007-05-01

Extant chondrichthyans possess a predominantly cartilaginous skeleton, even though primitive chondrichthyans produced bone. To gain insights into this peculiar skeletal evolution, and in particular to evaluate the extent to which chondrichthyan skeletogenesis retains features of an osteogenic programme, we performed a histological, histochemical and immunohistochemical analysis of the entire embryonic skeleton during development of the swell shark Cephaloscyllium ventriosum. Specifically, we compared staining properties among various mineralizing tissues, including neural arches of the vertebrae, dermal tissues supporting oral denticles and Meckel's cartilage of the lower jaw. Patterns of mineralization were predicted by spatially restricted alkaline phosphatase activity earlier in development. Regarding evidence for an osteogenic programme in extant sharks, a mineralized tissue in the perichondrium of C. ventriosum neural arches, and to a lesser extent a tissue supporting the oral denticle, displayed numerous properties of bone. Although we uncovered many differences between tissues in Meckel's cartilage and neural arches of C. ventriosum, both elements impart distinct tissue characteristics to the perichondral region. Considering the evolution of osteogenic processes, shark skeletogenesis may illuminate the transition from perichondrium to periosteum, which is a major bone-forming tissue during the process of endochondral ossification.

A Comparison of Conventional Linear Regression Methods and Neural Networks for Forecasting Educational Spending.

ERIC Educational Resources Information Center

Baker, Bruce D.; Richards, Craig E.

1999-01-01

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

Neurodynamics With Spatial Self-Organization

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1993-01-01

Report presents theoretical study of dynamics of neural network organizing own response in both phase space and in position space. Postulates several mathematical models of dynamics including spatial derivatives representing local interconnections among neurons. Shows how neural responses propagate via these interconnections and how spatial pattern of neural responses formed in homogeneous biological neural network.

Generalized Adaptive Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1993-01-01

Mathematical model of supervised learning by artificial neural network provides for simultaneous adjustments of both temperatures of neurons and synaptic weights, and includes feedback as well as feedforward synaptic connections. Extension of mathematical model described in "Adaptive Neurons For Artificial Neural Networks" (NPO-17803). Dynamics of neural network represented in new model by less-restrictive continuous formalism.

Recycling signals in the neural crest.

PubMed

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.

Extrapolation of a predictive model for growth of a low inoculum size of Salmonella typhimurium DT104 on chicken skin to higher inoculum sizes

USDA-ARS?s Scientific Manuscript database

Validation of model predictions for independent variables not included in model development can save time and money by identifying conditions for which new models are not needed. A single strain of Salmonella Typhimurium DT104 was used to develop a general regression neural network model for growth...

Neural Stem Cells (NSCs) and Proteomics*

PubMed Central

Shoemaker, Lorelei D.; Kornblum, Harley I.

2016-01-01

Neural stem cells (NSCs) can self-renew and give rise to the major cell types of the CNS. Studies of NSCs include the investigation of primary, CNS-derived cells as well as animal and human embryonic stem cell (ESC)-derived and induced pluripotent stem cell (iPSC)-derived sources. NSCs provide a means with which to study normal neural development, neurodegeneration, and neurological disease and are clinically relevant sources for cellular repair to the damaged and diseased CNS. Proteomics studies of NSCs have the potential to delineate molecules and pathways critical for NSC biology and the means by which NSCs can participate in neural repair. In this review, we provide a background to NSC biology, including the means to obtain them and the caveats to these processes. We then focus on advances in the proteomic interrogation of NSCs. This includes the analysis of posttranslational modifications (PTMs); approaches to analyzing different proteomic compartments, such the secretome; as well as approaches to analyzing temporal differences in the proteome to elucidate mechanisms of differentiation. We also discuss some of the methods that will undoubtedly be useful in the investigation of NSCs but which have not yet been applied to the field. While many proteomics studies of NSCs have largely catalogued the proteome or posttranslational modifications of specific cellular states, without delving into specific functions, some have led to understandings of functional processes or identified markers that could not have been identified via other means. Many challenges remain in the field, including the precise identification and standardization of NSCs used for proteomic analyses, as well as how to translate fundamental proteomics studies to functional biology. The next level of investigation will require interdisciplinary approaches, combining the skills of those interested in the biochemistry of proteomics with those interested in modulating NSC function. PMID:26494823

Prenatal cocaine exposure, illicit-substance use and stress and craving processes during adolescence.

PubMed

Yip, Sarah W; Lacadie, Cheryl M; Sinha, Rajita; Mayes, Linda C; Potenza, Marc N

2016-01-01

Prenatal cocaine exposure (PCE) is associated with increased rates of illicit-substance use during adolescence. In addition, both PCE and illicit-substance use are associated with alterations in cortico-striato-limbic neurocircuitry, development of which is ongoing throughout adolescence. However, the relationship between illicit-substance use, PCE and functional neural responses has not previously been assessed concurrently. Sixty-eight adolescents were recruited from an ongoing longitudinal study of childhood and adolescent development. All participants had been followed since birth. Functional magnetic resonance imaging (fMRI) data were acquired during presentation of personalized stressful, favorite-food and neutral/relaxing imagery scripts and compared between 46 PCE and 22 non-prenatally-drug-exposed (NDE) adolescents with and without lifetime illicit-substance use initiation. Data were analyzed using multi-level ANOVAs (pFWE<.05). There was a significant three-way interaction between illicit-substance use, PCE status and cue condition on neural responses within primarily cortical brain regions, including regions of the left and right insula. Among PCE versus NDE adolescents, illicit-substance use was associated with decreased subcortical and increased cortical activity during the favorite-food condition, whereas the opposite pattern of activation was observed during the neutral/relaxing condition. Among PCE versus NDE adolescents, illicit-substance use during stress processing was associated with decreased activity in cortical and subcortical regions including amygdala, hippocampus and prefrontal cortex. Neural activity within cortico-striato-limbic regions was significantly negatively associated with subjective ratings of anxiety and craving among illicit-substance users, but not among non-users. These findings suggest different neural substrates of experimentation with illicit drugs between adolescents with and without in utero cocaine exposure. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Intention Concepts and Brain-Machine Interfacing

PubMed Central

Thinnes-Elker, Franziska; Iljina, Olga; Apostolides, John Kyle; Kraemer, Felicitas; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio

2012-01-01

Intentions, including their temporal properties and semantic content, are receiving increased attention, and neuroscientific studies in humans vary with respect to the topography of intention-related neural responses. This may reflect the fact that the kind of intentions investigated in one study may not be exactly the same kind investigated in the other. Fine-grained intention taxonomies developed in the philosophy of mind may be useful to identify the neural correlates of well-defined types of intentions, as well as to disentangle them from other related mental states, such as mere urges to perform an action. Intention-related neural signals may be exploited by brain-machine interfaces (BMIs) that are currently being developed to restore speech and motor control in paralyzed patients. Such BMI devices record the brain activity of the agent, interpret (“decode”) the agent’s intended action, and send the corresponding execution command to an artificial effector system, e.g., a computer cursor or a robotic arm. In the present paper, we evaluate the potential of intention concepts from philosophy of mind to improve the performance and safety of BMIs based on higher-order, intention-related control signals. To this end, we address the distinction between future-, present-directed, and motor intentions, as well as the organization of intentions in time, specifically to what extent it is sequential or hierarchical. This has consequences as to whether these different types of intentions can be expected to occur simultaneously or not. We further illustrate how it may be useful or even necessary to distinguish types of intentions exposited in philosophy, including yes- vs. no-intentions and oblique vs. direct intentions, to accurately decode the agent’s intentions from neural signals in practical BMI applications. PMID:23162504

EDITORIAL: Focus on the neural interface Focus on the neural interface

NASA Astrophysics Data System (ADS)

Durand, Dominique M.

2009-10-01

The possibility of an effective connection between neural tissue and computers has inspired scientists and engineers to develop new ways of controlling and obtaining information from the nervous system. These applications range from `brain hacking' to neural control of artificial limbs with brain signals. Notwithstanding the significant advances in neural prosthetics in the last few decades and the success of some stimulation devices such as cochlear prosthesis, neurotechnology remains below its potential for restoring neural function in patients with nervous system disorders. One of the reasons for this limited impact can be found at the neural interface and close attention to the integration between electrodes and tissue should improve the possibility of successful outcomes. The neural interfaces research community consists of investigators working in areas such as deep brain stimulation, functional neuromuscular/electrical stimulation, auditory prostheses, cortical prostheses, neuromodulation, microelectrode array technology, brain-computer/machine interfaces. Following the success of previous neuroprostheses and neural interfaces workshops, funding (from NIH) was obtained to establish a biennial conference in the area of neural interfaces. The first Neural Interfaces Conference took place in Cleveland, OH in 2008 and several topics from this conference have been selected for publication in this special section of the Journal of Neural Engineering. Three `perspectives' review the areas of neural regeneration (Corredor and Goldberg), cochlear implants (O'Leary et al) and neural prostheses (Anderson). Seven articles focus on various aspects of neural interfacing. One of the most popular of these areas is the field of brain-computer interfaces. Fraser et al, report on a method to generate robust control with simple signal processing algorithms of signals obtained with electrodes implanted in the brain. One problem with implanted electrode arrays, however, is that they can fail to record reliably neural signals for long periods of time. McConnell et al show that by measuring the impedance of the tissue, one can evaluate the extent of the tissue response to the presence of the electrode. Another problem with the neural interface is the mismatch of the mechanical properties between electrode and tissue. Basinger et al use finite element modeling to analyze this mismatch in retinal prostheses and guide the design of new implantable devices. Electrical stimulation has been the method of choice to activate externally the nervous system. However, Zhang et al show that a novel dual hybrid device integrating electrical and optical stimulation can provide an effective interface for simultaneous recording and stimulation. By interfacing an EMG recording system and a movement detection system, Johnson and Fuglevand develop a model capable of predicting muscle activity during movement that could be important for the development of motor prostheses. Sensory restoration is another unsolved problem in neural prostheses. By developing a novel interface between the dorsal root ganglia and electrodes arrays, Gaunt et al show that it is possible to recruit afferent fibers for sensory substitution. Finally, by interfacing directly with muscles, Jung and colleagues show that stimulation of muscles involved in locomotion following spinal cord damage in rats can provide an effective treatment modality for incomplete spinal cord injury. This series of articles clearly shows that the interface is indeed one of the keys to successful therapeutic neural devices. The next Neural Interfaces Conference will take place in Los Angeles, CA in June 2010 and one can expect to see new developments in neural engineering obtained by focusing on the neural interface.

Newly developed double neural network concept for reliable fast plasma position control

NASA Astrophysics Data System (ADS)

Jeon, Young-Mu; Na, Yong-Su; Kim, Myung-Rak; Hwang, Y. S.

2001-01-01

Neural network is considered as a parameter estimation tool in plasma controls for next generation tokamak such as ITER. The neural network has been reported to be so accurate and fast for plasma equilibrium identification that it may be applied to the control of complex tokamak plasmas. For this application, the reliability of the conventional neural network needs to be improved. In this study, a new idea of double neural network is developed to achieve this. The new idea has been applied to simple plasma position identification of KSTAR tokamak for feasibility test. Characteristics of the concept show higher reliability and fault tolerance even in severe faulty conditions, which may make neural network applicable to plasma control reliably and widely in future tokamaks.

Plasticity-related genes in brain development and amygdala-dependent learning.

PubMed

Ehrlich, D E; Josselyn, S A

2016-01-01

Learning about motivationally important stimuli involves plasticity in the amygdala, a temporal lobe structure. Amygdala-dependent learning involves a growing number of plasticity-related signaling pathways also implicated in brain development, suggesting that learning-related signaling in juveniles may simultaneously influence development. Here, we review the pleiotropic functions in nervous system development and amygdala-dependent learning of a signaling pathway that includes brain-derived neurotrophic factor (BDNF), extracellular signaling-related kinases (ERKs) and cyclic AMP-response element binding protein (CREB). Using these canonical, plasticity-related genes as an example, we discuss the intersection of learning-related and developmental plasticity in the immature amygdala, when aversive and appetitive learning may influence the developmental trajectory of amygdala function. We propose that learning-dependent activation of BDNF, ERK and CREB signaling in the immature amygdala exaggerates and accelerates neural development, promoting amygdala excitability and environmental sensitivity later in life. © 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Visual development in primates: Neural mechanisms and critical periods

PubMed Central

Kiorpes, Lynne

2015-01-01

Despite many decades of research into the development of visual cortex, it remains unclear what neural processes set limitations on the development of visual function and define its vulnerability to abnormal visual experience. This selected review examines the development of visual function and its neural correlates, and highlights the fact that in most cases receptive field properties of infant neurons are substantially more mature than infant visual function. One exception is temporal resolution, which can be accounted for by resolution of neurons at the level of the LGN. In terms of spatial vision, properties of single neurons alone are not sufficient to account for visual development. Different visual functions develop over different time courses. Their onset may be limited by the existence of neural response properties that support a given perceptual ability, but the subsequent time course of maturation to adult levels remains unexplained. Several examples are offered suggesting that taking account of weak signaling by infant neurons, correlated firing, and pooled responses of populations of neurons brings us closer to an understanding of the relationship between neural and behavioral development. PMID:25649764

Insights into neural crest development and evolution from genomic analysis

PubMed Central

Simões-Costa, Marcos; Bronner, Marianne E.

