Artificial Neural Networks in Evaluation and Optimization of Modified Release Solid Dosage Forms

PubMed Central

Ibrić, Svetlana; Djuriš, Jelena; Parojčić, Jelena; Djurić, Zorica

2012-01-01

Implementation of the Quality by Design (QbD) approach in pharmaceutical development has compelled researchers in the pharmaceutical industry to employ Design of Experiments (DoE) as a statistical tool, in product development. Among all DoE techniques, response surface methodology (RSM) is the one most frequently used. Progress of computer science has had an impact on pharmaceutical development as well. Simultaneous with the implementation of statistical methods, machine learning tools took an important place in drug formulation. Twenty years ago, the first papers describing application of artificial neural networks in optimization of modified release products appeared. Since then, a lot of work has been done towards implementation of new techniques, especially Artificial Neural Networks (ANN) in modeling of production, drug release and drug stability of modified release solid dosage forms. The aim of this paper is to review artificial neural networks in evaluation and optimization of modified release solid dosage forms. PMID:24300369

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.

Maximization of Learning Speed Due to Neuronal Redundancy in Reinforcement Learning

NASA Astrophysics Data System (ADS)

Takiyama, Ken

2016-11-01

Adaptable neural activity contributes to the flexibility of human behavior, which is optimized in situations such as motor learning and decision making. Although learning signals in motor learning and decision making are low-dimensional, neural activity, which is very high dimensional, must be modified to achieve optimal performance based on the low-dimensional signal, resulting in a severe credit-assignment problem. Despite this problem, the human brain contains a vast number of neurons, leaving an open question: what is the functional significance of the huge number of neurons? Here, I address this question by analyzing a redundant neural network with a reinforcement-learning algorithm in which the numbers of neurons and output units are N and M, respectively. Because many combinations of neural activity can generate the same output under the condition of N ≫ M, I refer to the index N - M as neuronal redundancy. Although greater neuronal redundancy makes the credit-assignment problem more severe, I demonstrate that a greater degree of neuronal redundancy facilitates learning speed. Thus, in an apparent contradiction of the credit-assignment problem, I propose the hypothesis that a functional role of a huge number of neurons or a huge degree of neuronal redundancy is to facilitate learning speed.

Running, swimming and diving modifies neuroprotecting globins in the mammalian brain

PubMed Central

Williams, Terrie M; Zavanelli, Mary; Miller, Melissa A; Goldbeck, Robert A; Morledge, Michael; Casper, Dave; Pabst, D. Ann; McLellan, William; Cantin, Lucas P; Kliger, David S

2007-01-01

The vulnerability of the human brain to injury following just a few minutes of oxygen deprivation with submergence contrasts markedly with diving mammals, such as Weddell seals (Leptonychotes weddellii), which can remain underwater for more than 90 min while exhibiting no neurological or behavioural impairment. This response occurs despite exposure to blood oxygen levels concomitant with human unconsciousness. To determine whether such aquatic lifestyles result in unique adaptations for avoiding ischaemic–hypoxic neural damage, we measured the presence of circulating (haemoglobin) and resident (neuroglobin and cytoglobin) oxygen-carrying globins in the cerebral cortex of 16 mammalian species considered terrestrial, swimming or diving specialists. Here we report a striking difference in globin levels depending on activity lifestyle. A nearly 9.5-fold range in haemoglobin concentration (0.17–1.62 g Hb 100 g brain wet wt−1) occurred between terrestrial and deep-diving mammals; a threefold range in resident globins was evident between terrestrial and swimming specialists. Together, these two globin groups provide complementary mechanisms for facilitating oxygen transfer into neural tissues and the potential for protection against reactive oxygen and nitrogen groups. This enables marine mammals to maintain sensory and locomotor neural functions during prolonged submergence, and suggests new avenues for averting oxygen-mediated neural injury in the mammalian brain. PMID:18089537

The heparan sulfate-modifying enzyme glucuronyl C5-epimerase HSE-5 controls Caenorhabditis elegans Q neuroblast polarization during migration.

PubMed

Wang, Xiangming; Liu, Jianhong; Zhu, Zhiwen; Ou, Guangshuo

2015-03-15

Directional cell migration is fundamental for neural development, and extracellular factors are pivotal for this process. Heparan sulfate proteoglycans (HSPGs) that carry long chains of differentially modified sugar residues contribute to extracellular matrix; however, the functions of HSPG in guiding cell migration remain elusive. Here, we used the Caenorhabditis elegans mutant pool from the Million Mutation Project and isolated a mutant allele of the heparan sulfate-modifying enzyme glucuronyl C5-epimerase HSE-5. Loss-of-function of this enzyme resulted in defective Q neuroblast migration. We showed that hse-5 controlled Q cell migration in a cell non-autonomous manner. By performing live cell imaging in hse-5 mutant animals, we found that hse-5 controlled initial polarization during Q neuroblast migration. Furthermore, our genetic epistasis analysis demonstrated that lon-2 might act downstream of hse-5. Finally, rescue of the hse-5 mutant phenotype by expression of human and mouse hse-5 homologs suggested a conserved function for this gene in neural development. Taken together, our results indicated that proper HSPG modification in the extracellular matrix by HSE-5 is essential for neuroblast polarity during migration. Copyright © 2015 Elsevier Inc. All rights reserved.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Neural correlates of behavioral preference for culturally familiar drinks.

PubMed

McClure, Samuel M; Li, Jian; Tomlin, Damon; Cypert, Kim S; Montague, Latané M; Montague, P Read

2004-10-14

Coca-Cola (Coke) and Pepsi are nearly identical in chemical composition, yet humans routinely display strong subjective preferences for one or the other. This simple observation raises the important question of how cultural messages combine with content to shape our perceptions; even to the point of modifying behavioral preferences for a primary reward like a sugared drink. We delivered Coke and Pepsi to human subjects in behavioral taste tests and also in passive experiments carried out during functional magnetic resonance imaging (fMRI). Two conditions were examined: (1) anonymous delivery of Coke and Pepsi and (2) brand-cued delivery of Coke and Pepsi. For the anonymous task, we report a consistent neural response in the ventromedial prefrontal cortex that correlated with subjects' behavioral preferences for these beverages. In the brand-cued experiment, brand knowledge for one of the drinks had a dramatic influence on expressed behavioral preferences and on the measured brain responses.

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.

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) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: 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.

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

PubMed

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

2017-12-27

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Retinal pigment epithelium culture;a potential source of retinal stem cells.

PubMed

Akrami, Hassan; Soheili, Zahra-Soheila; Khalooghi, Keynoush; Ahmadieh, Hamid; Rezaie-Kanavi, Mojgan; Samiei, Shahram; Davari, Malihe; Ghaderi, Shima; Sanie-Jahromi, Fatemeh

2009-07-01

To establish human retinal pigment epithelial (RPE) cell culture as a source for cell replacement therapy in ocular diseases. Human cadaver globes were used to isolate RPE cells. Each globe was cut into several pieces of a few millimeters in size. After removing the sclera and choroid, remaining tissues were washed in phosphate buffer saline and RPE cells were isolated using dispase enzyme solution and cultured in Dulbecco's Modified Eagle's Medium: Nutrient Mixture F-12 supplemented with 10% fetal calf serum. Primary cultures of RPE cells were established and spheroid colonies related to progenitor/stem cells developed in a number of cultures. The colonies included purely pigmented or mixed pigmented and non-pigmented cells. After multiple cellular passages, several types of photoreceptors and neural-like cells were detected morphologically. Cellular plasticity in RPE cell cultures revealed promising results in terms of generation of stem/progenitor cells from human RPE cells. Whether the spheroids and neural-like retinal cells were directly derived from retinal stem cells or offspring of trans-differentiating or de-differentiating RPE cells remains to be answered.

Retinal Pigment Epithelium Culture;a Potential Source of Retinal Stem Cells

PubMed Central

Akrami, Hassan; Soheili, Zahra-Soheila; Khalooghi, Keynoush; Ahmadieh, Hamid; Rezaie-Kanavi, Mojgan; Samiei, Shahram; Davari, Malihe; Ghaderi, Shima; Sanie-Jahromi, Fatemeh

2009-01-01

Purpose To establish human retinal pigment epithelial (RPE) cell culture as a source for cell replacement therapy in ocular diseases. Methods Human cadaver globes were used to isolate RPE cells. Each globe was cut into several pieces of a few millimeters in size. After removing the sclera and choroid, remaining tissues were washed in phosphate buffer saline and RPE cells were isolated using dispase enzyme solution and cultured in Dulbecco’s Modified Eagle’s Medium: Nutrient Mixture F-12 supplemented with 10% fetal calf serum. Results Primary cultures of RPE cells were established and spheroid colonies related to progenitor/stem cells developed in a number of cultures. The colonies included purely pigmented or mixed pigmented and non-pigmented cells. After multiple cellular passages, several types of photoreceptors and neural-like cells were detected morphologically. Conclusion Cellular plasticity in RPE cell cultures revealed promising results in terms of generation of stem/progenitor cells from human RPE cells. Whether the spheroids and neural-like retinal cells were directly derived from retinal stem cells or offspring of trans-differentiating or de-differentiating RPE cells remains to be answered. PMID:23198062

Challenging emotional prejudice by changing self-concept: priming independent self-construal reduces racial in-group bias in neural responses to other’s pain

PubMed Central

Wu, Bing; Liu, Yi; Wu, Xinhuai; Han, Shihui

2015-01-01

Humans show stronger empathy for in-group compared with out-group members’ suffering and help in-group members more than out-group members. Moreover, the in-group bias in empathy and parochial altruism tend to be more salient in collectivistic than individualistic cultures. This work tested the hypothesis that modifying self-construals, which differentiate between collectivistic and individualistic cultural orientations, affects in-group bias in empathy for perceived own-race vs other-race pain. By scanning adults using functional magnetic resonance imaging, we found stronger neural activities in the mid-cingulate, left insula and supplementary motor area (SMA) in response to racial in-group compared with out-group members’ pain after participants had been primed with interdependent self-construals. However, the racial in-group bias in neural responses to others’ pain in the left SMA, mid-cingulate cortex and insula was significantly reduced by priming independent self-construals. Our findings suggest that shifting an individual’s self-construal leads to changes of his/her racial in-group bias in neural responses to others’ suffering. PMID:25605968

Neural Correlates of Visual–Spatial Attention in Electrocorticographic Signals in Humans

PubMed Central

Gunduz, Aysegul; Brunner, Peter; Daitch, Amy; Leuthardt, Eric C.; Ritaccio, Anthony L.; Pesaran, Bijan; Schalk, Gerwin

2011-01-01

Attention is a cognitive selection mechanism that allocates the limited processing resources of the brain to the sensory streams most relevant to our immediate goals, thereby enhancing responsiveness and behavioral performance. The underlying neural mechanisms of orienting attention are distributed across a widespread cortical network. While aspects of this network have been extensively studied, details about the electrophysiological dynamics of this network are scarce. In this study, we investigated attentional networks using electrocorticographic (ECoG) recordings from the surface of the brain, which combine broad spatial coverage with high temporal resolution, in five human subjects. ECoG was recorded when subjects covertly attended to a spatial location and responded to contrast changes in the presence of distractors in a modified Posner cueing task. ECoG amplitudes in the alpha, beta, and gamma bands identified neural changes associated with covert attention and motor preparation/execution in the different stages of the task. The results show that attentional engagement was primarily associated with ECoG activity in the visual, prefrontal, premotor, and parietal cortices. Motor preparation/execution was associated with ECoG activity in premotor/sensorimotor cortices. In summary, our results illustrate rich and distributed cortical dynamics that are associated with orienting attention and the subsequent motor preparation and execution. These findings are largely consistent with and expand on primate studies using intracortical recordings and human functional neuroimaging studies. PMID:22046153

Yarn-dyed fabric defect classification based on convolutional neural network

NASA Astrophysics Data System (ADS)

Jing, Junfeng; Dong, Amei; Li, Pengfei

2017-07-01

Considering that the manual inspection of the yarn-dyed fabric can be time consuming and less efficient, a convolutional neural network (CNN) solution based on the modified AlexNet structure for the classification of the yarn-dyed fabric defect is proposed. CNN has powerful ability of feature extraction and feature fusion which can simulate the learning mechanism of the human brain. In order to enhance computational efficiency and detection accuracy, the local response normalization (LRN) layers in AlexNet are replaced by the batch normalization (BN) layers. In the process of the network training, through several convolution operations, the characteristics of the image are extracted step by step, and the essential features of the image can be obtained from the edge features. And the max pooling layers, the dropout layers, the fully connected layers are also employed in the classification model to reduce the computation cost and acquire more precise features of fabric defect. Finally, the results of the defect classification are predicted by the softmax function. The experimental results show the capability of defect classification via the modified Alexnet model and indicate its robustness.

Acute Delayed Neurotoxicity Evaluation of Two Jet Engine Oils using a Modified Navy and EPA Protocol

DTIC Science & Technology

1992-08-01

Clinical Observations..................................................... 9 Sacrifice and Histopathology ...Single Dose ............... 13 5 Neural Histop.-Ohologic Incidence Summary (Repeated Assay) ..................... 15 6 Neural Histopathologic Lesions...Average Severity Scores (Repeated Assay) ......... 16 7 Neural Histopathologic Incidence Summary (Single-Dose Assay) .................. 17 8 Neural

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

PubMed Central

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

2009-01-01

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

Over-expression of Oct4 and Sox2 transcription factors enhances differentiation of human umbilical cord blood cells in vivo

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

Guseva, Daria; Hannover Medical School, Hannover; Rizvanov, Albert A.

2014-09-05

Highlights: • Gene and cell-based therapies comprise innovative aspects of regenerative medicine. • Genetically modified hUCB-MCs enhanced differentiation of cells in a mouse model of ALS. • Stem cells successfully transformed into micro-glial and endothelial lines in spinal cords. • Over-expressing oct4 and sox2 also induced production of neural marker PGP9.5. • Formation of new nerve cells, secreting trophic factors and neo-vascularisation could improve symptoms in ALS. - Abstract: Gene and cell-based therapies comprise innovative aspects of regenerative medicine. Even though stem cells represent a highly potential therapeutic strategy, their wide-spread exploitation is marred by ethical concerns, potential for malignantmore » transformation and a plethora of other technical issues, largely restricting their use to experimental studies. Utilizing genetically modified human umbilical cord blood mono-nuclear cells (hUCB-MCs), this communication reports enhanced differentiation of transplants in a mouse model of amyotrophic lateral sclerosis (ALS). Over-expressing Oct4 and Sox2 induced production of neural marker PGP9.5, as well as transformation of hUCB-MCs into micro-glial and endothelial lines in ALS spinal cords. In addition to producing new nerve cells, providing degenerated areas with trophic factors and neo-vascularisation might prevent and even reverse progressive loss of moto-neurons and skeletal muscle paralysis.« less

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.

Dissociation between Neural Signatures of Stimulus and Choice in Population Activity of Human V1 during Perceptual Decision-Making

PubMed Central

Choe, Kyoung Whan; Blake, Randolph

2014-01-01

Primary visual cortex (V1) forms the initial cortical representation of objects and events in our visual environment, and it distributes information about that representation to higher cortical areas within the visual hierarchy. Decades of work have established tight linkages between neural activity occurring in V1 and features comprising the retinal image, but it remains debatable how that activity relates to perceptual decisions. An actively debated question is the extent to which V1 responses determine, on a trial-by-trial basis, perceptual choices made by observers. By inspecting the population activity of V1 from human observers engaged in a difficult visual discrimination task, we tested one essential prediction of the deterministic view: choice-related activity, if it exists in V1, and stimulus-related activity should occur in the same neural ensemble of neurons at the same time. Our findings do not support this prediction: while cortical activity signifying the variability in choice behavior was indeed found in V1, that activity was dissociated from activity representing stimulus differences relevant to the task, being advanced in time and carried by a different neural ensemble. The spatiotemporal dynamics of population responses suggest that short-term priors, perhaps formed in higher cortical areas involved in perceptual inference, act to modulate V1 activity prior to stimulus onset without modifying subsequent activity that actually represents stimulus features within V1. PMID:24523561

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

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

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

Acute opioid withdrawal is associated with increased neural activity in reward-processing centers in healthy men: A functional magnetic resonance imaging study.

PubMed

Chu, Larry F; Lin, Joanne C; Clemenson, Anna; Encisco, Ellen; Sun, John; Hoang, Dan; Alva, Heather; Erlendson, Matthew; Clark, J David; Younger, Jarred W

2015-08-01

Opioid analgesics are frequently prescribed for chronic pain. One expected consequence of long-term opioid use is the development of physical dependence. Although previous resting state functional magnetic resonance imaging (fMRI) studies have demonstrated signal changes in reward-associated areas following morphine administration, the effects of acute withdrawal on the human brain have been less well-investigated. In an earlier study by our laboratory, ondansetron was shown to be effective in preventing symptoms associated with opioid withdrawal. The purpose of this current study was to characterize neural activity associated with acute opioid withdrawal and examine whether these changes are modified by ondansetron. Ten participants were enrolled in this placebo-controlled, randomized, double-blind, crossover study and attended three acute opioid withdrawal sessions. Participants received either placebo or ondansetron (8Ymg IV) before morphine administration (10Ymg/70Ykg IV). Participants then underwent acute naloxone-precipitated withdrawal during a resting state fMRI scan. Objective and subjective opioid withdrawal symptoms were assessed. Imaging results showed that naloxone-precipitated opioid withdrawal was associated with increased neural activity in several reward processing regions, including the right pregenual cingulate, putamen, and bilateral caudate, and decreased neural activity in networks involved in sensorimotor integration. Ondansetron pretreatment did not have a significant effect on the imaging correlates of opioid withdrawal. This study presents a preliminary investigation of the regional changes in neural activity during acute opioid withdrawal. The fMRI acute opioid withdrawal model may serve as a tool for studying opioid dependence and withdrawal in human participants. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Human neural stem cells improve cognition and promote synaptic growth in two complementary transgenic models of Alzheimer's disease and neuronal loss.

PubMed

Ager, Rahasson R; Davis, Joy L; Agazaryan, Andy; Benavente, Francisca; Poon, Wayne W; LaFerla, Frank M; Blurton-Jones, Mathew

2015-07-01

Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disorder, affecting over 35 million people worldwide. Pathologically, AD is characterized by the progressive accumulation of β-amyloid (Aβ) plaques and neurofibrillary tangles within the brain. Together, these pathologies lead to marked neuronal and synaptic loss and corresponding impairments in cognition. Current treatments, and recent clinical trials, have failed to modify the clinical course of AD; thus, the development of novel and innovative therapies is urgently needed. Over the last decade, the potential use of stem cells to treat cognitive impairment has received growing attention. Specifically, neural stem cell transplantation as a treatment for AD offers a novel approach with tremendous therapeutic potential. We previously reported that intrahippocampal transplantation of murine neural stem cells (mNSCs) can enhance synaptogenesis and improve cognition in 3xTg-AD mice and the CaM/Tet-DT(A) model of hippocampal neuronal loss. These promising findings prompted us to examine a human neural stem cell population, HuCNS-SC, which has already been clinically tested for other neurodegenerative disorders. In this study, we provide the first evidence that transplantation of research grade HuCNS-SCs can improve cognition in two complementary models of neurodegeneration. We also demonstrate that HuCNS-SC cells can migrate and differentiate into immature neurons and glia and significantly increase synaptic and growth-associated markers in both 3xTg-AD and CaM/Tet-DTA mice. Interestingly, improvements in aged 3xTg-AD mice were not associated with altered Aβ or tau pathology. Rather, our findings suggest that human NSC transplantation improves cognition by enhancing endogenous synaptogenesis. Taken together, our data provide the first preclinical evidence that human NSC transplantation could be a safe and effective therapeutic approach for treating AD. © 2014 The Authors. Hippocampus Published by Wiley Periodicals, Inc.

Challenging emotional prejudice by changing self-concept: priming independent self-construal reduces racial in-group bias in neural responses to other's pain.

PubMed

Wang, Chenbo; Wu, Bing; Liu, Yi; Wu, Xinhuai; Han, Shihui

2015-09-01

Humans show stronger empathy for in-group compared with out-group members' suffering and help in-group members more than out-group members. Moreover, the in-group bias in empathy and parochial altruism tend to be more salient in collectivistic than individualistic cultures. This work tested the hypothesis that modifying self-construals, which differentiate between collectivistic and individualistic cultural orientations, affects in-group bias in empathy for perceived own-race vs other-race pain. By scanning adults using functional magnetic resonance imaging, we found stronger neural activities in the mid-cingulate, left insula and supplementary motor area (SMA) in response to racial in-group compared with out-group members' pain after participants had been primed with interdependent self-construals. However, the racial in-group bias in neural responses to others' pain in the left SMA, mid-cingulate cortex and insula was significantly reduced by priming independent self-construals. Our findings suggest that shifting an individual's self-construal leads to changes of his/her racial in-group bias in neural responses to others' suffering. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness

PubMed Central

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-01-01

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly “domain general” conflict processing mechanisms, instead of conflict source specific effects. PMID:26169473

EEG neural oscillatory dynamics reveal semantic and response conflict at difference levels of conflict awareness.

PubMed

Jiang, Jun; Zhang, Qinglin; Van Gaal, Simon

2015-07-14

Although previous work has shown that conflict can be detected in the absence of awareness, it is unknown how different sources of conflict (i.e., semantic, response) are processed in the human brain and whether these processes are differently modulated by conflict awareness. To explore this issue, we extracted oscillatory power dynamics from electroencephalographic (EEG) data recorded while human participants performed a modified version of the Stroop task. Crucially, in this task conflict awareness was manipulated by masking a conflict-inducing color word preceding a color patch target. We isolated semantic from response conflict by introducing four color words/patches, of which two were matched to the same response. We observed that both semantic as well as response conflict were associated with mid-frontal theta-band and parietal alpha-band power modulations, irrespective of the level of conflict awareness (high vs. low), although awareness of conflict increased these conflict-related power dynamics. These results show that both semantic and response conflict can be processed in the human brain and suggest that the neural oscillatory mechanisms in EEG reflect mainly "domain general" conflict processing mechanisms, instead of conflict source specific effects.

Perceptual learning modifies the functional specializations of visual cortical areas.

PubMed

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

2016-05-17

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

Evaluation of the immunogenicity of human iPS cell-derived neural stem/progenitor cells in vitro.

PubMed

Ozaki, Masahiro; Iwanami, Akio; Nagoshi, Narihito; Kohyama, Jun; Itakura, Go; Iwai, Hiroki; Nishimura, Soraya; Nishiyama, Yuichiro; Kawabata, Soya; Sugai, Keiko; Iida, Tsuyoshi; Matsubayashi, Kohei; Isoda, Miho; Kashiwagi, Rei; Toyama, Yoshiaki; Matsumoto, Morio; Okano, Hideyuki; Nakamura, Masaya

2017-03-01

To achieve the goal of a first-in-human trial for human induced pluripotent stem cell (hiPSC)-based transplantation for the treatment of various diseases, allogeneic human leukocyte antigen (HLA)-matched hiPSC cell banks represent a realistic tool from the perspective of quality control and cost performance. Furthermore, considering the limited therapeutic time-window for acute injuries, including neurotraumatic injuries, an iPS cell bank is of potential interest. However, due to the relatively immunoprivileged environment of the central nervous system, it is unclear whether HLA matching is required in hiPSC-derived neural stem/progenitor cell (hiPSC-NS/PC) transplantation for the treatment of neurodegenerative diseases and neurotraumatic injuries. In this study, we evaluated the significance of HLA matching in hiPSC-NS/PC transplantation by performing modified mixed lymphocyte reaction (MLR) assays with hiPSC-NS/PCs. Compared to fetus-derived NS/PCs, the expression levels of human leukocyte antigen-antigen D related (HLA-DR) and co-stimulatory molecules on hiPSC-NS/PCs were significantly low, even with the addition of tumor necrosis factor-α (TNFα) and/or interferon-γ (IFNγ) to mimic the inflammatory environment surrounding transplanted hiPSC-NS/PCs in injured tissues. Interestingly, both the allogeneic HLA-matched and the HLA-mismatched responses were similarly low in the modified MLR assay. Furthermore, the autologous response was also similar to the allogeneic response. hiPSC-NS/PCs suppressed the proliferative responses of allogeneic HLA-mismatched peripheral blood mononuclear cells (PBMCs) in a dose-dependent manner. Thus, the low antigen-presenting function and immunosuppressive effects of hiPSC-NS/PCs result in a depressed immune response, even in an allogeneic HLA-mismatched setting. It is crucial to verify whether these in vitro results are reproducible in a clinical setting. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Modified neural networks for rapid recovery of tokamak plasma parameters for real time control

NASA Astrophysics Data System (ADS)

Sengupta, A.; Ranjan, P.

2002-07-01

Two modified neural network techniques are used for the identification of the equilibrium plasma parameters of the Superconducting Steady State Tokamak I from external magnetic measurements. This is expected to ultimately assist in a real time plasma control. As different from the conventional network structure where a single network with the optimum number of processing elements calculates the outputs, a multinetwork system connected in parallel does the calculations here in one of the methods. This network is called the double neural network. The accuracy of the recovered parameters is clearly more than the conventional network. The other type of neural network used here is based on the statistical function parametrization combined with a neural network. The principal component transformation removes linear dependences from the measurements and a dimensional reduction process reduces the dimensionality of the input space. This reduced and transformed input set, rather than the entire set, is fed into the neural network input. This is known as the principal component transformation-based neural network. The accuracy of the recovered parameters in the latter type of modified network is found to be a further improvement over the accuracy of the double neural network. This result differs from that obtained in an earlier work where the double neural network showed better performance. The conventional network and the function parametrization methods have also been used for comparison. The conventional network has been used for an optimization of the set of magnetic diagnostics. The effective set of sensors, as assessed by this network, are compared with the principal component based network. Fault tolerance of the neural networks has been tested. The double neural network showed the maximum resistance to faults in the diagnostics, while the principal component based network performed poorly. Finally the processing times of the methods have been compared. The double network and the principal component network involve the minimum computation time, although the conventional network also performs well enough to be used in real time.

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

PubMed

Balaban, Halely; Luria, Roy

2017-02-01

Visual working memory (VWM) guides behavior by holding a set of active representations and modifying them according to changes in the environment. This updating process relies on a unique mapping between each VWM representation and an actual object in the environment. Here, we destroyed this mapping by either presenting a coherent object but then breaking it into independent parts or presenting an object but then abruptly replacing it with a different object. This allowed us to introduce the neural marker and behavioral consequence of an online resetting process in humans' VWM. Across seven experiments, we demonstrate that this resetting process involves abandoning the old VWM contents because they no longer correspond to the objects in the environment. Then, VWM encodes the novel information and reestablishes the correspondence between the new representations and the objects. The resetting process was marked by a unique neural signature: a sharp drop in the amplitude of the electrophysiological index of VWM contents (the contralateral delay activity), presumably indicating the loss of the existent object-to-representation mappings. This marker was missing when an updating process occurred. Moreover, when tracking moving items, VWM failed to detect salient changes in the object's shape when these changes occurred during the resetting process. This happened despite the object being fully visible, presumably because the mapping between the object and a VWM representation was lost. Importantly, we show that resetting, its neural marker, and the behavioral cost it entails, are specific to situations that involve a destruction of the objects-to-representations correspondence. Visual working memory (VWM) maintains task-relevant information in an online state. Previous studies showed that VWM representations are accessed and modified after changes in the environment. Here, we show that this updating process critically depends on an ongoing mapping between the representations and the objects in the environment. When this mapping breaks, VWM cannot access the old representations and instead resets. The novel resetting process that we introduce removes the existing representations instead of modifying them and this process is accompanied by a unique neural marker. During the resetting process, VWM was blind to salient changes in the object's shape. The resetting process highlights the flexibility of our cognitive system in handling the dynamic environment by abruptly abandoning irrelevant schemas. Copyright © 2017 the authors 0270-6474/17/371225-15$15.00/0.

Hideen Markov Models and Neural Networks for Fault Detection in Dynamic Systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

None given. (From conclusion): Neural networks plus Hidden Markov Models(HMM)can provide excellene detection and false alarm rate performance in fault detection applications. Modified models allow for novelty detection. Also covers some key contributions of neural network model, and application status.

Genome Modification Leads to Phenotype Reversal in Human Myotonic Dystrophy type 1 iPS-cell Derived Neural Stem Cells

PubMed Central

Xia, Guangbin; Gao, Yuanzheng; Jin, Shouguang; Subramony, SH.; Terada, Naohiro; Ranum, Laura P.W.; Swanson, Maurice S.; Ashizawa, Tetsuo

2015-01-01

Objective Myotonic dystrophy type 1 (DM1) is caused by expanded CTG repeats in the 3'-untranslated region (3’ UTR) of the DMPK gene. Correcting the mutation in DM1 stem cells would be an important step towards autologous stem cell therapy. The objective of this study is to demonstrate in vitro genome editing to prevent production of toxic mutant transcripts and reverse phenotypes in DM1 stem cells. Methods Genome editing was performed in DM1 neural stem cells (NSCs) derived from human DM1 iPS cells. An editing cassette containing SV40/bGH polyA signals was integrated upstream of the CTG repeats by TALEN-mediated homologous recombination (HR). The expression of mutant CUG repeats transcript was monitored by nuclear RNA foci, the molecular hallmarks of DM1, using RNA fluorescence in situ hybridization (RNA-FISH). Alternative splicing of microtubule-associated protein tau (MAPT) and muscleblind-like (MBNL) proteins were analyzed to further monitor the phenotype reversal after genome modification. Results The cassette was successfully inserted into DMPK intron 9 and this genomic modification led to complete disappearance of nuclear RNA foci. MAPT and MBNL 1, 2 aberrant splicing in DM1 NSCs was reversed to normal pattern in genome-modified NSCs. Interpretation Genome modification by integration of exogenous polyA signals upstream of the DMPK CTG repeat expansion prevents the production of toxic RNA and leads to phenotype reversal in human DM1 iPS-cells derived stem cells. Our data provide proof-of-principle evidence that genome modification may be used to generate genetically modified progenitor cells as a first step toward autologous cell transfer therapy for DM1. PMID:25702800

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.

Motor Cortex Reorganization across the Lifespan

ERIC Educational Resources Information Center

Plowman, Emily K.; Kleim, Jeffrey A.

2010-01-01

The brain is a highly dynamic structure with the capacity for profound structural and functional change. Such neural plasticity has been well characterized within motor cortex and is believed to represent one of the neural mechanisms for acquiring and modifying motor behaviors. A number of behavioral and neural signals have been identified that…

GRAPES-Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain.

PubMed

Martin, Alex

2016-08-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Auditory Training: Evidence for Neural Plasticity in Older Adults

PubMed Central

Anderson, Samira; Kraus, Nina

2014-01-01

Improvements in digital amplification, cochlear implants, and other innovations have extended the potential for improving hearing function; yet, there remains a need for further hearing improvement in challenging listening situations, such as when trying to understand speech in noise or when listening to music. Here, we review evidence from animal and human models of plasticity in the brain’s ability to process speech and other meaningful stimuli. We considered studies targeting populations of younger through older adults, emphasizing studies that have employed randomized controlled designs and have made connections between neural and behavioral changes. Overall results indicate that the brain remains malleable through older adulthood, provided that treatment algorithms have been modified to allow for changes in learning with age. Improvements in speech-in-noise perception and cognition function accompany neural changes in auditory processing. The training-related improvements noted across studies support the need to consider auditory training strategies in the management of individuals who express concerns about hearing in difficult listening situations. Given evidence from studies engaging the brain’s reward centers, future research should consider how these centers can be naturally activated during training. PMID:25485037

The Neural Basis of Social Influence in a Dictator Decision.

PubMed

Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong

2017-01-01

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

Dynamic neural processing of linguistic cues related to death.

PubMed

Liu, Xi; Shi, Zhenhao; Ma, Yina; Qin, Jungang; Han, Shihui

2013-01-01

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

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.

Production and characterization of immortal human neural stem cell line with multipotent differentiation property.

PubMed

Kim, Seung U; Nagai, Atsushi; Nakagawa, Eiji; Choi, Hyun B; Bang, Jung H; Lee, Hong J; Lee, Myung A; Lee, Yong B; Park, In H

2008-01-01

We document the protocols and methods for the production of immortalized cell lines of human neural stem cells from the human fetal central nervous system (CNS) cells by using a retroviral vector encoding v-myc oncogene. One of the human neural stem cell lines (HB1.F3) was found to express nestin and other specific markers for human neural stem cells, giving rise to three fundamental cell types of the CNS: neurons, astrocytes, and oligodendrocytes. After transplantation into the brain of mouse model of stroke, implanted human neural stem cells were observed to migrate extensively from the site of implantation into other anatomical sites and to differentiate into neurons and glial cells.

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.

Neurological impressions on the organization of language networks in the human brain.

PubMed

Oliveira, Fabricio Ferreira de; Marin, Sheilla de Medeiros Correia; Bertolucci, Paulo Henrique Ferreira

2017-01-01

More than 95% of right-handed individuals, as well as almost 80% of left-handed individuals, have left hemisphere dominance for language. The perisylvian networks of the dominant hemisphere tend to be the most important language systems in human brains, usually connected by bidirectional fibres originated from the superior longitudinal fascicle/arcuate fascicle system and potentially modifiable by learning. Neuroplasticity mechanisms take place to preserve neural functions after brain injuries. Language is dependent on a hierarchical interlinkage of serial and parallel processing areas in distinct brain regions considered to be elementary processing units. Whereas aphasic syndromes typically result from injuries to the dominant hemisphere, the extent of the distribution of language functions seems to be variable for each individual. Review of the literature Results: Several theories try to explain the organization of language networks in the human brain from a point of view that involves either modular or distributed processing or sometimes both. The most important evidence for each approach is discussed under the light of modern theories of organization of neural networks. Understanding the connectivity patterns of language networks may provide deeper insights into language functions, supporting evidence-based rehabilitation strategies that focus on the enhancement of language organization for patients with aphasic syndromes.

GRAPES—Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain

PubMed Central

Martin, Alex

2016-01-01

In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed. PMID:25968087

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

PubMed

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

2003-08-01

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

Cryopreservation, Culture, and Transplantation of Human Fetal Mesencephalic Tissue into Monkeys

NASA Astrophysics Data System (ADS)

Redmond, D. E.; Naftolin, F.; Collier, T. J.; Leranth, C.; Robbins, R. J.; Sladek, C. D.; Roth, R. H.; Sladek, J. R.

1988-11-01

Studies in animals suggest that fetal neural grafts might restore lost neurological function in Parkinson's disease. In monkeys, such grafts survive for many months and reverse signs of parkinsonism, without attendant graft rejection. The successful and reliable application of a similar transplantation procedure to human patients, however, will require neural tissue obtained from human fetal cadavers, with demonstrated cellular identity, viability, and biological safety. In this report, human fetal neural tissue was successfully grafted into the brains of monkeys. Neural tissue was collected from human fetal cadavers after 9 to 12 weeks of gestation and cryopreserved in liquid nitrogen. Viability after up to 2 months of storage was demonstrated by cell culture and by transplantation into monkeys. Cryopreservation and storage of human fetal neural tissue would allow formation of a tissue bank. The stored cells could then be specifically tested to assure their cellular identity, viability, and bacteriological and virological safety before clinical use. The capacity to collect and maintain viable human fetal neural tissue would also facilitate research efforts to understand the development and function of the human brain and provide opportunities to study neurological diseases.

Applications of artificial intelligence in safe human-robot interactions.

PubMed

Najmaei, Nima; Kermani, Mehrdad R

2011-04-01

The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Williams-Hayes, Peggy; Kaneshige, John T.; Stachowiak, Susan J.

2006-01-01

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Williams-Hayes, Peggy; Karneshige, J. T.; Stachowiak, Susan J.

2006-01-01

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Intelligent Foreign Particle Inspection Machine for Injection Liquid Examination Based on Modified Pulse-Coupled Neural Networks

PubMed Central

Ge, Ji; Wang, YaoNan; Zhou, BoWen; Zhang, Hui

2009-01-01

A biologically inspired spiking neural network model, called pulse-coupled neural networks (PCNN), has been applied in an automatic inspection machine to detect visible foreign particles intermingled in glucose or sodium chloride injection liquids. Proper mechanisms and improved spin/stop techniques are proposed to avoid the appearance of air bubbles, which increases the algorithms' complexity. Modified PCNN is adopted to segment the difference images, judging the existence of foreign particles according to the continuity and smoothness properties of their moving traces. Preliminarily experimental results indicate that the inspection machine can detect the visible foreign particles effectively and the detection speed, accuracy and correct detection rate also satisfying the needs of medicine preparation. PMID:22412318

Cyclin-dependent kinase 4 signaling acts as a molecular switch between syngenic differentiation and neural transdifferentiation in human mesenchymal stem cells

PubMed Central

Lee, Janet; Baek, Jeong-Hwa; Choi, Kyu-Sil; Kim, Hyun-Soo; Park, Hye-Young; Ha, Geun-Hyoung; Park, Ho; Lee, Kyo-Won; Lee, Chang Geun; Yang, Dong-Yun; Moon, Hyo Eun; Paek, Sun Ha; Lee, Chang-Woo

2013-01-01

Multipotent mesenchymal stem/stromal cells (MSCs) are capable of differentiating into a variety of cell types from different germ layers. However, the molecular and biochemical mechanisms underlying the transdifferentiation of MSCs into specific cell types still need to be elucidated. In this study, we unexpectedly found that treatment of human adipose- and bone marrow-derived MSCs with cyclin-dependent kinase (CDK) inhibitor, in particular CDK4 inhibitor, selectively led to transdifferentiation into neural cells with a high frequency. Specifically, targeted inhibition of CDK4 expression using recombinant adenovial shRNA induced the neural transdifferentiation of human MSCs. However, the inhibition of CDK4 activity attenuated the syngenic differentiation of human adipose-derived MSCs. Importantly, the forced regulation of CDK4 activity showed reciprocal reversibility between neural differentiation and dedifferentiation of human MSCs. Together, these results provide novel molecular evidence underlying the neural transdifferentiation of human MSCs; in addition, CDK4 signaling appears to act as a molecular switch from syngenic differentiation to neural transdifferentiation of human MSCs. PMID:23324348

Dynamic Neural Processing of Linguistic Cues Related to Death

PubMed Central

Ma, Yina; Qin, Jungang; Han, Shihui

2013-01-01

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

The Neural Basis of Social Influence in a Dictator Decision

PubMed Central

Wei, Zhenyu; Zhao, Zhiying; Zheng, Yong

2017-01-01

Humans tend to reduce inequitable distributions. Previous neuroimaging studies have shown that inequitable decisions are related to brain regions that associated with negative emotion and signaling conflict. In the highly complex human social environment, our opinions and behaviors can be affected by social information. In current study, we used a modified dictator game to investigate the effect of social influence on making an equitable decision. We found that the choices of participants in present task was influenced by the choices of peers. However, participants’ decisions were influenced by equitable rather than inequitable group choices. fMRI results showed that brain regions that related to norm violation and social conflict were related to the inequitable social influence. The neural responses in the dorsomedial prefrontal cortex, rostral cingulate zone, and insula predicted subsequent conforming behavior in individuals. Additionally, psychophysiological interaction analysis revealed that the interconnectivity between the dorsal striatum and insula was elevated in advantageous inequity influence versus no-social influence conditions. We found decreased functional connectivity between the medial prefrontal cortex and insula, supplementary motor area, posterior cingulate gyrus and dorsal anterior cingulate cortex in the disadvantageous inequity influence versus no-social influence conditions. This suggests that a disadvantageous inequity influence may decrease the functional connectivity among brain regions that are related to reward processes. Thus, the neural mechanisms underlying social influence in an equitable decision may be similar to those implicated in social norms and reward processing. PMID:29375412

Optogenetic approaches to evaluate striatal function in animal models of Parkinson disease.

PubMed

Parker, Krystal L; Kim, Youngcho; Alberico, Stephanie L; Emmons, Eric B; Narayanan, Nandakumar S

2016-03-01

Optogenetics refers to the ability to control cells that have been genetically modified to express light-sensitive ion channels. The introduction of optogenetic approaches has facilitated the dissection of neural circuits. Optogenetics allows for the precise stimulation and inhibition of specific sets of neurons and their projections with fine temporal specificity. These techniques are ideally suited to investigating neural circuitry underlying motor and cognitive dysfunction in animal models of human disease. Here, we focus on how optogenetics has been used over the last decade to probe striatal circuits that are involved in Parkinson disease, a neurodegenerative condition involving motor and cognitive abnormalities resulting from degeneration of midbrain dopaminergic neurons. The precise mechanisms underlying the striatal contribution to both cognitive and motor dysfunction in Parkinson disease are unknown. Although optogenetic approaches are somewhat removed from clinical use, insight from these studies can help identify novel therapeutic targets and may inspire new treatments for Parkinson disease. Elucidating how neuronal and behavioral functions are influenced and potentially rescued by optogenetic manipulation in animal models could prove to be translatable to humans. These insights can be used to guide future brain-stimulation approaches for motor and cognitive abnormalities in Parkinson disease and other neuropsychiatric diseases.

Investigation on trophic state index by artificial neural networks (case study: Dez Dam of Iran)

NASA Astrophysics Data System (ADS)

Saghi, H.; Karimi, L.; Javid, A. H.

2015-06-01

Dam construction and surface runoff control is one of the most common approaches for water-needs supply of human societies. However, the increasing development of social activities and hence the subsequent increase in environmental pollutants leads to deterioration of water quality in dam reservoirs and eutrophication process could be intensified. So, the water quality of reservoirs is now one of the key factors in operation and water quality management of reservoirs. Hence, maintaining the quality of the stored water and identification and examination of changes along time has been a constant concern of humans that involves the water authorities. Traditionally, empirical trophic state indices of dam reservoirs often defined based on changes in concentration of effective factors (nutrients) and its consequences (increase in chlorophyll a), have been used as an efficient tool in the definition of dam reservoirs quality. In recent years, modeling techniques such as artificial neural networks have enhanced the prediction capability and the accuracy of these studies. In this study, artificial neural networks have been applied to analyze eutrophication process in the Dez Dam reservoir in Iran. In this paper, feed forward neural network with one input layer, one hidden layer and one output layer was applied using MATLAB neural network toolbox for trophic state index (TSI) analysis in the Dez Dam reservoir. The input data of this network are effective parameters in the eutrophication: nitrogen cycle parameters and phosphorous cycle parameters and parameters that will be changed by eutrophication: Chl a, SD, DO and the output data is TSI. Based on the results from estimation of modified Carlson trophic state index, Dez Dam reservoir is considered to be eutrophic in the early July to mid-November and would be mesotrophic with decrease in temperature. Therefore, a decrease in water quality of the dam reservoir during the warm seasons is expectable. The results indicated that artificial neural network (ANN) is a suitable tool for quality modeling of reservoir of dam and increment and decrement of nutrients in trend of eutrophication. Therefore, ANN is a suitable tool for quality modeling of reservoir of dam.

Dynamic Network Communication in the Human Functional Connectome Predicts Perceptual Variability in Visual Illusion.

PubMed

Wang, Zhiwei; Zeljic, Kristina; Jiang, Qinying; Gu, Yong; Wang, Wei; Wang, Zheng

2018-01-01

Ubiquitous variability between individuals in visual perception is difficult to standardize and has thus essentially been ignored. Here we construct a quantitative psychophysical measure of illusory rotary motion based on the Pinna-Brelstaff figure (PBF) in 73 healthy volunteers and investigate the neural circuit mechanisms underlying perceptual variation using functional magnetic resonance imaging (fMRI). We acquired fMRI data from a subset of 42 subjects during spontaneous and 3 stimulus conditions: expanding PBF, expanding modified-PBF (illusion-free) and expanding modified-PBF with physical rotation. Brain-wide graph analysis of stimulus-evoked functional connectivity patterns yielded a functionally segregated architecture containing 3 discrete hierarchical networks, commonly shared between rest and stimulation conditions. Strikingly, communication efficiency and strength between 2 networks predominantly located in visual areas robustly predicted individual perceptual differences solely in the illusory stimulus condition. These unprecedented findings demonstrate that stimulus-dependent, not spontaneous, dynamic functional integration between distributed brain networks contributes to perceptual variability in humans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

NASA Astrophysics Data System (ADS)

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

2003-03-01

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

In Vivo Neural Recording and Electrochemical Performance of Microelectrode Arrays Modified by Rough-Surfaced AuPt Alloy Nanoparticles with Nanoporosity

PubMed Central

Zhao, Zongya; Gong, Ruxue; Zheng, Liang; Wang, Jue

2016-01-01

In order to reduce the impedance and improve in vivo neural recording performance of our developed Michigan type silicon electrodes, rough-surfaced AuPt alloy nanoparticles with nanoporosity were deposited on gold microelectrode sites through electro-co-deposition of Au-Pt-Cu alloy nanoparticles, followed by chemical dealloying Cu. The AuPt alloy nanoparticles modified gold microelectrode sites were characterized by scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and in vivo neural recording experiment. The SEM images showed that the prepared AuPt alloy nanoparticles exhibited cauliflower-like shapes and possessed very rough surfaces with many different sizes of pores. Average impedance of rough-surfaced AuPt alloy nanoparticles modified sites was 0.23 MΩ at 1 kHz, which was only 4.7% of that of bare gold microelectrode sites (4.9 MΩ), and corresponding in vitro background noise in the range of 1 Hz to 7500 Hz decreased to 7.5 μVrms from 34.1 μVrms at bare gold microelectrode sites. Spontaneous spike signal recording was used to evaluate in vivo neural recording performance of modified microelectrode sites, and results showed that rough-surfaced AuPt alloy nanoparticles modified microelectrode sites exhibited higher average spike signal-to-noise ratio (SNR) of 4.8 in lateral globus pallidus (GPe) due to lower background noise compared to control microelectrodes. Electro-co-deposition of Au-Pt-Cu alloy nanoparticles combined with chemical dealloying Cu was a convenient way for increasing the effective surface area of microelectrode sites, which could reduce electrode impedance and improve the quality of in vivo spike signal recording. PMID:27827893

WDR62 Regulates Early Neural and Glial Progenitor Specification of Human Pluripotent Stem Cells

PubMed Central

Alshawaf, Abdullah J.; Antonic, Ana; Skafidas, Efstratios

2017-01-01

Mutations in WD40-repeat protein 62 (WDR62) are commonly associated with primary microcephaly and other developmental cortical malformations. We used human pluripotent stem cells (hPSC) to examine WDR62 function during human neural differentiation and model early stages of human corticogenesis. Neurospheres lacking WDR62 expression showed decreased expression of intermediate progenitor marker, TBR2, and also glial marker, S100β. In contrast, inhibition of c-Jun N-terminal kinase (JNK) signalling during hPSC neural differentiation induced upregulation of WDR62 with a corresponding increase in neural and glial progenitor markers, PAX6 and EAAT1, respectively. These findings may signify a role of WDR62 in specifying intermediate neural and glial progenitors during human pluripotent stem cell differentiation. PMID:28690640

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.

Reconfigurable Control Design with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

The viewgraphs present background information about reconfiguration control design, design methods used for paper, control failure survivability results, and results and time histories of tests. Topics examined include control reconfiguration, general information about adaptive controllers, model reference adaptive control (MRAC), the utility of neural networks, radial basis functions (RBF) neural network outputs, neurons, and results of investigations of failures.

Prenatal Ablation of Nicotinic Receptor alpha7 Cell Lineages Produces Lumbosacral Spina Bifida the Severity of Which is Modified by Choline and Nicotine Exposure

PubMed Central

Rogers, Scott W; Tvrdik, Petr; Capecchi, Mario R; Gahring, Lorise C

2012-01-01

Lumbosacral spina bifida is a common debilitating birth defect whose multiple causes are poorly understood. Here, we provide the first genetic delineation of cholinergic nicotinic receptor alpha7 (Chrna7) expression and link the ablation of the Chrna7 cell lineage to this condition in the mouse. Using homologous recombination, an IRES-Cre bi-cistronic cassette was introduced into the 3′ noncoding region of Chrna7 (Chrna7:Cre) for identifying cell lineages expressing this gene. This lineage first appears at embryonic day E9.0 in rhombomeres 3 and 5 of the neural tube and extends to cell subsets in most tissues by E14.5. Ablation of the Chrna7:Cre cell lineage in embryos from crosses with conditionally expressed attenuated diphtheria toxin results in precise developmental defects including omphalocele (89%) and open spina bifida (SB; 80%). We hypothesized that like humans, this defect would be modified by environmental compounds not only folic acid or choline but also nicotine. Prenatal chronic oral nicotine administration substantially worsened the defect to often include the rostral neural tube. In contrast, supplementation of the maternal diet with 2% choline decreased SB prevalence to 38% and dramatically reduced the defect severity. Folic acid supplementation only trended towards a reduced SB frequency. The omphalocele was unaffected by these interventions. These studies identify the Chrna7 cell lineage as participating in posterior neuropore closure and present a novel model of lower SB that can be substantially modified by the prenatal environment. © 2012 Wiley Periodicals, Inc. PMID:22473653

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

PubMed Central

Crabtree, Gregg W.; Gogos, Joseph A.

2014-01-01

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

Alzheimer’s in 3D culture: Challenges and perspectives

PubMed Central

D'Avanzo, Carla; Aronson, Jenna; Kim, Young Hye; Choi, Se Hoon; Tanzi, Rudolph E.; Kim, Doo Yeon

2015-01-01

Summary Alzheimer’s disease (AD) is the most common cause of dementia, and there is currently no cure. The “β-amyloid cascade hypothesis” of AD is the basis of current understanding of AD pathogenesis and drug discovery. However, no AD models have fully validated this hypothesis. We recently developed a human stem cell culture model of AD by cultivating genetically modified human neural stem cells in a three-dimensional (3D) cell culture system. These cells were able to recapitulate key events of AD pathology including β-amyloid plaques and neurofibrillary tangles. In this review, we will discuss the progress and current limitations of AD mouse models and human stem cell models as well as explore the breakthroughs of 3D cell culture systems. We will also share our perspective on the potential of dish models of neurodegenerative diseases for studying pathogenic cascades and therapeutic drug discovery. PMID:26252541

Machine Learning and Quantum Mechanics

NASA Astrophysics Data System (ADS)

Chapline, George

The author has previously pointed out some similarities between selforganizing neural networks and quantum mechanics. These types of neural networks were originally conceived of as away of emulating the cognitive capabilities of the human brain. Recently extensions of these networks, collectively referred to as deep learning networks, have strengthened the connection between self-organizing neural networks and human cognitive capabilities. In this note we consider whether hardware quantum devices might be useful for emulating neural networks with human-like cognitive capabilities, or alternatively whether implementations of deep learning neural networks using conventional computers might lead to better algorithms for solving the many body Schrodinger equation.

A Phenotyping Regimen for Genetically Modified Mice Used to Study Genes Implicated in Human Diseases of Aging.

PubMed

Patterson, Victoria L; Thompson, Brian S; Cherry, Catherine; Wang, Shao-Bin; Chen, Bo; Hoh, Josephine

2016-07-14

Age-related diseases are becoming increasingly prevalent and the burden continues to grow as our population ages. Effective treatments are necessary to lessen the impact of debilitating conditions but remain elusive in many cases. Only by understanding the causes and pathology of diseases associated with aging, can scientists begin to identify potential therapeutic targets and develop strategies for intervention. The most common age-related conditions are neurodegenerative disorders such as Parkinson's disease and blindness. Age-related macular degeneration (AMD) is the leading cause of blindness in the elderly. Genome wide association studies have previously identified loci that are associated with increased susceptibility to this disease and identified two regions of interest: complement factor H (CFH) and the 10q26 locus, where the age-related maculopathy susceptibility 2 (ARMS2) and high-temperature requirement factor A1 (HtrA1) genes are located. CFH acts as a negative regulator of the alternative pathway (AP) of the complement system while HtrA1 is an extracellular serine protease. ARMS2 is located upstream of HtrA1 in the primate genome, although the gene is absent in mice. To study the effects of these genes, humanized knock-in mouse lines of Cfh and ARMS2, knockouts of Cfh, HtrA1, HtrA2, HtrA3 and HtrA4 as well as a conditional neural deletion of HtrA2 were generated. Of all the genetically engineered mice produced only mice lacking HtrA2, either systemically or in neural tissues, displayed clear phenotypes. In order to examine these mice thoroughly and systematically, an initial phenotyping schedule was established, consisting of a series of tests related to two main diseases of interest: AMD and Parkinson's. Genetically modified mice can be subjected to appropriate experiments to identify phenotypes that may be related to the associated diseases in humans. A phenotyping regimen with a mitochondrial focus is presented here alongside representative results from the tests of interest.

Major transcriptome re-organisation and abrupt changes in signalling, cell cycle and chromatin regulation at neural differentiation in vivo.

PubMed

Olivera-Martinez, Isabel; Schurch, Nick; Li, Roman A; Song, Junfang; Halley, Pamela A; Das, Raman M; Burt, Dave W; Barton, Geoffrey J; Storey, Kate G

2014-08-01

Here, we exploit the spatial separation of temporal events of neural differentiation in the elongating chick body axis to provide the first analysis of transcriptome change in progressively more differentiated neural cell populations in vivo. Microarray data, validated against direct RNA sequencing, identified: (1) a gene cohort characteristic of the multi-potent stem zone epiblast, which contains neuro-mesodermal progenitors that progressively generate the spinal cord; (2) a major transcriptome re-organisation as cells then adopt a neural fate; and (3) increasing diversity as neural patterning and neuron production begin. Focussing on the transition from multi-potent to neural state cells, we capture changes in major signalling pathways, uncover novel Wnt and Notch signalling dynamics, and implicate new pathways (mevalonate pathway/steroid biogenesis and TGFβ). This analysis further predicts changes in cellular processes, cell cycle, RNA-processing and protein turnover as cells acquire neural fate. We show that these changes are conserved across species and provide biological evidence for reduced proteasome efficiency and a novel lengthening of S phase. This latter step may provide time for epigenetic events to mediate large-scale transcriptome re-organisation; consistent with this, we uncover simultaneous downregulation of major chromatin modifiers as the neural programme is established. We further demonstrate that transcription of one such gene, HDAC1, is dependent on FGF signalling, making a novel link between signals that control neural differentiation and transcription of a core regulator of chromatin organisation. Our work implicates new signalling pathways and dynamics, cellular processes and epigenetic modifiers in neural differentiation in vivo, identifying multiple new potential cellular and molecular mechanisms that direct differentiation. © 2014. Published by The Company of Biologists Ltd.

Scalable Expansion of Human Pluripotent Stem Cell-Derived Neural Progenitors in Stirred Suspension Bioreactor Under Xeno-free Condition.

PubMed

Nemati, Shiva; Abbasalizadeh, Saeed; Baharvand, Hossein

2016-01-01

Recent advances in neural differentiation technology have paved the way to generate clinical grade neural progenitor populations from human pluripotent stem cells. These cells are an excellent source for the production of neural cell-based therapeutic products to treat incurable central nervous system disorders such as Parkinson's disease and spinal cord injuries. This progress can be complemented by the development of robust bioprocessing technologies for large scale expansion of clinical grade neural progenitors under GMP conditions for promising clinical use and drug discovery applications. Here, we describe a protocol for a robust, scalable expansion of human neural progenitor cells from pluripotent stem cells as 3D aggregates in a stirred suspension bioreactor. The use of this platform has resulted in easily expansion of neural progenitor cells for several passages with a fold increase of up to 4.2 over a period of 5 days compared to a maximum 1.5-2-fold increase in the adherent static culture over a 1 week period. In the bioreactor culture, these cells maintained self-renewal, karyotype stability, and cloning efficiency capabilities. This approach can be also used for human neural progenitor cells derived from other sources such as the human fetal brain.

Comparison of the neuropoietic activity of gene-modified versus parental mesenchymal stromal cells and the identification of soluble and extracellular matrix-related neuropoietic mediators

PubMed Central

2014-01-01

Introduction Transplanting mesenchymal stromal cells (MSCs) or their derivatives into a neurodegenerative environment is believed to be beneficial because of the trophic support, migratory guidance, immunosuppression, and neurogenic stimuli they provide. SB623, a cell therapy for the treatment of chronic stroke, currently in a clinical trial, is derived from bone marrow MSCs by using transient transfection with a vector encoding the human Notch1 intracellular domain. This creates a new phenotype, which is effective in experimental stroke, exhibits immunosuppressive and angiogenic activity equal or superior to parental MSCs in vitro, and produces extracellular matrix (ECM) that is exceptionally supportive for neural cell growth. The neuropoietic activity of SB623 and parental MSCs has not been compared, and the SB623-derived neuropoietic mediators have not been identified. Methods SB623 or parental MSCs were cocultured with rat embryonic brain cortex cells on cell-derived ECM in a previously characterized quantitative neuropoiesis assay. Changes in expression of rat neural differentiation markers were quantified by using rat-specific qRT-PCR. Human mediators were identified by using expression profiling, an enzymatic crosslinking activity, and functional interference studies by means of blocking antibodies, biologic inhibitors, and siRNA. Cocultures were immunolabeled for presynaptic vesicular transporters to assess neuronal specialization. Results Among six MSC/SB623 pairs, SB623 induced expression of rat neural precursor, oligodendrocyte, and astrocyte markers on average 2.6 to 3 times stronger than did their parental MSCs. SB623 expressed significantly higher FGF2, FGF1, and BMP4, and lower FGFR1 and FGFR2 levels; and human FGF1, FGF2, BMPs, and HGF were implicated as neuropoietic mediators. Neural precursors grew faster on SB623- than on MSC-derived ECM. SB623 exhibited higher expression levels and crosslinking activity of tissue transglutaminase (TGM2). TGM2 silencing reduced neural precursor growth on SB623-ECM. SB623 also promoted the induction of GABA-ergic, but not glutamatergic, neurons more effectively than did MSCs. Conclusions These data demonstrate that SB623 cells tend to support neural cell growth more effectively than their parental MSCs and identify both soluble and insoluble mediators responsible, at least in part, for enhanced neuropoietic potency of SB623. The neuropoiesis assay is a useful tool for identifying beneficial factors produced by MSCs and their derivatives. PMID:24572070

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.

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

PubMed

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

2011-01-01

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

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.

Polysialic acid in human milk. CD36 is a new member of mammalian polysialic acid-containing glycoprotein.

PubMed

Yabe, Uichiro; Sato, Chihiro; Matsuda, Tsukasa; Kitajima, Ken

2003-04-18

The neural cell adhesion molecule and the voltage-sensitive sodium channel alpha-subunit are the only two molecules in mammals known to be modified by alpha-2,8-linked polysialic acid (polySia). We found a new polySia-containing glycoprotein in human milk and identified it as CD36, a member of the B class of the scavenger receptor superfamily. The polySia-containing glycan chain(s) were removed by alkaline treatment but not by peptide:N-glycanase F digestion, indicating that milk CD36 contained polySia on O-linked glycan chain(s). Polysialylation of CD36 occurs not only in human milk but also in mouse milk. However, CD36 in human platelets is not polysialylated. PolySia CD36 is secreted in milk at any lactation stage and reaches peak level at 1 month after parturition. Thus, it is suggested that polySia of milk CD36 is significant for neonatal development in terms of protection and nutrition.

Decision making by urgency gating: theory and experimental support.

PubMed

Thura, David; Beauregard-Racine, Julie; Fradet, Charles-William; Cisek, Paul

2012-12-01

It is often suggested that decisions are made when accumulated sensory information reaches a fixed accuracy criterion. This is supported by many studies showing a gradual build up of neural activity to a threshold. However, the proposal that this build up is caused by sensory accumulation is challenged by findings that decisions are based on information from a time window much shorter than the build-up process. Here, we propose that in natural conditions where the environment can suddenly change, the policy that maximizes reward rate is to estimate evidence by accumulating only novel information and then compare the result to a decreasing accuracy criterion. We suggest that the brain approximates this policy by multiplying an estimate of sensory evidence with a motor-related urgency signal and that the latter is primarily responsible for neural activity build up. We support this hypothesis using human behavioral data from a modified random-dot motion task in which motion coherence changes during each trial.

Recapitulation of Human Retinal Development from Human Pluripotent Stem Cells Generates Transplantable Populations of Cone Photoreceptors.

PubMed

Gonzalez-Cordero, Anai; Kruczek, Kamil; Naeem, Arifa; Fernando, Milan; Kloc, Magdalena; Ribeiro, Joana; Goh, Debbie; Duran, Yanai; Blackford, Samuel J I; Abelleira-Hervas, Laura; Sampson, Robert D; Shum, Ian O; Branch, Matthew J; Gardner, Peter J; Sowden, Jane C; Bainbridge, James W B; Smith, Alexander J; West, Emma L; Pearson, Rachael A; Ali, Robin R

2017-09-12

Transplantation of rod photoreceptors, derived either from neonatal retinae or pluripotent stem cells (PSCs), can restore rod-mediated visual function in murine models of inherited blindness. However, humans depend more upon cone photoreceptors that are required for daylight, color, and high-acuity vision. Indeed, macular retinopathies involving loss of cones are leading causes of blindness. An essential step for developing stem cell-based therapies for maculopathies is the ability to generate transplantable human cones from renewable sources. Here, we report a modified 2D/3D protocol for generating hPSC-derived neural retinal vesicles with well-formed ONL-like structures containing cones and rods bearing inner segments and connecting cilia, nascent outer segments, and presynaptic structures. This differentiation system recapitulates human photoreceptor development, allowing the isolation and transplantation of a pure population of stage-matched cones. Purified human long/medium cones survive and become incorporated within the adult mouse retina, supporting the potential of photoreceptor transplantation for treating retinal degeneration. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Comparative anatomy of the prosubiculum, subiculum, presubiculum, postsubiculum, and parasubiculum in human, monkey, and rodent.

PubMed

Ding, Song-Lin

2013-12-15

The subicular complex, including the prosubiculum (ProS), subiculum (Sub), presubiculum, postsubiculum (PoS), and parasubiculum (PaS), plays important roles in the medial temporal memory system and is heavily involved in many neurological diseases such as Alzheimer's disease and epilepsy. In the literature, the ProS (in primate) and PoS (in rodent) are inconstantly identified, making data comparison difficult across species. This review is an attempt to discuss equivalencies and extent of the five subicular components in human, monkey, and rodent based on available information on their cytoarchitecture, chemoarchitecture, molecular signature, and neural connectivity. All five subicular cortices exist in human, monkey, and rodent. In human and monkey, the ProS and Sub extend into the uncal region anteriorly, and the PoS and PaS reach the cingulate isthmus posteriorly. In rodent, most of the typical subicular cortices are located in the dorsal and caudal portions of the hippocampal formation, and the modified version of the ventral ProS and Sub corresponds to the modified description of the uncal ProS and Sub in monkey and human. An interesting triangular region in rodent located at the juncture of the PoS, PaS, retrosplenial cortex, and visual cortex appears to be the equivalent of the monkey area prostriata. Major connections of the five subicular cortices are also summarized based on unified criteria discussed in this review, with distinct connections revealed between the ProS and the Sub. Copyright © 2013 Wiley Periodicals, Inc.

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

PubMed

Han, Shihui; Northoff, Georg

2008-08-01

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

Application of artificial neural networks to gaming

NASA Astrophysics Data System (ADS)

Baba, Norio; Kita, Tomio; Oda, Kazuhiro

1995-04-01

Recently, neural network technology has been applied to various actual problems. It has succeeded in producing a large number of intelligent systems. In this article, we suggest that it could be applied to the field of gaming. In particular, we suggest that the neural network model could be used to mimic players' characters. Several computer simulation results using a computer gaming system which is a modified version of the COMMONS GAME confirm our idea.

Human Cortical Neural Stem Cells Expressing Insulin-Like Growth Factor-I: A Novel Cellular Therapy for Alzheimer’s Disease

PubMed Central

McGinley, Lisa M.; Sims, Erika; Lunn, J. Simon; Kashlan, Osama N.; Chen, Kevin S.; Bruno, Elizabeth S.; Pacut, Crystal M.; Hazel, Tom; Johe, Karl; Sakowski, Stacey A.