2013-01-01

The neural crest is an excellent model system for the study of cell type diversification during embryonic development due to its multipotency, motility, and ability to form a broad array of derivatives ranging from neurons and glia, to cartilage, bone, and melanocytes. As a uniquely vertebrate cell population, it also offers important clues regarding vertebrate origins. In the past 30 yr, introduction of recombinant DNA technology has facilitated the dissection of the genetic program controlling neural crest development and has provided important insights into gene regulatory mechanisms underlying cell migration and differentiation. More recently, new genomic approaches have provided a platform and tools that are changing the depth and breadth of our understanding of neural crest development at a “systems” level. Such advances provide an insightful view of the regulatory landscape of neural crest cells and offer a new perspective on developmental as well as stem cell and cancer biology. PMID:23817048

Aminopropyl carbazole analogues as potent enhancers of neurogenesis.

PubMed

Yoon, Hye Jin; Kong, Sun-Young; Park, Min-Hye; Cho, Yongsung; Kim, Sung-Eun; Shin, Jae-Yeon; Jung, Sunghye; Lee, Jiyoun; Farhanullah; Kim, Hyun-Jung; Lee, Jeewoo

2013-11-15

Neural stem cells are multipotent and self-renewing cells that can differentiate into new neurons and hold great promise for treating various neurological disorders including multiple sclerosis, Parkinson's disease, and Alzheimer's disease. Small molecules that can trigger neurogenesis and neuroprotection are particularly useful not only because of their therapeutic implications but also because they can provide an invaluable tool to study the mechanisms of neurogenesis. In this report, we have developed and screened 25 aminopropyl carbazole derivatives that can enhance neurogenesis of cultured neural stem cells. Among these analogues, compound 9 demonstrated an excellent proneurogenic and neuroprotective activity with no apparent toxicity. We believe that compound 9 can serve as an excellent lead to develop various analogues and to study the underlying mechanisms of neurogenesis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Oxytocin during Development: Possible Organizational Effects on Behavior.

PubMed

Miller, Travis V; Caldwell, Heather K

2015-01-01

Oxytocin (Oxt) is a neurohormone known for its physiological roles associated with lactation and parturition in mammals. Oxt can also profoundly influence mammalian social behaviors such as affiliative, parental, and aggressive behaviors. While the acute effects of Oxt signaling on adult behavior have been heavily researched in many species, including humans, the developmental effects of Oxt on the brain and behavior are just beginning to be explored. There is evidence that Oxt in early postnatal and peripubertal development, and perhaps during prenatal life, affects adult behavior by altering neural structure and function. However, the specific mechanisms by which this occurs remain unknown. Thus, this review will detail what is known about how developmental Oxt impacts behavior as well as explore the specific neurochemicals and neural substrates that are important to these behaviors.

Time Series Neural Network Model for Part-of-Speech Tagging Indonesian Language

NASA Astrophysics Data System (ADS)

Tanadi, Theo

2018-03-01

Part-of-speech tagging (POS tagging) is an important part in natural language processing. Many methods have been used to do this task, including neural network. This paper models a neural network that attempts to do POS tagging. A time series neural network is modelled to solve the problems that a basic neural network faces when attempting to do POS tagging. In order to enable the neural network to have text data input, the text data will get clustered first using Brown Clustering, resulting a binary dictionary that the neural network can use. To further the accuracy of the neural network, other features such as the POS tag, suffix, and affix of previous words would also be fed to the neural network.

High-Density Stretchable Electrode Grids for Chronic Neural Recording

PubMed Central

Tybrandt, Klas; Khodagholy, Dion; Dielacher, Bernd; Stauffer, Flurin; Renz, Aline F.; Buzsáki, György; Vörös, János

2018-01-01

Electrical interfacing with neural tissue is key to advancing diagnosis and therapies for neurological disorders, as well as providing detailed information about neural signals. A challenge for creating long-term stable interfaces between electronics and neural tissue is the huge mechanical mismatch between the systems. So far, materials and fabrication processes have restricted the development of soft electrode grids able to combine high performance, long-term stability, and high electrode density, aspects all essential for neural interfacing. Here, this challenge is addressed by developing a soft, high-density, stretchable electrode grid based on an inert, high-performance composite material comprising gold-coated titanium dioxide nanowires embedded in a silicone matrix. The developed grid can resolve high spatiotemporal neural signals from the surface of the cortex in freely moving rats with stable neural recording quality and preserved electrode signal coherence during 3 months of implantation. Due to its flexible and stretchable nature, it is possible to minimize the size of the craniotomy required for placement, further reducing the level of invasiveness. The material and device technology presented herein have potential for a wide range of emerging biomedical applications. PMID:29488263

Beta-Actin Is Required for Proper Mouse Neural Crest Ontogeny

PubMed Central

Tondeleir, Davina; Noelanders, Rivka; Bakkali, Karima; Ampe, Christophe

2014-01-01

The mouse genome consists of six functional actin genes of which the expression patterns are temporally and spatially regulated during development and in the adult organism. Deletion of beta-actin in mouse is lethal during embryonic development, although there is compensatory expression of other actin isoforms. This suggests different isoform specific functions and, more in particular, an important function for beta-actin during early mammalian development. We here report a role for beta-actin during neural crest ontogeny. Although beta-actin null neural crest cells show expression of neural crest markers, less cells delaminate and their migration arrests shortly after. These phenotypes were associated with elevated apoptosis levels in neural crest cells, whereas proliferation levels were unchanged. Specifically the pre-migratory neural crest cells displayed higher levels of apoptosis, suggesting increased apoptosis in the neural tube accounts for the decreased amount of migrating neural crest cells seen in the beta-actin null embryos. These cells additionally displayed a lack of membrane bound N-cadherin and dramatic decrease in cadherin-11 expression which was more pronounced in the pre-migratory neural crest population, potentially indicating linkage between the cadherin-11 expression and apoptosis. By inhibiting ROCK ex vivo, the knockout neural crest cells regained migratory capacity and cadherin-11 expression was upregulated. We conclude that the presence of beta-actin is vital for survival, specifically of pre-migratory neural crest cells, their proper emigration from the neural tube and their subsequent migration. Furthermore, the absence of beta-actin affects cadherin-11 and N-cadherin function, which could partly be alleviated by ROCK inhibition, situating the Rho-ROCK signaling in a feedback loop with cadherin-11. PMID:24409333

Deep learning classification in asteroseismology using an improved neural network: results on 15 000 Kepler red giants and applications to K2 and TESS data

NASA Astrophysics Data System (ADS)

Hon, Marc; Stello, Dennis; Yu, Jie

2018-05-01

Deep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower frequency resolution spectra expected from these missions. Additionally, we provide new classifications for 8633 Kepler red giants, out of which 426 have previously not been classified using asteroseismology. This brings the total to 14983 Kepler red giants classified with our new neural network. We also verify that our classifiers are remarkably robust to suboptimal data, including low signal-to-noise and incorrect training truth labels.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Myoung Woo; Moon, Young Joon; Yang, Mal Sook

2007-06-29

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,more » 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.« less

Modeling Behavioral Experiment Interaction and Environmental Stimuli for a Synthetic C. elegans.

PubMed

Mujika, Andoni; Leškovský, Peter; Álvarez, Roberto; Otaduy, Miguel A; Epelde, Gorka

2017-01-01

This paper focusses on the simulation of the neural network of the Caenorhabditis elegans living organism, and more specifically in the modeling of the stimuli applied within behavioral experiments and the stimuli that is generated in the interaction of the C. elegans with the environment. To the best of our knowledge, all efforts regarding stimuli modeling for the C. elegans are focused on a single type of stimulus, which is usually tested with a limited subnetwork of the C. elegans neural system. In this paper, we follow a different approach where we model a wide-range of different stimuli, with more flexible neural network configurations and simulations in mind. Moreover, we focus on the stimuli sensation by different types of sensory organs or various sensory principles of the neurons. As part of this work, most common stimuli involved in behavioral assays have been modeled. It includes models for mechanical, thermal, chemical, electrical and light stimuli, and for proprioception-related self-sensed information exchange with the neural network. The developed models have been implemented and tested with the hardware-based Si elegans simulation platform.

Neural and Synaptic Defects in slytherin a Zebrafish Model for Human Congenital Disorders of Glycosylation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Y Song; J Willer; P Scherer

2011-12-31

Congenital disorder of glycosylation type IIc (CDG IIc) is characterized by mental retardation, slowed growth and severe immunodeficiency, attributed to the lack of fucosylated glycoproteins. While impaired Notch signaling has been implicated in some aspects of CDG IIc pathogenesis, the molecular and cellular mechanisms remain poorly understood. We have identified a zebrafish mutant slytherin (srn), which harbors a missense point mutation in GDP-mannose 4,6 dehydratase (GMDS), the rate-limiting enzyme in protein fucosylation, including that of Notch. Here we report that some of the mechanisms underlying the neural phenotypes in srn and in CGD IIc are Notch-dependent, while others are Notch-independent.more » We show, for the first time in a vertebrate in vivo, that defects in protein fucosylation leads to defects in neuronal differentiation, maintenance, axon branching, and synapse formation. Srn is thus a useful and important vertebrate model for human CDG IIc that has provided new insights into the neural phenotypes that are hallmarks of the human disorder and has also highlighted the role of protein fucosylation in neural development.« less

Brain–heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field

PubMed Central

Raven, Erika P.; Duyn, Jeff H.

2016-01-01

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain–heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain–heart interactions. PMID:27044994

Brain-heart interactions: challenges and opportunities with functional magnetic resonance imaging at ultra-high field.

PubMed

Chang, Catie; Raven, Erika P; Duyn, Jeff H

2016-05-13

Magnetic resonance imaging (MRI) at ultra-high field (UHF) strengths (7 T and above) offers unique opportunities for studying the human brain with increased spatial resolution, contrast and sensitivity. However, its reliability can be compromised by factors such as head motion, image distortion and non-neural fluctuations of the functional MRI signal. The objective of this review is to provide a critical discussion of the advantages and trade-offs associated with UHF imaging, focusing on the application to studying brain-heart interactions. We describe how UHF MRI may provide contrast and resolution benefits for measuring neural activity of regions involved in the control and mediation of autonomic processes, and in delineating such regions based on anatomical MRI contrast. Limitations arising from confounding signals are discussed, including challenges with distinguishing non-neural physiological effects from the neural signals of interest that reflect cardiorespiratory function. We also consider how recently developed data analysis techniques may be applied to high-field imaging data to uncover novel information about brain-heart interactions. © 2016 The Author(s).

Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) using Complex Quantum Neuron (CQN): Applications to time series prediction.

PubMed

Cui, Yiqian; Shi, Junyou; Wang, Zili

2015-11-01

Quantum Neural Networks (QNN) models have attracted great attention since it innovates a new neural computing manner based on quantum entanglement. However, the existing QNN models are mainly based on the real quantum operations, and the potential of quantum entanglement is not fully exploited. In this paper, we proposes a novel quantum neuron model called Complex Quantum Neuron (CQN) that realizes a deep quantum entanglement. Also, a novel hybrid networks model Complex Rotation Quantum Dynamic Neural Networks (CRQDNN) is proposed based on Complex Quantum Neuron (CQN). CRQDNN is a three layer model with both CQN and classical neurons. An infinite impulse response (IIR) filter is embedded in the Networks model to enable the memory function to process time series inputs. The Levenberg-Marquardt (LM) algorithm is used for fast parameter learning. The networks model is developed to conduct time series predictions. Two application studies are done in this paper, including the chaotic time series prediction and electronic remaining useful life (RUL) prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cardiac Arrhythmia Classification by Multi-Layer Perceptron and Convolution Neural Networks.

PubMed

Savalia, Shalin; Emamian, Vahid

2018-05-04

The electrocardiogram (ECG) plays an imperative role in the medical field, as it records heart signal over time and is used to discover numerous cardiovascular diseases. If a documented ECG signal has a certain irregularity in its predefined features, this is called arrhythmia, the types of which include tachycardia, bradycardia, supraventricular arrhythmias, and ventricular, etc. This has encouraged us to do research that consists of distinguishing between several arrhythmias by using deep neural network algorithms such as multi-layer perceptron (MLP) and convolution neural network (CNN). The TensorFlow library that was established by Google for deep learning and machine learning is used in python to acquire the algorithms proposed here. The ECG databases accessible at PhysioBank.com and kaggle.com were used for training, testing, and validation of the MLP and CNN algorithms. The proposed algorithm consists of four hidden layers with weights, biases in MLP, and four-layer convolution neural networks which map ECG samples to the different classes of arrhythmia. The accuracy of the algorithm surpasses the performance of the current algorithms that have been developed by other cardiologists in both sensitivity and precision.

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

Diagonal recurrent neural network based adaptive control of nonlinear dynamical systems using lyapunov stability criterion.