2016-01-01

Alzheimer’s disease (AD) is the most prevalent age-related neurodegenerative disorder and a leading cause of dementia. Current treatment fails to modify underlying disease pathologies and very little progress has been made to develop effective drug treatments. Cellular therapies impact disease by multiple mechanisms, providing increased efficacy compared with traditional single-target approaches. In amyotrophic lateral sclerosis, we have shown that transplanted spinal neural stem cells (NSCs) integrate into the spinal cord, form synapses with the host, improve inflammation, and reduce disease-associated pathologies. Our current goal is to develop a similar “best in class” cellular therapy for AD. Here, we characterize a novel human cortex-derived NSC line modified to express insulin-like growth factor-I (IGF-I), HK532-IGF-I. Because IGF-I promotes neurogenesis and synaptogenesis in vivo, this enhanced NSC line offers additional environmental enrichment, enhanced neuroprotection, and a multifaceted approach to treating complex AD pathologies. We show that autocrine IGF-I production does not impact the cell secretome or normal cellular functions, including proliferation, migration, or maintenance of progenitor status. However, HK532-IGF-I cells preferentially differentiate into gamma-aminobutyric acid-ergic neurons, a subtype dysregulated in AD; produce increased vascular endothelial growth factor levels; and display an increased neuroprotective capacity in vitro. We also demonstrate that HK532-IGF-I cells survive peri-hippocampal transplantation in a murine AD model and exhibit long-term persistence in targeted brain areas. In conclusion, we believe that harnessing the benefits of cellular and IGF-I therapies together will provide the optimal therapeutic benefit to patients, and our findings support further preclinical development of HK532-IGF-I cells into a disease-modifying intervention for AD. Significance There is no cure for Alzheimer’s disease (AD) and no means of prevention. Current drug treatments temporarily slow dementia symptoms but ultimately fail to alter disease course. Given the prevalence of AD and an increasingly aging population, alternative therapeutic strategies are necessary. Cellular therapies impact disease by multiple mechanisms, providing increased efficacy compared with traditional, single-target drug discovery approaches. This study describes a novel enhanced human stem cell line that produces increased amounts of growth factors beneficial to the disease environment. Findings support further development into a potentially safe and clinically translatable cellular therapy for patients with AD. PMID:26744412

Estimation of tissue stiffness, reflex activity, optimal muscle length and slack length in stroke patients using an electromyography driven antagonistic wrist model.

PubMed

de Gooijer-van de Groep, Karin L; de Vlugt, Erwin; van der Krogt, Hanneke J; Helgadóttir, Áróra; Arendzen, J Hans; Meskers, Carel G M; de Groot, Jurriaan H

2016-06-01

About half of all chronic stroke patients experience loss of arm function coinciding with increased stiffness, reduced range of motion and a flexed wrist due to a change in neural and/or structural tissue properties. Quantitative assessment of these changes is of clinical importance, yet not trivial. The goal of this study was to quantify the neural and structural properties contributing to wrist joint stiffness and to compare these properties between healthy subjects and stroke patients. Stroke patients (n=32) and healthy volunteers (n=14) were measured using ramp-and-hold rotations applied to the wrist joint by a haptic manipulator. Neural (reflexive torque) and structural (connective tissue stiffness and slack lengths and (contractile) optimal muscle lengths) parameters were estimated using an electromyography driven antagonistic wrist model. Kruskal-Wallis analysis with multiple comparisons was used to compare results between healthy subjects, stroke patients with modified Ashworth score of zero and stroke patients with modified Ashworth score of one or more. Stroke patients with modified Ashworth score of one or more differed from healthy controls (P<0.05) by increased tissue stiffness, increased reflexive torque, decreased optimal muscle length and decreased slack length of connective tissue of the flexor muscles. Non-invasive quantitative analysis, including estimation of optimal muscle lengths, enables to identify neural and non-neural changes in chronic stroke patients. Monitoring these changes in time is important to understand the recovery process and to optimize treatment. Copyright © 2016 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

Neural Cell Chip Based Electrochemical Detection of Nanotoxicity

PubMed Central

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

2015-01-01

Development of a rapid, sensitive and cost-effective method for toxicity assessment of commonly used nanoparticles is urgently needed for the sustainable development of nanotechnology. A neural cell with high sensitivity and conductivity has become a potential candidate for a cell chip to investigate toxicity of environmental influences. A neural cell immobilized on a conductive surface has become a potential tool for the assessment of nanotoxicity based on electrochemical methods. The effective electrochemical monitoring largely depends on the adequate attachment of a neural cell on the chip surfaces. Recently, establishment of integrin receptor specific ligand molecules arginine-glycine-aspartic acid (RGD) or its several modifications RGD-Multi Armed Peptide terminated with cysteine (RGD-MAP-C), C(RGD)4 ensure farm attachment of neural cell on the electrode surfaces either in their two dimensional (dot) or three dimensional (rod or pillar) like nano-scale arrangement. A three dimensional RGD modified electrode surface has been proven to be more suitable for cell adhesion, proliferation, differentiation as well as electrochemical measurement. This review discusses fabrication as well as electrochemical measurements of neural cell chip with particular emphasis on their use for nanotoxicity assessments sequentially since inception to date. Successful monitoring of quantum dot (QD), graphene oxide (GO) and cosmetic compound toxicity using the newly developed neural cell chip were discussed here as a case study. This review recommended that a neural cell chip established on a nanostructured ligand modified conductive surface can be a potential tool for the toxicity assessments of newly developed nanomaterials prior to their use on biology or biomedical technologies. PMID:28347059

Mechanisms of in vivo muscle fatigue in humans: investigating age‐related fatigue resistance with a computational model

PubMed Central

Callahan, Damien M.; Umberger, Brian R.

2016-01-01

Key points Muscle fatigue can be defined as the transient decrease in maximal force that occurs in response to muscle use. Fatigue develops because of a complex set of changes within the neuromuscular system that are difficult to evaluate simultaneously in humans.The skeletal muscle of older adults fatigues less than that of young adults during static contractions. The potential sources of this difference are multiple and intertwined.To evaluate the individual mechanisms of fatigue, we developed an integrative computational model based on neural, biochemical, morphological and physiological properties of human skeletal muscle.Our results indicate first that the model provides accurate predictions of fatigue and second that the age‐related resistance to fatigue is due largely to a lower reliance on glycolytic metabolism during contraction.This model should prove useful for generating hypotheses for future experimental studies into the mechanisms of muscle fatigue. Abstract During repeated or sustained muscle activation, force‐generating capacity becomes limited in a process referred to as fatigue. Multiple factors, including motor unit activation patterns, muscle fibre contractile properties and bioenergetic function, can impact force‐generating capacity and thus the potential to resist fatigue. Given that neuromuscular fatigue depends on interrelated factors, quantifying their independent effects on force‐generating capacity is not possible in vivo. Computational models can provide insight into complex systems in which multiple inputs determine discrete outputs. However, few computational models to date have investigated neuromuscular fatigue by incorporating the multiple levels of neuromuscular function known to impact human in vivo function. To address this limitation, we present a computational model that predicts neural activation, biomechanical forces, intracellular metabolic perturbations and, ultimately, fatigue during repeated isometric contractions. This model was compared with metabolic and contractile responses to repeated activation using values reported in the literature. Once validated in this way, the model was modified to reflect age‐related changes in neuromuscular function. Comparisons between initial and age‐modified simulations indicated that the age‐modified model predicted less fatigue during repeated isometric contractions, consistent with reports in the literature. Together, our simulations suggest that reduced glycolytic flux is the greatest contributor to the phenomenon of age‐related fatigue resistance. In contrast, oxidative resynthesis of phosphocreatine between intermittent contractions and inherent buffering capacity had minimal impact on predicted fatigue during isometric contractions. The insights gained from these simulations cannot be achieved through traditional in vivo or in vitro experimentation alone. PMID:26824934

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates.

PubMed

Steele, James S; Bush, Keith; Stowe, Zachary N; James, George A; Smitherman, Sonet; Kilts, Clint D; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates

PubMed Central

Bush, Keith; Stowe, Zachary N.; James, George A.; Smitherman, Sonet; Kilts, Clint D.; Cisler, Josh

2018-01-01

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior. PMID:29489856

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

PubMed Central

Ritchie, Marylyn D; White, Bill C; Parker, Joel S; Hahn, Lance W; Moore, Jason H

2003-01-01

Background Appropriate definition of neural network architecture prior to data analysis is crucial for successful data mining. This can be challenging when the underlying model of the data is unknown. The goal of this study was to determine whether optimizing neural network architecture using genetic programming as a machine learning strategy would improve the ability of neural networks to model and detect nonlinear interactions among genes in studies of common human diseases. Results Using simulated data, we show that a genetic programming optimized neural network approach is able to model gene-gene interactions as well as a traditional back propagation neural network. Furthermore, the genetic programming optimized neural network is better than the traditional back propagation neural network approach in terms of predictive ability and power to detect gene-gene interactions when non-functional polymorphisms are present. Conclusion This study suggests that a machine learning strategy for optimizing neural network architecture may be preferable to traditional trial-and-error approaches for the identification and characterization of gene-gene interactions in common, complex human diseases. PMID:12846935

Anti-proliferative Effect of Engineered Neural Stem Cells Expressing Cytosine Deaminase and Interferon-β against Lymph Node–Derived Metastatic Colorectal Adenocarcinoma in Cellular and Xenograft Mouse Models

PubMed Central

Park, Geon-Tae; Kim, Seung U.; Choi, Kyung-Chul

2017-01-01

Purpose Genetically engineered stem cells may be advantageous for gene therapy against various human cancers due to their inherent tumor-tropic properties. In this study, genetically engineered human neural stem cells (HB1.F3) expressing Escherichia coli cytosine deaminase (CD) (HB1.F3.CD) and human interferon-β (IFN-β) (HB1.F3.CD.IFN-β) were employed against lymph node–derived metastatic colorectal adenocarcinoma. Materials and Methods CD can convert a prodrug, 5-fluorocytosine (5-FC), to active 5-fluorouracil, which inhibits tumor growth through the inhibition of DNA synthesis,while IFN-β also strongly inhibits tumor growth by inducing the apoptotic process. In reverse transcription polymerase chain reaction analysis, we confirmed that HB1.F3.CD cells expressed the CD gene and HB1.F3.CD.IFN-β cells expressed both CD and IFN-β genes. Results In results of a modified trans-well migration assay, HB1.F3.CD and HB1.F3.CD.IFN-β cells selectively migrated toward SW-620, human lymph node–derived metastatic colorectal adenocarcinoma cells. The viability of SW-620 cells was significantly reduced when co-cultured with HB1.F3.CD or HB1.F3.CD.IFN-β cells in the presence of 5-FC. In addition, it was found that the tumor-tropic properties of these engineered human neural stem cells (hNSCs) were attributed to chemoattractant molecules including stromal cell-derived factor 1, c-Kit, urokinase receptor, urokinase-type plasminogen activator, and C-C chemokine receptor type 2 secreted by SW-620 cells. In a xenograft mouse model, treatment with hNSC resulted in significantly inhibited growth of the tumor mass without virulent effects on the animals. Conclusion The current results indicate that engineered hNSCs and a prodrug treatment inhibited the growth of SW-620 cells. Therefore, hNSC therapy may be a clinically effective tool for the treatment of lymph node metastatic colorectal cancer. PMID:27188205

Neural Mechanisms of Recognizing Camouflaged Objects: A Human fMRI Study

DTIC Science & Technology

2015-07-30

Unlimited Final Report: Neural Mechanisms of Recognizing Camouflaged Objects: A Human fMRI Study The views, opinions and/or findings contained in this...27709-2211 Visual search, Camouflage, Functional magnetic resonance imaging ( fMRI ), Perceptual learning REPORT DOCUMENTATION PAGE 11. SPONSOR...ABSTRACT Number of Papers published in peer-reviewed journals: Final Report: Neural Mechanisms of Recognizing Camouflaged Objects: A Human fMRI Study

Linguistic threat activates the human amygdala

PubMed Central

Isenberg, N.; Silbersweig, D.; Engelien, A.; Emmerich, S.; Malavade, K.; Beattie, B.; Leon, A. C.; Stern, E.

1999-01-01

Studies in animals demonstrate a crucial role for the amygdala in emotional and social behavior, especially as related to fear and aggression. Whereas lesion and functional-imaging studies in humans indicate the amygdala’s participation in assessing the significance of nonverbal as well as paralinguistic cues, direct evidence for its role in the emotional processing of linguistic cues is lacking. In this study, we use a modified Stroop task along with a high-sensitivity neuroimaging technique to target the neural substrate engaged specifically when processing linguistic threat. Healthy volunteer subjects were instructed to name the color of words of either threat or neutral valence, presented in different color fonts, while neural activity was measured by using H215O positron-emission tomography. Bilateral amygdalar activation was significantly greater during color naming of threat words than during color naming of neutral words. Associated activations were also noted in sensory-evaluative and motor-planning areas of the brain. Thus, our results demonstrate the amygdala’s role in the processing of danger elicited by language. In addition, the results reinforce the amygdala’s role in the modulation of the perception of, and response to, emotionally salient stimuli. The current study further suggests conservation of phylogenetically older mechanisms of emotional evaluation in the context of more recently evolved linguistic function. PMID:10468630

Stem cell responses to plasma surface modified electrospun polyurethane scaffolds.

PubMed

Zandén, Carl; Hellström Erkenstam, Nina; Padel, Thomas; Wittgenstein, Julia; Liu, Johan; Kuhn, H Georg

2014-07-01

The topographical effects from functional materials on stem cell behavior are currently of interest in tissue engineering and regenerative medicine. Here we investigate the influence of argon, oxygen, and hydrogen plasma surface modification of electrospun polyurethane fibers on human embryonic stem cell (hESC) and rat postnatal neural stem cell (NSC) responses. The plasma gases were found to induce three combinations of fiber surface functionalities and roughness textures. On randomly oriented fibers, plasma treatments lead to substantially increased hESC attachment and proliferation as compared to native fibers. Argon plasma was found to induce the most optimal combination of surface functionality and roughness for cell expansion. Contact guided migration of cells and alignment of cell processes were observed on aligned fibers. Neuronal differentiation around 5% was found for all samples and was not significantly affected by the induced variations of surface functional group distribution or individual fiber topography. In this study the influence of argon, oxygen, and hydrogen plasma surface modification of electrospun polyurethane fibers on human embryonic stem cell and rat postnatal neural stem cell (NSC) responses is studied with the goal of clarifying the potential effects of functional materials on stem cell behavior, a topic of substantial interest in tissue engineering and regenerative medicine. Copyright © 2014 Elsevier Inc. All rights reserved.

Neural network based speech synthesizer: A preliminary report

NASA Technical Reports Server (NTRS)

Villarreal, James A.; Mcintire, Gary

1987-01-01

A neural net based speech synthesis project is discussed. The novelty is that the reproduced speech was extracted from actual voice recordings. In essence, the neural network learns the timing, pitch fluctuations, connectivity between individual sounds, and speaking habits unique to that individual person. The parallel distributed processing network used for this project is the generalized backward propagation network which has been modified to also learn sequences of actions or states given in a particular plan.

A little rein on addiction.

PubMed

Mathuru, Ajay S

2018-06-01

Rewarding and aversive experiences influence emotions, motivate specific behaviors, and modify future action in animals. Multiple conserved vertebrate neural circuits have been discovered that act in a species-specific manner to reinforce behaviors that are rewarding, while attenuating those with an adverse outcome. A growing body of research now suggests that malfunction of the same circuits is an underlying cause for many human disorders and mental ailments. The habenula (Latin for "little rein") complex, an epithalamic structure that regulates midbrain monoaminergic activity has emerged in recent years as one such region in the vertebrate brain that modulates behavior. Its dysfunction, on the other hand, is implicated in a spectrum of psychiatric disorders in humans such as schizophrenia, depression and addiction. Here, I review the progress in identification of potential mechanisms involving the habenula in addiction. Copyright © 2017. Published by Elsevier Ltd.

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.

Single-site neural tube closure in human embryos revisited.

PubMed

de Bakker, Bernadette S; Driessen, Stan; Boukens, Bastiaan J D; van den Hoff, Maurice J B; Oostra, Roelof-Jan

2017-10-01

Since the multi-site closure theory was first proposed in 1991 as explanation for the preferential localizations of neural tube defects, the closure of the neural tube has been debated. Although the multi-site closure theory is much cited in clinical literature, single-site closure is most apparent in literature concerning embryology. Inspired by Victor Hamburgers (1900-2001) statement that "our real teacher has been and still is the embryo, who is, incidentally, the only teacher who is always right", we decided to critically review both theories of neural tube closure. To verify the theories of closure, we studied serial histological sections of 10 mouse embryos between 8.5 and 9.5 days of gestation and 18 human embryos of the Carnegie collection between Carnegie stage 9 (19-21 days) and 13 (28-32 days). Neural tube closure was histologically defined by the neuroepithelial remodeling of the two adjoining neural fold tips in the midline. We did not observe multiple fusion sites in neither mouse nor human embryos. A meta-analysis of case reports on neural tube defects showed that defects can occur at any level of the neural axis. Our data indicate that the human neural tube fuses at a single site and, therefore, we propose to reinstate the single-site closure theory for neural tube closure. We showed that neural tube defects are not restricted to a specific location, thereby refuting the reasoning underlying the multi-site closure theory. Clin. Anat. 30:988-999, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Intercellular crosstalk in human malignant melanoma.

PubMed

Dvořánková, Barbora; Szabo, Pavol; Kodet, Ondřej; Strnad, Hynek; Kolář, Michal; Lacina, Lukáš; Krejčí, Eliška; Naňka, Ondřej; Šedo, Aleksi; Smetana, Karel

2017-05-01

Incidence of malignant melanoma is increasing globally. While the initial stages of tumors can be easily treated by a simple surgery, the therapy of advanced stages is rather limited. Melanoma cells spread rapidly through the body of a patient to form multiple metastases. Consequently, the survival rate is poor. Therefore, emphasis in melanoma research is given on early diagnosis and development of novel and more potent therapeutic options. The malignant melanoma is arising from melanocytes, cells protecting mitotically active keratinocytes against damage caused by UV light irradiation. The melanocytes originate in the neural crest and consequently migrate to the epidermis. The relationship between the melanoma cells, the melanocytes, and neural crest stem cells manifests when the melanoma cells are implanted to an early embryo: they use similar migratory routes as the normal neural crest cells. Moreover, malignant potential of these melanoma cells is overdriven in this experimental model, probably due to microenvironmental reprogramming. This observation demonstrates the crucial role of the microenvironment in melanoma biology. Indeed, malignant tumors in general represent complex ecosystems, where multiple cell types influence the growth of genetically mutated cancer cells. This concept is directly applicable to the malignant melanoma. Our review article focuses on possible strategies to modify the intercellular crosstalk in melanoma that can be employed for therapeutic purposes.

Neurocognitive processes of linguistic cues related to death.

PubMed

Han, Shihui; Qin, Jungang; Ma, Yina

2010-10-01

Consciousness of the finiteness of one's personal existence influences human thoughts and behaviors tremendously. However, the neural substrates underlying the processing of death-related information remain unclear. The current study addressed this issue by scanning 20 female adults, using functional magnetic resonance imaging, in a modified Stroop task that required naming colors of death-related, negative-valence, and neutral-valence words. We found that, while both death-related and negative-valence words increased activity in the precuneus/posterior cingulate and lateral frontal cortex relative to neutral-valence words, the neural correlate of the processing of death-related words was characterized by decreased activity in bilateral insula relative to both negative-valence and neutral-valence words. Moreover, the decreased activity in the left insula correlated with subjective ratings of death relevance of death-related words and the decreased activity in the right insula correlated with subjective ratings of arousal induced by death-related words. Our fMRI findings suggest that, while both death-related and negative-valence words are associated with enhanced arousal and emotion regulation, the processing of linguistic cues related to death is associated with modulations of the activity in the insula that mediates neural representation of the sentient self. Copyright © 2010 Elsevier Ltd. All rights reserved.

More than Just Two Sexes: The Neural Correlates of Voice Gender Perception in Gender Dysphoria

PubMed Central

Junger, Jessica; Habel, Ute; Bröhr, Sabine; Neulen, Josef; Neuschaefer-Rube, Christiane; Birkholz, Peter; Kohler, Christian; Schneider, Frank; Derntl, Birgit; Pauly, Katharina

2014-01-01

Gender dysphoria (also known as “transsexualism”) is characterized as a discrepancy between anatomical sex and gender identity. Research points towards neurobiological influences. Due to the sexually dimorphic characteristics of the human voice, voice gender perception provides a biologically relevant function, e.g. in the context of mating selection. There is evidence for a better recognition of voices of the opposite sex and a differentiation of the sexes in its underlying functional cerebral correlates, namely the prefrontal and middle temporal areas. This fMRI study investigated the neural correlates of voice gender perception in 32 male-to-female gender dysphoric individuals (MtFs) compared to 20 non-gender dysphoric men and 19 non-gender dysphoric women. Participants indicated the sex of 240 voice stimuli modified in semitone steps in the direction to the other gender. Compared to men and women, MtFs showed differences in a neural network including the medial prefrontal gyrus, the insula, and the precuneus when responding to male vs. female voices. With increased voice morphing men recruited more prefrontal areas compared to women and MtFs, while MtFs revealed a pattern more similar to women. On a behavioral and neuronal level, our results support the feeling of MtFs reporting they cannot identify with their assigned sex. PMID:25375171

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.

Neuroanatomically Separable Effects of Imageability and Grammatical Class during Single-Word Comprehension

ERIC Educational Resources Information Center

Bedny, Marina; Thompson-Schill, Sharon L.

2006-01-01

The present study characterizes the neural correlates of noun and verb imageability and addresses the question of whether components of the neural network supporting word recognition can be separately modified by variations in grammatical class and imageability. We examined the effect of imageability on BOLD signal during single-word comprehension…

Differences in Feedback- and Inhibition-Related Neural Activity in Adult ADHD

ERIC Educational Resources Information Center

Dibbets, Pauline; Evers, Lisbeth; Hurks, Petra; Marchetta, Natalie; Jolles, Jelle

2009-01-01

The objective of this study was to examine response inhibition- and feedback-related neural activity in adults with attention deficit hyperactivity disorder (ADHD) using event-related functional MRI. Sixteen male adults with ADHD and 13 healthy/normal controls participated in this study and performed a modified Go/NoGo task. Behaviourally,…

The Effects of Simulated Stuttering and Prolonged Speech on the Neural Activation Patterns of Stuttering and Nonstuttering Adults

ERIC Educational Resources Information Center

De Nil, Luc F.; Beal, Deryk S.; Lafaille, Sophie J.; Kroll, Robert M.; Crawley, Adrian P.; Gracco, Vincent L.

2008-01-01

Functional magnetic resonance imaging was used to investigate the neural correlates of passive listening, habitual speech and two modified speech patterns (simulated stuttering and prolonged speech) in stuttering and nonstuttering adults. Within-group comparisons revealed increased right hemisphere biased activation of speech-related regions…

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Engineering Human Neural Tissue by 3D Bioprinting.

PubMed

Gu, Qi; Tomaskovic-Crook, Eva; Wallace, Gordon G; Crook, Jeremy M

2018-01-01

Bioprinting provides an opportunity to produce three-dimensional (3D) tissues for biomedical research and translational drug discovery, toxicology, and tissue replacement. Here we describe a method for fabricating human neural tissue by 3D printing human neural stem cells with a bioink, and subsequent gelation of the bioink for cell encapsulation, support, and differentiation to functional neurons and supporting neuroglia. The bioink uniquely comprises the polysaccharides alginate, water-soluble carboxymethyl-chitosan, and agarose. Importantly, the method could be adapted to fabricate neural and nonneural tissues from other cell types, with the potential to be applied for both research and clinical product development.

Which way and how far? Tracking of translation and rotation information for human path integration.

PubMed

Chrastil, Elizabeth R; Sherrill, Katherine R; Hasselmo, Michael E; Stern, Chantal E

2016-10-01

Path integration, the constant updating of the navigator's knowledge of position and orientation during movement, requires both visuospatial knowledge and memory. This study aimed to develop a systems-level understanding of human path integration by examining the basic building blocks of path integration in humans. To achieve this goal, we used functional imaging to examine the neural mechanisms that support the tracking and memory of translational and rotational components of human path integration. Critically, and in contrast to previous studies, we examined movement in translation and rotation tasks with no defined end-point or goal. Navigators accumulated translational and rotational information during virtual self-motion. Activity in hippocampus, retrosplenial cortex (RSC), and parahippocampal cortex (PHC) increased during both translation and rotation encoding, suggesting that these regions track self-motion information during path integration. These results address current questions regarding distance coding in the human brain. By implementing a modified delayed match to sample paradigm, we also examined the encoding and maintenance of path integration signals in working memory. Hippocampus, PHC, and RSC were recruited during successful encoding and maintenance of path integration information, with RSC selective for tasks that required processing heading rotation changes. These data indicate distinct working memory mechanisms for translation and rotation, which are essential for updating neural representations of current location. The results provide evidence that hippocampus, PHC, and RSC flexibly track task-relevant translation and rotation signals for path integration and could form the hub of a more distributed network supporting spatial navigation. Hum Brain Mapp 37:3636-3655, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

An improved protocol that induces human embryonic stem cells to differentiate into neural cells in vitro.

PubMed

Zhou, Jun-Mei; Chu, Jian-Xin; Chen, Xue-Jin

2008-01-01

Human embryonic stem (ES) cells have the capacity for self-renewal and are able to differentiate into any cell type. However, obtaining high-efficient neural differentiation from human ES cells remains a challenge. This study describes an improved 4-stage protocol to induce a human ES cell line derived from a Chinese population to differentiate into neural cells. At the first stage, embryonic bodies (EBs) were formed in a chemically-defined neural inducing medium rather than in traditional serum or serum-replacement medium. At the second stage, rosette-like structures were formed. At the third stage, the rosette-like structures were manually selected rather than enzymatically digested to form floating neurospheres. At the fourth stage, the neurospheres were further differentiated into neurons. The results show that, at the second stage, the rate of the formation of rosette-like structures from EBs induced by noggin was 88+/-6.32%, higher than that of retinoic acid 55+/-5.27%. Immunocytochemistry staining was used to confirm the neural identity of the cells. These results show a major improvement in obtaining efficient neural differentiation of human ES cells.

Processing of social and monetary rewards in the human striatum.

PubMed

Izuma, Keise; Saito, Daisuke N; Sadato, Norihiro

2008-04-24

Despite an increasing focus on the neural basis of human decision making in neuroscience, relatively little attention has been paid to decision making in social settings. Moreover, although human social decision making has been explored in a social psychology context, few neural explanations for the observed findings have been considered. To bridge this gap and improve models of human social decision making, we investigated whether acquiring a good reputation, which is an important incentive in human social behaviors, activates the same reward circuitry as monetary rewards. In total, 19 subjects participated in functional magnetic resonance imaging (fMRI) experiments involving monetary and social rewards. The acquisition of one's good reputation robustly activated reward-related brain areas, notably the striatum, and these overlapped with the areas activated by monetary rewards. Our findings support the idea of a "common neural currency" for rewards and represent an important first step toward a neural explanation for complex human social behaviors.

Neural mechanisms of mother-infant bonding and pair bonding: Similarities, differences, and broader implications.

PubMed

Numan, Michael; Young, Larry J

2016-01-01

This article is part of a Special Issue "Parental Care". Mother-infant bonding is a characteristic of virtually all mammals. The maternal neural system may have provided the scaffold upon which other types of social bonds in mammals have been built. For example, most mammals exhibit a polygamous mating system, but monogamy and pair bonding between mating partners occur in ~5% of mammalian species. In mammals, it is plausible that the neural mechanisms that promote mother-infant bonding have been modified by natural selection to establish the capacity to develop a selective bond with a mate during the evolution of monogamous mating strategies. Here we compare the details of the neural mechanisms that promote mother-infant bonding in rats and other mammals with those that underpin pair bond formation in the monogamous prairie vole. Although details remain to be resolved, remarkable similarities and a few differences between the mechanisms underlying these two types of bond formation are revealed. For example, amygdala and nucleus accumbens-ventral pallidum (NA-VP) circuits are involved in both types of bond formation, and dopamine and oxytocin actions within NA appear to promote the synaptic plasticity that allows either infant or mating partner stimuli to persistently activate NA-VP attraction circuits, leading to an enduring social attraction and bonding. Further, although the medial preoptic area is essential for maternal behavior, its role in pair bonding remains to be determined. Our review concludes by examining the broader implications of this comparative analysis, and evidence is provided that the maternal care system may have also provided the basic neural foundation for other types of strong social relationships, beyond pair bonding, in mammals, including humans. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural mechanisms of mother-infant bonding and pair bonding: Similarities, differences, and broader implications

PubMed Central

Numan, Michael; Young, Larry J.

2015-01-01

Mother-infant bonding is a characteristic of virtually all mammals. The maternal neural system may have provided the scaffold upon which other types of social bonds in mammals have been built. For example, most mammals exhibit a polygamous mating system, but monogamy and pair bonding between mating partners occurs in ∼5% of mammalian species. In mammals, it is plausible that the neural mechanisms that promote mother-infant bonding have been modified by natural selection to establish the capacity to develop a selective bond with a mate during the evolution of monogamous mating strategies. Here we compare the details of the neural mechanisms that promote mother-infant bonding in rats and other mammals with those that underpin pair bond formation in the monogamous prairie vole. Although details remain to be resolved, remarkable similarities and a few differences between the mechanisms underlying these two types of bond formation are revealed. For example, amygdala and nucleus accumbens-ventral pallidum (NA-VP) circuits are involved in both types of bond formation, and dopamine and oxytocin action within NA appears to promote the synaptic plasticity that allows either infant or mating partner stimuli to persistently activate NA-VP attraction circuits, leading to an enduring social attraction and bonding. Further, although the medial preoptic area is essential for maternal behavior, its role in pair bonding remains to be determined. Our review concludes by examining the broader implications of this comparative analysis, and evidence is provided that the maternal care system may have also provided the basic neural foundation for other types of strong social relationships, beyond pair bonding, in mammals, including humans. PMID:26062432

Evidence for Neural Computations of Temporal Coherence in an Auditory Scene and Their Enhancement during Active Listening.

PubMed

O'Sullivan, James A; Shamma, Shihab A; Lalor, Edmund C

2015-05-06

The human brain has evolved to operate effectively in highly complex acoustic environments, segregating multiple sound sources into perceptually distinct auditory objects. A recent theory seeks to explain this ability by arguing that stream segregation occurs primarily due to the temporal coherence of the neural populations that encode the various features of an individual acoustic source. This theory has received support from both psychoacoustic and functional magnetic resonance imaging (fMRI) studies that use stimuli which model complex acoustic environments. Termed stochastic figure-ground (SFG) stimuli, they are composed of a "figure" and background that overlap in spectrotemporal space, such that the only way to segregate the figure is by computing the coherence of its frequency components over time. Here, we extend these psychoacoustic and fMRI findings by using the greater temporal resolution of electroencephalography to investigate the neural computation of temporal coherence. We present subjects with modified SFG stimuli wherein the temporal coherence of the figure is modulated stochastically over time, which allows us to use linear regression methods to extract a signature of the neural processing of this temporal coherence. We do this under both active and passive listening conditions. Our findings show an early effect of coherence during passive listening, lasting from ∼115 to 185 ms post-stimulus. When subjects are actively listening to the stimuli, these responses are larger and last longer, up to ∼265 ms. These findings provide evidence for early and preattentive neural computations of temporal coherence that are enhanced by active analysis of an auditory scene. Copyright © 2015 the authors 0270-6474/15/357256-08$15.00/0.

Spike avalanches in vivo suggest a driven, slightly subcritical brain state

PubMed Central

Priesemann, Viola; Wibral, Michael; Valderrama, Mario; Pröpper, Robert; Le Van Quyen, Michel; Geisel, Theo; Triesch, Jochen; Nikolić, Danko; Munk, Matthias H. J.

2014-01-01

In self-organized critical (SOC) systems avalanche size distributions follow power-laws. Power-laws have also been observed for neural activity, and so it has been proposed that SOC underlies brain organization as well. Surprisingly, for spiking activity in vivo, evidence for SOC is still lacking. Therefore, we analyzed highly parallel spike recordings from awake rats and monkeys, anesthetized cats, and also local field potentials from humans. We compared these to spiking activity from two established critical models: the Bak-Tang-Wiesenfeld model, and a stochastic branching model. We found fundamental differences between the neural and the model activity. These differences could be overcome for both models through a combination of three modifications: (1) subsampling, (2) increasing the input to the model (this way eliminating the separation of time scales, which is fundamental to SOC and its avalanche definition), and (3) making the model slightly sub-critical. The match between the neural activity and the modified models held not only for the classical avalanche size distributions and estimated branching parameters, but also for two novel measures (mean avalanche size, and frequency of single spikes), and for the dependence of all these measures on the temporal bin size. Our results suggest that neural activity in vivo shows a mélange of avalanches, and not temporally separated ones, and that their global activity propagation can be approximated by the principle that one spike on average triggers a little less than one spike in the next step. This implies that neural activity does not reflect a SOC state but a slightly sub-critical regime without a separation of time scales. Potential advantages of this regime may be faster information processing, and a safety margin from super-criticality, which has been linked to epilepsy. PMID:25009473

How learning might strengthen existing visual object representations in human object-selective cortex.

PubMed

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Strategy towards independent electrical stimulation from cochlear implants: Guided auditory neuron growth on topographically modified nanocrystalline diamond.

PubMed

Cai, Yixiao; Edin, Fredrik; Jin, Zhe; Alexsson, Andrei; Gudjonsson, Olafur; Liu, Wei; Rask-Andersen, Helge; Karlsson, Mikael; Li, Hao

2016-02-01

Cochlear implants (CI) have been used for several decades to treat patients with profound hearing loss. Nevertheless, results vary between individuals, and fine hearing is generally poor due to the lack of discrete neural stimulation from the individual receptor hair cells. A major problem is the deliverance of independent stimulation signals to individual auditory neurons. Fine hearing requires significantly more stimulation contacts with intimate neuron/electrode interphases from ordered axonal re-growth, something current CI technology cannot provide. Here, we demonstrate the potential application of micro-textured nanocrystalline diamond (NCD) surfaces on CI electrode arrays. Such textured NCD surfaces consist of micrometer-sized nail-head-shaped pillars (size 5×5μm(2)) made with sequences of micro/nano-fabrication processes, including sputtering, photolithography and plasma etching. The results show that human and murine inner-ear ganglion neurites and, potentially, neural progenitor cells can attach to patterned NCD surfaces without an extracellular matrix coating. Microscopic methods revealed adhesion and neural growth, specifically along the nail-head-shaped NCD pillars in an ordered manner, rather than in non-textured areas. This pattern was established when the inter-NCD pillar distance varied between 4 and 9μm. The findings demonstrate that regenerating auditory neurons show a strong affinity to the NCD pillars, and the technique could be used for neural guidance and the creation of new neural networks. Together with the NCD's unique anti-bacterial and electrical properties, patterned NCD surfaces could provide designed neural/electrode interfaces to create independent electrical stimulation signals in CI electrode arrays for the neural population. Cochlear implant is currently a successful way to treat sensorineural hearing loss and deafness especially in children. Although clinically successful, patients' fine hearing cannot be completely restored. One problem is the amount of the electrodes; 12-20 electrodes are used to replace the function of 3400 inner hair cells. Intense research is ongoing aiming to increase the number of electrodes. This study demonstrates the use of nanocrystalline diamond as a potential nerve-electrode interface. Micrometer-sized nanocrystalline diamond pillars showed high affinity to regenerated human neurons, which grew into a pre-defined network based on the pillar design. Our findings are of particular interest since they can be applied on any silicon-based implant to increase electrode count and to achieve individual neuron stimulation patterns. Copyright © 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Behavioral and neurophysiological correlates of regret in rat decision-making on a neuroeconomic task

PubMed Central

Steiner, Adam P.; Redish, A. David

2014-01-01

Summary Disappointment entails the recognition that one did not get the value one expected. In contrast, regret entails the recognition that an alternate (counterfactual) action would have produced a more valued outcome. Thus, the key to identifying regret is the representation of that counterfactual option in situations in which a mistake has been made. In humans, the orbitofrontal cortex is active during expressions of regret, and humans with damage to the orbitofrontal cortex do not express regret. In rats and non-human primates, both the orbitofrontal cortex and the ventral striatum have been implicated in decision-making, particularly in representations of expectations of reward. In order to examine representations of regretful situations, we recorded neural ensembles from orbitofrontal cortex and ventral striatum in rats encountering a spatial sequence of wait/skip choices for delayed delivery of different food flavors. We were able to measure preferences using an economic framework. Rats occasionally skipped low-cost choices and then encountered a high-cost choice. This sequence economically defines a potential regret-inducing instance. In these situations, rats looked backwards towards the lost option, the cells within the orbitofrontal cortex and ventral striatum represented that missed action, rats were more likely to wait for the long delay, and rats rushed through eating the food after that delay. That these situations drove rats to modify their behavior suggests that regret-like processes modify decision-making in non-human mammals. PMID:24908102

A Study for the Feature Selection to Identify GIEMSA-Stained Human Chromosomes Based on Artificial Neural Network

DTIC Science & Technology

2001-10-25

neural network (ANN) has been adopted for the human chromosome classification. It is important to select optimum features for training neural network...Many studies for computer-based chromosome analysis have shown that it is possible to classify chromosomes into 24 subgroups. In addition, artificial

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.

2007-01-01

This paper describes the performance of a simplified dynamic inversion controller with neural network supplementation. This 6 DOF (Degree-of-Freedom) simulation study focuses on the results with and without adaptation of neural networks using a simulation of the NASA modified F-15 which has canards. One area of interest is the performance of a simulated surface failure while attempting to minimize the inertial cross coupling effect of a [B] matrix failure (a control derivative anomaly associated with a jammed or missing control surface). Another area of interest and presented is simulated aerodynamic failures ([A] matrix) such as a canard failure. The controller uses explicit models to produce desired angular rate commands. The dynamic inversion calculates the necessary surface commands to achieve the desired rates. The simplified dynamic inversion uses approximate short period and roll axis dynamics. Initial results indicated that the transient response for a [B] matrix failure using a Neural Network (NN) improved the control behavior when compared to not using a neural network for a given failure, However, further evaluation of the controller was comparable, with objections io the cross coupling effects (after changes were made to the controller). This paper describes the methods employed to reduce the cross coupling effect and maintain adequate tracking errors. The IA] matrix failure results show that control of the aircraft without adaptation is more difficult [leas damped) than with active neural networks, Simulation results show Neural Network augmentation of the controller improves performance in terms of backing error and cross coupling reduction and improved performance with aerodynamic-type failures.

The Neural Representations Underlying Human Episodic Memory.

PubMed

Xue, Gui

2018-06-01

A fundamental question of human episodic memory concerns the cognitive and neural representations and processes that give rise to the neural signals of memory. By integrating behavioral tests, formal computational models, and neural measures of brain activity patterns, recent studies suggest that memory signals not only depend on the neural processes and representations during encoding and retrieval, but also on the interaction between encoding and retrieval (e.g., transfer-appropriate processing), as well as on the interaction between the tested events and all other events in the episodic memory space (e.g., global matching). In addition, memory signals are also influenced by the compatibility of the event with the existing long-term knowledge (e.g., schema matching). These studies highlight the interactive nature of human episodic memory. Copyright © 2018 Elsevier Ltd. All rights reserved.

Frequency modulation entrains slow neural oscillations and optimizes human listening behavior

PubMed Central

Henry, Molly J.; Obleser, Jonas

2012-01-01

The human ability to continuously track dynamic environmental stimuli, in particular speech, is proposed to profit from “entrainment” of endogenous neural oscillations, which involves phase reorganization such that “optimal” phase comes into line with temporally expected critical events, resulting in improved processing. The current experiment goes beyond previous work in this domain by addressing two thus far unanswered questions. First, how general is neural entrainment to environmental rhythms: Can neural oscillations be entrained by temporal dynamics of ongoing rhythmic stimuli without abrupt onsets? Second, does neural entrainment optimize performance of the perceptual system: Does human auditory perception benefit from neural phase reorganization? In a human electroencephalography study, listeners detected short gaps distributed uniformly with respect to the phase angle of a 3-Hz frequency-modulated stimulus. Listeners’ ability to detect gaps in the frequency-modulated sound was not uniformly distributed in time, but clustered in certain preferred phases of the modulation. Moreover, the optimal stimulus phase was individually determined by the neural delta oscillation entrained by the stimulus. Finally, delta phase predicted behavior better than stimulus phase or the event-related potential after the gap. This study demonstrates behavioral benefits of phase realignment in response to frequency-modulated auditory stimuli, overall suggesting that frequency fluctuations in natural environmental input provide a pacing signal for endogenous neural oscillations, thereby influencing perceptual processing. PMID:23151506

Neural network regulation driven by autonomous neural firings

NASA Astrophysics Data System (ADS)

Cho, Myoung Won

2016-07-01

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

Age and Experience Shape Developmental Changes in the Neural Basis of Language-Related Learning

ERIC Educational Resources Information Center

McNealy, Kristin; Mazziotta, John C.; Dapretto, Mirella

2011-01-01

Very little is known about the neural underpinnings of language learning across the lifespan and how these might be modified by maturational and experiential factors. Building on behavioral research highlighting the importance of early word segmentation (i.e. the detection of word boundaries in continuous speech) for subsequent language learning,…

Preclinical Analysis of Fetal Human Mesencephalic Neural Progenitor Cell Lines: Characterization and Safety In Vitro and In Vivo

PubMed Central

Moon, Jisook; Schwarz, Sigrid C.; Lee, Hyun‐Seob; Kang, Jun Mo; Lee, Young‐Eun; Kim, Bona; Sung, Mi‐Young; Höglinger, Günter; Wegner, Florian; Kim, Jin Su; Chung, Hyung‐Min; Chang, Sung Woon; Cha, Kwang Yul; Kim, Kwang‐Soo

2016-01-01

Abstract We have developed a good manufacturing practice for long‐term cultivation of fetal human midbrain‐derived neural progenitor cells. The generation of human dopaminergic neurons may serve as a tool of either restorative cell therapies or cellular models, particularly as a reference for phenotyping region‐specific human neural stem cell lines such as human embryonic stem cells and human inducible pluripotent stem cells. We cultivated 3 different midbrain neural progenitor lines at 10, 12, and 14 weeks of gestation for more than a year and characterized them in great detail, as well as in comparison with Lund mesencephalic cells. The whole cultivation process of tissue preparation, cultivation, and cryopreservation was developed using strict serum‐free conditions and standardized operating protocols under clean‐room conditions. Long‐term‐cultivated midbrain‐derived neural progenitor cells retained stemness, midbrain fate specificity, and floorplate markers. The potential to differentiate into authentic A9‐specific dopaminergic neurons was markedly elevated after prolonged expansion, resulting in large quantities of functional dopaminergic neurons without genetic modification. In restorative cell therapeutic approaches, midbrain‐derived neural progenitor cells reversed impaired motor function in rodents, survived well, and did not exhibit tumor formation in immunodeficient nude mice in the short or long term (8 and 30 weeks, respectively). We conclude that midbrain‐derived neural progenitor cells are a promising source for human dopaminergic neurons and suitable for long‐term expansion under good manufacturing practice, thus opening the avenue for restorative clinical applications or robust cellular models such as high‐content or high‐throughput screening. Stem Cells Translational Medicine 2017;6:576–588 PMID:28191758

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

PubMed

Su, Chih-Ying; Wang, Jing W

2014-12-01

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

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.

Human Fetal Keratocytes Have Multipotent Characteristics in the Developing Avian Embryo

PubMed Central

Chao, Jennifer R.; Bronner, Marianne E.

2013-01-01

The human cornea contains stem cells that can be induced to express markers consistent with multipotency in cell culture; however, there have been no studies demonstrating that human corneal keratocytes are multipotent. The objective of this study is to examine the potential of human fetal keratocytes (HFKs) to differentiate into neural crest-derived tissues when challenged in an embryonic environment. HFKs were injected bilaterally into the cranial mesenchyme adjacent to the neural tube and the periocular mesenchyme in chick embryos at embryonic days 1.5 and 3, respectively. The injected keratocytes were detected by immunofluorescence using the human cell-specific marker, HuNu. HuNu-positive keratocytes injected along the neural crest pathway were localized adjacent to HNK-1-positive migratory host neural crest cells and in the cardiac cushion mesenchyme. The HuNu-positive cells transformed into neural crest derivatives such as smooth muscle in cranial blood vessels, stromal keratocytes, and corneal endothelium. However, they failed to form neurons despite their presence in the condensing trigeminal ganglion. These results show that HFKs retain the ability to differentiate into some neural crest-derived tissues. Their ability to respond to embryonic cues and generate corneal endothelium and stromal keratocytes provides a basis for understanding the feasibility of creating specialized cells for possible use in regenerative medicine. PMID:23461574

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

PubMed Central

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

2017-01-01

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

Top-Down Inhibition of BMP Signaling Enables Robust Induction of hPSCs Into Neural Crest in Fully Defined, Xeno-free Conditions.

PubMed

Hackland, James O S; Frith, Tom J R; Thompson, Oliver; Marin Navarro, Ana; Garcia-Castro, Martin I; Unger, Christian; Andrews, Peter W

2017-10-10

Defects in neural crest development have been implicated in many human disorders, but information about human neural crest formation mostly depends on extrapolation from model organisms. Human pluripotent stem cells (hPSCs) can be differentiated into in vitro counterparts of the neural crest, and some of the signals known to induce neural crest formation in vivo are required during this process. However, the protocols in current use tend to produce variable results, and there is no consensus as to the precise signals required for optimal neural crest differentiation. Using a fully defined culture system, we have now found that the efficient differentiation of hPSCs to neural crest depends on precise levels of BMP signaling, which are vulnerable to fluctuations in endogenous BMP production. We present a method that controls for this phenomenon and could be applied to other systems where endogenous signaling can also affect the outcome of differentiation protocols. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Neural correlates of economic game playing.

PubMed

Krueger, Frank; Grafman, Jordan; McCabe, Kevin

2008-12-12

The theory of games provides a mathematical formalization of strategic choices, which have been studied in both economics and neuroscience, and more recently has become the focus of neuroeconomics experiments with human and non-human actors. This paper reviews the results from a number of game experiments that establish a unitary system for forming subjective expected utility maps in the brain, and acting on these maps to produce choices. Social situations require the brain to build an understanding of the other person using neuronal mechanisms that share affective and intentional mental states. These systems allow subjects to better predict other players' choices, and allow them to modify their subjective utility maps to value pro-social strategies. New results for a trust game are presented, which show that the trust relationship includes systems common to both trusting and trustworthy behaviour, but they also show that the relative temporal positions of first and second players require computations unique to that role.

Neural crest cells: from developmental biology to clinical interventions.

PubMed

Noisa, Parinya; Raivio, Taneli

2014-09-01

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

Perceptual learning increases the strength of the earliest signals in visual cortex.

PubMed

Bao, Min; Yang, Lin; Rios, Cristina; He, Bin; Engel, Stephen A

2010-11-10

Training improves performance on most visual tasks. Such perceptual learning can modify how information is read out from, and represented in, later visual areas, but effects on early visual cortex are controversial. In particular, it remains unknown whether learning can reshape neural response properties in early visual areas independent from feedback arising in later cortical areas. Here, we tested whether learning can modify feedforward signals in early visual cortex as measured by the human electroencephalogram. Fourteen subjects were trained for >24 d to detect a diagonal grating pattern in one quadrant of the visual field. Training improved performance, reducing the contrast needed for reliable detection, and also reliably increased the amplitude of the earliest component of the visual evoked potential, the C1. Control orientations and locations showed smaller effects of training. Because the C1 arises rapidly and has a source in early visual cortex, our results suggest that learning can increase early visual area response through local receptive field changes without feedback from later areas.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Maternal thyroid hormones are essential for neural development in zebrafish.

PubMed

Campinho, Marco A; Saraiva, João; Florindo, Claudia; Power, Deborah M

2014-07-01

Teleost eggs contain an abundant store of maternal thyroid hormones (THs), and early in zebrafish embryonic development, all the genes necessary for TH signaling are expressed. Nonetheless the function of THs in embryonic development remains elusive. To test the hypothesis that THs are fundamental for zebrafish embryonic development, an monocarboxilic transporter 8 (Mct8) knockdown strategy was deployed to prevent maternal TH uptake. Absence of maternal THs did not affect early specification of the neural epithelia but profoundly modified later dorsal specification of the brain and spinal cord as well as specific neuron differentiation. Maternal THs acted upstream of pax2a, pax7, and pax8 genes but downstream of shha and fgf8a signaling. The lack of inhibitory spinal cord interneurons and increased motoneurons in the mct8 morphants is consistent with their stiff axial body and impaired mobility. The mct8 mutations are associated with X-linked mental retardation in humans, and the cellular and molecular consequences of MCT8 knockdown during embryonic development in zebrafish provides new insight into the potential role of THs in this condition.

Maternal Thyroid Hormones Are Essential for Neural Development in Zebrafish

PubMed Central

Saraiva, João; Florindo, Claudia; Power, Deborah M.

2014-01-01

Teleost eggs contain an abundant store of maternal thyroid hormones (THs), and early in zebrafish embryonic development, all the genes necessary for TH signaling are expressed. Nonetheless the function of THs in embryonic development remains elusive. To test the hypothesis that THs are fundamental for zebrafish embryonic development, an monocarboxilic transporter 8 (Mct8) knockdown strategy was deployed to prevent maternal TH uptake. Absence of maternal THs did not affect early specification of the neural epithelia but profoundly modified later dorsal specification of the brain and spinal cord as well as specific neuron differentiation. Maternal THs acted upstream of pax2a, pax7, and pax8 genes but downstream of shha and fgf8a signaling. The lack of inhibitory spinal cord interneurons and increased motoneurons in the mct8 morphants is consistent with their stiff axial body and impaired mobility. The mct8 mutations are associated with X-linked mental retardation in humans, and the cellular and molecular consequences of MCT8 knockdown during embryonic development in zebrafish provides new insight into the potential role of THs in this condition. PMID:24877564

Yarn-dyed fabric defect classification based on convolutional neural network

NASA Astrophysics Data System (ADS)

Jing, Junfeng; Dong, Amei; Li, Pengfei; Zhang, Kaibing

2017-09-01

Considering that manual inspection of the yarn-dyed fabric can be time consuming and inefficient, we propose a yarn-dyed fabric defect classification method by using a convolutional neural network (CNN) based on a modified AlexNet. CNN shows powerful ability in performing feature extraction and fusion by simulating the learning mechanism of human brain. The local response normalization layers in AlexNet are replaced by the batch normalization layers, which can enhance both the computational efficiency and classification accuracy. In the training process of the network, the characteristics of the defect are extracted step by step and the essential features of the image can be obtained from the fusion of the edge details with several convolution operations. Then the max-pooling layers, the dropout layers, and the fully connected layers are employed in the classification model to reduce the computation cost and extract more precise features of the defective fabric. Finally, the results of the defect classification are predicted by the softmax function. The experimental results show promising performance with an acceptable average classification rate and strong robustness on yarn-dyed fabric defect classification.

An Evolutionarily Conserved SoxB-Hdac2 Crosstalk Regulates Neurogenesis in a Cnidarian.

PubMed

Flici, Hakima; Schnitzler, Christine E; Millane, R Cathriona; Govinden, Graham; Houlihan, Amy; Boomkamp, Stephanie D; Shen, Sanbing; Baxevanis, Andreas D; Frank, Uri

2017-02-07

SoxB transcription factors and histone deacetylases (HDACs) are each major players in the regulation of neurogenesis, but a functional link between them has not been previously demonstrated. Here, we show that SoxB2 and Hdac2 act together to regulate neurogenesis in the cnidarian Hydractinia echinata during tissue homeostasis and head regeneration. We find that misexpression of SoxB genes modifies the number of neural cells in all life stages and interferes with head regeneration. Hdac2 was co-expressed with SoxB2, and its downregulation phenocopied SoxB2 knockdown. We also show that SoxB2 and Hdac2 promote each other's transcript levels, but Hdac2 counteracts this amplification cycle by deacetylating and destabilizing SoxB2 protein. Finally, we present evidence for conservation of these interactions in human neural progenitors. We hypothesize that crosstalk between SoxB transcription factors and Hdac2 is an ancient feature of metazoan neurogenesis and functions to stabilize the correct levels of these multifunctional proteins. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Determining electrically evoked compound action potential thresholds: a comparison of computer versus human analysis methods.

PubMed

Glassman, E Katelyn; Hughes, Michelle L

2013-01-01

Current cochlear implants (CIs) have telemetry capabilities for measuring the electrically evoked compound action potential (ECAP). Neural Response Telemetry (Cochlear) and Neural Response Imaging (Advanced Bionics [AB]) can measure ECAP responses across a range of stimulus levels to obtain an amplitude growth function. Software-specific algorithms automatically mark the leading negative peak, N1, and the following positive peak/plateau, P2, and apply linear regression to estimate ECAP threshold. Alternatively, clinicians may apply expert judgments to modify the peak markers placed by the software algorithms, or use visual detection to identify the lowest level yielding a measurable ECAP response. The goals of this study were to: (1) assess the variability between human and computer decisions for (a) marking N1 and P2 and (b) determining linear-regression threshold (LRT) and visual-detection threshold (VDT); and (2) compare LRT and VDT methods within and across human- and computer-decision methods. ECAP amplitude-growth functions were measured for three electrodes in each of 20 ears (10 Cochlear Nucleus® 24RE/CI512, and 10 AB CII/90K). LRT, defined as the current level yielding an ECAP with zero amplitude, was calculated for both computer- (C-LRT) and human-picked peaks (H-LRT). VDT, defined as the lowest level resulting in a measurable ECAP response, was also calculated for both computer- (C-VDT) and human-picked peaks (H-VDT). Because Neural Response Imaging assigns peak markers to all waveforms but does not include waveforms with amplitudes less than 20 μV in its regression calculation, C-VDT for AB subjects was defined as the lowest current level yielding an amplitude of 20 μV or more. Overall, there were significant correlations between human and computer decisions for peak-marker placement, LRT, and VDT for both manufacturers (r = 0.78-1.00, p < 0.001). For Cochlear devices, LRT and VDT correlated equally well for both computer- and human-picked peaks (r = 0.98-0.99, p < 0.001), which likely reflects the well-defined Neural Response Telemetry algorithm and the lower noise floor in the 24RE and CI512 devices. For AB devices, correlations between LRT and VDT for both peak-picker methods were weaker than for Cochlear devices (r = 0.69-0.85, p < 0.001), which likely reflect the higher noise floor of the system. Disagreement between computer and human decisions regarding the presence of an ECAP response occurred for 5 % of traces for Cochlear devices and 2.1 % of traces for AB devices. Results indicate that human and computer peak-picking methods can be used with similar accuracy for both Cochlear and AB devices. Either C-VDT or C-LRT can be used with equal confidence for Cochlear 24RE and CI512 recipients because both methods are strongly correlated with human decisions. However, for AB devices, greater variability exists between different threshold-determination methods. This finding should be considered in the context of using ECAP measures to assist with programming CIs.

Neural Substrates of the Topology Test to Measure Fluid Reasoning: An fMRI Study

ERIC Educational Resources Information Center

Masunaga, Hiromi; Kawashima, Ryuta; Horn, John L.; Sassa, Yuko; Sekiguchi, Atsushi

2008-01-01

In our prior study the negative correlation between Topology, a behavioral measure of fluid reasoning, and adult age diminished with the increase in the level of expertise in a cognitively-demanding domain of expertise in the game of GO. The present fMRI study was designed to investigate neural substrates of Topology. The modified topology…

Modeling constitutive behavior of a 15Cr-15Ni-2.2Mo-Ti modified austenitic stainless steel under hot compression using artificial neural network

NASA Astrophysics Data System (ADS)

Mandal, Sumantra

2006-11-01

ABSTRACT In this paper, an artificial neural network (ANN) model has been suggested to predict the constitutive flow behavior of a 15Cr-15Ni-2.2Mo-Ti modified austenitic stainless steel under hot deformation. Hot compression tests in the temperature range 850°C- 1250°C and strain rate range 10-3-102 s-1 were carried out. These tests provided the required data for training the neural network and for subsequent testing. The inputs of the neural network are strain, log strain rate and temperature while flow stress is obtained as output. A three layer feed-forward network with ten neurons in a single hidden layer and back-propagation learning algorithm has been employed. A very good correlation between experimental and predicted result has been obtained. The effect of temperature and strain rate on flow behavior has been simulated employing the ANN model. The results have been found to be consistent with the metallurgical trend. Finally, a monte carlo analiysis has been carried out to find out the noise sensitivity of the developed model.

Associative memory model with spontaneous neural activity

NASA Astrophysics Data System (ADS)

Kurikawa, Tomoki; Kaneko, Kunihiko

2012-05-01

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

Neural imaging in songbirds using fiber optic fluorescence microscopy

NASA Astrophysics Data System (ADS)

Nooshabadi, Fatemeh; Hearn, Gentry; Lints, Thierry; Maitland, Kristen C.

2012-02-01

The song control system of juvenile songbirds is an important model for studying the developmental acquisition and generation of complex learned vocal motor sequences, two processes that are fundamental to human speech and language. To understand the neural mechanisms underlying song production, it is critical to characterize the activity of identified neurons in the song control system when the bird is singing. Neural imaging in unrestrained singing birds, although technically challenging, will advance our understanding of neural ensemble coding mechanisms in this system. We are exploring the use of a fiber optic microscope for functional imaging in the brain of behaving and singing birds in order to better understand the contribution of a key brain nucleus (high vocal center nucleus; HVC) to temporal aspects of song motor control. We have constructed a fluorescence microscope with LED illumination, a fiber bundle for transmission of fluorescence excitation and emission light, a ~2x GRIN lens, and a CCD for image acquisition. The system has 2 μm resolution, 375 μm field of view, 200 μm working distance, and 1 mm outer diameter. As an initial characterization of this setup, neurons in HVC were imaged using the fiber optic microscope after injection of quantum dots or fluorescent retrograde tracers into different song nuclei. A Lucid Vivascope confocal microscope was used to confirm the imaging results. Long-term imaging of the activity of these neurons in juvenile birds during singing may lead us to a better understanding of the central motor codes for song and the central mechanism by which auditory experience modifies song motor commands to enable vocal learning and imitation.

New wideband radar target classification method based on neural learning and modified Euclidean metric

NASA Astrophysics Data System (ADS)

Jiang, Yicheng; Cheng, Ping; Ou, Yangkui

2001-09-01

A new method for target classification of high-range resolution radar is proposed. It tries to use neural learning to obtain invariant subclass features of training range profiles. A modified Euclidean metric based on the Box-Cox transformation technique is investigated for Nearest Neighbor target classification improvement. The classification experiments using real radar data of three different aircraft have demonstrated that classification error can reduce 8% if this method proposed in this paper is chosen instead of the conventional method. The results of this paper have shown that by choosing an optimized metric, it is indeed possible to reduce the classification error without increasing the number of samples.

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

PubMed

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

2016-05-01

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

Human bone marrow harbors cells with neural crest-associated characteristics like human adipose and dermis tissues

PubMed Central

Coste, Cécile; Neirinckx, Virginie; Sharma, Anil; Agirman, Gulistan; Rogister, Bernard; Foguenne, Jacques; Lallemend, François

2017-01-01

Adult neural crest stem-derived cells (NCSC) are of extraordinary high plasticity and promising candidates for use in regenerative medicine. Several locations such as skin, adipose tissue, dental pulp or bone marrow have been described in rodent, as sources of NCSC. However, very little information is available concerning their correspondence in human tissues, and more precisely for human bone marrow. The main objective of this study was therefore to characterize NCSC from adult human bone marrow. In this purpose, we compared human bone marrow stromal cells to human adipose tissue and dermis, already described for containing NCSC. We performed comparative analyses in terms of gene and protein expression as well as functional characterizations. It appeared that human bone marrow, similarly to adipose tissue and dermis, contains NESTIN+ / SOX9+ / TWIST+ / SLUG+ / P75NTR+ / BRN3A+/ MSI1+/ SNAIL1+ cells and were able to differentiate into melanocytes, Schwann cells and neurons. Moreover, when injected into chicken embryos, all those cells were able to migrate and follow endogenous neural crest migration pathways. Altogether, the phenotypic characterization and migration abilities strongly suggest the presence of neural crest-derived cells in human adult bone marrow. PMID:28683107

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

PubMed

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

2018-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Transplantation of neurons derived from human iPS cells cultured on collagen matrix into guinea-pig cochleae.

PubMed

Ishikawa, Masaaki; Ohnishi, Hiroe; Skerleva, Desislava; Sakamoto, Tatsunori; Yamamoto, Norio; Hotta, Akitsu; Ito, Juichi; Nakagawa, Takayuki

2017-06-01

The present study examined the efficacy of a neural induction method for human induced pluripotent stem (iPS) cells to eliminate undifferentiated cells and to determine the feasibility of transplanting neurally induced cells into guinea-pig cochleae for replacement of spiral ganglion neurons (SGNs). A stepwise method for differentiation of human iPS cells into neurons was used. First, a neural induction method was established on Matrigel-coated plates; characteristics of cell populations at each differentiation step were assessed. Second, neural stem cells were differentiated into neurons on a three-dimensional (3D) collagen matrix, using the same protocol of culture on Matrigel-coated plates; neuron subtypes in differentiated cells on a 3D collagen matrix were examined. Then, human iPS cell-derived neurons cultured on a 3D collagen matrix were transplanted into intact guinea-pig cochleae, followed by histological analysis. In vitro analyses revealed successful induction of neural stem cells from human iPS cells, with no retention of undifferentiated cells expressing OCT3/4. After the neural differentiation of neural stem cells, approximately 70% of cells expressed a neuronal marker, 90% of which were positive for vesicular glutamate transporter 1 (VGLUT1). The expression pattern of neuron subtypes in differentiated cells on a 3D collagen matrix was identical to that of the differentiated cells on Matrigel-coated plates. In addition, the survival of transplant-derived neurons was achieved when inflammatory responses were appropriately controlled. Our preparation method for human iPS cell-derived neurons efficiently eliminated undifferentiated cells and contributed to the settlement of transplant-derived neurons expressing VGLUT1 in guinea-pig cochleae. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Algorithm for predicting the evolution of series of dynamics of complex systems in solving information problems

NASA Astrophysics Data System (ADS)

Kasatkina, T. I.; Dushkin, A. V.; Pavlov, V. A.; Shatovkin, R. R.

2018-03-01

In the development of information, systems and programming to predict the series of dynamics, neural network methods have recently been applied. They are more flexible, in comparison with existing analogues and are capable of taking into account the nonlinearities of the series. In this paper, we propose a modified algorithm for predicting the series of dynamics, which includes a method for training neural networks, an approach to describing and presenting input data, based on the prediction by the multilayer perceptron method. To construct a neural network, the values of a series of dynamics at the extremum points and time values corresponding to them, formed based on the sliding window method, are used as input data. The proposed algorithm can act as an independent approach to predicting the series of dynamics, and be one of the parts of the forecasting system. The efficiency of predicting the evolution of the dynamics series for a short-term one-step and long-term multi-step forecast by the classical multilayer perceptron method and a modified algorithm using synthetic and real data is compared. The result of this modification was the minimization of the magnitude of the iterative error that arises from the previously predicted inputs to the inputs to the neural network, as well as the increase in the accuracy of the iterative prediction of the neural network.

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

PubMed

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

2017-07-01

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

Study of the neural dynamics for understanding communication in terms of complex hetero systems.

PubMed

Tsuda, Ichiro; Yamaguchi, Yoko; Hashimoto, Takashi; Okuda, Jiro; Kawasaki, Masahiro; Nagasaka, Yasuo

2015-01-01

The purpose of the research project was to establish a new research area named "neural information science for communication" by elucidating its neural mechanism. The research was performed in collaboration with applied mathematicians in complex-systems science and experimental researchers in neuroscience. The project included measurements of brain activity during communication with or without languages and analyses performed with the help of extended theories for dynamical systems and stochastic systems. The communication paradigm was extended to the interactions between human and human, human and animal, human and robot, human and materials, and even animal and animal. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Neural networks for vertical microcode compaction

NASA Astrophysics Data System (ADS)

Chu, Pong P.