PubMed

Kumar, Rajesh; Srivastava, Smriti; Gupta, J R P

2017-03-01

In this paper adaptive control of nonlinear dynamical systems using diagonal recurrent neural network (DRNN) is proposed. The structure of DRNN is a modification of fully connected recurrent neural network (FCRNN). Presence of self-recurrent neurons in the hidden layer of DRNN gives it an ability to capture the dynamic behaviour of the nonlinear plant under consideration (to be controlled). To ensure stability, update rules are developed using lyapunov stability criterion. These rules are then used for adjusting the various parameters of DRNN. The responses of plants obtained with DRNN are compared with those obtained when multi-layer feed forward neural network (MLFFNN) is used as a controller. Also, in example 4, FCRNN is also investigated and compared with DRNN and MLFFNN. Robustness of the proposed control scheme is also tested against parameter variations and disturbance signals. Four simulation examples including one-link robotic manipulator and inverted pendulum are considered on which the proposed controller is applied. The results so obtained show the superiority of DRNN over MLFFNN as a controller. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Neurobiology of cognitive remediation therapy for schizophrenia: a systematic review.

PubMed

Thorsen, Anders Lillevik; Johansson, Kyrre; Løberg, Else-Marie

2014-01-01

Cognitive impairment is an important aspect of schizophrenia, where cognitive remediation therapy (CRT) is a promising treatment for improving cognitive functioning. While neurobiological dysfunction in schizophrenia has been the target of much research, the neural substrate of cognitive remediation and recovery has not been thoroughly examined. The aim of the present article is to systematically review the evidence for neural changes after CRT for schizophrenia. The reviewed studies indicate that CRT affects several brain regions and circuits, including prefrontal, parietal, and limbic areas, both in terms of activity and structure. Changes in prefrontal areas are the most reported finding, fitting to previous evidence of dysfunction in this region. Two limitations of the current research are the few studies and the lack of knowledge on the mechanisms underlying neural and cognitive changes after treatment. Despite these limitations, the current evidence suggests that CRT is associated with both neurobiological and cognitive improvement. The evidence from these findings may shed light on both the neural substrate of cognitive impairment in schizophrenia, and how better treatment can be developed and applied.

Impaired neuronal maturation of hippocampal neural progenitor cells in mice lacking CRAF.

PubMed

Pfeiffer, Verena; Götz, Rudolf; Camarero, Guadelupe; Heinsen, Helmut; Blum, Robert; Rapp, Ulf Rüdiger

2018-01-01

RAF kinases are major constituents of the mitogen activated signaling pathway, regulating cell proliferation, differentiation and cell survival of many cell types, including neurons. In mammals, the family of RAF proteins consists of three members, ARAF, BRAF, and CRAF. Ablation of CRAF kinase in inbred mouse strains causes major developmental defects during fetal growth and embryonic or perinatal lethality. Heterozygous germline mutations in CRAF result in Noonan syndrome, which is characterized by neurocognitive impairment that may involve hippocampal physiology. The role of CRAF signaling during hippocampal development and generation of new postnatal hippocampal granule neurons has not been examined and may provide novel insight into the cause of hippocampal dysfunction in Noonan syndrome. In this study, by crossing CRAF-deficiency to CD-1 outbred mice, a CRAF mouse model was established which enabled us to investigate the interplay of neural progenitor proliferation and postmitotic differentiation during adult neurogenesis in the hippocampus. Albeit the general morphology of the hippocampus was unchanged, CRAF-deficient mice displayed smaller granule cell layer (GCL) volume at postnatal day 30 (P30). In CRAF-deficient mice a substantial number of abnormal, chromophilic, fast dividing cells were found in the subgranular zone (SGZ) and hilus of the dentate gyrus (DG), indicating that CRAF signaling contributes to hippocampal neural progenitor proliferation. CRAF-deficient neural progenitor cells showed an increased cell death rate and reduced neuronal maturation. These results indicate that CRAF function affects postmitotic neural cell differentiation and points to a critical role of CRAF-dependent growth factor signaling pathway in the postmitotic development of adult-born neurons.

Impaired neuronal maturation of hippocampal neural progenitor cells in mice lacking CRAF

PubMed Central

Götz, Rudolf; Camarero, Guadelupe; Heinsen, Helmut; Blum, Robert; Rapp, Ulf Rüdiger

2018-01-01

RAF kinases are major constituents of the mitogen activated signaling pathway, regulating cell proliferation, differentiation and cell survival of many cell types, including neurons. In mammals, the family of RAF proteins consists of three members, ARAF, BRAF, and CRAF. Ablation of CRAF kinase in inbred mouse strains causes major developmental defects during fetal growth and embryonic or perinatal lethality. Heterozygous germline mutations in CRAF result in Noonan syndrome, which is characterized by neurocognitive impairment that may involve hippocampal physiology. The role of CRAF signaling during hippocampal development and generation of new postnatal hippocampal granule neurons has not been examined and may provide novel insight into the cause of hippocampal dysfunction in Noonan syndrome. In this study, by crossing CRAF-deficiency to CD-1 outbred mice, a CRAF mouse model was established which enabled us to investigate the interplay of neural progenitor proliferation and postmitotic differentiation during adult neurogenesis in the hippocampus. Albeit the general morphology of the hippocampus was unchanged, CRAF-deficient mice displayed smaller granule cell layer (GCL) volume at postnatal day 30 (P30). In CRAF-deficient mice a substantial number of abnormal, chromophilic, fast dividing cells were found in the subgranular zone (SGZ) and hilus of the dentate gyrus (DG), indicating that CRAF signaling contributes to hippocampal neural progenitor proliferation. CRAF-deficient neural progenitor cells showed an increased cell death rate and reduced neuronal maturation. These results indicate that CRAF function affects postmitotic neural cell differentiation and points to a critical role of CRAF-dependent growth factor signaling pathway in the postmitotic development of adult-born neurons. PMID:29590115

Meninges: from protective membrane to stem cell niche.

PubMed

Decimo, Ilaria; Fumagalli, Guido; Berton, Valeria; Krampera, Mauro; Bifari, Francesco

2012-01-01

Meninges are a three tissue membrane primarily known as coverings of the brain. More in depth studies on meningeal function and ultrastructure have recently changed the view of meninges as a merely protective membrane. Accurate evaluation of the anatomical distribution in the CNS reveals that meninges largely penetrate inside the neural tissue. Meninges enter the CNS by projecting between structures, in the stroma of choroid plexus and form the perivascular space (Virchow-Robin) of every parenchymal vessel. Thus, meninges may modulate most of the physiological and pathological events of the CNS throughout the life. Meninges are present since the very early embryonic stages of cortical development and appear to be necessary for normal corticogenesis and brain structures formation. In adulthood meninges contribute to neural tissue homeostasis by secreting several trophic factors including FGF2 and SDF-1. Recently, for the first time, we have identified the presence of a stem cell population with neural differentiation potential in meninges. In addition, we and other groups have further described the presence in meninges of injury responsive neural precursors. In this review we will give a comprehensive view of meninges and their multiple roles in the context of a functional network with the neural tissue. We will highlight the current literature on the developmental feature of meninges and their role in cortical development. Moreover, we will elucidate the anatomical distribution of the meninges and their trophic properties in adult CNS. Finally, we will emphasize recent evidences suggesting the potential role of meninges as stem cell niche harbouring endogenous precursors that can be activated by injury and are able to contribute to CNS parenchymal reaction.

The Application of a Chemical Determination of N-Homocysteinylation Levels in Developing Mouse Embryos: Implication for Folate Responsive Birth Defects

PubMed Central

Fathe, Kristin; Person, Maria D.; Finnell, Richard H.

2014-01-01

Elevated homocysteine levels have long been associated with various disease states, including cardiovascular disease and birth defects, including neural tube defects (NTDs). One hypothesis regarding the strong correlation between these various disorders and high levels of homocysteine is that a reactive form of this small molecule can attach to mammalian proteins in a phenomenon known as homocysteinylation. These posttranslational modifications may become antigenic, or may even directly disrupt certain protein function. It remains to be determined whether dietary influences that can cause globally increased levels of circulating homocysteine confer negative effects maternally, or may otherwise negatively and materially impact the metabolic balance in developing embryos. Herein we present the application of a chemical method of determination of N-homocysteinylation to a set of neural tube closure stage mouse embryos and their mothers. We explore the uses of this newly-described technique to investigate levels of maternal and embryonic N-homocysteinylation using dietary manipulations of onecarbon metabolism with two known folate responsive neural tube defect mouse models. The data presented reveals that although diet appeared to have significant effects on the maternal metabolic status, those effects did not directly correlate to the embryonic folate or N-homocysteinylation status. Our studies indicate that maternal diet and embryonic genotype most significantly affected the embryonic developmental outcome. PMID:25620692

Aberrant differentiation of the axially condensed tail bud mesenchyme in human embryos with lumbosacral myeloschisis.

PubMed

Saitsu, Hirotomo; Yamada, Shigehito; Uwabe, Chigako; Ishibashi, Makoto; Shiota, Kohei

2007-03-01

Development of the posterior neural tube (PNT) in human embryos is a complicated process that involves both primary and secondary neurulation. Recently, we histologically examined 20 human embryos around the stage of posterior neuropore closure and found that the axially condensed mesenchyme (AM) intervened between the neural plate/tube and the notochord in the junctional region of the primary and secondary neural tubes. The AM appeared to be incorporated into the most ventral part of the primary neural tube, and no cavity was observed in the AM. In this study, we report three cases of human embryos with myeloschisis in which the open primary neural tube and the closed secondary neural tube overlap dorsoventrally. In all three cases, part of the closed neural tube was located ventrally to the open neural tube in the lumbosacral region. The open and closed neural tubes appeared to be part of the primary and the AM-derived secondary neural tubes, respectively. Thus, these findings suggest that, in those embryos with myeloschisis, the AM may not be incorporated into the ventral part of the primary neural tube but aberrantly differentiate into the secondary neural tube containing cavities, leading to dorsoventral overlapping of the primary and secondary neural tubes. The aberrant differentiation of the AM in embryos with lumbosacral myeloschisis suggests that the AM plays some roles in normal as well as abnormal development of the human posterior neural tube.

Vascular pattern of the dentate gyrus is regulated by neural progenitors.

PubMed

Pombero, Ana; Garcia-Lopez, Raquel; Estirado, Alicia; Martinez, Salvador

2018-05-01

Neurogenesis is a vital process that begins during early embryonic development and continues until adulthood, though in the latter case, it is restricted to the subventricular zone and the subgranular zone of the dentate gyrus (DG). In particular, the DG's neurogenic properties are structurally and functionally unique, which may be related to its singular vascular pattern. Neurogenesis and angiogenesis share molecular signals and act synergistically, supporting the concept of a neurogenic niche as a functional unit between neural precursors cells and their environment, in which the blood vessels play an important role. Whereas it is well known that vascular development controls neural proliferation in the embryonary and in the adult brain, by releasing neurotrophic factors; the potential influence of neural cells on vascular components during angiogenesis is largely unknown. We have demonstrated that the reduction of neural progenitors leads to a significant impairment of vascular development. Since VEGF is a potential regulator in the neurogenesis-angiogenesis crosstalk, we were interested in assessing the possible role of this molecule in the hippocampal neurovascular development. Our results showed that VEGF is the molecule involved in the regulation of vascular development by neural progenitor cells in the DG.

Nuclear receptor TLX regulates cell cycle progression in neural stem cells of the developing brain.

PubMed

Li, Wenwu; Sun, Guoqiang; Yang, Su; Qu, Qiuhao; Nakashima, Kinichi; Shi, Yanhong

2008-01-01

TLX is an orphan nuclear receptor that is expressed exclusively in vertebrate forebrains. Although TLX is known to be expressed in embryonic brains, the mechanism by which it influences neural development remains largely unknown. We show here that TLX is expressed specifically in periventricular neural stem cells in embryonic brains. Significant thinning of neocortex was observed in embryonic d 14.5 TLX-null brains with reduced nestin labeling and decreased cell proliferation in the germinal zone. Cell cycle analysis revealed both prolonged cell cycles and increased cell cycle exit in TLX-null embryonic brains. Increased expression of a cyclin-dependent kinase inhibitor p21 and decreased expression of cyclin D1 provide a molecular basis for the deficiency of cell cycle progression in embryonic brains of TLX-null mice. Furthermore, transient knockdown of TLX by in utero electroporation led to precocious cell cycle exit and differentiation of neural stem cells followed by outward migration. Together these results indicate that TLX plays an important role in neural development by regulating cell cycle progression and exit of neural stem cells in the developing brain.