1992-09-01

Neural networks provide an alternative way to solve complex optimization problems. Instead of performing a program of instructions sequentially as in a traditional computer, neural network model explores many competing hypotheses simultaneously using its massively parallel net. The paper shows how to use the neural network approach to perform vertical micro-code compaction for a micro-programmed control unit. The compaction procedure includes two basic steps. The first step determines the compatibility classes and the second step selects a minimal subset to cover the control signals. Since the selection process is an NP- complete problem, to find an optimal solution is impractical. In this study, we employ a customized neural network to obtain the minimal subset. We first formalize this problem, and then define an `energy function' and map it to a two-layer fully connected neural network. The modified network has two types of neurons and can always obtain a valid solution.

Biological characteristics of human-urine-derived stem cells: potential for cell-based therapy in neurology.

PubMed

Guan, Jun-Jie; Niu, Xin; Gong, Fei-Xiang; Hu, Bin; Guo, Shang-Chun; Lou, Yuan-Lei; Zhang, Chang-Qing; Deng, Zhi-Feng; Wang, Yang

2014-07-01

Stem cells in human urine have gained attention in recent years; however, urine-derived stem cells (USCs) are far from being well elucidated. In this study, we compared the biological characteristics of USCs with adipose-derived stem cells (ASCs) and investigated whether USCs could serve as a potential cell source for neural tissue engineering. USCs were isolated from voided urine with a modified culture medium. Through a series of experiments, we examined the growth rate, surface antigens, and differentiation potential of USCs, and compared them with ASCs. USCs showed robust proliferation ability. After serial propagation, USCs retained normal karyotypes. Cell surface antigen expression of USCs was similar to ASCs. With lineage-specific induction factors, USCs could differentiate toward the osteogenic, chondrogenic, adipogenic, and neurogenic lineages. To assess the ability of USCs to survive, differentiate, and migrate, they were seeded onto hydrogel scaffold and transplanted into rat brain. The results showed that USCs were able to survive in the lesion site, migrate to other areas, and express proteins that were associated with neural phenotypes. The results of our study demonstrate that USCs possess similar biological characteristics with ASCs and have multilineage differentiation potential. Moreover USCs can differentiate to neuron-like cells in rat brain. The present study shows that USCs are a promising cell source for tissue engineering and regenerative medicine.

Magnetically enhanced adeno-associated viral vector delivery for human neural stem cell infection.

PubMed

Kim, Eunmi; Oh, Ji-Seon; Ahn, Ik-Sung; Park, Kook In; Jang, Jae-Hyung

2011-11-01

Gene therapy technology is a powerful tool to elucidate the molecular cues that precisely regulate stem cell fates, but developing safe vehicles or mechanisms that are capable of delivering genes to stem cells with high efficiency remains a challenge. In this study, we developed a magnetically guided adeno-associated virus (AAV) delivery system for gene delivery to human neural stem cells (hNSCs). Magnetically guided AAV delivery resulted in rapid accumulation of vectors on target cells followed by forced penetration of the vectors across the plasma membrane, ultimately leading to fast and efficient cellular transduction. To combine AAV vectors with the magnetically guided delivery, AAV was genetically modified to display hexa-histidine (6xHis) on the physically exposed loop of the AAV2 capsid (6xHis AAV), which interacted with nickel ions chelated on NTA-biotin conjugated to streptavidin-coated superparamagnetic iron oxide nanoparticles (NiStNPs). NiStNP-mediated 6xHis AAV delivery under magnetic fields led to significantly enhanced cellular transduction in a non-permissive cell type (i.e., hNSCs). In addition, this delivery method reduced the viral exposure times required to induce a high level of transduction by as much as to 2-10 min of hNSC infection, thus demonstrating the great potential of magnetically guided AAV delivery for numerous gene therapy and stem cell applications. Copyright © 2011 Elsevier Ltd. All rights reserved.

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 ...

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

PubMed

Ho, Lin; Hsu, Shan-Hui

2018-04-01

3D bioprinting is a technique which enables the direct printing of biodegradable materials with cells into 3D tissue. So far there is no cell reprogramming in situ performed with the 3D bioprinting process. Forkhead box D3 (FoxD3) is a transcription factor and neural crest marker, which was reported to reprogram human fibroblasts into neural crest stem-like cells. In this study, we synthesized a new biodegradable thermo-responsive waterborne polyurethane (PU) gel as a bioink. FoxD3 plasmids and human fibroblasts were co-extruded with the PU hydrogel through the syringe needle tip for cell reprogramming. The rheological properties of the PU hydrogel including the modulus, gelation time, and shear thinning were optimized for the transfection effect of FoxD3 in situ. The corresponding shear rate and shear stress were examined. Results showed that human fibroblasts could be reprogrammed into neural crest stem-like cells with high cell viability during the extrusion process under an average shear stress ∼190 Pa. We further translated the method to the extrusion-based 3D bioprinting, and demonstrated that human fibroblasts co-printed with FoxD3 in the thermo-responsive PU hydrogel could be reprogrammed and differentiated into a neural-tissue like construct at 14 days after induction. The neural-like tissue construct produced by 3D bioprinting from human fibroblasts may be applied to personalized drug screening or neuroregeneration. There is no study so far on cell reprogramming in situ with 3D bioprinting. In this manuscript, a new thermoresponsive polyurethane bioink was developed and employed to deliver FoxD3 plasmid into human fibroblasts by the extrusion-based bioprinting. When the polyurethane gel was extruded through the syringe tip, the shear stress generated may have caused the transient membrane permeability for transfection. The shear stress was optimized for transfection in situ by 3D bioprinting. We demonstrated that human fibroblasts could be reprogrammed into neural crest-like stem cells by 3D bioprinting with the gel, and the reprogrammed cells underwent neural differentiation in the printed structure after induction. The neural-like tissue engineering constructs fabricated by 3D bioprinting from human fibroblasts may be applied for neuroregeneration or further developed as mini-brain for basic research and drug screening. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Hidden Markov models and neural networks for fault detection in dynamic systems

NASA Technical Reports Server (NTRS)

Smyth, Padhraic

1994-01-01

Neural networks plus hidden Markov models (HMM) can provide excellent detection and false alarm rate performance in fault detection applications, as shown in this viewgraph presentation. Modified models allow for novelty detection. Key contributions of neural network models are: (1) excellent nonparametric discrimination capability; (2) a good estimator of posterior state probabilities, even in high dimensions, and thus can be embedded within overall probabilistic model (HMM); and (3) simple to implement compared to other nonparametric models. Neural network/HMM monitoring model is currently being integrated with the new Deep Space Network (DSN) antenna controller software and will be on-line monitoring a new DSN 34-m antenna (DSS-24) by July, 1994.

Size and synchronization of auditory cortex promotes musical, literacy, and attentional skills in children.

PubMed

Seither-Preisler, Annemarie; Parncutt, Richard; Schneider, Peter

2014-08-13

Playing a musical instrument is associated with numerous neural processes that continuously modify the human brain and may facilitate characteristic auditory skills. In a longitudinal study, we investigated the auditory and neural plasticity of musical learning in 111 young children (aged 7-9 y) as a function of the intensity of instrumental practice and musical aptitude. Because of the frequent co-occurrence of central auditory processing disorders and attentional deficits, we also tested 21 children with attention deficit (hyperactivity) disorder [AD(H)D]. Magnetic resonance imaging and magnetoencephalography revealed enlarged Heschl's gyri and enhanced right-left hemispheric synchronization of the primary evoked response (P1) to harmonic complex sounds in children who spent more time practicing a musical instrument. The anatomical characteristics were positively correlated with frequency discrimination, reading, and spelling skills. Conversely, AD(H)D children showed reduced volumes of Heschl's gyri and enhanced volumes of the plana temporalia that were associated with a distinct bilateral P1 asynchrony. This may indicate a risk for central auditory processing disorders that are often associated with attentional and literacy problems. The longitudinal comparisons revealed a very high stability of auditory cortex morphology and gray matter volumes, suggesting that the combined anatomical and functional parameters are neural markers of musicality and attention deficits. Educational and clinical implications are considered. Copyright © 2014 the authors 0270-6474/14/3410937-13$15.00/0.

Using human brain activity to guide machine learning.

PubMed

Fong, Ruth C; Scheirer, Walter J; Cox, David D

2018-03-29

Machine learning is a field of computer science that builds algorithms that learn. In many cases, machine learning algorithms are used to recreate a human ability like adding a caption to a photo, driving a car, or playing a game. While the human brain has long served as a source of inspiration for machine learning, little effort has been made to directly use data collected from working brains as a guide for machine learning algorithms. Here we demonstrate a new paradigm of "neurally-weighted" machine learning, which takes fMRI measurements of human brain activity from subjects viewing images, and infuses these data into the training process of an object recognition learning algorithm to make it more consistent with the human brain. After training, these neurally-weighted classifiers are able to classify images without requiring any additional neural data. We show that our neural-weighting approach can lead to large performance gains when used with traditional machine vision features, as well as to significant improvements with already high-performing convolutional neural network features. The effectiveness of this approach points to a path forward for a new class of hybrid machine learning algorithms which take both inspiration and direct constraints from neuronal data.

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

PubMed

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

2018-05-21

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

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.

Notochord-derived Shh concentrates in close association with the apically positioned basal body in neural target cells and forms a dynamic gradient during neural patterning.

PubMed

Chamberlain, Chester E; Jeong, Juhee; Guo, Chaoshe; Allen, Benjamin L; McMahon, Andrew P

2008-03-01

Sonic hedgehog (Shh) ligand secreted by the notochord induces distinct ventral cell identities in the adjacent neural tube by a concentration-dependent mechanism. To study this process, we genetically engineered mice that produce bioactive, fluorescently labeled Shh from the endogenous locus. We show that Shh ligand concentrates in close association with the apically positioned basal body of neural target cells, forming a dynamic, punctate gradient in the ventral neural tube. Both ligand lipidation and target field response influence the gradient profile, but not the ability of Shh to concentrate around the basal body. Further, subcellular analysis suggests that Shh from the notochord might traffic into the neural target field by means of an apical-to-basal-oriented microtubule scaffold. This study, in which we directly observe, measure, localize and modify notochord-derived Shh ligand in the context of neural patterning, provides several new insights into mechanisms of Shh morphogen action.

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

PubMed

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

2018-04-01

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

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

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

Manceur, Aziza P.; Donnelly Centre, University of Toronto, Toronto, Ontario; Tseng, Michael

2011-09-10

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

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…

Attention selectively modifies the representation of individual faces in the human brain

PubMed Central

Gratton, Caterina; Sreenivasan, Kartik K.; Silver, Michael A.; D’Esposito, Mark

2013-01-01

Attention modifies neural tuning for low-level features, but it is unclear how attention influences tuning for complex stimuli. We investigated this question in humans using fMRI and face stimuli. Participants were shown six faces (F1-F6) along a morph continuum, and selectivity was quantified by constructing tuning curves for individual voxels. Face-selective voxels exhibited greater responses to their preferred face than to non-preferred faces, particularly in posterior face areas. Anterior face areas instead displayed tuning for face categories: voxels in these areas preferred either the first (F1-F3) or second (F4-F6) half of the morph continuum. Next, we examined the effects of attention on voxel tuning by having subjects direct attention to one of the superimposed images of F1 and F6. We found that attention selectively enhanced responses in voxels preferring the attended face. Taken together, our results demonstrate that single voxels carry information about individual faces and that the nature of this information varies across cortical face areas. Additionally, we found that attention selectively enhances these representations. Our findings suggest that attention may act via a unitary principle of selective enhancement of responses to both simple and complex stimuli across multiple stages of the visual hierarchy. PMID:23595755

Neural signature of reward-modulated unconscious inhibitory control.

PubMed

Diao, Liuting; Qi, Senqing; Xu, Mengsi; Li, Zhiai; Ding, Cody; Chen, Antao; Zheng, Yan; Yang, Dong

2016-09-01

Consciously initiated cognitive control is generally determined by motivational incentives (e.g., monetary reward). Recent studies have revealed that human cognitive control processes can nevertheless operate without awareness. However, whether monetary reward can impinge on unconscious cognitive control remains unclear. To clarify this issue, a task consisting of several runs was designed to combine a modified version of the reward-priming paradigm with an unconscious version of the Go/No-Go task. At the beginning of each run, participants were exposed to a high- or low-value coin, followed by the modified Go/No-Go task. Participants could earn the coin only if they responded correctly to each trial of the run. Event-related potential (ERP) results indicated that high-value rewards (vs. low-value rewards) induced a greater centro-parietal P3 component associated with conscious and unconscious inhibitory control. Moreover, the P3 amplitude correlated positively with the magnitude of reaction time slowing reflecting the intensity of activation of unconscious inhibitory control in the brain. These findings suggest that high-value reward may facilitate human higher-order inhibitory processes that are independent of conscious awareness, which provides insights into the brain processes that underpin motivational modulation of cognitive control. Copyright © 2016 Elsevier B.V. All rights reserved.

Uniform neural tissue models produced on synthetic hydrogels using standard culture techniques.

PubMed

Barry, Christopher; Schmitz, Matthew T; Propson, Nicholas E; Hou, Zhonggang; Zhang, Jue; Nguyen, Bao K; Bolin, Jennifer M; Jiang, Peng; McIntosh, Brian E; Probasco, Mitchell D; Swanson, Scott; Stewart, Ron; Thomson, James A; Schwartz, Michael P; Murphy, William L

2017-11-01

The aim of the present study was to test sample reproducibility for model neural tissues formed on synthetic hydrogels. Human embryonic stem (ES) cell-derived precursor cells were cultured on synthetic poly(ethylene glycol) (PEG) hydrogels to promote differentiation and self-organization into model neural tissue constructs. Neural progenitor, vascular, and microglial precursor cells were combined on PEG hydrogels to mimic developmental timing, which produced multicomponent neural constructs with 3D neuronal and glial organization, organized vascular networks, and microglia with ramified morphologies. Spearman's rank correlation analysis of global gene expression profiles and a comparison of coefficient of variation for expressed genes demonstrated that replicate neural constructs were highly uniform to at least day 21 for samples from independent experiments. We also demonstrate that model neural tissues formed on PEG hydrogels using a simplified neural differentiation protocol correlated more strongly to in vivo brain development than samples cultured on tissue culture polystyrene surfaces alone. These results provide a proof-of-concept demonstration that 3D cellular models that mimic aspects of human brain development can be produced from human pluripotent stem cells with high sample uniformity between experiments by using standard culture techniques, cryopreserved cell stocks, and a synthetic extracellular matrix. Impact statement Pluripotent stem (PS) cells have been characterized by an inherent ability to self-organize into 3D "organoids" resembling stomach, intestine, liver, kidney, and brain tissues, offering a potentially powerful tool for modeling human development and disease. However, organoid formation must be quantitatively reproducible for applications such as drug and toxicity screening. Here, we report a strategy to produce uniform neural tissue constructs with reproducible global gene expression profiles for replicate samples from multiple experiments.

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

PubMed

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

2018-01-01

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

Covalent bonding of YIGSR and RGD to PEDOT/PSS/MWCNT-COOH composite material to improve the neural interface.

PubMed

Wang, Kun; Tang, Rong-Yu; Zhao, Xiao-Bo; Li, Jun-Jie; Lang, Yi-Ran; Jiang, Xiao-Xia; Sun, Hong-Ji; Lin, Qiu-Xia; Wang, Chang-Yong

2015-11-28

The development of coating materials for neural interfaces has been a pursued to improve the electrical, mechanical and biological performances. For these goals, a bioactive coating was developed in this work featuring a poly(3,4-ethylenedioxythiophene) (PEDOT)/carbon nanotube (CNT) composite and covalently bonded YIGSR and RGD. Its biological effect and electrical characteristics were assessed in vivo on microwire arrays (MWA). The coated electrodes exhibited a significantly higher charge storage capacity (CSC) and lower electrochemical impedance at 1 kHz which are desired to improve the stimulating and recording performances, respectively. Acute neural recording experiments revealed that coated MWA possess a higher signal/noise ratio capturing spikes undetected by uncoated electrodes. Moreover, coated MWA possessed more active sites and single units, and the noise floor of coated electrodes was lower than that of uncoated electrodes. There is little information in the literature concerning the chronic performance of bioactively modified neural interfaces in vivo. Therefore in this work, chronic in vivo tests were conducted and the PEDOT/PSS/MWCNT-polypeptide coated arrays exhibited excellent performances with the highest mean maximal amplitude from day 4 to day 12 during which the acute response severely compromised the performance of the electrodes. In brief, we developed a simple method of covalently bonding YIGSR and RGD to a PEDOT/PSS/MWCNT-COOH composite improving both the biocompatibility and electrical performance of the neural interface. Our findings suggest that YIGSR and RGD modified PEDOT/PSS/MWCNT is a promising bioactivated composite coating for neural recording and stimulating.

Metabotropic glutamate receptor 5 responses dictate differentiation of neural progenitors to NMDA-responsive cells in fragile X syndrome.

PubMed

Achuta, Venkat Swaroop; Grym, Heli; Putkonen, Noora; Louhivuori, Verna; Kärkkäinen, Virve; Koistinaho, Jari; Roybon, Laurent; Castrén, Maija L

2017-04-01

Disrupted metabotropic glutamate receptor 5 (mGluR5) signaling is implicated in many neuropsychiatric disorders, including autism spectrum disorder, found in fragile X syndrome (FXS). Here we report that intracellular calcium responses to the group I mGluR agonist (S)-3,5-dihydroxyphenylglycine (DHPG) are augmented, and calcium-dependent mGluR5-mediated mechanisms alter the differentiation of neural progenitors in neurospheres derived from human induced pluripotent FXS stem cells and the brains of mouse model of FXS. Treatment with the mGluR5 antagonist 2-methyl-6-(phenylethynyl)-pyridine (MPEP) prevents an abnormal clustering of DHPG-responsive cells that are responsive to activation of ionotropic receptors in mouse FXS neurospheres. MPEP also corrects morphological defects of differentiated cells and enhanced migration of neuron-like cells in mouse FXS neurospheres. Unlike in mouse neurospheres, MPEP increases the differentiation of DHPG-responsive radial glial cells as well as the subpopulation of cells responsive to both DHPG and activation of ionotropic receptors in human neurospheres. However, MPEP normalizes the FXS-specific increase in the differentiation of cells responsive only to N-methyl-d-aspartate (NMDA) present in human neurospheres. Exposure to MPEP prevents the accumulation of intermediate basal progenitors in embryonic FXS mouse brain suggesting that rescue effects of GluR5 antagonist are progenitor type-dependent and species-specific differences of basal progenitors may modify effects of MPEP on the cortical development. © 2016 Wiley Periodicals, Inc. Develop Neurobiol 77: 419-437, 2017. © 2016 Wiley Periodicals, Inc.

A human chemosignal modulates frontolimbic activity and connectivity in response to emotional stimuli.

PubMed

Hummer, Tom A; Phan, K Luan; Kern, David W; McClintock, Martha K

2017-01-01

Evidence suggests the putative human pheromone Δ4,16-androstadien-3-one (androstadienone), a natural component of human sweat, increases attention to emotional information when passively inhaled, even in minute amounts. However, the neural mechanisms underlying androstadienone's impact on the perception of emotional stimuli have not been clarified. To characterize how the compound modifies neural circuitry while attending to emotional information, 22 subjects (11 women) underwent two fMRI scanning sessions, one with an androstadienone solution and one with a carrier control solution alone on their upper lip. During each session, participants viewed blocks of emotionally positive, negative, or neutral images. The BOLD response to emotional images (relative to neutral images) was greater during exposure to androstadienone in right orbitofrontal and lateral prefrontal cortex, particularly during positive image blocks. Androstadienone did not impact the response to social images, compared to nonsocial images, and results were not related to participant sex or olfactory sensitivity. To examine how androstadienone influences effective connectivity of this network, a dynamic causal model was employed with primary visual cortex (V1), amygdala, prefrontal cortex, and orbitofrontal cortex on each side. These models indicated that emotional images increased the drive from V1 to the amygdala during the control session. With androstadienone present, this drive to amygdala was decreased specifically for positive images, which drove downstream increases in orbitofrontal and prefrontal activity. This evidence suggests that androstadienone may act as a chemical signal to increase attention to positively valenced information via modifications to amygdala connectivity. Copyright © 2016. Published by Elsevier Ltd.

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

PubMed

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

2017-06-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Generation of the Human Biped Stance by a Neural Controller Able to Compensate Neurological Time Delay

PubMed Central

Jiang, Ping; Chiba, Ryosuke; Takakusaki, Kaoru; Ota, Jun

2016-01-01

The development of a physiologically plausible computational model of a neural controller that can realize a human-like biped stance is important for a large number of potential applications, such as assisting device development and designing robotic control systems. In this paper, we develop a computational model of a neural controller that can maintain a musculoskeletal model in a standing position, while incorporating a 120-ms neurological time delay. Unlike previous studies that have used an inverted pendulum model, a musculoskeletal model with seven joints and 70 muscular-tendon actuators is adopted to represent the human anatomy. Our proposed neural controller is composed of both feed-forward and feedback controls. The feed-forward control corresponds to the constant activation input necessary for the musculoskeletal model to maintain a standing posture. This compensates for gravity and regulates stiffness. The developed neural controller model can replicate two salient features of the human biped stance: (1) physiologically plausible muscle activations for quiet standing; and (2) selection of a low active stiffness for low energy consumption. PMID:27655271

Human high intelligence is involved in spectral redshift of biophotonic activities in the brain

PubMed Central

Wang, Niting; Li, Zehua; Xiao, Fangyan; Dai, Jiapei

2016-01-01

Human beings hold higher intelligence than other animals on Earth; however, it is still unclear which brain properties might explain the underlying mechanisms. The brain is a major energy-consuming organ compared with other organs. Neural signal communications and information processing in neural circuits play an important role in the realization of various neural functions, whereas improvement in cognitive function is driven by the need for more effective communication that requires less energy. Combining the ultraweak biophoton imaging system (UBIS) with the biophoton spectral analysis device (BSAD), we found that glutamate-induced biophotonic activities and transmission in the brain, which has recently been demonstrated as a novel neural signal communication mechanism, present a spectral redshift from animals (in order of bullfrog, mouse, chicken, pig, and monkey) to humans, even up to a near-infrared wavelength (∼865 nm) in the human brain. This brain property may be a key biophysical basis for explaining high intelligence in humans because biophoton spectral redshift could be a more economical and effective measure of biophotonic signal communications and information processing in the human brain. PMID:27432962

Solving differential equations with unknown constitutive relations as recurrent neural networks

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

Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.

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

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Detection of whale calls in noise: performance comparison between a beluga whale, human listeners, and a neural network.

PubMed

Erbe, C

2000-07-01

This article examines the masking by anthropogenic noise of beluga whale calls. Results from human masking experiments and a software backpropagation neural network are compared to the performance of a trained beluga whale. The goal was to find an accurate, reliable, and fast model to replace lengthy and expensive animal experiments. A beluga call was masked by three types of noise, an icebreaker's bubbler system and propeller noise, and ambient arctic ice-cracking noise. Both the human experiment and the neural network successfully modeled the beluga data in the sense that they classified the noises in the same order from strongest to weakest masking as the whale and with similar call-detection thresholds. The neural network slightly outperformed the humans. Both models were then used to predict the masking of a fourth type of noise, Gaussian white noise. Their prediction ability was judged by returning to the aquarium to measure masked-hearing thresholds of a beluga in white noise. Both models and the whale identified bubbler noise as the strongest masker, followed by ramming, then white noise. Natural ice-cracking noise masked the least. However, the humans and the neural network slightly overpredicted the amount of masking for white noise. This is neglecting individual variation in belugas, because only one animal could be trained. Comparing the human model to the neural network model, the latter has the advantage of objectivity, reproducibility of results, and efficiency, particularly if the interference of a large number of signals and noise is to be examined.

Differences and similarities between human and chimpanzee neural progenitors during cerebral cortex development

PubMed Central

Mora-Bermúdez, Felipe; Badsha, Farhath; Kanton, Sabina; Camp, J Gray; Vernot, Benjamin; Köhler, Kathrin; Voigt, Birger; Okita, Keisuke; Maricic, Tomislav; He, Zhisong; Lachmann, Robert; Pääbo, Svante; Treutlein, Barbara; Huttner, Wieland B

2016-01-01

Human neocortex expansion likely contributed to the remarkable cognitive abilities of humans. This expansion is thought to primarily reflect differences in proliferation versus differentiation of neural progenitors during cortical development. Here, we have searched for such differences by analysing cerebral organoids from human and chimpanzees using immunohistofluorescence, live imaging, and single-cell transcriptomics. We find that the cytoarchitecture, cell type composition, and neurogenic gene expression programs of humans and chimpanzees are remarkably similar. Notably, however, live imaging of apical progenitor mitosis uncovered a lengthening of prometaphase-metaphase in humans compared to chimpanzees that is specific to proliferating progenitors and not observed in non-neural cells. Consistent with this, the small set of genes more highly expressed in human apical progenitors points to increased proliferative capacity, and the proportion of neurogenic basal progenitors is lower in humans. These subtle differences in cortical progenitors between humans and chimpanzees may have consequences for human neocortex evolution. DOI: http://dx.doi.org/10.7554/eLife.18683.001 PMID:27669147

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.

IR wireless cluster synapses of HYDRA very large neural networks

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Forrester, Thomas

2008-04-01

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

Early driver fatigue detection from electroencephalography signals using artificial neural networks.

PubMed

King, L M; Nguyen, H T; Lal, S K L

2006-01-01

This paper describes a driver fatigue detection system using an artificial neural network (ANN). Using electroencephalogram (EEG) data sampled from 20 professional truck drivers and 35 non professional drivers, the time domain data are processed into alpha, beta, delta and theta bands and then presented to the neural network to detect the onset of driver fatigue. The neural network uses a training optimization technique called the magnified gradient function (MGF). This technique reduces the time required for training by modifying the standard back propagation (SBP) algorithm. The MGF is shown to classify professional driver fatigue with 81.49% accuracy (80.53% sensitivity, 82.44% specificity) and non-professional driver fatigue with 83.06% accuracy (84.04% sensitivity and 82.08% specificity).

Expansion and differentiation of neural progenitors derived from the human adult enteric nervous system.

PubMed

Metzger, Marco; Bareiss, Petra M; Danker, Timm; Wagner, Silvia; Hennenlotter, Joerg; Guenther, Elke; Obermayr, Florian; Stenzl, Arnulf; Koenigsrainer, Alfred; Skutella, Thomas; Just, Lothar

2009-12-01

Neural stem and progenitor cells from the enteric nervous system have been proposed for use in cell-based therapies against specific neurogastrointestinal disorders. Recently, enteric neural progenitors were generated from human neonatal and early postnatal (until 5 years after birth) gastrointestinal tract tissues. We investigated the proliferation and differentiation of enteric nervous system progenitors isolated from human adult gastrointestinal tract. Human enteric spheroids were generated from adult small and large intestine tissues and then expanded and differentiated, depending on the applied cell culture conditions. For implantation studies, spheres were grafted into fetal slice cultures and embryonic aganglionic hindgut explants from mice. Differentiating enteric neural progenitors were characterized by 5-bromo-2-deoxyuridine labeling, in situ hybridization, immunocytochemistry, quantitative real-time polymerase chain reaction, and electrophysiological studies. The yield of human neurosphere-like bodies was increased by culture in conditional medium derived from fetal mouse enteric progenitors. We were able to generate proliferating enterospheres from adult human small or large intestine tissues; these enterospheres could be subcultured and maintained for several weeks in vitro. Spheroid-derived cells could be differentiated into a variety of neuronal subtypes and glial cells with characteristics of the enteric nervous system. Experiments involving implantation into organotypic intestinal cultures showed the differentiation capacity of neural progenitors in a 3-dimensional environment. It is feasible to isolate and expand enteric progenitor cells from human adult tissue. These findings offer new strategies for enteric stem cell research and future cell-based therapies.

Human brain networks function in connectome-specific harmonic waves.

PubMed

Atasoy, Selen; Donnelly, Isaac; Pearson, Joel

2016-01-21

A key characteristic of human brain activity is coherent, spatially distributed oscillations forming behaviour-dependent brain networks. However, a fundamental principle underlying these networks remains unknown. Here we report that functional networks of the human brain are predicted by harmonic patterns, ubiquitous throughout nature, steered by the anatomy of the human cerebral cortex, the human connectome. We introduce a new technique extending the Fourier basis to the human connectome. In this new frequency-specific representation of cortical activity, that we call 'connectome harmonics', oscillatory networks of the human brain at rest match harmonic wave patterns of certain frequencies. We demonstrate a neural mechanism behind the self-organization of connectome harmonics with a continuous neural field model of excitatory-inhibitory interactions on the connectome. Remarkably, the critical relation between the neural field patterns and the delicate excitation-inhibition balance fits the neurophysiological changes observed during the loss and recovery of consciousness.

Human Neural Cell-Based Biosensor

DTIC Science & Technology

2013-05-28

ionotropic receptors in human embryonic stem cell derived neural progenitors. Neuroscience. 2011 Sep 29;192:793-805. Krishnamoorthy M, Gerwe BA, Scharer...coupled receptors . Pharmacol Ther. 2011 Mar;129(3):290-306. Workshop/conference abstracts, presentations, posters, and papers Powe, A, et al

L-Dopa decarboxylase expression profile in human cancer cells.

PubMed

Chalatsa, Ioanna; Nikolouzou, Eleftheria; Fragoulis, Emmanuel G; Vassilacopoulou, Dido

2011-02-01

L-Dopa decarboxylase (DDC) catalyses the decarboxylation of L-Dopa. It has been shown that the DDC gene undergoes alternative splicing within its 5'-untranslated region (UTR), in a tissue-specific manner, generating identical protein products. The employment of two alternative 5'UTRs is thought to be responsible for tissue-specific expression of the human DDC mRNA. In this study, we focused on the investigation of the nature of the mRNA expression in human cell lines of neural and non-neural origin. Our results show the expression of a neural-type DDC mRNA splice variant, lacking exon 3 in all cell lines studied. Co-expression of the full length non-neural DDC mRNA and the neural-type DDC splice variant lacking exon 3 was detected in all cell lines. The alternative DDC protein isoform, Alt-DDC, was detected in SH-SY5Y and HeLa cells. Our findings suggest that the human DDC gene undergoes complex processing, leading to the formation of multiple mRNA isoforms. The study of the significance of this phenomenon of multiple DDC mRNA isoforms could provide us with new information leading to the elucidation of the complex biological pathways that the human enzyme is involved in.

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

PubMed Central

Kwong, C. K.; Fung, K. Y.; Jiang, Huimin; Chan, K. Y.

2013-01-01

Affective design is an important aspect of product development to achieve a competitive edge in the marketplace. A neural-fuzzy network approach has been attempted recently to model customer satisfaction for affective design and it has been proved to be an effective one to deal with the fuzziness and non-linearity of the modeling as well as generate explicit customer satisfaction models. However, such an approach to modeling customer satisfaction has two limitations. First, it is not suitable for the modeling problems which involve a large number of inputs. Second, it cannot adapt to new data sets, given that its structure is fixed once it has been developed. In this paper, a modified dynamic evolving neural-fuzzy approach is proposed to address the above mentioned limitations. A case study on the affective design of mobile phones was conducted to illustrate the effectiveness of the proposed methodology. Validation tests were conducted and the test results indicated that: (1) the conventional Adaptive Neuro-Fuzzy Inference System (ANFIS) failed to run due to a large number of inputs; (2) the proposed dynamic neural-fuzzy model outperforms the subtractive clustering-based ANFIS model and fuzzy c-means clustering-based ANFIS model in terms of their modeling accuracy and computational effort. PMID:24385884

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

PubMed

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

2013-01-01

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

SMAD7 directly converts human embryonic stem cells to telencephalic fate by a default mechanism

PubMed Central

Ozair, Mohammad Zeeshan; Noggle, Scott; Warmflash, Aryeh; Krzyspiak, Joanna Ela; Brivanlou, Ali H.