Nuclear Receptor TLX Regulates Cell Cycle Progression in Neural Stem Cells of the Developing Brain

PubMed Central

Li, Wenwu; Sun, Guoqiang; Yang, Su; Qu, Qiuhao; Nakashima, Kinichi; Shi, Yanhong

2008-01-01

TLX is an orphan nuclear receptor that is expressed exclusively in vertebrate forebrains. Although TLX is known to be expressed in embryonic brains, the mechanism by which it influences neural development remains largely unknown. We show here that TLX is expressed specifically in periventricular neural stem cells in embryonic brains. Significant thinning of neocortex was observed in embryonic d 14.5 TLX-null brains with reduced nestin labeling and decreased cell proliferation in the germinal zone. Cell cycle analysis revealed both prolonged cell cycles and increased cell cycle exit in TLX-null embryonic brains. Increased expression of a cyclin-dependent kinase inhibitor p21 and decreased expression of cyclin D1 provide a molecular basis for the deficiency of cell cycle progression in embryonic brains of TLX-null mice. Furthermore, transient knockdown of TLX by in utero electroporation led to precocious cell cycle exit and differentiation of neural stem cells followed by outward migration. Together these results indicate that TLX plays an important role in neural development by regulating cell cycle progression and exit of neural stem cells in the developing brain. PMID:17901127

Towards automatic musical instrument timbre recognition

NASA Astrophysics Data System (ADS)

Park, Tae Hong

This dissertation is comprised of two parts---focus on issues concerning research and development of an artificial system for automatic musical instrument timbre recognition and musical compositions. The technical part of the essay includes a detailed record of developed and implemented algorithms for feature extraction and pattern recognition. A review of existing literature introducing historical aspects surrounding timbre research, problems associated with a number of timbre definitions, and highlights of selected research activities that have had significant impact in this field are also included. The developed timbre recognition system follows a bottom-up, data-driven model that includes a pre-processing module, feature extraction module, and a RBF/EBF (Radial/Elliptical Basis Function) neural network-based pattern recognition module. 829 monophonic samples from 12 instruments have been chosen from the Peter Siedlaczek library (Best Service) and other samples from the Internet and personal collections. Significant emphasis has been put on feature extraction development and testing to achieve robust and consistent feature vectors that are eventually passed to the neural network module. In order to avoid a garbage-in-garbage-out (GIGO) trap and improve generality, extra care was taken in designing and testing the developed algorithms using various dynamics, different playing techniques, and a variety of pitches for each instrument with inclusion of attack and steady-state portions of a signal. Most of the research and development was conducted in Matlab. The compositional part of the essay includes brief introductions to "A d'Ess Are ," "Aboji," "48 13 N, 16 20 O," and "pH-SQ." A general outline pertaining to the ideas and concepts behind the architectural designs of the pieces including formal structures, time structures, orchestration methods, and pitch structures are also presented.

Quantum neural networks: Current status and prospects for development

NASA Astrophysics Data System (ADS)

Altaisky, M. V.; Kaputkina, N. E.; Krylov, V. A.

2014-11-01

The idea of quantum artificial neural networks, first formulated in [34], unites the artificial neural network concept with the quantum computation paradigm. Quantum artificial neural networks were first systematically considered in the PhD thesis by T. Menneer (1998). Based on the works of Menneer and Narayanan [42, 43], Kouda, Matsui, and Nishimura [35, 36], Altaisky [2, 68], Zhou [67], and others, quantum-inspired learning algorithms for neural networks were developed, and are now used in various training programs and computer games [29, 30]. The first practically realizable scaled hardware-implemented model of the quantum artificial neural network is obtained by D-Wave Systems, Inc. [33]. It is a quantum Hopfield network implemented on the basis of superconducting quantum interference devices (SQUIDs). In this work we analyze possibilities and underlying principles of an alternative way to implement quantum neural networks on the basis of quantum dots. A possibility of using quantum neural network algorithms in automated control systems, associative memory devices, and in modeling biological and social networks is examined.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception.

PubMed

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.

Neural Activity Patterns in the Human Brain Reflect Tactile Stickiness Perception

PubMed Central

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

The Role of Platelet-Derived Growth Factor C and Its Splice Variant in Breast Cancer

DTIC Science & Technology

2012-02-01

epithelial-mesenchymal transition leading instead to apoptosis (8). Furthermore, inhibition of PDGFR signaling by the PDGFR inhibitor STI571...PDGFRs are expressed in many different cell types including endothelial, epithelial and neural cells and are necessary for embryological development (as

QUANTITATIVE IN VITRO MEASUREMENT OF CELLULAR PROCESSES CRITICAL TO THE DEVELOPMENT OF NEURAL CONNECTIVITY USING HCA.

EPA Science Inventory

New methods are needed to screen thousands of environmental chemicals for toxicity, including developmental neurotoxicity. In vitro, cell-based assays that model key cellular events have been proposed for high throughput screening of chemicals for developmental neurotoxicity. Whi...

Functional Network Architecture of Reading-Related Regions across Development

ERIC Educational Resources Information Center

Vogel, Alecia C.; Church, Jessica A.; Power, Jonathan D.; Miezin, Fran M.; Petersen, Steven E.; Schlaggar, Bradley L.

2013-01-01

Reading requires coordinated neural processing across a large number of brain regions. Studying relationships between reading-related regions informs the specificity of information processing performed in each region. Here, regions of interest were defined from a meta-analysis of reading studies, including a developmental study. Relationships…

Language Disorders of Children: The Bases and Diagnoses.

ERIC Educational Resources Information Center

Berry, Mildred Freburg

Taking an interdisciplinary approach, the text is intended as an introduction to language disorders in children. Aspects of tracking language in the nervous system considered include neural substrates of language development, operational systems, and operational mechanisms. Language and learning are discussed in terms of the psychological…

Neural Cross-Frequency Coupling: Connecting Architectures, Mechanisms, and Functions.

PubMed

Hyafil, Alexandre; Giraud, Anne-Lise; Fontolan, Lorenzo; Gutkin, Boris

2015-11-01

Neural oscillations are ubiquitously observed in the mammalian brain, but it has proven difficult to tie oscillatory patterns to specific cognitive operations. Notably, the coupling between neural oscillations at different timescales has recently received much attention, both from experimentalists and theoreticians. We review the mechanisms underlying various forms of this cross-frequency coupling. We show that different types of neural oscillators and cross-frequency interactions yield distinct signatures in neural dynamics. Finally, we associate these mechanisms with several putative functions of cross-frequency coupling, including neural representations of multiple environmental items, communication over distant areas, internal clocking of neural processes, and modulation of neural processing based on temporal predictions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neuroconstructivism

ERIC Educational Resources Information Center

Westermann, Gert; Mareschal, Denis; Johnson, Mark H.; Sirois, Sylvain; Spratling, Michael W.; Thomas, Michael S. C.

2007-01-01

Neuroconstructivism is a theoretical framework focusing on the construction of representations in the developing brain. Cognitive development is explained as emerging from the experience-dependent development of neural structures supporting mental representations. Neural development occurs in the context of multiple interacting constraints acting…

Carbon nanotubes in neural interfacing applications

NASA Astrophysics Data System (ADS)

Voge, Christopher M.; Stegemann, Jan P.

2011-02-01

Carbon nanotubes (CNT) are remarkable materials with a simple and inert molecular structure that gives rise to a range of potentially valuable physical and electronic properties, including high aspect ratio, high mechanical strength and excellent electrical conductivity. This review summarizes recent research on the application of CNT-based materials to study and control cells of the nervous system. It includes the use of CNT as cell culture substrates, to create patterned surfaces and to study cell-matrix interactions. It also summarizes recent investigations of CNT toxicity, particularly as related to neural cells. The application of CNT-based materials to directing the differentiation of progenitor and stem cells toward neural lineages is also discussed. The emphasis is on how CNT surface chemistry and nanotopography can be altered, and how such changes can affect neural cell function. This knowledge can be applied to creating improved neural interfaces and devices, as well as providing new approaches to neural tissue engineering and regeneration.

Optical Neural Interfaces

PubMed Central

Warden, Melissa R.; Cardin, Jessica A.; Deisseroth, Karl

2014-01-01

Genetically encoded optical actuators and indicators have changed the landscape of neuroscience, enabling targetable control and readout of specific components of intact neural circuits in behaving animals. Here, we review the development of optical neural interfaces, focusing on hardware designed for optical control of neural activity, integrated optical control and electrical readout, and optical readout of population and single-cell neural activity in freely moving mammals. PMID:25014785

Precursors to morality in development as a complex interplay between neural, socioenvironmental, and behavioral facets

PubMed Central

Cowell, Jason M.; Decety, Jean

2015-01-01

The nature and underpinnings of infants’ seemingly complex, third-party, social evaluations remain highly contentious. Theoretical perspectives oscillate between rich and lean interpretations of the same expressed preferences. Although some argue that infants and toddlers possess a “moral sense” based on core knowledge of the social world, others suggest that social evaluations are hierarchical in nature and the product of an integration of rudimentary general processes such as attention allocation and approach and avoidance. Moreover, these biologically prepared minds interact in social environments that include significant variation, which are likely to impact early social evaluations and behavior. The present study examined the neural underpinnings of and precursors to moral sensitivity in infants and toddlers (n = 73, ages 12–24 mo) through a series of interwoven measures, combining multiple levels of analysis including electrophysiological, eye-tracking, behavioral, and socioenvironmental. Continuous EEG and time-locked event-related potentials (ERPs) and gaze fixation were recorded while children watched characters engaging in prosocial and antisocial actions in two different tasks. All children demonstrated a neural differentiation in both spectral EEG power density modulations and time-locked ERPs when perceiving prosocial or antisocial agents. Time-locked neural differences predicted children’s preference for prosocial characters and were influenced by parental values regarding justice and fairness. Overall, this investigation casts light on the fundamental nature of moral cognition, including its underpinnings in general processes such as attention and approach–withdrawal, providing plausible mechanisms of early change and a foundation for forward movement in the field of developmental social neuroscience. PMID:26324885

3D culture models of Alzheimer's disease: a road map to a "cure-in-a-dish".

PubMed

Choi, Se Hoon; Kim, Young Hye; Quinti, Luisa; Tanzi, Rudolph E; Kim, Doo Yeon

2016-12-09

Alzheimer's disease (AD) transgenic mice have been used as a standard AD model for basic mechanistic studies and drug discovery. These mouse models showed symbolic AD pathologies including β-amyloid (Aβ) plaques, gliosis and memory deficits but failed to fully recapitulate AD pathogenic cascades including robust phospho tau (p-tau) accumulation, clear neurofibrillary tangles (NFTs) and neurodegeneration, solely driven by familial AD (FAD) mutation(s). Recent advances in human stem cell and three-dimensional (3D) culture technologies made it possible to generate novel 3D neural cell culture models that recapitulate AD pathologies including robust Aβ deposition and Aβ-driven NFT-like tau pathology. These new 3D human cell culture models of AD hold a promise for a novel platform that can be used for mechanism studies in human brain-like environment and high-throughput drug screening (HTS). In this review, we will summarize the current progress in recapitulating AD pathogenic cascades in human neural cell culture models using AD patient-derived induced pluripotent stem cells (iPSCs) or genetically modified human stem cell lines. We will also explain how new 3D culture technologies were applied to accelerate Aβ and p-tau pathologies in human neural cell cultures, as compared the standard two-dimensional (2D) culture conditions. Finally, we will discuss a potential impact of the human 3D human neural cell culture models on the AD drug-development process. These revolutionary 3D culture models of AD will contribute to accelerate the discovery of novel AD drugs.

Automatic discovery of cell types and microcircuitry from neural connectomics

PubMed Central

Jonas, Eric; Kording, Konrad

2015-01-01

Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity, better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets. DOI: http://dx.doi.org/10.7554/eLife.04250.001 PMID:25928186

Automatic discovery of cell types and microcircuitry from neural connectomics

DOE PAGES

Jonas, Eric; Kording, Konrad

2015-04-30

Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity,more » better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets.« less

Elements of an algorithm for optimizing a parameter-structural neural network

NASA Astrophysics Data System (ADS)

Mrówczyńska, Maria

2016-06-01

The field of processing information provided by measurement results is one of the most important components of geodetic technologies. The dynamic development of this field improves classic algorithms for numerical calculations in the aspect of analytical solutions that are difficult to achieve. Algorithms based on artificial intelligence in the form of artificial neural networks, including the topology of connections between neurons have become an important instrument connected to the problem of processing and modelling processes. This concept results from the integration of neural networks and parameter optimization methods and makes it possible to avoid the necessity to arbitrarily define the structure of a network. This kind of extension of the training process is exemplified by the algorithm called the Group Method of Data Handling (GMDH), which belongs to the class of evolutionary algorithms. The article presents a GMDH type network, used for modelling deformations of the geometrical axis of a steel chimney during its operation.

Automatic discovery of cell types and microcircuitry from neural connectomics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jonas, Eric; Kording, Konrad

Neural connectomics has begun producing massive amounts of data, necessitating new analysis methods to discover the biological and computational structure. It has long been assumed that discovering neuron types and their relation to microcircuitry is crucial to understanding neural function. Here we developed a non-parametric Bayesian technique that identifies neuron types and microcircuitry patterns in connectomics data. It combines the information traditionally used by biologists in a principled and probabilistically coherent manner, including connectivity, cell body location, and the spatial distribution of synapses. We show that the approach recovers known neuron types in the retina and enables predictions of connectivity,more » better than simpler algorithms. It also can reveal interesting structure in the nervous system of Caenorhabditis elegans and an old man-made microprocessor. Our approach extracts structural meaning from connectomics, enabling new approaches of automatically deriving anatomical insights from these emerging datasets.« less

Bias-dependent hybrid PKI empirical-neural model of microwave FETs

NASA Astrophysics Data System (ADS)

Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera

2011-10-01

Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.