2013-01-01

Human embryonic stem cells (hESCs) provide a valuable window into the dissection of the molecular circuitry underlying the early formation of the human forebrain. However, dissection of signaling events in forebrain development using current protocols is complicated by non-neural contamination and fluctuation of extrinsic influences. Here we show that SMAD7, a cell-intrinsic inhibitor of TGFβ signaling, is sufficient to directly convert pluripotent hESCs to an anterior neural fate. Time-course gene expression revealed down-regulation of MAPK components, and combining MEK1/2 inhibition with SMAD7-mediated TGFβ inhibition promoted telencephalic conversion. FGF-MEK and TGFβ-SMAD signaling maintain hESCs by promoting pluripotency genes and repressing neural genes. Our findings suggest that in the absence of these cues, pluripotent cells simply revert to a program of neural conversion. Hence the “primed” state of hESCs requires inhibition of the “default” state of neural fate acquisition. This has parallels in amphibians, suggesting an evolutionarily conserved mechanism. PMID:23034881

Evolutionary Construction of Block-Based Neural Networks in Consideration of Failure

NASA Astrophysics Data System (ADS)

Takamori, Masahito; Koakutsu, Seiichi; Hamagami, Tomoki; Hirata, Hironori

In this paper we propose a modified gene coding and an evolutionary construction in consideration of failure in evolutionary construction of Block-Based Neural Networks. In the modified gene coding, we arrange the genes of weights on a chromosome in consideration of the position relation of the genes of weight and structure. By the modified gene coding, the efficiency of search by crossover is increased. Thereby, it is thought that improvement of the convergence rate of construction and shortening of construction time can be performed. In the evolutionary construction in consideration of failure, the structure which is adapted for failure is built in the state where failure occured. Thereby, it is thought that BBNN can be reconstructed in a short time at the time of failure. To evaluate the proposed method, we apply it to pattern classification and autonomous mobile robot control problems. The computational experiments indicate that the proposed method can improve convergence rate of construction and shorten of construction and reconstruction time.

Vitamin D and ferritin correlation with chronic neck pain using standard statistics and a novel artificial neural network prediction model.

PubMed

Eloqayli, Haytham; Al-Yousef, Ali; Jaradat, Raid

2018-02-15

Despite the high prevalence of chronic neck pain, there is limited consensus about the primary etiology, risk factors, diagnostic criteria and therapeutic outcome. Here, we aimed to determine if Ferritin and Vitamin D are modifiable risk factors with chronic neck pain using slandered statistics and artificial intelligence neural network (ANN). Fifty-four patients with chronic neck pain treated between February 2016 and August 2016 in King Abdullah University Hospital and 54 patients age matched controls undergoing outpatient or minor procedures were enrolled. Patients and control demographic parameters, height, weight and single measurement of serum vitamin D, Vitamin B12, ferritin, calcium, phosphorus, zinc were obtained. An ANN prediction model was developed. The statistical analysis reveals that patients with chronic neck pain have significantly lower serum Vitamin D and Ferritin (p-value <.05). 90% of patients with chronic neck pain were females. Multilayer Feed Forward Neural Network with Back Propagation(MFFNN) prediction model were developed and designed based on vitamin D and ferritin as input variables and CNP as output. The ANN model output results show that, 92 out of 108 samples were correctly classified with 85% classification accuracy. Although Iron and vitamin D deficiency cannot be isolated as the sole risk factors of chronic neck pain, they should be considered as two modifiable risk. The high prevalence of chronic neck pain, hypovitaminosis D and low ferritin amongst women is of concern. Bioinformatics predictions with artificial neural network can be of future benefit in classification and prediction models for chronic neck pain. We hope this initial work will encourage a future larger cohort study addressing vitamin D and iron correction as modifiable factors and the application of artificial intelligence models in clinical practice.

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode.

PubMed

Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Kim, Hyungmin; Youn, Inchan

2017-12-21

Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time.

An Implantable Wireless Neural Interface System for Simultaneous Recording and Stimulation of Peripheral Nerve with a Single Cuff Electrode

PubMed Central

Shon, Ahnsei; Chu, Jun-Uk; Jung, Jiuk; Youn, Inchan

2017-01-01

Recently, implantable devices have become widely used in neural prostheses because they eliminate endemic drawbacks of conventional percutaneous neural interface systems. However, there are still several issues to be considered: low-efficiency wireless power transmission; wireless data communication over restricted operating distance with high power consumption; and limited functionality, working either as a neural signal recorder or as a stimulator. To overcome these issues, we suggest a novel implantable wireless neural interface system for simultaneous neural signal recording and stimulation using a single cuff electrode. By using widely available commercial off-the-shelf (COTS) components, an easily reconfigurable implantable wireless neural interface system was implemented into one compact module. The implantable device includes a wireless power consortium (WPC)-compliant power transmission circuit, a medical implant communication service (MICS)-band-based radio link and a cuff-electrode path controller for simultaneous neural signal recording and stimulation. During in vivo experiments with rabbit models, the implantable device successfully recorded and stimulated the tibial and peroneal nerves while communicating with the external device. The proposed system can be modified for various implantable medical devices, especially such as closed-loop control based implantable neural prostheses requiring neural signal recording and stimulation at the same time. PMID:29267230

Exfoliated Human Olfactory Neuroepithelium: A Source of Neural Progenitor Cells.

PubMed

Jiménez-Vaca, Ana L; Benitez-King, Gloria; Ruiz, Víctor; Ramírez-Rodríguez, Gerardo B; Hernández-de la Cruz, Beatriz; Salamanca-Gómez, Fabio A; González-Márquez, Humberto; Ramírez-Sánchez, Israel; Ortíz-López, Leonardo; Vélez-Del Valle, Cristina; Ordoñez-Razo, Rosa Ma

2018-03-01

Neural progenitor cells (NPC) contained in the human adult olfactory neuroepithelium (ONE) possess an undifferentiated state, the capability of self-renewal, the ability to generate neural and glial cells as well as being kept as neurospheres in cell culture conditions. Recently, NPC have been isolated from human or animal models using high-risk surgical methods. Therefore, it was necessary to improve methodologies to obtain and maintain human NPC as well as to achieve better knowledge of brain disorders. In this study, we propose the establishment and characterization of NPC cultures derived from the human olfactory neuroepithelium, using non-invasive procedures. Twenty-two healthy individuals (29.7 ± 4.5 years of age) were subjected to nasal exfoliation. Cells were recovered and kept as neurospheres under serum-free conditions. The neural progenitor origin of these neurospheres was determined by immunocytochemistry and qPCR. Their ability for self-renewal and multipotency was analyzed by clonogenic and differentiation assays, respectively. In the cultures, the ONE cells preserved the phenotype of the neurospheres. The expression levels of Nestin, Musashi, Sox2, and βIII-tubulin demonstrated the neural origin of the neurospheres; 48% of the cells separated could generate neurospheres, determining that they retained their self-renewal capacity. Neurospheres were differentiated in the absence of growth factors (EGF and FGF), and their multipotency ability was maintained as well. We were also able to isolate and grow human neural progenitor cells (neurospheres) through nasal exfoliates (non-invasive method) of the ONE from healthy adults, which is an extremely important contribution for the study of brain disorders and for the development of new therapies.

EZ spheres: a stable and expandable culture system for the generation of pre-rosette multipotent stem cells from human ESCs and iPSCs.

PubMed

Ebert, Allison D; Shelley, Brandon C; Hurley, Amanda M; Onorati, Marco; Castiglioni, Valentina; Patitucci, Teresa N; Svendsen, Soshana P; Mattis, Virginia B; McGivern, Jered V; Schwab, Andrew J; Sareen, Dhruv; Kim, Ho Won; Cattaneo, Elena; Svendsen, Clive N

2013-05-01

We have developed a simple method to generate and expand multipotent, self-renewing pre-rosette neural stem cells from both human embryonic stem cells (hESCs) and human induced pluripotent stem cells (iPSCs) without utilizing embryoid body formation, manual selection techniques, or complex combinations of small molecules. Human ESC and iPSC colonies were lifted and placed in a neural stem cell medium containing high concentrations of EGF and FGF-2. Cell aggregates (termed EZ spheres) could be expanded for long periods using a chopping method that maintained cell-cell contact. Early passage EZ spheres rapidly down-regulated OCT4 and up-regulated SOX2 and nestin expression. They retained the potential to form neural rosettes and consistently differentiated into a range of central and peripheral neural lineages. Thus, they represent a very early neural stem cell with greater differentiation flexibility than other previously described methods. As such, they will be useful for the rapidly expanding field of neurological development and disease modeling, high-content screening, and regenerative therapies based on pluripotent stem cell technology. Copyright © 2013 Elsevier B.V. All rights reserved.

Analysis of electromyographic activity in spastic biceps brachii muscle following neural mobilization.

PubMed

Castilho, Jéssica; Ferreira, Luiz Alfredo Braun; Pereira, Wagner Menna; Neto, Hugo Pasini; Morelli, José Geraldo da Silva; Brandalize, Danielle; Kerppers, Ivo Ilvan; Oliveira, Claudia Santos

2012-07-01

Hypertonia is prevalent in anti-gravity muscles, such as the biceps brachii. Neural mobilization is one of the techniques currently used to reduce spasticity. The aim of the present study was to assess electromyographic (EMG) activity in spastic biceps brachii muscles before and after neural mobilization of the upper limb contralateral to the hemiplegia. Repeated pre-test and post-test EMG measurements were performed on six stroke victims with grade 1 or 2 spasticity (Modified Ashworth Scale). The Upper Limb Neurodynamic Test (ULNT1) was the mobilization technique employed. After neural mobilization contralateral to the lesion, electromyographic activity in the biceps brachii decreased by 17% and 11% for 90° flexion and complete extension of the elbow, respectively. However, the results were not statistically significant (p gt; 0.05). When performed using contralateral techniques, neural mobilization alters the electrical signal of spastic muscles. Copyright © 2011 Elsevier Ltd. All rights reserved.

Classification of Company Performance using Weighted Probabilistic Neural Network

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

The precuneus may encode irrationality in human gambling.

PubMed

Sacre, P; Kerr, M S D; Subramanian, S; Kahn, K; Gonzalez-Martinez, J; Johnson, M A; Sarma, S V; Gale, J T

2016-08-01

Humans often make irrational decisions, especially psychiatric patients who have dysfunctional cognitive and emotional circuitry. Understanding the neural basis of decision-making is therefore essential towards patient management, yet current studies suffer from several limitations. Functional magnetic resonance imaging (fMRI) studies in humans have dominated decision-making neuroscience, but have poor temporal resolution and the blood oxygenation level-dependent signal is only a proxy for neural activity. On the other hand, lesion studies in humans used to infer functionality in decision-making lack characterization of neural activity altogether. Using a combination of local field potential recordings in human subjects performing a financial decision-making task, spectral analyses, and non-parametric cluster statistics, we analyzed the activity in the precuneus. In nine subjects, the neural activity modulated significantly between rational and irrational trials in the precuneus (p <; 0.001). In particular, high-frequency activity (70-100 Hz) increased when irrational decisions were made. Although preliminary, these results suggest suppression of gamma rhythms via electrical stimulation in the precuneus as a therapeutic intervention for pathological decision-making.

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.

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

PubMed

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

2015-06-01

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

Molecular stages of rapid and uniform neuralization of human embryonic stem cells.

PubMed

Bajpai, R; Coppola, G; Kaul, M; Talantova, M; Cimadamore, F; Nilbratt, M; Geschwind, D H; Lipton, S A; Terskikh, A V

2009-06-01

Insights into early human development are fundamental for our understanding of human biology. Efficient differentiation of human embryonic stem cells (hESCs) into neural precursor cells is critical for future cell-based therapies. Here, using defined conditions, we characterized a new method for rapid and uniform differentiation of hESCs into committed neural precursor cells (designated C-NPCs). Dynamic gene expression analysis identified several distinct stages of ESC neuralization and revealed functional modules of coregulated genes and pathways. The first wave of gene expression changes, likely corresponding to the transition through primitive ectoderm, started at day 3, preceding the formation of columnar neuroepithelial rosettes. The second wave started at day 5, coinciding with the formation of rosettes. The majority of C-NPCs were positive for both anterior and posterior markers of developing neuroepithelium. In culture, C-NPCs became electrophysiologically functional neurons; on transplantation into neonatal mouse brains, C-NPCs integrated into the cortex and olfactory bulb, acquiring appropriate neuronal morphologies and markers. Compared to rosette-NPCs,(1) C-NPCs exhibited limited in vitro expansion capacity and did not express potent oncogenes such as PLAG1 or RSPO3. Concordantly, we never detected tumors or excessive neural proliferation after transplantation of C-NPCs into mouse brains. In conclusion, our study provides a framework for future analysis of molecular signaling during ESC neuralization.

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 of Open Brain Simulator for Human Biomechatronics

NASA Astrophysics Data System (ADS)

Otake, Mihoko; Takagi, Toshihisa; Asama, Hajime

Modeling and simulation based on mechanisms is important in order to design and control mechatronic systems. In particular, in-depth understanding and realistic modeling of biological systems is indispensable for biomechatronics. This paper presents open brain simulator, which estimates the neural state of human through external measurement for the purpose of improving motor and social skills. Macroscopic anatomical nervous systems model was built which can be connected to the musculoskeletal model. Microscopic anatomical and physiological neural models were interfaced to the macroscopic model. Neural activities of somatosensory area and Purkinje cell were calculated from motion capture data. The simulator provides technical infrastructure for human biomechatronics, which is promising for the novel diagnosis of neurological disorders and their treatments through medication and movement therapy, and for motor learning support system supporting acquisition of motor skill considering neural mechanism.

Characterization of Human Neural Progenitor Cell Models for Developmental Neurotoxicity Screening

EPA Science Inventory

Current testing methods for developmental neurotoxicity (DNT) make evaluation of the effects of large numbers of chemicals impractical and prohibitively expensive. As such, we are evaluating two different human neural progenitor cell (hNPC) models for their utility in screens for...

The psychosis-like effects of Δ(9)-tetrahydrocannabinol are associated with increased cortical noise in healthy humans.

PubMed

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

2015-12-01

Drugs that induce psychosis may do so by increasing the level of task-irrelevant random neural activity or neural noise. Increased levels of neural noise have been demonstrated in psychotic disorders. We tested the hypothesis that neural noise could also be involved in the psychotomimetic effects of delta-9-tetrahydrocannabinol (Δ(9)-THC), the principal active constituent of cannabis. Neural noise was indexed by measuring the level of randomness in the electroencephalogram during the prestimulus baseline period of an oddball task using Lempel-Ziv complexity, a nonlinear measure of signal randomness. The acute, dose-related effects of Δ(9)-THC on Lempel-Ziv complexity and signal power were studied in humans (n = 24) who completed 3 test days during which they received intravenous Δ(9)-THC (placebo, .015 and .03 mg/kg) in a double-blind, randomized, crossover, and counterbalanced design. Δ(9)-THC increased neural noise in a dose-related manner. Furthermore, there was a strong positive relationship between neural noise and the psychosis-like positive and disorganization symptoms induced by Δ(9)-THC, which was independent of total signal power. Instead, there was no relationship between noise and negative-like symptoms. In addition, Δ(9)-THC reduced total signal power during both active drug conditions compared with placebo, but no relationship was detected between signal power and psychosis-like symptoms. At doses that produced psychosis-like effects, Δ(9)-THC increased neural noise in humans in a dose-dependent manner. Furthermore, increases in neural noise were related with increases in Δ(9)-THC-induced psychosis-like symptoms but not negative-like symptoms. These findings suggest that increases in neural noise may contribute to the psychotomimetic effects of Δ(9)-THC. Published by Elsevier Inc.

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.

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

PubMed

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

2018-03-01

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

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

Video-based convolutional neural networks for activity recognition from robot-centric videos

NASA Astrophysics Data System (ADS)

Ryoo, M. S.; Matthies, Larry

2016-05-01

In this evaluation paper, we discuss convolutional neural network (CNN)-based approaches for human activity recognition. In particular, we investigate CNN architectures designed to capture temporal information in videos and their applications to the human activity recognition problem. There have been multiple previous works to use CNN-features for videos. These include CNNs using 3-D XYT convolutional filters, CNNs using pooling operations on top of per-frame image-based CNN descriptors, and recurrent neural networks to learn temporal changes in per-frame CNN descriptors. We experimentally compare some of these different representatives CNNs while using first-person human activity videos. We especially focus on videos from a robots viewpoint, captured during its operations and human-robot interactions.

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

NASA Technical Reports Server (NTRS)

Ross, Muriel D.

1991-01-01

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

Neural codes of seeing architectural styles

PubMed Central

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

2017-01-01

Images of iconic buildings, such as the CN Tower, instantly transport us to specific places, such as Toronto. Despite the substantial impact of architectural design on people’s visual experience of built environments, we know little about its neural representation in the human brain. In the present study, we have found patterns of neural activity associated with specific architectural styles in several high-level visual brain regions, but not in primary visual cortex (V1). This finding suggests that the neural correlates of the visual perception of architectural styles stem from style-specific complex visual structure beyond the simple features computed in V1. Surprisingly, the network of brain regions representing architectural styles included the fusiform face area (FFA) in addition to several scene-selective regions. Hierarchical clustering of error patterns further revealed that the FFA participated to a much larger extent in the neural encoding of architectural styles than entry-level scene categories. We conclude that the FFA is involved in fine-grained neural encoding of scenes at a subordinate-level, in our case, architectural styles of buildings. This study for the first time shows how the human visual system encodes visual aspects of architecture, one of the predominant and longest-lasting artefacts of human culture. PMID:28071765

Recurrent genomic instability of chromosome 1q in neural derivatives of human embryonic stem cells

PubMed Central

Varela, Christine; Denis, Jérôme Alexandre; Polentes, Jérôme; Feyeux, Maxime; Aubert, Sophie; Champon, Benoite; Piétu, Geneviève; Peschanski, Marc; Lefort, Nathalie

2012-01-01

Human pluripotent stem cells offer a limitless source of cells for regenerative medicine. Neural derivatives of human embryonic stem cells (hESCs) are currently being used for cell therapy in 3 clinical trials. However, hESCs are prone to genomic instability, which could limit their clinical utility. Here, we report that neural differentiation of hESCs systematically produced a neural stem cell population that could be propagated for more than 50 passages without entering senescence; this was true for all 6 hESC lines tested. The apparent spontaneous loss of evolution toward normal senescence of somatic cells was associated with a jumping translocation of chromosome 1q. This chromosomal defect has previously been associated with hematologic malignancies and pediatric brain tumors with poor clinical outcome. Neural stem cells carrying the 1q defect implanted into the brains of rats failed to integrate and expand, whereas normal cells engrafted. Our results call for additional quality controls to be implemented to ensure genomic integrity not only of undifferentiated pluripotent stem cells, but also of hESC derivatives that form cell therapy end products, particularly neural lines. PMID:22269325

Neural codes of seeing architectural styles.

PubMed

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

2017-01-10

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

An Implantable Wireless Neural Interface for Recording Cortical Circuit Dynamics in Moving Primates

PubMed Central

Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

2013-01-01

Objective Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims, and those living with severe neuromotor disease. Such systems must be chronically safe, durable, and effective. Approach We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous, and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based MEA via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1Hz to 7.8kHz, ×200 gain) and multiplexed by a custom application specific integrated circuit, digitized, and then packaged for transmission. The neural data (24 Mbps) was transmitted by a wireless data link carried on an frequency shift key modulated signal at 3.2GHz and 3.8GHz to a receiver 1 meter away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7-hour continuous operation between recharge via an inductive transcutaneous wireless power link at 2MHz. Main results Device verification and early validation was performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight on how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of neurological conditions, and will advance brain research. PMID:23428937

An implantable wireless neural interface for recording cortical circuit dynamics in moving primates

NASA Astrophysics Data System (ADS)

Borton, David A.; Yin, Ming; Aceros, Juan; Nurmikko, Arto

2013-04-01

Objective. Neural interface technology suitable for clinical translation has the potential to significantly impact the lives of amputees, spinal cord injury victims and those living with severe neuromotor disease. Such systems must be chronically safe, durable and effective. Approach. We have designed and implemented a neural interface microsystem, housed in a compact, subcutaneous and hermetically sealed titanium enclosure. The implanted device interfaces the brain with a 510k-approved, 100-element silicon-based microelectrode array via a custom hermetic feedthrough design. Full spectrum neural signals were amplified (0.1 Hz to 7.8 kHz, 200× gain) and multiplexed by a custom application specific integrated circuit, digitized and then packaged for transmission. The neural data (24 Mbps) were transmitted by a wireless data link carried on a frequency-shift-key-modulated signal at 3.2 and 3.8 GHz to a receiver 1 m away by design as a point-to-point communication link for human clinical use. The system was powered by an embedded medical grade rechargeable Li-ion battery for 7 h continuous operation between recharge via an inductive transcutaneous wireless power link at 2 MHz. Main results. Device verification and early validation were performed in both swine and non-human primate freely-moving animal models and showed that the wireless implant was electrically stable, effective in capturing and delivering broadband neural data, and safe for over one year of testing. In addition, we have used the multichannel data from these mobile animal models to demonstrate the ability to decode neural population dynamics associated with motor activity. Significance. We have developed an implanted wireless broadband neural recording device evaluated in non-human primate and swine. The use of this new implantable neural interface technology can provide insight into how to advance human neuroprostheses beyond the present early clinical trials. Further, such tools enable mobile patient use, have the potential for wider diagnosis of neurological conditions and will advance brain research.

Neural-network-based online HJB solution for optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems.

PubMed

Liu, Derong; Wang, Ding; Wang, Fei-Yue; Li, Hongliang; Yang, Xiong

2014-12-01

In this paper, the infinite horizon optimal robust guaranteed cost control of continuous-time uncertain nonlinear systems is investigated using neural-network-based online solution of Hamilton-Jacobi-Bellman (HJB) equation. By establishing an appropriate bounded function and defining a modified cost function, the optimal robust guaranteed cost control problem is transformed into an optimal control problem. It can be observed that the optimal cost function of the nominal system is nothing but the optimal guaranteed cost of the original uncertain system. A critic neural network is constructed to facilitate the solution of the modified HJB equation corresponding to the nominal system. More importantly, an additional stabilizing term is introduced for helping to verify the stability, which reinforces the updating process of the weight vector and reduces the requirement of an initial stabilizing control. The uniform ultimate boundedness of the closed-loop system is analyzed by using the Lyapunov approach as well. Two simulation examples are provided to verify the effectiveness of the present control approach.

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.

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

PubMed

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

2013-11-01

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

Rho/ROCK pathway is essential to the expansion, differentiation, and morphological rearrangements of human neural stem/progenitor cells induced by lysophosphatidic acid.

PubMed

Frisca, Frisca; Crombie, Duncan E; Dottori, Mirella; Goldshmit, Yona; Pébay, Alice

2013-05-01

We previously reported that lysophosphatidic acid (LPA) inhibits the neuronal differentiation of human embryonic stem cells (hESC). We extended these studies by analyzing LPA's effects on the expansion of neural stem/progenitor cells (NS/PC) derived from hESCs and human induced pluripotent stem cells (iPSC), and we assessed whether data obtained on the neural differentiation of hESCs were relevant to iPSCs. We showed that hESCs and iPSCs exhibited comparable mRNA expression profiles of LPA receptors and producing enzymes upon neural differentiation. We demonstrated that LPA inhibited the expansion of NS/PCs of both origins, mainly by increased apoptosis in a Rho/Rho-associated kinase (ROCK)-dependent mechanism. Furthermore, LPA inhibited the neuronal differentiation of iPSCs. Lastly, LPA induced neurite retraction of NS/PC-derived early neurons through Rho/ROCK, which was accompanied by myosin light chain (MLC) phosphorylation. Our data demonstrate the consistency of LPA effects across various sources of human NS/PCs, rendering hESCs and iPSCs valuable models for studying lysophospholipid signaling in human neural cells. Our data also highlight the importance of the Rho/ROCK pathway in human NS/PCs. As LPA levels are increased in the central nervous system (CNS) following injury, LPA-mediated effects on NS/PCs and early neurons could contribute to the poor neurogenesis observed in the CNS following injury.

The efficacy of using human myoelectric signals to control the limbs of robots in space

NASA Technical Reports Server (NTRS)

Clark, Jane E.; Phillips, Sally J.

1988-01-01

This project was designed to investigate the usefulness of the myoelectric signal as a control in robotics applications. More specifically, the neural patterns associated with human arm and hand actions were studied to determine the efficacy of using these myoelectric signals to control the manipulator arm of a robot. The advantage of this approach to robotic control was the use of well-defined and well-practiced neural patterns already available to the system, as opposed to requiring the human operator to learn new tasks and establish new neural patterns in learning to control a joystick or mechanical coupling device.

Development of on-line monitoring system for Nuclear Power Plant (NPP) using neuro-expert, noise analysis, and modified neural networks

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

Subekti, M.; Center for Development of Reactor Safety Technology, National Nuclear Energy Agency of Indonesia, Puspiptek Complex BO.80, Serpong-Tangerang, 15340; Ohno, T.

2006-07-01

The neuro-expert has been utilized in previous monitoring-system research of Pressure Water Reactor (PWR). The research improved the monitoring system by utilizing neuro-expert, conventional noise analysis and modified neural networks for capability extension. The parallel method applications required distributed architecture of computer-network for performing real-time tasks. The research aimed to improve the previous monitoring system, which could detect sensor degradation, and to perform the monitoring demonstration in High Temperature Engineering Tested Reactor (HTTR). The developing monitoring system based on some methods that have been tested using the data from online PWR simulator, as well as RSG-GAS (30 MW research reactormore » in Indonesia), will be applied in HTTR for more complex monitoring. (authors)« less

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

PubMed Central

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain–computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method. PMID:28558002

Maternal Folic Acid Supplementation during Pregnancy and Childhood Allergic Disease Outcomes: A Question of Timing?

PubMed Central

McStay, Catrina L.; Prescott, Susan L.; Bower, Carol; Palmer, Debra J.

2017-01-01

Since the early 1990s, maternal folic acid supplementation has been recommended prior to and during the first trimester of pregnancy, to reduce the risk of infant neural tube defects. In addition, many countries have also implemented the folic acid fortification of staple foods, in order to promote sufficient intakes amongst women of a childbearing age, based on concerns surrounding variable dietary and supplementation practices. As many women continue to take folic acid supplements beyond the recommended first trimester, there has been an overall increase in folate intakes, particularly in countries with mandatory fortification. This has raised questions on the consequences for the developing fetus, given that folic acid, a methyl donor, has the potential to epigenetically modify gene expression. In animal studies, folic acid has been shown to promote an allergic phenotype in the offspring, through changes in DNA methylation. Human population studies have also described associations between folate status in pregnancy and the risk of subsequent childhood allergic disease. In this review, we address the question of whether ongoing maternal folic acid supplementation after neural tube closure, could be contributing to the rise in early life allergic diseases. PMID:28208798

Structural and functional maturation of the developing primate brain.

PubMed

Levitt, Pat

2003-10-01

Descriptive studies have established that the developmental events responsible for the assembly of neural systems and circuitry are conserved across mammalian species. However, primates are unique regarding the time during which histogenesis occurs and the extended postnatal period during which myelination of pathways and circuitry formation occur and are then subsequently modified, particularly in the cerebral cortex. As in lower mammals, the framework for subcortical-cortical connectivity in primates is established before midgestation and already begins to remodel before birth. Association systems, responsible for modulating intracortical circuits that integrate information across functional domains, also form before birth, but their growth and reorganization extend into puberty. There are substantial differences across species in the patterns of development of specific neurochemical systems. The complexity is even greater when considering that the development of any particular cellular component may differ among cortical areas in the same primate species. Developmental and behavioral neurobiologists, psychologists, and pediatricians are challenged with understanding how functional maturation relates to the evolving anatomical organization of the human brain during childhood, and moreover, how genetic and environmental perturbations affect the adaptive changes exhibited by neural circuits in response to developmental disruption.

Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network.

PubMed

Zafar, Raheel; Kamel, Nidal; Naufal, Mohamad; Malik, Aamir Saeed; Dass, Sarat C; Ahmad, Rana Fayyaz; Abdullah, Jafri M; Reza, Faruque

2017-01-01

Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. Selection of significant features is an important part of fMRI data analysis, since it reduces the computational burden and improves the prediction performance; significant features are selected using t-test. MVPA uses machine learning algorithms to classify different brain states and helps in prediction during the task. General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. The proposed method showed better overall accuracy (68.6%) compared to ROI (61.88%) and estimation values (64.17%).

Brain Signal Variability is Parametrically Modifiable

PubMed Central

Garrett, Douglas D.; McIntosh, Anthony R.; Grady, Cheryl L.

2014-01-01

Moment-to-moment brain signal variability is a ubiquitous neural characteristic, yet remains poorly understood. Evidence indicates that heightened signal variability can index and aid efficient neural function, but it is not known whether signal variability responds to precise levels of environmental demand, or instead whether variability is relatively static. Using multivariate modeling of functional magnetic resonance imaging-based parametric face processing data, we show here that within-person signal variability level responds to incremental adjustments in task difficulty, in a manner entirely distinct from results produced by examining mean brain signals. Using mixed modeling, we also linked parametric modulations in signal variability with modulations in task performance. We found that difficulty-related reductions in signal variability predicted reduced accuracy and longer reaction times within-person; mean signal changes were not predictive. We further probed the various differences between signal variance and signal means by examining all voxels, subjects, and conditions; this analysis of over 2 million data points failed to reveal any notable relations between voxel variances and means. Our results suggest that brain signal variability provides a systematic task-driven signal of interest from which we can understand the dynamic function of the human brain, and in a way that mean signals cannot capture. PMID:23749875

Notch3 is necessary for neuronal differentiation and maturation in the adult spinal cord

PubMed Central

Rusanescu, Gabriel; Mao, Jianren

2014-01-01

Notch receptors are key regulators of nervous system development and promoters of neural stem cells renewal and proliferation. Defects in the expression of Notch genes result in severe, often lethal developmental abnormalities. Notch3 is generally thought to have a similar proliferative, anti-differentiation and gliogenic role to Notch1. However, in some cases, Notch3 has an opposite, pro-differentiation effect. Here, we show that Notch3 segregates from Notch1 and is transiently expressed in adult rat and mouse spinal cord neuron precursors and immature neurons. This suggests that during the differentiation of adult neural progenitor cells, Notch signalling may follow a modified version of the classical lateral inhibition model, involving the segregation of individual Notch receptors. Notch3 knockout mice, otherwise neurologically normal, are characterized by a reduced number of mature inhibitory interneurons and an increased number of highly excitable immature neurons in spinal cord laminae I–II. As a result, these mice have permanently lower nociceptive thresholds, similar to chronic pain. These results suggest that defective neuronal differentiation, for example as a result of reduced Notch3 expression or activation, may underlie human cases of intractable chronic pain, such as fibromyalgia and neuropathic pain. PMID:25164209

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

PubMed

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

2016-10-04

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

Resistance Training Enhances Skeletal Muscle Innervation Without Modifying the Number of Satellite Cells or their Myofiber Association in Obese Older Adults

PubMed Central

Messi, María Laura; Li, Tao; Wang, Zhong-Min; Marsh, Anthony P.; Nicklas, Barbara

2016-01-01

Studies in humans and animal models provide compelling evidence for age-related skeletal muscle denervation, which may contribute to muscle fiber atrophy and loss. Skeletal muscle denervation seems relentless; however, long-term, high-intensity physical activity appears to promote muscle reinnervation. Whether 5-month resistance training (RT) enhances skeletal muscle innervation in obese older adults is unknown. This study found that neural cell-adhesion molecule, NCAM+ muscle area decreased with RT and was inversely correlated with muscle strength. NCAM1 and RUNX1 gene transcripts significantly decreased with the intervention. Type I and type II fiber grouping in the vastus lateralis did not change significantly but increases in leg press and knee extensor strength inversely correlated with type I, but not with type II, fiber grouping. RT did not modify the total number of satellite cells, their number per area, or the number associated with specific fiber subtypes or innervated/denervated fibers. Our results suggest that RT has a beneficial impact on skeletal innervation, even when started late in life by sedentary obese older adults. PMID:26447161

Neural network face recognition using wavelets

NASA Astrophysics Data System (ADS)

Karunaratne, Passant V.; Jouny, Ismail I.

1997-04-01

The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neural networks and image processing. This research is involved in the study of neural networks and wavelet image processing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The image processing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.