VLSI circuits implementing computational models of neocortical circuits.

PubMed

Wijekoon, Jayawan H B; Dudek, Piotr

2012-09-15

This paper overviews the design and implementation of three neuromorphic integrated circuits developed for the COLAMN ("Novel Computing Architecture for Cognitive Systems based on the Laminar Microcircuitry of the Neocortex") project. The circuits are implemented in a standard 0.35 μm CMOS technology and include spiking and bursting neuron models, and synapses with short-term (facilitating/depressing) and long-term (STDP and dopamine-modulated STDP) dynamics. They enable execution of complex nonlinear models in accelerated-time, as compared with biology, and with low power consumption. The neural dynamics are implemented using analogue circuit techniques, with digital asynchronous event-based input and output. The circuits provide configurable hardware blocks that can be used to simulate a variety of neural networks. The paper presents experimental results obtained from the fabricated devices, and discusses the advantages and disadvantages of the analogue circuit approach to computational neural modelling. Copyright © 2012 Elsevier B.V. All rights reserved.

Instrumentation for Scientific Computing in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics.

DTIC Science & Technology

1987-10-01

include Security Classification) Instrumentation for scientific computing in neural networks, information science, artificial intelligence, and...instrumentation grant to purchase equipment for support of research in neural networks, information science, artificail intellignece , and applied mathematics...in Neural Networks, Information Science, Artificial Intelligence, and Applied Mathematics Contract AFOSR 86-0282 Principal Investigator: Stephen

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

The Expression and Function of the Achaete-Scute Genes in Tribolium castaneum Reveals Conservation and Variation in Neural Pattern Formation and Cell Fate Specification

NASA Technical Reports Server (NTRS)

Wheeler, Scott R.; Carrico, Michelle L.; Wilson, Beth A.; Brown, Susan J.; Skeath, James B.

2003-01-01

SUMMARY The study of achaete-scute (ac/sc) genes has recently become a paradigm to understand the evolution and development of the arthropod nervous system. We describe the identification and characterization of the ache genes in the coleopteran insect species Tribolium castaneum. We have identified two Tribolium ache genes - achaete-scute homolog (Tc-ASH) a proneural gene and asense (Tc-ase) a neural precursor gene that reside in a gene complex. Focusing on the embryonic central nervous system we fmd that Tc-ASH is expressed in all neural precursors and the proneural clusters from which they segregate. Through RNAi and misexpression studies we show that Tc-ASH is necessary for neural precursor formation in Triboliurn and sufficient for neural precursor formation in Drosophila. Comparison of the function of the Drosophila and Triboliurn proneural ac/sc genes suggests that in the Drosophila lineage these genes have maintained their ancestral function in neural precursor formation and have acquired a new role in the fate specification of individual neural precursors. Furthermore, we find that Tc-use is expressed in all neural precursors suggesting an important and conserved role for asense genes in insect nervous system development. Our analysis of the Triboliurn ache genes indicates significant plasticity in gene number, expression and function, and implicates these modifications in the evolution of arthropod neural development.

The expression and function of the achaete-scute genes in Tribolium castaneum reveals conservation and variation in neural pattern formation and cell fate specification

NASA Technical Reports Server (NTRS)

Wheeler, Scott R.; Carrico, Michelle L.; Wilson, Beth A.; Brown, Susan J.; Skeath, James B.

2003-01-01

The study of achaete-scute (ac/sc) genes has recently become a paradigm to understand the evolution and development of the arthropod nervous system. We describe the identification and characterization of the ac/sc genes in the coleopteran insect species Tribolium castaneum. We have identified two Tribolium ac/sc genes - achaete-scute homolog (Tc-ASH) a proneural gene and asense (Tc-ase) a neural precursor gene that reside in a gene complex. Focusing on the embryonic central nervous system we find that Tc-ASH is expressed in all neural precursors and the proneural clusters from which they segregate. Through RNAi and misexpression studies we show that Tc-ASH is necessary for neural precursor formation in Tribolium and sufficient for neural precursor formation in Drosophila. Comparison of the function of the Drosophila and Tribolium proneural ac/sc genes suggests that in the Drosophila lineage these genes have maintained their ancestral function in neural precursor formation and have acquired a new role in the fate specification of individual neural precursors. Furthermore, we find that Tc-ase is expressed in all neural precursors suggesting an important and conserved role for asense genes in insect nervous system development. Our analysis of the Tribolium ac/sc genes indicates significant plasticity in gene number, expression and function, and implicates these modifications in the evolution of arthropod neural development.

Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

PubMed

Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

2018-04-17

The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

Using Reinforcement Learning to Provide Stable Brain-Machine Interface Control Despite Neural Input Reorganization

PubMed Central

Pohlmeyer, Eric A.; Mahmoudi, Babak; Geng, Shijia; Prins, Noeline W.; Sanchez, Justin C.

2014-01-01

Brain-machine interface (BMI) systems give users direct neural control of robotic, communication, or functional electrical stimulation systems. As BMI systems begin transitioning from laboratory settings into activities of daily living, an important goal is to develop neural decoding algorithms that can be calibrated with a minimal burden on the user, provide stable control for long periods of time, and can be responsive to fluctuations in the decoder’s neural input space (e.g. neurons appearing or being lost amongst electrode recordings). These are significant challenges for static neural decoding algorithms that assume stationary input/output relationships. Here we use an actor-critic reinforcement learning architecture to provide an adaptive BMI controller that can successfully adapt to dramatic neural reorganizations, can maintain its performance over long time periods, and which does not require the user to produce specific kinetic or kinematic activities to calibrate the BMI. Two marmoset monkeys used the Reinforcement Learning BMI (RLBMI) to successfully control a robotic arm during a two-target reaching task. The RLBMI was initialized using random initial conditions, and it quickly learned to control the robot from brain states using only a binary evaluative feedback regarding whether previously chosen robot actions were good or bad. The RLBMI was able to maintain control over the system throughout sessions spanning multiple weeks. Furthermore, the RLBMI was able to quickly adapt and maintain control of the robot despite dramatic perturbations to the neural inputs, including a series of tests in which the neuron input space was deliberately halved or doubled. PMID:24498055

Increasing Spontaneous Retinal Activity before Eye Opening Accelerates the Development of Geniculate Receptive Fields

PubMed Central

Davis, Zachary W.; Chapman, Barbara

2015-01-01

Visually evoked activity is necessary for the normal development of the visual system. However, little is known about the capacity for patterned spontaneous activity to drive the maturation of receptive fields before visual experience. Retinal waves provide instructive retinotopic information for the anatomical organization of the visual thalamus. To determine whether retinal waves also drive the maturation of functional responses, we increased the frequency of retinal waves pharmacologically in the ferret (Mustela putorius furo) during a period of retinogeniculate development before eye opening. The development of geniculate receptive fields after receiving these increased neural activities was measured using single-unit electrophysiology. We found that increased retinal waves accelerate the developmental reduction of geniculate receptive field sizes. This reduction is due to a decrease in receptive field center size rather than an increase in inhibitory surround strength. This work reveals an instructive role for patterned spontaneous activity in guiding the functional development of neural circuits. SIGNIFICANCE STATEMENT Patterned spontaneous neural activity that occurs during development is known to be necessary for the proper formation of neural circuits. However, it is unknown whether the spontaneous activity alone is sufficient to drive the maturation of the functional properties of neurons. Our work demonstrates for the first time an acceleration in the maturation of neural function as a consequence of driving patterned spontaneous activity during development. This work has implications for our understanding of how neural circuits can be modified actively to improve function prematurely or to recover from injury with guided interventions of patterned neural activity. PMID:26511250

An experimental study on neural crest migration in Barbus conchonius (Cyprinidae, Teleostei), with special reference to the origin of the enteroendocrine cells.

PubMed

Lamers, C H; Rombout, J W; Timmermans, L P

1981-04-01

A neural crest transplantation technique is described for fish. As in other classes of vertebrates, two pathways of neural crest migration can be distinguished: a lateroventral pathway between somites and ectoderm, and a medioventral pathway between somites and neural tube/notochord. In this paper evidence is presented for a neural crest origin of spinal ganglion cells and pigment cells, and indication for such an origin is obtained for sympathetic and enteric ganglion cells and for cells that are probably homologues to adrenomedullary and paraganglion cells in the future kidney area. The destiny of neural crest cells near the developing lateral-line sense organs is discussed. When grafted into the yolk, neural crest cells or neural tube cells appear to differentiate into 'periblast cells'; this suggests a highly activating influence of the yolk. Many neural crest cells are found around the urinary ducts and, when grafted below the notochord, even within the urinary duct epithelium. These neural crest cells do not invade the gut epithelium, even when grafted adjacent to the developing gut. Consequently enteroendocrine cells in fish are not likely to have a trunk- or rhombencephalic neural crest origin. Another possible origin of these cells will be proposed.

Force Field for Water Based on Neural Network.

PubMed

Wang, Hao; Yang, Weitao

2018-05-18

We developed a novel neural network based force field for water based on training with high level ab initio theory. The force field was built based on electrostatically embedded many-body expansion method truncated at binary interactions. Many-body expansion method is a common strategy to partition the total Hamiltonian of large systems into a hierarchy of few-body terms. Neural networks were trained to represent electrostatically embedded one-body and two-body interactions, which require as input only one and two water molecule calculations at the level of ab initio electronic structure method CCSD/aug-cc-pVDZ embedded in the molecular mechanics water environment, making it efficient as a general force field construction approach. Structural and dynamic properties of liquid water calculated with our force field show good agreement with experimental results. We constructed two sets of neural network based force fields: non-polarizable and polarizable force fields. Simulation results show that the non-polarizable force field using fixed TIP3P charges has already behaved well, since polarization effects and many-body effects are implicitly included due to the electrostatic embedding scheme. Our results demonstrate that the electrostatically embedded many-body expansion combined with neural network provides a promising and systematic way to build the next generation force fields at high accuracy and low computational costs, especially for large systems.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals.

PubMed

Zhuang, Ning; Zeng, Ying; Yang, Kai; Zhang, Chi; Tong, Li; Yan, Bin

2018-03-12

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.

Functional electrical stimulation controlled by artificial neural networks: pilot experiments with simple movements are promising for rehabilitation applications.

PubMed

Ferrante, Simona; Pedrocchi, Alessandra; Iannò, Marco; De Momi, Elena; Ferrarin, Maurizio; Ferrigno, Giancarlo

2004-01-01

This study falls within the ambit of research on functional electrical stimulation for the design of rehabilitation training for spinal cord injured patients. In this context, a crucial issue is the control of the stimulation parameters in order to optimize the patterns of muscle activation and to increase the duration of the exercises. An adaptive control system (NEURADAPT) based on artificial neural networks (ANNs) was developed to control the knee joint in accordance with desired trajectories by stimulating quadriceps muscles. This strategy includes an inverse neural model of the stimulated limb in the feedforward line and a neural network trained on-line in the feedback loop. NEURADAPT was compared with a linear closed-loop proportional integrative derivative (PID) controller and with a model-based neural controller (NEUROPID). Experiments on two subjects (one healthy and one paraplegic) show the good performance of NEURADAPT, which is able to reduce the time lag introduced by the PID controller. In addition, control systems based on ANN techniques do not require complicated calibration procedures at the beginning of each experimental session. After the initial learning phase, the ANN, thanks to its generalization capacity, is able to cope with a certain range of variability of skeletal muscle properties.

Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

PubMed Central

Zeng, Ying; Yang, Kai; Tong, Li; Yan, Bin

2018-01-01

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods. PMID:29534515

Applying Gradient Descent in Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Cui, Nan

2018-04-01

With the development of the integrated circuit and computer science, people become caring more about solving practical issues via information technologies. Along with that, a new subject called Artificial Intelligent (AI) comes up. One popular research interest of AI is about recognition algorithm. In this paper, one of the most common algorithms, Convolutional Neural Networks (CNNs) will be introduced, for image recognition. Understanding its theory and structure is of great significance for every scholar who is interested in this field. Convolution Neural Network is an artificial neural network which combines the mathematical method of convolution and neural network. The hieratical structure of CNN provides it reliable computer speed and reasonable error rate. The most significant characteristics of CNNs are feature extraction, weight sharing and dimension reduction. Meanwhile, combining with the Back Propagation (BP) mechanism and the Gradient Descent (GD) method, CNNs has the ability to self-study and in-depth learning. Basically, BP provides an opportunity for backwardfeedback for enhancing reliability and GD is used for self-training process. This paper mainly discusses the CNN and the related BP and GD algorithms, including the basic structure and function of CNN, details of each layer, the principles and features of BP and GD, and some examples in practice with a summary in the end.

Effects of the popular food additive sodium benzoate on neural tube development in the chicken embryo.

PubMed

Emon, Selin Tural; Orakdogen, Metin; Uslu, Serap; Somay, Hakan

2015-01-01

Many more additives have been introduced with the development of processed foods. Neural tube defects are congenital malformations of the central nervous system. More than 300 000 children are born with neural tube defects every year and surviving children remain disabled for life. Sodium benzoate is used intensively in our daily lives. We therefore aimed to evaluate the effects of sodium benzoate on neural tube defects in chicken embryos. Fertile, specific pathogen-free eggs were used. The study was conducted on five groups. After 30 hours of incubation, the eggs were opened under 4x optical magnification. The embryonic disc was identified and sodium benzoate solution was injected. Eggs were closed with sterile adhesive strips and incubation was continued till the end of the 72nd hour. All eggs were then reopened and embryos were dissected from embryonic membranes and evaluated histopathologically. We found that the development of all embryos was consistent with the stage. We detected neural tube obstruction in one embryo. Neural tube defects were not detected in any embryos. This study showed that sodium benzoate as one of the widely used food preservatives has no effect to neural tube defect development in chicken embryos even at high doses.

Neural substrates of decision-making.

PubMed

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

2016-06-01

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

Mis-expression of grainyhead-like transcription factors in zebrafish leads to defects in enveloping layer (EVL) integrity, cellular morphogenesis and axial extension.

PubMed

Miles, Lee B; Darido, Charbel; Kaslin, Jan; Heath, Joan K; Jane, Stephen M; Dworkin, Sebastian

2017-12-14

The grainyhead-like (grhl) transcription factors play crucial roles in craniofacial development, epithelial morphogenesis, neural tube closure, and dorso-ventral patterning. By utilising the zebrafish to differentially regulate expression of family members grhl2b and grhl3, we show that both genes regulate epithelial migration, particularly convergence-extension (CE) type movements, during embryogenesis. Genetic deletion of grhl3 via CRISPR/Cas9 results in failure to complete epiboly and pre-gastrulation embryonic rupture, whereas morpholino (MO)-mediated knockdown of grhl3 signalling leads to aberrant neural tube morphogenesis at the midbrain-hindbrain boundary (MHB), a phenotype likely due to a compromised overlying enveloping layer (EVL). Further disruptions of grhl3-dependent pathways (through co-knockdown of grhl3 with target genes spec1 and arhgef19) confirm significant MHB morphogenesis and neural tube closure defects. Concomitant MO-mediated disruption of both grhl2b and grhl3 results in further extensive CE-like defects in body patterning, notochord and somite morphogenesis. Interestingly, over-expression of either grhl2b or grhl3 also leads to numerous phenotypes consistent with disrupted cellular migration during gastrulation, including embryo dorsalisation, axial duplication and impaired neural tube migration leading to cyclopia. Taken together, our study ascribes novel roles to the Grhl family in the context of embryonic development and morphogenesis.

Center for Neural Engineering at Tennessee State University, ASSERT Annual Progress Report.

DTIC Science & Technology

1995-07-01

neural networks . Their research topics are: (1) developing frequency dependent oscillatory neural networks ; (2) long term pontentiation learning rules...as applied to spatial navigation; (3) design and build a servo joint robotic arm and (4) neural network based prothesis control. One graduate student

Prospects for neural stem cell-based therapies for neurological diseases.

PubMed

Imitola, Jaime

2007-10-01

Neural stem and progenitor cells have great potential for the treatment of neurological disorders. However, many obstacles remain to translate this field to the patient's bedside, including rationales for using neural stem cells in individual neurological disorders; the challenges of neural stem cell biology; and the caveats of current strategies of isolation and culturing neural precursors. Addressing these challenges is critical for the translation of neural stem cell biology to the clinic. Recent work using neural stem cells has yielded novel biologic concepts such as the importance of the reciprocal interaction between neural stem cells and the neurodegenerative environment. The prospect of using transplants of neural stem cells and progenitors to treat neurological diseases requires a better understanding of the molecular mechanisms of both neural stem cell behavior in experimental models and the intrinsic repair capacity of the injured brain.

Neural network approaches to capture temporal information

NASA Astrophysics Data System (ADS)

van Veelen, Martijn; Nijhuis, Jos; Spaanenburg, Ben

2000-05-01

The automated design and construction of neural networks receives growing attention of the neural networks community. Both the growing availability of computing power and development of mathematical and probabilistic theory have had severe impact on the design and modelling approaches of neural networks. This impact is most apparent in the use of neural networks to time series prediction. In this paper, we give our views on past, contemporary and future design and modelling approaches to neural forecasting.

Transcriptome Dynamics of Developing Photoreceptors in Three‐Dimensional Retina Cultures Recapitulates Temporal Sequence of Human Cone and Rod Differentiation Revealing Cell Surface Markers and Gene Networks

PubMed Central

Kaewkhaw, Rossukon; Kaya, Koray Dogan; Brooks, Matthew; Homma, Kohei; Zou, Jizhong; Chaitankar, Vijender; Rao, Mahendra

2015-01-01

Abstract The derivation of three‐dimensional (3D) stratified neural retina from pluripotent stem cells has permitted investigations of human photoreceptors. We have generated a H9 human embryonic stem cell subclone that carries a green fluorescent protein (GFP) reporter under the control of the promoter of cone‐rod homeobox (CRX), an established marker of postmitotic photoreceptor precursors. The CRXp‐GFP reporter replicates endogenous CRX expression in vitro when the H9 subclone is induced to form self‐organizing 3D retina‐like tissue. At day 37, CRX+ photoreceptors appear in the basal or middle part of neural retina and migrate to apical side by day 67. Temporal and spatial patterns of retinal cell type markers recapitulate the predicted sequence of development. Cone gene expression is concomitant with CRX, whereas rod differentiation factor neural retina leucine zipper protein (NRL) is first observed at day 67. At day 90, robust expression of NRL and its target nuclear receptor NR2E3 is evident in many CRX+ cells, while minimal S‐opsin and no rhodopsin or L/M‐opsin is present. The transcriptome profile, by RNA‐seq, of developing human photoreceptors is remarkably concordant with mRNA and immunohistochemistry data available for human fetal retina although many targets of CRX, including phototransduction genes, exhibit a significant delay in expression. We report on temporal changes in gene signatures, including expression of cell surface markers and transcription factors; these expression changes should assist in isolation of photoreceptors at distinct stages of differentiation and in delineating coexpression networks. Our studies establish the first global expression database of developing human photoreceptors, providing a reference map for functional studies in retinal cultures. Stem Cells 2015;33:3504–3518 PMID:26235913

E-cigarette aerosol exposure can cause craniofacial defects in Xenopus laevis embryos and mammalian neural crest cells

PubMed Central

Kennedy, Allyson E.; Kandalam, Suraj; Olivares-Navarrete, Rene

2017-01-01

Since electronic cigarette (ECIG) introduction to American markets in 2007, vaping has surged in popularity. Many, including women of reproductive age, also believe that ECIG use is safer than traditional tobacco cigarettes and is not hazardous when pregnant. However, there are few studies investigating the effects of ECIG exposure on the developing embryo and nothing is known about potential effects on craniofacial development. Therefore, we have tested the effects of several aerosolized e-cigarette liquids (e-cigAM) in an in vivo craniofacial model, Xenopus laevis, as well as a mammalian neural crest cell line. Results demonstrate that e-cigAM exposure during embryonic development induces a variety of defects, including median facial clefts and midface hypoplasia in two of e-cigAMs tested e-cigAMs. Detailed quantitative analyses of the facial morphology revealed that nicotine is not the main factor in inducing craniofacial defects, but can exacerbate the effects of the other e-liquid components. Additionally, while two different e-cigAMs can have very similar consequences on facial appearances, there are subtle differences that could be due to the differences in e-cigAM components. Further assessment of embryos exposed to these particular e-cigAMs revealed cranial cartilage and muscle defects and a reduction in the blood supply to the face. Finally, the expression of markers for vascular and cartilage differentiation was reduced in a mammalian neural crest cell line corroborating the in vivo effects. Our work is the first to show that ECIG use could pose a potential hazard to the developing embryo and cause craniofacial birth defects. This emphasizes the need for more testing and regulation of this new popular product. PMID:28957438

E-cigarette aerosol exposure can cause craniofacial defects in Xenopus laevis embryos and mammalian neural crest cells.

PubMed

Kennedy, Allyson E; Kandalam, Suraj; Olivares-Navarrete, Rene; Dickinson, Amanda J G

2017-01-01

Since electronic cigarette (ECIG) introduction to American markets in 2007, vaping has surged in popularity. Many, including women of reproductive age, also believe that ECIG use is safer than traditional tobacco cigarettes and is not hazardous when pregnant. However, there are few studies investigating the effects of ECIG exposure on the developing embryo and nothing is known about potential effects on craniofacial development. Therefore, we have tested the effects of several aerosolized e-cigarette liquids (e-cigAM) in an in vivo craniofacial model, Xenopus laevis, as well as a mammalian neural crest cell line. Results demonstrate that e-cigAM exposure during embryonic development induces a variety of defects, including median facial clefts and midface hypoplasia in two of e-cigAMs tested e-cigAMs. Detailed quantitative analyses of the facial morphology revealed that nicotine is not the main factor in inducing craniofacial defects, but can exacerbate the effects of the other e-liquid components. Additionally, while two different e-cigAMs can have very similar consequences on facial appearances, there are subtle differences that could be due to the differences in e-cigAM components. Further assessment of embryos exposed to these particular e-cigAMs revealed cranial cartilage and muscle defects and a reduction in the blood supply to the face. Finally, the expression of markers for vascular and cartilage differentiation was reduced in a mammalian neural crest cell line corroborating the in vivo effects. Our work is the first to show that ECIG use could pose a potential hazard to the developing embryo and cause craniofacial birth defects. This emphasizes the need for more testing and regulation of this new popular product.

Active Control of Wind-Tunnel Model Aeroelastic Response Using Neural Networks

NASA Technical Reports Server (NTRS)

Scott, Robert C.

2000-01-01

NASA Langley Research Center, Hampton, VA 23681 Under a joint research and development effort conducted by the National Aeronautics and Space Administration and The Boeing Company (formerly McDonnell Douglas) three neural-network based control systems were developed and tested. The control systems were experimentally evaluated using a transonic wind-tunnel model in the Langley Transonic Dynamics Tunnel. One system used a neural network to schedule flutter suppression control laws, another employed a neural network in a predictive control scheme, and the third employed a neural network in an inverse model control scheme. All three of these control schemes successfully suppressed flutter to or near the limits of the testing apparatus, and represent the first experimental applications of neural networks to flutter suppression. This paper will summarize the findings of this project.

Adaptive Fuzzy Systems in Computational Intelligence

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

An oil fraction neural sensor developed using electrical capacitance tomography sensor data.

PubMed

Zainal-Mokhtar, Khursiah; Mohamad-Saleh, Junita

2013-08-26

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.

Artificial neural network intelligent method for prediction

NASA Astrophysics Data System (ADS)

Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

2017-09-01

Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

An Oil Fraction Neural Sensor Developed Using Electrical capacitance Tomography Sensor Data

PubMed Central

Zainal-Mokhtar, Khursiah; Mohamad-Saleh, Junita

2013-01-01

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes. PMID:24064598

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers.

PubMed

Yamada, Takashi; Hashimoto, Ryu-Ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko; Kawato, Mitsuo

2017-10-01

Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., "theranostic biomarker") is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. © The Author 2017. Published by Oxford University Press on behalf of CINP.

Resting-State Functional Connectivity-Based Biomarkers and Functional MRI-Based Neurofeedback for Psychiatric Disorders: A Challenge for Developing Theranostic Biomarkers

PubMed Central

Yamada, Takashi; Hashimoto, Ryu-ichiro; Yahata, Noriaki; Ichikawa, Naho; Yoshihara, Yujiro; Okamoto, Yasumasa; Kato, Nobumasa; Takahashi, Hidehiko

2017-01-01

Abstract Psychiatric research has been hampered by an explanatory gap between psychiatric symptoms and their neural underpinnings, which has resulted in poor treatment outcomes. This situation has prompted us to shift from symptom-based diagnosis to data-driven diagnosis, aiming to redefine psychiatric disorders as disorders of neural circuitry. Promising candidates for data-driven diagnosis include resting-state functional connectivity MRI (rs-fcMRI)-based biomarkers. Although biomarkers have been developed with the aim of diagnosing patients and predicting the efficacy of therapy, the focus has shifted to the identification of biomarkers that represent therapeutic targets, which would allow for more personalized treatment approaches. This type of biomarker (i.e., “theranostic biomarker”) is expected to elucidate the disease mechanism of psychiatric conditions and to offer an individualized neural circuit-based therapeutic target based on the neural cause of a condition. To this end, researchers have developed rs-fcMRI-based biomarkers and investigated a causal relationship between potential biomarkers and disease-specific behavior using functional MRI (fMRI)-based neurofeedback on functional connectivity. In this review, we introduce a recent approach for creating a theranostic biomarker, which consists mainly of 2 parts: (1) developing an rs-fcMRI-based biomarker that can predict diagnosis and/or symptoms with high accuracy, and (2) the introduction of a proof-of-concept study investigating the relationship between normalizing the biomarker and symptom changes using fMRI-based neurofeedback. In parallel with the introduction of recent studies, we review rs-fcMRI-based biomarker and fMRI-based neurofeedback, focusing on the technological improvements and limitations associated with clinical use. PMID:28977523

A novel neural-inspired learning algorithm with application to clinical risk prediction.