Long-term hydrocephalus alters the cytoarchitecture of the adult subventricular zone

PubMed Central

Campos-Ordoñez, Tania; Herranz-Pérez, Vicente; Chaichana, Kaisorn L.; Rincon-Torroella, Jordina; Rigamonti, Daniele; García-Verdugo, Jose M.; Quiñones-Hinojosa, Alfredo; Gonzalez-Perez, Oscar

2014-01-01

Hydrocephalus can develop secondarily to a disturbance in production, flow and/or absorption of cerebrospinal fluid. Experimental models of hydrocephalus, especially subacute and chronic hydrocephalus, are few and limited, and the effects of hydrocephalus on the subventricular zone are unclear. The aim of this study was to analyze the effects of long-term obstructive hydrocephalus on the subventricular zone, which is the neurogenic niche lining the lateral ventricles. We developed a new method to induce hydrocephalus by obstructing the aqueduct of Sylvius in the mouse brain, thus simulating aqueductal stenosis in humans. In 120-day-old rodents (n = 18 per group), the degree of ventricular dilatation and cellular composition of the subventricular zone were studied by immunofluorescence and transmission electron microscopy. In adult patients (age > 18 years), the sizes of the subventricular zone, corpus callosum, and internal capsule were analyzed by magnetic resonance images obtained from patients with and without aqueductal stenosis (n=25 per group). Mice with 60-day hydrocephalus had a reduced number of Ki67+ and doublecortin+ cells on immunofluorescence, as well as decreased number of neural progenitors and neuroblasts in the subventricular zone on electron microscopy analysis as compared to non-hydrocephalic mice. Remarkably, a number of extracellular matrix structures (fractones) contacting the ventricular lumen and blood vessels were also observed around the subventricular zone in mice with hydrocephalus. In humans, the widths of the subventricular zone, corpus callosum, and internal capsule in patients with aqueductal stenosis were significantly smaller than age and gender-matched patients without aqueductal stenosis. In summary, supratentorial hydrocephalus reduces the proliferation rate of neural progenitors and modifies the cytoarchitecture and extracellular matrix compounds of the subventricular zone. In humans, this similar process reduces the subventricular niche as well as the width of corpus callosum and internal capsule. PMID:24858805

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

EPA Science Inventory

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

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.

Examining FKBP5 mRNA expression in human iPSC-derived neural cells

PubMed Central

Lieberman, Richard; Kranzler, Henry R.; Levine, Eric S.; Covault, Jonathan

2016-01-01

In peripheral blood leukocytes, FKBP5 mRNA expression is upregulated following glucocorticoid receptor activation. The single nucleotide polymorphism rs1360780 in FKBP5 is associated with psychiatric illness and has functional molecular effects. However, examination of FKBP5 regulation has largely been limited to peripheral cells, which may not reflect regulation in neural cells. We used 27 human induced pluripotent stem cell lines (iPSCs) derived from 20 subjects to examine FKBP5 mRNA expression following GR activation. Following differentiation into forebrain-lineage neural cultures, cells were exposed to 1μM dexamethasone and mRNA expression of FKBP5 and NR3C1 analyzed. Results from the iPSC-derived neural cells were compared with those from 15 donor matched fibroblast lines. Following dexamethasone treatment, there was a 670% increase in FKBP5 expression in fibroblasts, mimicking findings in peripheral blood-derived cells, but only a 23% increase in iPSC-derived neural cultures. FKBP5 rs1360780 genotype did not affect the induction of FKBP5 mRNA in either fibroblasts or neural cells. These results suggest that iPSC-derived forebrain-lineage neurons may not be an optimal neural cell type in which to examine relationships between GR activation, FKBP5 expression, and genetic variation in human subjects. Further, FKBP5 induction following GR activation may differ between cell types derived from the same individual. PMID:27915167

Distributed Neural Activity Patterns during Human-to-Human Competition

PubMed Central

Piva, Matthew; Zhang, Xian; Noah, J. Adam; Chang, Steve W. C.; Hirsch, Joy

2017-01-01

Interpersonal interaction is the essence of human social behavior. However, conventional neuroimaging techniques have tended to focus on social cognition in single individuals rather than on dyads or groups. As a result, relatively little is understood about the neural events that underlie face-to-face interaction. We resolved some of the technical obstacles inherent in studying interaction using a novel imaging modality and aimed to identify neural mechanisms engaged both within and across brains in an ecologically valid instance of interpersonal competition. Functional near-infrared spectroscopy was utilized to simultaneously measure hemodynamic signals representing neural activity in pairs of subjects playing poker against each other (human–human condition) or against computer opponents (human–computer condition). Previous fMRI findings concerning single subjects confirm that neural areas recruited during social cognition paradigms are individually sensitive to human–human and human–computer conditions. However, it is not known whether face-to-face interactions between opponents can extend these findings. We hypothesize distributed effects due to live processing and specific variations in across-brain coherence not observable in single-subject paradigms. Angular gyrus (AG), a component of the temporal-parietal junction (TPJ) previously found to be sensitive to socially relevant cues, was selected as a seed to measure within-brain functional connectivity. Increased connectivity was confirmed between AG and bilateral dorsolateral prefrontal cortex (dlPFC) as well as a complex including the left subcentral area (SCA) and somatosensory cortex (SS) during interaction with a human opponent. These distributed findings were supported by contrast measures that indicated increased activity at the left dlPFC and frontopolar area that partially overlapped with the region showing increased functional connectivity with AG. Across-brain analyses of neural coherence between the players revealed synchrony between dlPFC and supramarginal gyrus (SMG) and SS in addition to synchrony between AG and the fusiform gyrus (FG) and SMG. These findings present the first evidence of a frontal-parietal neural complex including the TPJ, dlPFC, SCA, SS, and FG that is more active during human-to-human social cognition both within brains (functional connectivity) and across brains (across-brain coherence), supporting a model of functional integration of socially and strategically relevant information during live face-to-face competitive behaviors. PMID:29218005

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

PubMed

Collins, Anne G E; Frank, Michael J

2018-03-06

Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

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.

A neural circuit encoding sexual preference in humans

PubMed Central

Poeppl, Timm B.; Langguth, Berthold; Rupprecht, Rainer; Laird, Angela R; Eickhoff, Simon B.

2016-01-01

Sexual preference determines mate choice for reproduction and hence guarantees conservation of species in mammals. Despite this fundamental role in human behavior, current knowledge on its target-specific neurofunctional substrate is based on lesion studies and therefore limited. We used meta-analytic remodeling of neuroimaging data from 364 human subjects with diverse sexual interests during sexual stimulation to quantify neural regions associated with sexual preference manipulations. We found that sexual preference is encoded by four phylogenetically old, subcortical brain structures. More specifically, sexual preference is controlled by the anterior and preoptic area of the hypothalamus, the anterior and mediodorsal thalamus, the septal area, and the perirhinal parahippocampus including the dentate gyrus. In contrast, sexual non-preference is regulated by the substantia innominata. We anticipate the identification of a core neural circuit for sexual preferences to be a starting point for further sophisticated investigations into the neural principles of sexual behavior and particularly of its aberrations. PMID:27339689

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

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Krajíček, Jiří

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

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

PubMed

Jin, Jia; Yu, Liping; Ma, Qingguo

2015-01-01

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

Controlling basins of attraction in a neural network-based telemetry monitor

NASA Technical Reports Server (NTRS)

Bell, Benjamin; Eilbert, James L.

1988-01-01

The size of the basins of attraction around fixed points in recurrent neural nets (NNs) can be modified by a training process. Controlling these attractive regions by presenting training data with various amount of noise added to the prototype signal vectors is discussed. Application of this technique to signal processing results in a classification system whose sensitivity can be controlled. This new technique is applied to the classification of temporal sequences in telemetry data.

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

PubMed

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

2016-03-30

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

The Magnitude of Trial-By-Trial Neural Variability Is Reproducible over Time and across Tasks in Humans.

PubMed

Arazi, Ayelet; Gonen-Yaacovi, Gil; Dinstein, Ilan

2017-01-01

Numerous studies have shown that neural activity in sensory cortices is remarkably variable over time and across trials even when subjects are presented with an identical repeating stimulus or task. This trial-by-trial neural variability is relatively large in the prestimulus period and considerably smaller (quenched) following stimulus presentation. Previous studies have suggested that the magnitude of neural variability affects behavior such that perceptual performance is better on trials and in individuals where variability quenching is larger. To what degree are neural variability magnitudes of individual subjects flexible or static? Here, we used EEG recordings from adult humans to demonstrate that neural variability magnitudes in visual cortex are remarkably consistent across different tasks and recording sessions. While magnitudes of neural variability differed dramatically across individual subjects, they were surprisingly stable across four tasks with different stimuli, temporal structures, and attentional/cognitive demands as well as across experimental sessions separated by one year. These experiments reveal that, in adults, neural variability magnitudes are mostly solidified individual characteristics that change little with task or time, and are likely to predispose individual subjects to exhibit distinct behavioral capabilities.

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.

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

PubMed

Witoonchart, Peerajak; Chongstitvatana, Prabhas

2017-08-01

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

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

PubMed

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

2017-08-14

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

Finding the beat: a neural perspective across humans and non-human primates.

PubMed

Merchant, Hugo; Grahn, Jessica; Trainor, Laurel; Rohrmeier, Martin; Fitch, W Tecumseh

2015-03-19

Humans possess an ability to perceive and synchronize movements to the beat in music ('beat perception and synchronization'), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia-thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization-continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Finding the beat: a neural perspective across humans and non-human primates

PubMed Central

Merchant, Hugo; Grahn, Jessica; Trainor, Laurel; Rohrmeier, Martin; Fitch, W. Tecumseh

2015-01-01

Humans possess an ability to perceive and synchronize movements to the beat in music (‘beat perception and synchronization’), and recent neuroscientific data have offered new insights into this beat-finding capacity at multiple neural levels. Here, we review and compare behavioural and neural data on temporal and sequential processing during beat perception and entrainment tasks in macaques (including direct neural recording and local field potential (LFP)) and humans (including fMRI, EEG and MEG). These abilities rest upon a distributed set of circuits that include the motor cortico-basal-ganglia–thalamo-cortical (mCBGT) circuit, where the supplementary motor cortex (SMA) and the putamen are critical cortical and subcortical nodes, respectively. In addition, a cortical loop between motor and auditory areas, connected through delta and beta oscillatory activity, is deeply involved in these behaviours, with motor regions providing the predictive timing needed for the perception of, and entrainment to, musical rhythms. The neural discharge rate and the LFP oscillatory activity in the gamma- and beta-bands in the putamen and SMA of monkeys are tuned to the duration of intervals produced during a beat synchronization–continuation task (SCT). Hence, the tempo during beat synchronization is represented by different interval-tuned cells that are activated depending on the produced interval. In addition, cells in these areas are tuned to the serial-order elements of the SCT. Thus, the underpinnings of beat synchronization are intrinsically linked to the dynamics of cell populations tuned for duration and serial order throughout the mCBGT. We suggest that a cross-species comparison of behaviours and the neural circuits supporting them sets the stage for a new generation of neurally grounded computational models for beat perception and synchronization. PMID:25646516

Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example

NASA Technical Reports Server (NTRS)

Decker, Arthur J.; Krasowski, Michael J.; Weiland, Kenneth E.

1993-01-01

This report describes an effort at NASA Lewis Research Center to use artificial neural networks to automate the alignment and control of optical measurement systems. Specifically, it addresses the use of commercially available neural network software and hardware to direct alignments of the common laser-beam-smoothing spatial filter. The report presents a general approach for designing alignment records and combining these into training sets to teach optical alignment functions to neural networks and discusses the use of these training sets to train several types of neural networks. Neural network configurations used include the adaptive resonance network, the back-propagation-trained network, and the counter-propagation network. This work shows that neural networks can be used to produce robust sequencers. These sequencers can learn by example to execute the step-by-step procedures of optical alignment and also can learn adaptively to correct for environmentally induced misalignment. The long-range objective is to use neural networks to automate the alignment and operation of optical measurement systems in remote, harsh, or dangerous aerospace environments. This work also shows that when neural networks are trained by a human operator, training sets should be recorded, training should be executed, and testing should be done in a manner that does not depend on intellectual judgments of the human operator.

Post interaural neural net-based vowel recognition

NASA Astrophysics Data System (ADS)

Jouny, Ismail I.

2001-10-01

Interaural head related transfer functions are used to process speech signatures prior to neural net based recognition. Data representing the head related transfer function of a dummy has been collected at MIT and made available on the Internet. This data is used to pre-process vowel signatures to mimic the effects of human ear on speech perception. Signatures representing various vowels of the English language are then presented to a multi-layer perceptron trained using the back propagation algorithm for recognition purposes. The focus in this paper is to assess the effects of human interaural system on vowel recognition performance particularly when using a classification system that mimics the human brain such as a neural net.

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

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

PubMed Central

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

2013-01-01

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

The immune-neuro-endocrine interactions.

PubMed

Tomaszewska, D; Przekop, F

1997-06-01

This article reviews data concerning the interactions between immune, endocrine and neural systems in physiological, pathophysiological and stress conditions in animals and humans. Numerous studies have provided evidence that these systems interact with each other in maintaining homeostasis. This interaction may be classified as follows: immune, endocrine and neural cell products coexist in lymphoid, endocrine and neural tissue. Endocrine and neural mediators modulate immune system activity. Immune, endocrine and neural cells express receptors for cytokines, hormones, neuropeptides and transmitters.

GABRA2 Alcohol Dependence Risk Allele is Associated with Reduced Expression of Chromosome 4p12 GABAA Subunit Genes in Human Neural Cultures.

PubMed

Lieberman, Richard; Kranzler, Henry R; Joshi, Pujan; Shin, Dong-Guk; Covault, Jonathan

2015-09-01

Genetic variation in a region of chromosome 4p12 that includes the GABAA subunit gene GABRA2 has been reproducibly associated with alcohol dependence (AD). However, the molecular mechanisms underlying the association are unknown. This study examined correlates of in vitro gene expression of the AD-associated GABRA2 rs279858*C-allele in human neural cells using an induced pluripotent stem cell (iPSC) model system. We examined mRNA expression of chromosome 4p12 GABAA subunit genes (GABRG1, GABRA2, GABRA4, and GABRB1) in 36 human neural cell lines differentiated from iPSCs using quantitative polymerase chain reaction and next-generation RNA sequencing. mRNA expression in adult human brain was examined using the BrainCloud and BRAINEAC data sets. We found significantly lower levels of GABRA2 mRNA in neural cell cultures derived from rs279858*C-allele carriers. Levels of GABRA2 RNA were correlated with those of the other 3 chromosome 4p12 GABAA genes, but not other neural genes. Cluster analysis based on the relative RNA levels of the 4 chromosome 4p12 GABAA genes identified 2 distinct clusters of cell lines, a low-expression cluster associated with rs279858*C-allele carriers and a high-expression cluster enriched for the rs279858*T/T genotype. In contrast, there was no association of genotype with chromosome 4p12 GABAA gene expression in postmortem adult cortex in either the BrainCloud or BRAINEAC data sets. AD-associated variation in GABRA2 is associated with differential expression of the entire cluster of GABAA subunit genes on chromosome 4p12 in human iPSC-derived neural cell cultures. The absence of a parallel effect in postmortem human adult brain samples suggests that AD-associated genotype effects on GABAA expression, although not present in mature cortex, could have effects on regulation of the chromosome 4p12 GABAA cluster during neural development. Copyright © 2015 by the Research Society on Alcoholism.

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

PubMed

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

2018-01-01

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

Human induced pluripotent stem cell-derived glial cells and neural progenitors display divergent responses to Zika and dengue infections.

PubMed

Muffat, Julien; Li, Yun; Omer, Attya; Durbin, Ann; Bosch, Irene; Bakiasi, Grisilda; Richards, Edward; Meyer, Aaron; Gehrke, Lee; Jaenisch, Rudolf

2018-06-18

Maternal Zika virus (ZIKV) infection during pregnancy is recognized as the cause of an epidemic of microcephaly and other neurological anomalies in human fetuses. It remains unclear how ZIKV accesses the highly vulnerable population of neural progenitors of the fetal central nervous system (CNS), and which cell types of the CNS may be viral reservoirs. In contrast, the related dengue virus (DENV) does not elicit teratogenicity. To model viral interaction with cells of the fetal CNS in vitro, we investigated the tropism of ZIKV and DENV for different induced pluripotent stem cell-derived human cells, with a particular focus on microglia-like cells. We show that ZIKV infected isogenic neural progenitors, astrocytes, and microglia-like cells (pMGLs), but was only cytotoxic to neural progenitors. Infected glial cells propagated ZIKV and maintained ZIKV load over time, leading to viral spread to susceptible cells. DENV triggered stronger immune responses and could be cleared by neural and glial cells more efficiently. pMGLs, when cocultured with neural spheroids, invaded the tissue and, when infected with ZIKV, initiated neural infection. Since microglia derive from primitive macrophages originating in proximity to the maternal vasculature, they may act as a viral reservoir for ZIKV and establish infection of the fetal brain. Infection of immature neural stem cells by invading microglia may occur in the early stages of pregnancy, before angiogenesis in the brain rudiments. Our data are also consistent with ZIKV and DENV affecting the integrity of the blood-brain barrier, thus allowing infection of the brain later in life.

DUF1220 protein domains drive proliferation in human neural stem cells and are associated with increased cortical volume in anthropoid primates.

PubMed

Keeney, J G; Davis, J M; Siegenthaler, J; Post, M D; Nielsen, B S; Hopkins, W D; Sikela, J M

2015-09-01

Genome sequences encoding DUF1220 protein domains show a burst in copy number among anthropoid species and especially humans, where they have undergone the greatest human lineage-specific copy number expansion of any protein coding sequence in the genome. While DUF1220 copy number shows a dosage-related association with brain size in both normal populations and in 1q21.1-associated microcephaly and macrocephaly, a function for these domains has not yet been described. Here we provide multiple lines of evidence supporting the view that DUF1220 domains function as drivers of neural stem cell proliferation among anthropoid species including humans. First, we show that brain MRI data from 131 individuals across 7 anthropoid species shows a strong correlation between DUF1220 copy number and multiple brain size-related measures. Using in situ hybridization analyses of human fetal brain, we also show that DUF1220 domains are expressed in the ventricular zone and primarily during human cortical neurogenesis, and are therefore expressed at the right time and place to be affecting cortical brain development. Finally, we demonstrate that in vitro expression of DUF1220 sequences in neural stem cells strongly promotes proliferation. Taken together, these data provide the strongest evidence so far reported implicating DUF1220 dosage in anthropoid and human brain expansion through mechanisms involving increasing neural stem cell proliferation.

Multitask neurovision processor with extensive feedback and feedforward connections

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1991-11-01

A multi-task neuro-vision parameter which performs a variety of information processing operations associated with the early stages of biological vision is presented. The network architecture of this neuro-vision processor, called the positive-negative (PN) neural processor, is loosely based on the neural activity fields exhibited by thalamic and cortical nervous tissue layers. The computational operation performed by the processor arises from the strength of the recurrent feedback among the numerous positive and negative neural computing units. By adjusting the feedback connections it is possible to generate diverse dynamic behavior that may be used for short-term visual memory (STVM), spatio-temporal filtering (STF), and pulse frequency modulation (PFM). The information attributes that are to be processes may be regulated by modifying the feedforward connections from the signal space to the neural processor.

Neurophysiology and Neuroanatomy of Reflexive and Volitional Saccades: Evidence from Studies of Humans

ERIC Educational Resources Information Center

McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin P.; Clementz, Brett A.

2008-01-01

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually guided saccades (redirections of gaze to a visual stimulus or pro-saccades) and more complex volitional saccades require similar basic neural circuitry…

FACS-based Isolation of Neural and Glioma Stem Cell Populations from Fresh Human Tissues Utilizing EGF Ligand

PubMed Central

Tome-Garcia, Jessica; Doetsch, Fiona; Tsankova, Nadejda M.

2018-01-01

Direct isolation of human neural and glioma stem cells from fresh tissues permits their biological study without prior culture and may capture novel aspects of their molecular phenotype in their native state. Recently, we demonstrated the ability to prospectively isolate stem cell populations from fresh human germinal matrix and glioblastoma samples, exploiting the ability of cells to bind the Epidermal Growth Factor (EGF) ligand in fluorescence-activated cell sorting (FACS). We demonstrated that FACS-isolated EGF-bound neural and glioblastoma populations encompass the sphere-forming colonies in vitro, and are capable of both self-renewal and multilineage differentiation. Here we describe in detail the purification methodology of EGF-bound (i.e., EGFR+) human neural and glioma cells with stem cell properties from fresh postmortem and surgical tissues. The ability to prospectively isolate stem cell populations using native ligand-binding ability opens new doors for understanding both normal and tumor cell biology in uncultured conditions, and is applicable for various downstream molecular sequencing studies at both population and single-cell resolution. PMID:29516026

Ultra-low-power wireless transmitter for neural prostheses with modified pulse position modulation.

PubMed

Goodarzy, Farhad; Skafidas, Stan E

2014-01-01

An ultra-low-power wireless transmitter for embedded bionic systems is proposed, which achieves 40 pJ/b energy efficiency and delivers 500 kb/s data using the medical implant communication service frequency band (402-405 MHz). It consumes a measured peak power of 200 µW from a 1.2 V supply while occupying an active area of 0.0016 mm(2) in a 130 nm technology. A modified pulse position modulation technique called saturated amplified signal is proposed and implemented, which can reduce the overall and per bit transferred power consumption of the transmitter while reducing the complexity of the transmitter architectures, and hence potentially shrinking the size of the implemented circuitry. The design is capable of being fully integrated on single-chip solutions for surgically implanted bionic systems, wearable devices and neural embedded systems.

Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.

PubMed

Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S; Fong, Simon James; Sen, Soumya

2018-04-01

Dengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.

Deciphering the Neural Control of Sympathetic Nerve Activity: Status Report and Directions for Future Research.

PubMed

Barman, Susan M; Yates, Bill J

2017-01-01

Sympathetic nerve activity (SNA) contributes appreciably to the control of physiological function, such that pathological alterations in SNA can lead to a variety of diseases. The goal of this review is to discuss the characteristics of SNA, briefly review the methodology that has been used to assess SNA and its control, and to describe the essential role of neurophysiological studies in conscious animals to provide additional insights into the regulation of SNA. Studies in both humans and animals have shown that SNA is rhythmic or organized into bursts whose frequency varies depending on experimental conditions and the species. These rhythms are generated by brainstem neurons, and conveyed to sympathetic preganglionic neurons through several pathways, including those emanating from the rostral ventrolateral medulla. Although rhythmic SNA is present in decerebrate animals (indicating that neurons in the brainstem and spinal cord are adequate to generate this activity), there is considerable evidence that a variety of supratentorial structures including the insular and prefrontal cortices, amygdala, and hypothalamic subnuclei provide inputs to the brainstem regions that regulate SNA. It is also known that the characteristics of SNA are altered during stress and particular behaviors such as the defense response and exercise. While it is a certainty that supratentorial structures contribute to changes in SNA during these behaviors, the neural underpinnings of the responses are yet to be established. Understanding how SNA is modified during affective responses and particular behaviors will require neurophysiological studies in awake, behaving animals, including those that entail recording activity from neurons that generate SNA. Recent studies have shown that responses of neurons in the central nervous system to most sensory inputs are context-specific. Future neurophysiological studies in conscious animals should also ascertain whether this general rule also applies to sensory signals that modify SNA.

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

PubMed

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

2017-07-01

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

A curly-tail modifier locus, mct1, on mouse chromosome 17

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

Letts, V.A.; Schork, N.J.; Frankel, W.N.

1995-10-10

The major gene for neural tube defects, ct, in the curly-tail (CT) mouse strain was mapped previously to mouse chromosome 4 by combining linkage data from several backcrosses. The penetrance of the neural tube trait, already incomplete in the CT strain, was further reduced in several of these backcrosses, suggesting the existence of recessive modifiers or strain-specific susceptibility alleles. Here we describe the mapping of a curly-tail modifier locus, mct1, to chromosome 17 in moderate and low penetrance crosses of CT with BALB/cByJ and Mus spretus. No effect of mct1 was seen in a higher penetrance cross with the BXD-8/Tymore » strain, confirming that ct is the major gene in the model. Homozygosity at both ct and mct1 loci was sufficient to account for all of the affected individuals in the BALB/cByJ cross and most of the affected individuals in the M. spretus cross and was the preferred model overall. No evidence was found for epistatic interaction between ct and mct1. 30 refs., 2 figs., 3 tabs.« less

Tinnitus alters resting state functional connectivity (RSFC) in human auditory and non-auditory brain regions as measured by functional near-infrared spectroscopy (fNIRS)

PubMed Central

Hu, Xiao-Su; Issa, Mohamad; Bisconti, Silvia; Kovelman, Ioulia; Kileny, Paul; Basura, Gregory

2017-01-01

Tinnitus, or phantom sound perception, leads to increased spontaneous neural firing rates and enhanced synchrony in central auditory circuits in animal models. These putative physiologic correlates of tinnitus to date have not been well translated in the brain of the human tinnitus sufferer. Using functional near-infrared spectroscopy (fNIRS) we recently showed that tinnitus in humans leads to maintained hemodynamic activity in auditory and adjacent, non-auditory cortices. Here we used fNIRS technology to investigate changes in resting state functional connectivity between human auditory and non-auditory brain regions in normal-hearing, bilateral subjective tinnitus and controls before and after auditory stimulation. Hemodynamic activity was monitored over the region of interest (primary auditory cortex) and non-region of interest (adjacent non-auditory cortices) and functional brain connectivity was measured during a 60-second baseline/period of silence before and after a passive auditory challenge consisting of alternating pure tones (750 and 8000Hz), broadband noise and silence. Functional connectivity was measured between all channel-pairs. Prior to stimulation, connectivity of the region of interest to the temporal and fronto-temporal region was decreased in tinnitus participants compared to controls. Overall, connectivity in tinnitus was differentially altered as compared to controls following sound stimulation. Enhanced connectivity was seen in both auditory and non-auditory regions in the tinnitus brain, while controls showed a decrease in connectivity following sound stimulation. In tinnitus, the strength of connectivity was increased between auditory cortex and fronto-temporal, fronto-parietal, temporal, occipito-temporal and occipital cortices. Together these data suggest that central auditory and non-auditory brain regions are modified in tinnitus and that resting functional connectivity measured by fNIRS technology may contribute to conscious phantom sound perception and potentially serve as an objective measure of central neural pathology. PMID:28604786

Linear analysis of auto-organization in Hebbian neural networks.

PubMed

Carlos Letelier, J; Mpodozis, J

1995-01-01

The self-organization of neurotopies where neural connections follow Hebbian dynamics is framed in terms of linear operator theory. A general and exact equation describing the time evolution of the overall synaptic strength connecting two neural laminae is derived. This linear matricial equation, which is similar to the equations used to describe oscillating systems in physics, is modified by the introduction of non-linear terms, in order to capture self-organizing (or auto-organizing) processes. The behavior of a simple and small system, that contains a non-linearity that mimics a metabolic constraint, is analyzed by computer simulations. The emergence of a simple "order" (or degree of organization) in this low-dimensionality model system is discussed.

Generating trunk neural crest from human pluripotent stem cells

PubMed Central

Huang, Miller; Miller, Matthew L.; McHenry, Lauren K.; Zheng, Tina; Zhen, Qiqi; Ilkhanizadeh, Shirin; Conklin, Bruce R.; Bronner, Marianne E.; Weiss, William A.

2016-01-01

Neural crest cells (NCC) are stem cells that generate different lineages, including neuroendocrine, melanocytic, cartilage, and bone. The differentiation potential of NCC varies according to the level from which cells emerge along the neural tube. For example, only anterior “cranial” NCC form craniofacial bone, whereas solely posterior “trunk” NCC contribute to sympathoadrenal cells. Importantly, the isolation of human fetal NCC carries ethical and scientific challenges, as NCC induction typically occur before pregnancy is detectable. As a result, current knowledge of NCC biology derives primarily from non-human organisms. Important differences between human and non-human NCC, such as expression of HNK1 in human but not mouse NCC, suggest a need to study human NCC directly. Here, we demonstrate that current protocols to differentiate human pluripotent stem cells (PSC) to NCC are biased toward cranial NCC. Addition of retinoic acid drove trunk-related markers and HOX genes characteristic of a posterior identity. Subsequent treatment with bone morphogenetic proteins (BMPs) enhanced differentiation to sympathoadrenal cells. Our approach provides methodology for detailed studies of human NCC, and clarifies roles for retinoids and BMPs in the differentiation of human PSC to trunk NCC and to sympathoadrenal lineages. PMID:26812940

Human activity recognition based on feature selection in smart home using back-propagation algorithm.

PubMed

Fang, Hongqing; He, Lei; Si, Hao; Liu, Peng; Xie, Xiaolei

2014-09-01

In this paper, Back-propagation(BP) algorithm has been used to train the feed forward neural network for human activity recognition in smart home environments, and inter-class distance method for feature selection of observed motion sensor events is discussed and tested. And then, the human activity recognition performances of neural network using BP algorithm have been evaluated and compared with other probabilistic algorithms: Naïve Bayes(NB) classifier and Hidden Markov Model(HMM). The results show that different feature datasets yield different activity recognition accuracy. The selection of unsuitable feature datasets increases the computational complexity and degrades the activity recognition accuracy. Furthermore, neural network using BP algorithm has relatively better human activity recognition performances than NB classifier and HMM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

The neural bases for valuing social equality.

PubMed

Aoki, Ryuta; Yomogida, Yukihito; Matsumoto, Kenji

2015-01-01

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

Transcranial electric stimulation for the investigation of speech perception and comprehension

PubMed Central

Zoefel, Benedikt; Davis, Matthew H.

2017-01-01

ABSTRACT Transcranial electric stimulation (tES), comprising transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS), involves applying weak electrical current to the scalp, which can be used to modulate membrane potentials and thereby modify neural activity. Critically, behavioural or perceptual consequences of this modulation provide evidence for a causal role of neural activity in the stimulated brain region for the observed outcome. We present tES as a tool for the investigation of which neural responses are necessary for successful speech perception and comprehension. We summarise existing studies, along with challenges that need to be overcome, potential solutions, and future directions. We conclude that, although standardised stimulation parameters still need to be established, tES is a promising tool for revealing the neural basis of speech processing. Future research can use this method to explore the causal role of brain regions and neural processes for the perception and comprehension of speech. PMID:28670598

Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles

PubMed Central

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P. Read; Camerer, Colin F.

2014-01-01

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations—price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation. PMID:25002476

Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

PubMed

Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

2014-07-22

Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

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.

Evolvable Neural Software System

NASA Technical Reports Server (NTRS)

Curtis, Steven A.

2009-01-01

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

Tunable vertical-cavity surface-emitting laser with feedback to implement a pulsed neural model. 1. Principles and experimental demonstration.

PubMed

Romariz, Alexandre R S; Wagner, Kelvin H

2007-07-20

An optoelectronic implementation of a modified FitzHugh-Nagumo neuron model is proposed, analyzed, and experimentally demonstrated. The setup uses linear optics and linear electronics for implementing an optical wavelength-domain nonlinearity. The system attains instability through a bifurcation mechanism present in a class of neuron models, a fact that is shown analytically. The implementation exhibits basic features of neural dynamics including threshold, production of short pulses (or spikes), and refractoriness.

Using a neural network to proximity correct patterns written with a Cambridge electron beam microfabricator 10.5 lithography system

NASA Astrophysics Data System (ADS)

Cummings, K. D.; Frye, R. C.; Rietman, E. A.

1990-10-01

This letter describes the initial results of using a theoretical determination of the proximity function and an adaptively trained neural network to proximity-correct patterns written on a Cambridge electron beam lithography system. The methods described are complete and may be applied to any electron beam exposure system that can modify the dose during exposure. The patterns produced in resist show the effects of proximity correction versus noncorrected patterns.

The neural basis of understanding the expression of the emotions in man and animals

PubMed Central

Ellsworth, Emily; Adolphs, Ralph

2017-01-01

Abstract Humans cannot help but attribute human emotions to non-human animals. Although such attributions are often regarded as gratuitous anthropomorphisms and held apart from the attributions humans make about each other’s internal states, they may be the product of a general mechanism for flexibly interpreting adaptive behavior. To examine this, we used functional magnetic resonance imaging (fMRI) in humans to compare the neural mechanisms associated with attributing emotions to humans and non-human animal behavior. Although undergoing fMRI, participants first passively observed the facial displays of human, non-human primate and domestic dogs, and subsequently judged the acceptability of emotional (e.g. ‘annoyed’) and facial descriptions (e.g. ‘baring teeth’) for the same images. For all targets, emotion attributions selectively activated regions in prefrontal and anterior temporal cortices associated with causal explanation in prior studies. These regions were similarly activated by both human and non-human targets even during the passive observation task; moreover, the degree of neural similarity was dependent on participants’ self-reported beliefs in the mental capacities of non-human animals. These results encourage a non-anthropocentric view of emotion understanding, one that treats the idea that animals have emotions as no more gratuitous than the idea that humans other than ourselves do. PMID:27803286

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

PubMed

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

2009-01-01

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

Changing the Spatial Scope of Attention Alters Patterns of Neural Gain in Human Cortex

PubMed Central

Garcia, Javier O.; Rungratsameetaweemana, Nuttida; Sprague, Thomas C.