PubMed

Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

2015-04-01

Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. Copyright © 2015 Elsevier Inc. All rights reserved.

Gap-Junctional communication between developing Drosophila muscles is essential for their normal development.

PubMed

Todman, M G; Baines, R A; Stebbings, L A; Davies, J A; Bacon, J P

1999-01-01

Recent experiments have demonstrated that a family of proteins, known as the innexins, are structural components of invertebrate gap junctions. The shaking-B (shak-B) locus of Drosophila encodes two members of this emerging family, Shak-B(lethal) and Shak-B(neural). This study focuses on the role of Shak-B gap junctions in the development of embryonic and larval muscle. During embryogenesis, shak-B transcripts are expressed in a subset of the somatic muscles; expression is strong in ventral oblique muscles (VO4-6) but only weak in ventral longitudinals (VL3 and 4). Carboxyfluorescein injected into VO4 of wild-type early stage 16 embryos spreads, via gap junctions, to label adjacent muscles, including VL3 and 4. In shak-B2 embryos (in which the shak-B(neural) function is disrupted), dye injected into VO4 fails to spread into other muscles. In the first instar larva, when dye coupling between muscles is no longer present, another effect of the shak-B2 mutation is revealed by whole-cell voltage clamp. In a calcium-free saline, only two voltage-activated potassium currents are present in wild-type muscles; a fast IA and a slow IK current. In shak-B2 larvae, these two currents are significantly reduced in magnitude in VO4 and 5, but remain normal in VL3. Expression of shak-B(neural) in a shak-B2 background fully rescues both dye coupling in embryonic muscle and whole-cell currents in first instar VO4 and 5. Our observations show that Shak-B(neural) is one of a set of embryonic gap-junction proteins, and that it is required for the normal temporal development of potassium currents in some larval muscles.

Accelerating bioelectric functional development of neural stem cells by graphene coupling: Implications for neural interfacing with conductive materials.

PubMed

Guo, Rongrong; Zhang, Shasha; Xiao, Miao; Qian, Fuping; He, Zuhong; Li, Dan; Zhang, Xiaoli; Li, Huawei; Yang, Xiaowei; Wang, Ming; Chai, Renjie; Tang, Mingliang

2016-11-01

In order to govern cell-specific behaviors in tissue engineering for neural repair and regeneration, a better understanding of material-cell interactions, especially the bioelectric functions, is extremely important. Graphene has been reported to be a potential candidate for use as a scaffold and neural interfacing material. However, the bioelectric evolvement of cell membranes on these conductive graphene substrates remains largely uninvestigated. In this study, we used a neural stem cell (NSC) model to explore the possible changes in membrane bioelectric properties - including resting membrane potentials and action potentials - and cell behaviors on graphene films under both proliferation and differentiation conditions. We used a combination of single-cell electrophysiological recordings and traditional cell biology techniques. Graphene did not affect the basic membrane electrical parameters (capacitance and input resistance), but resting membrane potentials of cells on graphene substrates were more strongly negative under both proliferation and differentiation conditions. Also, NSCs and their progeny on graphene substrates exhibited increased firing of action potentials during development compared to controls. However, graphene only slightly affected the electric characterizations of mature NSC progeny. The modulation of passive and active bioelectric properties on the graphene substrate was accompanied by enhanced NSC differentiation. Furthermore, spine density, synapse proteins expressions and synaptic activity were all increased in graphene group. Modeling of the electric field on conductive graphene substrates suggests that the electric field produced by the electronegative cell membrane is much higher on graphene substrates than that on control, and this might explain the observed changes of bioelectric development by graphene coupling. Our results indicate that graphene is able to accelerate NSC maturation during development, especially with regard to bioelectric evolvement. Our findings provide a fundamental understanding of the role of conductive materials in tuning the membrane bioelectric properties in a graphene model and pave the way for future studies on the development of methods and materials for manipulating membrane properties in a controllable way for NSC-based therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing neuronal networks: Self-organized criticality predicts the future

NASA Astrophysics Data System (ADS)

Pu, Jiangbo; Gong, Hui; Li, Xiangning; Luo, Qingming

2013-01-01

Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and ``aging'' process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.

Maturation of Cortico-Subcortical Structural Networks-Segregation and Overlap of Medial Temporal and Fronto-Striatal Systems in Development.

PubMed

Walhovd, Kristine B; Tamnes, Christian K; Bjørnerud, Atle; Due-Tønnessen, Paulina; Holland, Dominic; Dale, Anders M; Fjell, Anders M

2015-07-01

The brain consists of partly segregated neural circuits within which structural convergence and functional integration occurs during development. The relationship of structural cortical and subcortical maturation is largely unknown. We aimed to study volumetric development of the hippocampus and basal ganglia (caudate, putamen, pallidum, accumbens) in relation to volume changes throughout the cortex. Longitudinal MRI data were obtained across a mean interval of 2.6 years in 85 participants with an age range of 8-19 years at study start. Left and right subcortical changes were related to cortical change vertex-wise in the ipsilateral hemisphere with general linear models with age, sex, interval between scans, and mean cortical volume change as covariates. Hippocampal-cortical change relationships centered on parts of the Papez circuit, including entorhinal, parahippocampal, and isthmus cingulate areas, and lateral temporal, insular, and orbitofrontal cortices in the left hemisphere. Basal ganglia-cortical change relationships were observed in mostly nonoverlapping and more anterior cortical areas, all including the anterior cingulate. Other patterns were unique to specific basal ganglia structures, including pre-, post-, and paracentral patterns relating to putamen change. In conclusion, patterns of cortico-subcortical development as assessed by morphometric analyses in part map out segregated neural circuits at the macrostructural level. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Combined Use of Tissue Morphology, Neural Network Analysis of Chromatin Texture and Clinical Variables to Predict Prostate Cancer Agressiveness from Biopsy Water

DTIC Science & Technology

2000-10-01

Purpose: To combine clinical, serum, pathologic and computer derived information into an artificial neural network to develop/validate a model to...Development of an artificial neural network (year 02). Prospective validation of this model (projected year 03). All models will be tested and

Combined Use of Tissue Morphology, Neural Network Analysis of Chromatin Texture & Clinical Variables to Predict Prostate Cancer Agressiveness from Biopsy Material

DTIC Science & Technology

1999-10-01

THE PURPOSE OF THIS REPORT IS TO COMBINE CLINICAL, SERUM, PATHOLOGICAL AND COMPUTER DERIVED INFORMATION INTO AN ARTIFICIAL NEURAL NETWORK TO DEVELOP...01). Development of a artificial neural network model (year 02). Prospective validation of this model (projected year 03). All models will be tested

Non-Intrusive Gaze Tracking Using Artificial Neural Networks

DTIC Science & Technology

1994-01-05

We have developed an artificial neural network based gaze tracking, system which can be customized to individual users. A three layer feed forward...empirical analysis of the performance of a large number of artificial neural network architectures for this task. Suggestions for further explorations...for neurally based gaze trackers are presented, and are related to other similar artificial neural network applications such as autonomous road following.

Experiments in Neural-Network Control of a Free-Flying Space Robot

NASA Technical Reports Server (NTRS)

Wilson, Edward

1995-01-01

Four important generic issues are identified and addressed in some depth in this thesis as part of the development of an adaptive neural network based control system for an experimental free flying space robot prototype. The first issue concerns the importance of true system level design of the control system. A new hybrid strategy is developed here, in depth, for the beneficial integration of neural networks into the total control system. A second important issue in neural network control concerns incorporating a priori knowledge into the neural network. In many applications, it is possible to get a reasonably accurate controller using conventional means. If this prior information is used purposefully to provide a starting point for the optimizing capabilities of the neural network, it can provide much faster initial learning. In a step towards addressing this issue, a new generic Fully Connected Architecture (FCA) is developed for use with backpropagation. A third issue is that neural networks are commonly trained using a gradient based optimization method such as backpropagation; but many real world systems have Discrete Valued Functions (DVFs) that do not permit gradient based optimization. One example is the on-off thrusters that are common on spacecraft. A new technique is developed here that now extends backpropagation learning for use with DVFs. The fourth issue is that the speed of adaptation is often a limiting factor in the implementation of a neural network control system. This issue has been strongly resolved in the research by drawing on the above new contributions.

Integrating Artificial Immune, Neural and Endrocine Systems in Autonomous Sailing Robots

DTIC Science & Technology

2010-09-24

system - Development of an adaptive hormone system capable of changing operation and control of the neural network depending on changing enviromental ...and control of the neural network depending on changing enviromental conditions • First basic design of the MOOP and a simple neural-endocrine based

A New Animal Model for Developing a Somatosensory Neural Interface for Prosthetic Limbs

DTIC Science & Technology

2008-02-12

interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D. University of Pittsburgh 1 10/15/2007 Scientific progress and accomplishments. We...information to the brain. A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D...A new animal model for developing a somatosensory neural interface for neuroprosthetic limbs . PI: Douglas J. Weber, Ph.D. University of Pittsburgh

Neural network controller development for a magnetically suspended flywheel energy storage system

NASA Technical Reports Server (NTRS)

Fittro, Roger L.; Pang, Da-Chen; Anand, Davinder K.

1994-01-01

A neural network controller has been developed to accommodate disturbances and nonlinearities and improve the robustness of a magnetically suspended flywheel energy storage system. The controller is trained using the back propagation-through-time technique incorporated with a time-averaging scheme. The resulting nonlinear neural network controller improves system performance by adapting flywheel stiffness and damping based on operating speed. In addition, a hybrid multi-layered neural network controller is developed off-line which is capable of improving system performance even further. All of the research presented in this paper was implemented via a magnetic bearing computer simulation. However, careful attention was paid to developing a practical methodology which will make future application to the actual bearing system fairly straightforward.

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

EPA Science Inventory

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...

An Engineered Organoid Culture Model That Incorporates Human Mesenchymal and Epithelial Cells to Model Palatal Fusion.

EPA Science Inventory

During embryonic development, fusion events are critical to morphogenesis of organs and tissues, including the iris, urethra, heart, neural tube, and secondary palate. Modeling this process in vitro is challenging as the interactions of mesenchymal and epithelial cells can be cr...

Alcohol-Induced Molecular Dysregulation in Human Embryonic Stem Cell-Derived Neural Precursor Cells

PubMed Central

Kim, Yi Young; Roubal, Ivan; Lee, Youn Soo; Kim, Jin Seok; Hoang, Michael; Mathiyakom, Nathan; Kim, Yong

2016-01-01

Adverse effect of alcohol on neural function has been well documented. Especially, the teratogenic effect of alcohol on neurodevelopment during embryogenesis has been demonstrated in various models, which could be a pathologic basis for fetal alcohol spectrum disorders (FASDs). While the developmental defects from alcohol abuse during gestation have been described, the specific mechanisms by which alcohol mediates these injuries have yet to be determined. Recent studies have shown that alcohol has significant effect on molecular and cellular regulatory mechanisms in embryonic stem cell (ESC) differentiation including genes involved in neural development. To test our hypothesis that alcohol induces molecular alterations during neural differentiation we have derived neural precursor cells from pluripotent human ESCs in the presence or absence of ethanol treatment. Genome-wide transcriptomic profiling identified molecular alterations induced by ethanol exposure during neural differentiation of hESCs into neural rosettes and neural precursor cell populations. The Database for Annotation, Visualization and Integrated Discovery (DAVID) functional analysis on significantly altered genes showed potential ethanol’s effect on JAK-STAT signaling pathway, neuroactive ligand-receptor interaction, Toll-like receptor (TLR) signaling pathway, cytokine-cytokine receptor interaction and regulation of autophagy. We have further quantitatively verified ethanol-induced alterations of selected candidate genes. Among verified genes we further examined the expression of P2RX3, which is associated with nociception, a peripheral pain response. We found ethanol significantly reduced the level of P2RX3 in undifferentiated hESCs, but induced the level of P2RX3 mRNA and protein in hESC-derived NPCs. Our result suggests ethanol-induced dysregulation of P2RX3 along with alterations in molecules involved in neural activity such as neuroactive ligand-receptor interaction may be a molecular event associated with alcohol-related peripheral neuropathy of an enhanced nociceptive response. PMID:27682028

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

PubMed

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

2012-01-01

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

Single-Factor SOX2 Mediates Direct Neural Reprogramming of Human Mesenchymal Stem Cells via Transfection of In Vitro Transcribed mRNA.

PubMed

Kim, Bo-Eun; Choi, Soon Won; Shin, Ji-Hee; Kim, Jae-Jun; Kang, Insung; Lee, Byung-Chul; Lee, Jin Young; Kook, Myoung Geun; Kang, Kyung-Sun

2018-01-01

Neural stem cells (NSCs) are a prominent cell source for understanding neural pathogenesis and for developing therapeutic applications to treat neurodegenerative disease because of their regenerative capacity and multipotency. Recently, a variety of cellular reprogramming technologies have been developed to facilitate in vitro generation of NSCs, called induced NSCs (iNSCs). However, the genetic safety aspects of established virus-based reprogramming methods have been considered, and non-integrating reprogramming methods have been developed. Reprogramming with in vitro transcribed (IVT) mRNA is one of the genetically safe reprogramming methods because exogenous mRNA temporally exists in the cell and is not integrated into the chromosome. Here, we successfully generated expandable iNSCs from human umbilical cord blood-derived mesenchymal stem cells (UCB-MSCs) via transfection with IVT mRNA encoding SOX2 (SOX2 mRNA) with properly optimized conditions. We confirmed that generated human UCB-MSC-derived iNSCs (UM-iNSCs) possess characteristics of NSCs, including multipotency and self-renewal capacity. Additionally, we transfected human dermal fibroblasts (HDFs) with SOX2 mRNA. Compared with human embryonic stem cell-derived NSCs, HDFs transfected with SOX2 mRNA exhibited neural reprogramming with similar morphologies and NSC-enriched mRNA levels, but they showed limited proliferation ability. Our results demonstrated that human UCB-MSCs can be used for direct reprogramming into NSCs through transfection with IVT mRNA encoding a single factor, which provides an integration-free reprogramming tool for future therapeutic application.

Dynamic network communication as a unifying neural basis for cognition, development, aging, and disease.

PubMed

Voytek, Bradley; Knight, Robert T

2015-06-15

Perception, cognition, and social interaction depend upon coordinated neural activity. This coordination operates within noisy, overlapping, and distributed neural networks operating at multiple timescales. These networks are built upon a structural scaffolding with intrinsic neuroplasticity that changes with development, aging, disease, and personal experience. In this article, we begin from the perspective that successful interregional communication relies upon the transient synchronization between distinct low-frequency (<80 Hz) oscillations, allowing for brief windows of communication via phase-coordinated local neuronal spiking. From this, we construct a theoretical framework for dynamic network communication, arguing that these networks reflect a balance between oscillatory coupling and local population spiking activity and that these two levels of activity interact. We theorize that when oscillatory coupling is too strong, spike timing within the local neuronal population becomes too synchronous; when oscillatory coupling is too weak, spike timing is too disorganized. Each results in specific disruptions to neural communication. These alterations in communication dynamics may underlie cognitive changes associated with healthy development and aging, in addition to neurological and psychiatric disorders. A number of neurological and psychiatric disorders-including Parkinson's disease, autism, depression, schizophrenia, and anxiety-are associated with abnormalities in oscillatory activity. Although aging, psychiatric and neurological disease, and experience differ in the biological changes to structural gray or white matter, neurotransmission, and gene expression, our framework suggests that any resultant cognitive and behavioral changes in normal or disordered states or their treatment are a product of how these physical processes affect dynamic network communication. Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2016-02-01

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

Molecular Parallels between Neural and Vascular Development

PubMed Central

Eichmann, Anne; Thomas, Jean-Léon

2013-01-01

The human central nervous system (CNS) features a network of ∼400 miles of blood vessels that receives >20% of the body’s cardiac output and uses most of its blood glucose. Many human diseases, including stroke, retinopathy, and cancer, are associated with the biology of CNS blood vessels. These vessels originate from extrinsic cell populations, including endothelial cells and pericytes that colonize the CNS and interact with glia and neurons to establish the blood–brain barrier and control cerebrovascular exchanges. Neurovascular interactions also play important roles in adult neurogenic niches, which harbor a unique population of neural stem cells that are intimately associated with blood vessels. We here review the cellular and molecular mechanisms required to establish the CNS vascular network, with a special focus on neurovascular interactions and the functions of vascular endothelial growth factors. PMID:23024177

Postnatal brain development: Structural imaging of dynamic neurodevelopmental processes

PubMed Central

Jernigan, Terry L.; Baaré, William F. C.; Stiles, Joan; Madsen, Kathrine Skak

2013-01-01

After birth, there is striking biological and functional development of the brain’s fiber tracts as well as remodeling of cortical and subcortical structures. Behavioral development in children involves a complex and dynamic set of genetically guided processes by which neural structures interact constantly with the environment. This is a protracted process, beginning in the third week of gestation and continuing into early adulthood. Reviewed here are studies using structural imaging techniques, with a special focus on diffusion weighted imaging, describing age-related brain maturational changes in children and adolescents, as well as studies that link these changes to behavioral differences. Finally, we discuss evidence for effects on the brain of several factors that may play a role in mediating these brain–behavior associations in children, including genetic variation, behavioral interventions, and hormonal variation associated with puberty. At present longitudinal studies are few, and we do not yet know how variability in individual trajectories of biological development in specific neural systems map onto similar variability in behavioral trajectories. PMID:21489384

Role of Dlx6 in regulation of an endothelin-1-dependent, dHAND branchial arch enhancer

PubMed Central

Charité, Jeroen; McFadden, David G.; Merlo, Giorgio; Levi, Giovanni; Clouthier, David E.; Yanagisawa, Masashi; Richardson, James A.; Olson, Eric N.

2001-01-01

Neural crest cells play a key role in craniofacial development. The endothelin family of secreted polypeptides regulates development of several neural crest sublineages, including the branchial arch neural crest. The basic helix–loop–helix transcription factor dHAND is also required for craniofacial development, and in endothelin-1 (ET-1) mutant embryos, dHAND expression in the branchial arches is down-regulated, implicating it as a transcriptional effector of ET-1 action. To determine the mechanism that links ET-1 signaling to dHAND transcription, we analyzed the dHAND gene for cis-regulatory elements that control transcription in the branchial arches. We describe an evolutionarily conserved dHAND enhancer that requires ET-1 signaling for activity. This enhancer contains four homeodomain binding sites that are required for branchial arch expression. By comparing protein binding to these sites in branchial arch extracts from endothelin receptor A (EdnrA) mutant and wild-type mouse embryos, we identified Dlx6, a member of the Distal-less family of homeodomain proteins, as an ET-1-dependent binding factor. Consistent with this conclusion, Dlx6 was down-regulated in branchial arches from EdnrA mutant mice. These results suggest that Dlx6 acts as an intermediary between ET-1 signaling and dHAND transcription during craniofacial morphogenesis. PMID:11711438

Real-time functional magnetic resonance imaging neurofeedback in motor neurorehabilitation.

PubMed

Linden, David E J; Turner, Duncan L

2016-08-01

Recent developments in functional magnetic resonance imaging (fMRI) have catalyzed a new field of translational neuroscience. Using fMRI to monitor the aspects of task-related changes in neural activation or brain connectivity, investigators can offer feedback of simple or complex neural signals/patterns back to the participant on a quasireal-time basis [real-time-fMRI-based neurofeedback (rt-fMRI-NF)]. Here, we introduce some background methodology of the new developments in this field and give a perspective on how they may be used in neurorehabilitation in the future. The development of rt-fMRI-NF has been used to promote self-regulation of activity in several brain regions and networks. In addition, and unlike other noninvasive techniques, rt-fMRI-NF can access specific subcortical regions and in principle any region that can be monitored using fMRI including the cerebellum, brainstem and spinal cord. In Parkinson's disease and stroke, rt-fMRI-NF has been demonstrated to alter neural activity after the self-regulation training was completed and to modify specific behaviours. Future exploitation of rt-fMRI-NF could be used to induce neuroplasticity in brain networks that are involved in certain neurological conditions. However, currently, the use of rt-fMRI-NF in randomized, controlled clinical trials is in its infancy.

Differential display cloning of a novel rat cDNA (RNB6) that shows high expression in the neonatal brain revealed a member of Ena/VASP family.

PubMed

Ohta, S; Mineta, T; Kimoto, M; Tabuchi, K

1997-08-18

We have used the differential display method to identify genes that control the neural cell development in CNS. Screening of the differential display bands that showed higher expression at neonate than at adult age enabled us to identify a novel rat cDNA (RNB6) coding for a protein of 393 amino acid residues. Database search revealed this gene as a rat homologue of the murine EVL, a member of Ena/VASP protein family that is implicated to be involved in the control of cell motility through actin filament assembly by their GP5 motifs. Although the precise characterization of EVL was not reported, our Northern blot and immunoblot analyses demonstrated that RNB6 expression in the brain gradually increases during embryonic development, reaches maximum at postnatal day 1 and decreases thereafter. Studies of tissue distribution revealed the expression of RNB6 not only in the brain but also in the spleen, thymus and testis. Histochemical analyses showed that RNB6 protein is mainly expressed in neurons and may be expressed in neural fibers. Our analyses suggest that RNB6 is critically involved in the development of CNS probably through the control of neural cell motility and/or including neuronal fiber extension.

In vitro generation of three-dimensional substrate-adherent embryonic stem cell-derived neural aggregates for application in animal models of neurological disorders.

PubMed

Hargus, Gunnar; Cui, Yi-Fang; Dihné, Marcel; Bernreuther, Christian; Schachner, Melitta

2012-05-01

In vitro-differentiated embryonic stem (ES) cells comprise a useful source for cell replacement therapy, but the efficiency and safety of a translational approach are highly dependent on optimized protocols for directed differentiation of ES cells into the desired cell types in vitro. Furthermore, the transplantation of three-dimensional ES cell-derived structures instead of a single-cell suspension may improve graft survival and function by providing a beneficial microenvironment for implanted cells. To this end, we have developed a new method to efficiently differentiate mouse ES cells into neural aggregates that consist predominantly (>90%) of postmitotic neurons, neural progenitor cells, and radial glia-like cells. When transplanted into the excitotoxically lesioned striatum of adult mice, these substrate-adherent embryonic stem cell-derived neural aggregates (SENAs) showed significant advantages over transplanted single-cell suspensions of ES cell-derived neural cells, including improved survival of GABAergic neurons, increased cell migration, and significantly decreased risk of teratoma formation. Furthermore, SENAs mediated functional improvement after transplantation into animal models of Parkinson's disease and spinal cord injury. This unit describes in detail how SENAs are efficiently derived from mouse ES cells in vitro and how SENAs are isolated for transplantation. Furthermore, methods are presented for successful implantation of SENAs into animal models of Huntington's disease, Parkinson's disease, and spinal cord injury to study the effects of stem cell-derived neural aggregates in a disease context in vivo.

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

NASA Astrophysics Data System (ADS)

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

2016-10-01

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

Visuospatial Asymmetries Arise from Differences in the Onset Time of Perceptual Evidence Accumulation.

PubMed

Newman, Daniel P; Loughnane, Gerard M; Kelly, Simon P; O'Connell, Redmond G; Bellgrove, Mark A

2017-03-22

Healthy subjects tend to exhibit a bias of visual attention whereby left hemifield stimuli are processed more quickly and accurately than stimuli appearing in the right hemifield. It has long been held that this phenomenon arises from the dominant role of the right cerebral hemisphere in regulating attention. However, methods that would enable more precise understanding of the mechanisms underpinning visuospatial bias have remained elusive. We sought to finely trace the temporal evolution of spatial biases by leveraging a novel bilateral dot motion detection paradigm. In combination with electroencephalography, this paradigm enables researchers to isolate discrete neural signals reflecting the key neural processes needed for making these detection decisions. These include signals for spatial attention, early target selection, evidence accumulation, and motor preparation. Using this method, we established that three key neural markers accounted for unique between-subject variation in visuospatial bias: hemispheric asymmetry in posterior α power measured before target onset, which is related to the distribution of preparatory attention across the visual field; asymmetry in the peak latency of the early N2c target-selection signal; and, finally, asymmetry in the onset time of the subsequent neural evidence-accumulation process with earlier onsets for left hemifield targets. Our development of a single paradigm to dissociate distinct processing components that track the temporal evolution of spatial biases not only advances our understanding of the neural mechanisms underpinning normal visuospatial attention bias, but may also in the future aid differential diagnoses in disorders of spatial attention. SIGNIFICANCE STATEMENT The significance of this research is twofold. First, it shows that individual differences in how humans direct their attention between left and right space reflects physiological differences in how early the brain starts to accumulate evidence for the existence of a visual target. Second, the novel methods developed here may have particular relevance to disorders of attention, such as unilateral spatial neglect. In the case of spatial neglect, pathological inattention to left space could have multiple underlying causes, including biased attention, impaired decision formation, or a motor deficit related to one side of space. Our development of a single paradigm to dissociate each of these components may aid in supporting more precise differential diagnosis in such heterogeneous disorders. Copyright © 2017 the authors 0270-6474/17/373378-08$15.00/0.

The Neural Border: Induction, Specification and Maturation of the territory that generates Neural Crest cells.

PubMed

Pla, Patrick; Monsoro-Burq, Anne H

2018-05-28

The neural crest is induced at the edge between the neural plate and the nonneural ectoderm, in an area called the neural (plate) border, during gastrulation and neurulation. In recent years, many studies have explored how this domain is patterned, and how the neural crest is induced within this territory, that also participates to the prospective dorsal neural tube, the dorsalmost nonneural ectoderm, as well as placode derivatives in the anterior area. This review highlights the tissue interactions, the cell-cell signaling and the molecular mechanisms involved in this dynamic spatiotemporal patterning, resulting in the induction of the premigratory neural crest. Collectively, these studies allow building a complex neural border and early neural crest gene regulatory network, mostly composed by transcriptional regulations but also, more recently, including novel signaling interactions. Copyright © 2018. Published by Elsevier Inc.

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

PubMed Central

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

2016-01-01

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