2014-01-01

Over the last several decades, spatial attention has been shown to influence the activity of neurons in visual cortex in various ways. These conflicting observations have inspired competing models to account for the influence of attention on perception and behavior. Here, we used electroencephalography (EEG) to assess steady-state visual evoked potentials (SSVEP) in human subjects and showed that highly focused spatial attention primarily enhanced neural responses to high-contrast stimuli (response gain), whereas distributed attention primarily enhanced responses to medium-contrast stimuli (contrast gain). Together, these data suggest that different patterns of neural modulation do not reflect fundamentally different neural mechanisms, but instead reflect changes in the spatial extent of attention. PMID:24381272

Deep neural networks for direct, featureless learning through observation: The case of two-dimensional spin models

NASA Astrophysics Data System (ADS)

Mills, Kyle; Tamblyn, Isaac

2018-03-01

We demonstrate the capability of a convolutional deep neural network in predicting the nearest-neighbor energy of the 4 ×4 Ising model. Using its success at this task, we motivate the study of the larger 8 ×8 Ising model, showing that the deep neural network can learn the nearest-neighbor Ising Hamiltonian after only seeing a vanishingly small fraction of configuration space. Additionally, we show that the neural network has learned both the energy and magnetization operators with sufficient accuracy to replicate the low-temperature Ising phase transition. We then demonstrate the ability of the neural network to learn other spin models, teaching the convolutional deep neural network to accurately predict the long-range interaction of a screened Coulomb Hamiltonian, a sinusoidally attenuated screened Coulomb Hamiltonian, and a modified Potts model Hamiltonian. In the case of the long-range interaction, we demonstrate the ability of the neural network to recover the phase transition with equivalent accuracy to the numerically exact method. Furthermore, in the case of the long-range interaction, the benefits of the neural network become apparent; it is able to make predictions with a high degree of accuracy, and do so 1600 times faster than a CUDA-optimized exact calculation. Additionally, we demonstrate how the neural network succeeds at these tasks by looking at the weights learned in a simplified demonstration.

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

USDA-ARS?s Scientific Manuscript database

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

Critical Branching Neural Networks

ERIC Educational Resources Information Center

Kello, Christopher T.

2013-01-01

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

A GPU-accelerated cortical neural network model for visually guided robot navigation.

PubMed

Beyeler, Michael; Oros, Nicolas; Dutt, Nikil; Krichmar, Jeffrey L

2015-12-01

Humans and other terrestrial animals use vision to traverse novel cluttered environments with apparent ease. On one hand, although much is known about the behavioral dynamics of steering in humans, it remains unclear how relevant perceptual variables might be represented in the brain. On the other hand, although a wealth of data exists about the neural circuitry that is concerned with the perception of self-motion variables such as the current direction of travel, little research has been devoted to investigating how this neural circuitry may relate to active steering control. Here we present a cortical neural network model for visually guided navigation that has been embodied on a physical robot exploring a real-world environment. The model includes a rate based motion energy model for area V1, and a spiking neural network model for cortical area MT. The model generates a cortical representation of optic flow, determines the position of objects based on motion discontinuities, and combines these signals with the representation of a goal location to produce motor commands that successfully steer the robot around obstacles toward the goal. The model produces robot trajectories that closely match human behavioral data. This study demonstrates how neural signals in a model of cortical area MT might provide sufficient motion information to steer a physical robot on human-like paths around obstacles in a real-world environment, and exemplifies the importance of embodiment, as behavior is deeply coupled not only with the underlying model of brain function, but also with the anatomical constraints of the physical body it controls. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural networks: A simulation technique under uncertainty conditions

NASA Technical Reports Server (NTRS)

Mcallister, M. Luisa Nicosia

1992-01-01

This paper proposes a new definition of fuzzy graphs and shows how transmission through a graph with linguistic expressions as labels provides an easy computational tool. These labels are represented by modified Kauffmann Fuzzy numbers.

Associative Processes in Early Olfactory Preference Acquisition

PubMed Central

Sullivan, Regina M.; Wilson, Donald A.; Leon, Michael

2007-01-01

Acquisition of behavioral conditioned responding and learned odor preferences during olfactory classical conditioning in rat pups requires forward or simultaneous pairings of the conditioned stimulus (CS) and the unconditioned stimulus (US). Other temporal relationships between the CS and US do not usually result in learning. The present study examined the influence of this CS-US relationship upon the neural olfactory bulb modifications that are acquired during early classical conditioning. Wistar rat pups were trained from Postnatal Days (PN) 1-18 with either forward (odor overlapping temporally with reinforcing stroking) or backward (stroking followed by odor) CS-US pairings. On PN 19, pups received either a behavioral odor preference test to the odor CS or an injection of 14C 2-DG and exposure to the odor CS, or olfactory bulb single unit responses were recorded in response to exposure to the odor CS. Only pups that received forward presentations of the CS and US exhibited both a preference for the CS and modified olfactory bulb neural responses to the CS. These results, then, suggest that the modified olfactory bulb neural responses acquired during classical conditioning are guided by the same temporal constraints as those which govern the acquisition of behavioral conditioned responses. PMID:17572798

This Neural Implant is designed to be implanted in the Human Central and Nervous System

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

None

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.

This Neural Implant is designed to be implanted in the Human Central and Nervous System

ScienceCinema

None

2018-06-12

A new class of neural implants being developed at the Livermore Lab are the first clinical quality devices capable of two-way conversations with the human nervous systems. Unlike existing interfaces that only sense or only stimulate, these devices are capable of stimulating and sensing using both electric and chemical signals.

EVALUATION OF HUMAN NEURAL PROGENITOR CELLS FOR DEVELOPMENTAL NEUROTOXICITY SCREENING: TIME COURSE OF EFFECTS ON CELL PROLIFERATION AND VIABILITY.

EPA Science Inventory

Current testing methods for developmental neurotoxicity (DNT) make evaluation of the effects of large numbers of chemicals impractical and prohibitively expensive. As such, we are evaluating human neural progenitor cells (NPCs) as a screen for DNT. ReNcell CX (ReN CX) cells are a...

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

PubMed Central

Op de Beeck, Hans P.

2016-01-01

Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have largely failed. Recent studies suggest that state-of-the-art convolutional ‘deep’ neural networks (DNNs) capture important aspects of human object perception. We hypothesized that these successes might be partially related to a human-like representation of object shape. Here we demonstrate that sensitivity for shape features, characteristic to human and primate vision, emerges in DNNs when trained for generic object recognition from natural photographs. We show that these models explain human shape judgments for several benchmark behavioral and neural stimulus sets on which earlier models mostly failed. In particular, although never explicitly trained for such stimuli, DNNs develop acute sensitivity to minute variations in shape and to non-accidental properties that have long been implicated to form the basis for object recognition. Even more strikingly, when tested with a challenging stimulus set in which shape and category membership are dissociated, the most complex model architectures capture human shape sensitivity as well as some aspects of the category structure that emerges from human judgments. As a whole, these results indicate that convolutional neural networks not only learn physically correct representations of object categories but also develop perceptually accurate representational spaces of shapes. An even more complete model of human object representations might be in sight by training deep architectures for multiple tasks, which is so characteristic in human development. PMID:27124699

Learning Perfectly Secure Cryptography to Protect Communications with Adversarial Neural Cryptography

PubMed Central

2018-01-01

Researches in Artificial Intelligence (AI) have achieved many important breakthroughs, especially in recent years. In some cases, AI learns alone from scratch and performs human tasks faster and better than humans. With the recent advances in AI, it is natural to wonder whether Artificial Neural Networks will be used to successfully create or break cryptographic algorithms. Bibliographic review shows the main approach to this problem have been addressed throughout complex Neural Networks, but without understanding or proving the security of the generated model. This paper presents an analysis of the security of cryptographic algorithms generated by a new technique called Adversarial Neural Cryptography (ANC). Using the proposed network, we show limitations and directions to improve the current approach of ANC. Training the proposed Artificial Neural Network with the improved model of ANC, we show that artificially intelligent agents can learn the unbreakable One-Time Pad (OTP) algorithm, without human knowledge, to communicate securely through an insecure communication channel. This paper shows in which conditions an AI agent can learn a secure encryption scheme. However, it also shows that, without a stronger adversary, it is more likely to obtain an insecure one. PMID:29695066

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

PubMed

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

2018-04-24

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

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

PubMed Central

Sánchez, Daniela; Melin, Patricia

2017-01-01

A grey wolf optimizer for modular neural network (MNN) with a granular approach is proposed. The proposed method performs optimal granulation of data and design of modular neural networks architectures to perform human recognition, and to prove its effectiveness benchmark databases of ear, iris, and face biometric measures are used to perform tests and comparisons against other works. The design of a modular granular neural network (MGNN) consists in finding optimal parameters of its architecture; these parameters are the number of subgranules, percentage of data for the training phase, learning algorithm, goal error, number of hidden layers, and their number of neurons. Nowadays, there is a great variety of approaches and new techniques within the evolutionary computing area, and these approaches and techniques have emerged to help find optimal solutions to problems or models and bioinspired algorithms are part of this area. In this work a grey wolf optimizer is proposed for the design of modular granular neural networks, and the results are compared against a genetic algorithm and a firefly algorithm in order to know which of these techniques provides better results when applied to human recognition. PMID:28894461

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

PubMed

Sánchez, Daniela; Melin, Patricia; Castillo, Oscar

2017-01-01

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

A tale of two species: neural integration in zebrafish and monkeys

PubMed Central

Joshua, Mati; Lisberger, Stephen G.

2014-01-01

Selection of a model organism creates a tension between competing constraints. The recent explosion of modern molecular techniques has revolutionized the analysis of neural systems in organisms that are amenable to genetic techniques. Yet, the non-human primate remains the gold-standard for the analysis of the neural basis of behavior, and as a bridge to the operation of the human brain. The challenge is to generalize across species in a way that exposes the operation of circuits as well as the relationship of circuits to behavior. Eye movements provide an opportunity to cross the bridge from mechanism to behavior through research on diverse species. Here, we review experiments and computational studies on a circuit function called “neural integration” that occurs in the brainstems of larval zebrafish, non-human primates, and species “in between”. We show that analysis of circuit structure using modern molecular and imaging approaches in zebrafish has remarkable explanatory power for the details of the responses of integrator neurons in the monkey. The combination of research from the two species has led to a much stronger hypothesis for the implementation of the neural integrator than could have been achieved using either species alone. PMID:24797331

Antagonism between the transcription factors NANOG and OTX2 specifies rostral or caudal cell fate during neural patterning transition.

PubMed

Su, Zhenghui; Zhang, Yanqi; Liao, Baojian; Zhong, Xiaofen; Chen, Xin; Wang, Haitao; Guo, Yiping; Shan, Yongli; Wang, Lihui; Pan, Guangjin

2018-03-23

During neurogenesis, neural patterning is a critical step during which neural progenitor cells differentiate into neurons with distinct functions. However, the molecular determinants that regulate neural patterning remain poorly understood. Here we optimized the "dual SMAD inhibition" method to specifically promote differentiation of human pluripotent stem cells (hPSCs) into forebrain and hindbrain neural progenitor cells along the rostral-caudal axis. We report that neural patterning determination occurs at the very early stage in this differentiation. Undifferentiated hPSCs expressed basal levels of the transcription factor orthodenticle homeobox 2 (OTX2) that dominantly drove hPSCs into the "default" rostral fate at the beginning of differentiation. Inhibition of glycogen synthase kinase 3β (GSK3β) through CHIR99021 application sustained transient expression of the transcription factor NANOG at early differentiation stages through Wnt signaling. Wnt signaling and NANOG antagonized OTX2 and, in the later stages of differentiation, switched the default rostral cell fate to the caudal one. Our findings have uncovered a mutual antagonism between NANOG and OTX2 underlying cell fate decisions during neural patterning, critical for the regulation of early neural development in humans. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

The role of symmetry in neural networks and their Laplacian spectra.

PubMed

de Lange, Siemon C; van den Heuvel, Martijn P; de Reus, Marcel A

2016-11-01

Human and animal nervous systems constitute complexly wired networks that form the infrastructure for neural processing and integration of information. The organization of these neural networks can be analyzed using the so-called Laplacian spectrum, providing a mathematical tool to produce systems-level network fingerprints. In this article, we examine a characteristic central peak in the spectrum of neural networks, including anatomical brain network maps of the mouse, cat and macaque, as well as anatomical and functional network maps of human brain connectivity. We link the occurrence of this central peak to the level of symmetry in neural networks, an intriguing aspect of network organization resulting from network elements that exhibit similar wiring patterns. Specifically, we propose a measure to capture the global level of symmetry of a network and show that, for both empirical networks and network models, the height of the main peak in the Laplacian spectrum is strongly related to node symmetry in the underlying network. Moreover, examination of spectra of duplication-based model networks shows that neural spectra are best approximated using a trade-off between duplication and diversification. Taken together, our results facilitate a better understanding of neural network spectra and the importance of symmetry in neural networks. Copyright © 2016 Elsevier Inc. All rights reserved.

A feed-forward Hopfield neural network algorithm (FHNNA) with a colour satellite image for water quality mapping

NASA Astrophysics Data System (ADS)

Asal Kzar, Ahmed; Mat Jafri, M. Z.; Hwee San, Lim; Al-Zuky, Ali A.; Mutter, Kussay N.; Hassan Al-Saleh, Anwar

2016-06-01

There are many techniques that have been given for water quality problem, but the remote sensing techniques have proven their success, especially when the artificial neural networks are used as mathematical models with these techniques. Hopfield neural network is one type of artificial neural networks which is common, fast, simple, and efficient, but it when it deals with images that have more than two colours such as remote sensing images. This work has attempted to solve this problem via modifying the network that deals with colour remote sensing images for water quality mapping. A Feed-forward Hopfield Neural Network Algorithm (FHNNA) was modified and used with a satellite colour image from type of Thailand earth observation system (THEOS) for TSS mapping in the Penang strait, Malaysia, through the classification of TSS concentrations. The new algorithm is based essentially on three modifications: using HNN as feed-forward network, considering the weights of bitplanes, and non-self-architecture or zero diagonal of weight matrix, in addition, it depends on a validation data. The achieved map was colour-coded for visual interpretation. The efficiency of the new algorithm has found out by the higher correlation coefficient (R=0.979) and the lower root mean square error (RMSE=4.301) between the validation data that were divided into two groups. One used for the algorithm and the other used for validating the results. The comparison was with the minimum distance classifier. Therefore, TSS mapping of polluted water in Penang strait, Malaysia, can be performed using FHNNA with remote sensing technique (THEOS). It is a new and useful application of HNN, so it is a new model with remote sensing techniques for water quality mapping which is considered important environmental problem.

Capturing the temporal evolution of choice across prefrontal cortex

PubMed Central

Hunt, Laurence T; Behrens, Timothy EJ; Hosokawa, Takayuki; Wallis, Jonathan D; Kennerley, Steven W

2015-01-01

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making. DOI: http://dx.doi.org/10.7554/eLife.11945.001 PMID:26653139

Human fatigue expression recognition through image-based dynamic multi-information and bimodal deep learning

NASA Astrophysics Data System (ADS)

Zhao, Lei; Wang, Zengcai; Wang, Xiaojin; Qi, Yazhou; Liu, Qing; Zhang, Guoxin

2016-09-01

Human fatigue is an important cause of traffic accidents. To improve the safety of transportation, we propose, in this paper, a framework for fatigue expression recognition using image-based facial dynamic multi-information and a bimodal deep neural network. First, the landmark of face region and the texture of eye region, which complement each other in fatigue expression recognition, are extracted from facial image sequences captured by a single camera. Then, two stacked autoencoder neural networks are trained for landmark and texture, respectively. Finally, the two trained neural networks are combined by learning a joint layer on top of them to construct a bimodal deep neural network. The model can be used to extract a unified representation that fuses landmark and texture modalities together and classify fatigue expressions accurately. The proposed system is tested on a human fatigue dataset obtained from an actual driving environment. The experimental results demonstrate that the proposed method performs stably and robustly, and that the average accuracy achieves 96.2%.

The auditory representation of speech sounds in human motor cortex

PubMed Central

Cheung, Connie; Hamilton, Liberty S; Johnson, Keith; Chang, Edward F

2016-01-01

In humans, listening to speech evokes neural responses in the motor cortex. This has been controversially interpreted as evidence that speech sounds are processed as articulatory gestures. However, it is unclear what information is actually encoded by such neural activity. We used high-density direct human cortical recordings while participants spoke and listened to speech sounds. Motor cortex neural patterns during listening were substantially different than during articulation of the same sounds. During listening, we observed neural activity in the superior and inferior regions of ventral motor cortex. During speaking, responses were distributed throughout somatotopic representations of speech articulators in motor cortex. The structure of responses in motor cortex during listening was organized along acoustic features similar to auditory cortex, rather than along articulatory features as during speaking. Motor cortex does not contain articulatory representations of perceived actions in speech, but rather, represents auditory vocal information. DOI: http://dx.doi.org/10.7554/eLife.12577.001 PMID:26943778

Mastering the game of Go without human knowledge.

PubMed

Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Hui, Fan; Sifre, Laurent; van den Driessche, George; Graepel, Thore; Hassabis, Demis

2017-10-18

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo's own move selections and also the winner of AlphaGo's games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100-0 against the previously published, champion-defeating AlphaGo.

Mastering the game of Go without human knowledge

NASA Astrophysics Data System (ADS)

Silver, David; Schrittwieser, Julian; Simonyan, Karen; Antonoglou, Ioannis; Huang, Aja; Guez, Arthur; Hubert, Thomas; Baker, Lucas; Lai, Matthew; Bolton, Adrian; Chen, Yutian; Lillicrap, Timothy; Hui, Fan; Sifre, Laurent; van den Driessche, George; Graepel, Thore; Hassabis, Demis

2017-10-01

A long-standing goal of artificial intelligence is an algorithm that learns, tabula rasa, superhuman proficiency in challenging domains. Recently, AlphaGo became the first program to defeat a world champion in the game of Go. The tree search in AlphaGo evaluated positions and selected moves using deep neural networks. These neural networks were trained by supervised learning from human expert moves, and by reinforcement learning from self-play. Here we introduce an algorithm based solely on reinforcement learning, without human data, guidance or domain knowledge beyond game rules. AlphaGo becomes its own teacher: a neural network is trained to predict AlphaGo’s own move selections and also the winner of AlphaGo’s games. This neural network improves the strength of the tree search, resulting in higher quality move selection and stronger self-play in the next iteration. Starting tabula rasa, our new program AlphaGo Zero achieved superhuman performance, winning 100-0 against the previously published, champion-defeating AlphaGo.

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

Enteric nervous system abnormalities are present in human necrotizing enterocolitis: potential neurotransplantation therapy

PubMed Central

2013-01-01

Introduction Intestinal dysmotility following human necrotizing enterocolitis suggests that the enteric nervous system is injured during the disease. We examined human intestinal specimens to characterize the enteric nervous system injury that occurs in necrotizing enterocolitis, and then used an animal model of experimental necrotizing enterocolitis to determine whether transplantation of neural stem cells can protect the enteric nervous system from injury. Methods Human intestinal specimens resected from patients with necrotizing enterocolitis (n = 18), from control patients with bowel atresia (n = 8), and from necrotizing enterocolitis and control patients undergoing stoma closure several months later (n = 14 and n = 6 respectively) were subjected to histologic examination, immunohistochemistry, and real-time reverse-transcription polymerase chain reaction to examine the myenteric plexus structure and neurotransmitter expression. In addition, experimental necrotizing enterocolitis was induced in newborn rat pups and neurotransplantation was performed by administration of fluorescently labeled neural stem cells, with subsequent visualization of transplanted cells and determination of intestinal integrity and intestinal motility. Results There was significant enteric nervous system damage with increased enteric nervous system apoptosis, and decreased neuronal nitric oxide synthase expression in myenteric ganglia from human intestine resected for necrotizing enterocolitis compared with control intestine. Structural and functional abnormalities persisted months later at the time of stoma closure. Similar abnormalities were identified in rat pups exposed to experimental necrotizing enterocolitis. Pups receiving neural stem cell transplantation had improved enteric nervous system and intestinal integrity, differentiation of transplanted neural stem cells into functional neurons, significantly improved intestinal transit, and significantly decreased mortality compared with control pups. Conclusions Significant injury to the enteric nervous system occurs in both human and experimental necrotizing enterocolitis. Neural stem cell transplantation may represent a novel future therapy for patients with necrotizing enterocolitis. PMID:24423414

A three-dimensional human neural cell culture model of Alzheimer's disease.

PubMed

Choi, Se Hoon; Kim, Young Hye; Hebisch, Matthias; Sliwinski, Christopher; Lee, Seungkyu; D'Avanzo, Carla; Chen, Hechao; Hooli, Basavaraj; Asselin, Caroline; Muffat, Julien; Klee, Justin B; Zhang, Can; Wainger, Brian J; Peitz, Michael; Kovacs, Dora M; Woolf, Clifford J; Wagner, Steven L; Tanzi, Rudolph E; Kim, Doo Yeon

2014-11-13

Alzheimer's disease is the most common form of dementia, characterized by two pathological hallmarks: amyloid-β plaques and neurofibrillary tangles. The amyloid hypothesis of Alzheimer's disease posits that the excessive accumulation of amyloid-β peptide leads to neurofibrillary tangles composed of aggregated hyperphosphorylated tau. However, to date, no single disease model has serially linked these two pathological events using human neuronal cells. Mouse models with familial Alzheimer's disease (FAD) mutations exhibit amyloid-β-induced synaptic and memory deficits but they do not fully recapitulate other key pathological events of Alzheimer's disease, including distinct neurofibrillary tangle pathology. Human neurons derived from Alzheimer's disease patients have shown elevated levels of toxic amyloid-β species and phosphorylated tau but did not demonstrate amyloid-β plaques or neurofibrillary tangles. Here we report that FAD mutations in β-amyloid precursor protein and presenilin 1 are able to induce robust extracellular deposition of amyloid-β, including amyloid-β plaques, in a human neural stem-cell-derived three-dimensional (3D) culture system. More importantly, the 3D-differentiated neuronal cells expressing FAD mutations exhibited high levels of detergent-resistant, silver-positive aggregates of phosphorylated tau in the soma and neurites, as well as filamentous tau, as detected by immunoelectron microscopy. Inhibition of amyloid-β generation with β- or γ-secretase inhibitors not only decreased amyloid-β pathology, but also attenuated tauopathy. We also found that glycogen synthase kinase 3 (GSK3) regulated amyloid-β-mediated tau phosphorylation. We have successfully recapitulated amyloid-β and tau pathology in a single 3D human neural cell culture system. Our unique strategy for recapitulating Alzheimer's disease pathology in a 3D neural cell culture model should also serve to facilitate the development of more precise human neural cell models of other neurodegenerative disorders.

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

PubMed

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

2018-01-01

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

The Neural Crest in Cardiac Congenital Anomalies

PubMed Central

Keyte, Anna; Hutson, Mary Redmond

2012-01-01

This review discusses the function of neural crest as they relate to cardiovascular defects. The cardiac neural crest cells are a subpopulation of cranial neural crest discovered nearly 30 years ago by ablation of premigratory neural crest. The cardiac neural crest cells are necessary for normal cardiovascular development. We begin with a description of the crest cells in normal development, including their function in remodeling the pharyngeal arch arteries, outflow tract septation, valvulogenesis, and development of the cardiac conduction system. The cells are also responsible for modulating signaling in the caudal pharynx, including the second heart field. Many of the molecular pathways that are known to influence specification, migration, patterning and final targeting of the cardiac neural crest cells are reviewed. The cardiac neural crest cells play a critical role in the pathogenesis of various human cardiocraniofacial syndromes such as DiGeorge, Velocardiofacial, CHARGE, Fetal Alcohol, Alagille, LEOPARD, and Noonan syndromes, as well as Retinoic Acid Embryopathy. The loss of neural crest cells or their dysfunction may not always directly cause abnormal cardiovascular development, but are involved secondarily because crest cells represent a major component in the complex tissue interactions in the head, pharynx and outflow tract. Thus many of the human syndromes linking defects in the heart, face and brain can be better understood when considered within the context of a single cardiocraniofacial developmental module with the neural crest being a key cell type that interconnects the regions. PMID:22595346

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks

PubMed Central

Simão, Daniel; Terrasso, Ana P.; Teixeira, Ana P.; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M.

2016-01-01

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-13C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells. PMID:27619889

Functional metabolic interactions of human neuron-astrocyte 3D in vitro networks.

PubMed

Simão, Daniel; Terrasso, Ana P; Teixeira, Ana P; Brito, Catarina; Sonnewald, Ursula; Alves, Paula M

2016-09-13

The generation of human neural tissue-like 3D structures holds great promise for disease modeling, drug discovery and regenerative medicine strategies. Promoting the establishment of complex cell-cell interactions, 3D culture systems enable the development of human cell-based models with increased physiological relevance, over monolayer cultures. Here, we demonstrate the establishment of neuronal and astrocytic metabolic signatures and shuttles in a human 3D neural cell model, namely the glutamine-glutamate-GABA shuttle. This was indicated by labeling of neuronal GABA following incubation with the glia-specific substrate [2-(13)C]acetate, which decreased by methionine sulfoximine-induced inhibition of the glial enzyme glutamine synthetase. Cell metabolic specialization was further demonstrated by higher pyruvate carboxylase-derived labeling in glutamine than in glutamate, indicating its activity in astrocytes and not in neurons. Exposure to the neurotoxin acrylamide resulted in intracellular accumulation of glutamate and decreased GABA synthesis. These results suggest an acrylamide-induced impairment of neuronal synaptic vesicle trafficking and imbalanced glutamine-glutamate-GABA cycle, due to loss of cell-cell contacts at synaptic sites. This work demonstrates, for the first time to our knowledge, that neural differentiation of human cells in a 3D setting recapitulates neuronal-astrocytic metabolic interactions, highlighting the relevance of these models for toxicology and better understanding the crosstalk between human neural cells.

Bottom-up driven involuntary auditory evoked field change: constant sound sequencing amplifies but does not sharpen neural activity.

PubMed

Okamoto, Hidehiko; Stracke, Henning; Lagemann, Lothar; Pantev, Christo

2010-01-01

The capability of involuntarily tracking certain sound signals during the simultaneous presence of noise is essential in human daily life. Previous studies have demonstrated that top-down auditory focused attention can enhance excitatory and inhibitory neural activity, resulting in sharpening of frequency tuning of auditory neurons. In the present study, we investigated bottom-up driven involuntary neural processing of sound signals in noisy environments by means of magnetoencephalography. We contrasted two sound signal sequencing conditions: "constant sequencing" versus "random sequencing." Based on a pool of 16 different frequencies, either identical (constant sequencing) or pseudorandomly chosen (random sequencing) test frequencies were presented blockwise together with band-eliminated noises to nonattending subjects. The results demonstrated that the auditory evoked fields elicited in the constant sequencing condition were significantly enhanced compared with the random sequencing condition. However, the enhancement was not significantly different between different band-eliminated noise conditions. Thus the present study confirms that by constant sound signal sequencing under nonattentive listening the neural activity in human auditory cortex can be enhanced, but not sharpened. Our results indicate that bottom-up driven involuntary neural processing may mainly amplify excitatory neural networks, but may not effectively enhance inhibitory neural circuits.

The Neural Basis of Vocal Pitch Imitation in Humans.

PubMed

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

2016-04-01

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

Identifying a Network of Brain Regions Involved in Aversion-Related Processing: A Cross-Species Translational Investigation

PubMed Central

Hayes, Dave J.; Northoff, Georg

2011-01-01

The ability to detect and respond appropriately to aversive stimuli is essential for all organisms, from fruit flies to humans. This suggests the existence of a core neural network which mediates aversion-related processing. Human imaging studies on aversion have highlighted the involvement of various cortical regions, such as the prefrontal cortex, while animal studies have focused largely on subcortical regions like the periaqueductal gray and hypothalamus. However, whether and how these regions form a core neural network of aversion remains unclear. To help determine this, a translational cross-species investigation in humans (i.e., meta-analysis) and other animals (i.e., systematic review of functional neuroanatomy) was performed. Our results highlighted the recruitment of the anterior cingulate cortex, the anterior insula, and the amygdala as well as other subcortical (e.g., thalamus, midbrain) and cortical (e.g., orbitofrontal) regions in both animals and humans. Importantly, involvement of these regions remained independent of sensory modality. This study provides evidence for a core neural network mediating aversion in both animals and humans. This not only contributes to our understanding of the trans-species neural correlates of aversion but may also carry important implications for psychiatric disorders where abnormal aversive behavior can often be observed. PMID:22102836

A neural circuitry that emphasizes spinal feedback generates diverse behaviours of human locomotion

PubMed Central

Song, Seungmoon; Geyer, Hartmut

2015-01-01

Neural networks along the spinal cord contribute substantially to generating locomotion behaviours in humans and other legged animals. However, the neural circuitry involved in this spinal control remains unclear. We here propose a specific circuitry that emphasizes feedback integration over central pattern generation. The circuitry is based on neurophysiologically plausible muscle-reflex pathways that are organized in 10 spinal modules realizing limb functions essential to legged systems in stance and swing. These modules are combined with a supraspinal control layer that adjusts the desired foot placements and selects the leg that is to transition into swing control during double support. Using physics-based simulation, we test the proposed circuitry in a neuromuscular human model that includes neural transmission delays, musculotendon dynamics and compliant foot–ground contacts. We find that the control network is sufficient to compose steady and transitional 3-D locomotion behaviours including walking and running, acceleration and deceleration, slope and stair negotiation, turning, and deliberate obstacle avoidance. The results suggest feedback integration to be functionally more important than central pattern generation in human locomotion across behaviours. In addition, the proposed control architecture may serve as a guide in the search for the neurophysiological origin and circuitry of spinal control in humans. PMID:25920414

GABAergic modulation of human social interaction in a prisoner's dilemma model by acute administration of alprazolam.

PubMed

Lane, Scott D; Gowin, Joshua L

2009-10-01

Recent work in neuroeconomics has used game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner's dilemma model after acute administration of the γ-aminobutyric acid (GABA)-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated prisoner's dilemma game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics.

GABAergic modulation of human social interaction in a prisoner’s dilemma model via acute administration of alprazolam

PubMed Central

Lane, Scott D.; Gowin, Joshua L.

2010-01-01

Recent work in neuroeconomics has utilized game theory paradigms to examine neural systems that subserve human social interaction and decision making. Attempts to modify social interaction through pharmacological manipulation have been less common. Here we show dose-dependent modification of human social behavior in a prisoner’s dilemma (PD) model following acute administration of the GABA-A modulating benzodiazepine alprazolam. Nine healthy adults received doses of placebo, 0.5, 1.0, and 2.0 mg alprazolam in a counterbalanced within-subject design, while completing multiple test blocks per day on an iterated PD game. During test blocks in which peak subjective effects of alprazolam were reported, cooperative choices were significantly decreased as a function of dose. Consistent with previous reports showing that high acute doses of GABA-modulating drugs are associated with violence and other antisocial behavior, our data suggest that at sufficiently high doses, alprazolam can decrease cooperation. These behavioral changes may be facilitated by changes in inhibitory control facilitated by GABA. Game theory paradigms may prove useful in behavioral pharmacology studies seeking to measure social interaction, and may help inform the emerging field of neuroeconomics. PMID:19667972

Methylenetetrahydrofolate reductase and transcobalamin genetic polymorphisms in human spontaneous abortion: biological and clinical implications

PubMed Central

Zetterberg, Henrik

2004-01-01

The pathogenesis of human spontaneous abortion involves a complex interaction of several genetic and environmental factors. The firm association between increased homocysteine concentration and neural tube defects (NTD) has led to the hypothesis that high concentrations of homocysteine might be embryotoxic and lead to decreased fetal viability. There are several genetic polymorphisms that are associated with defects in folate- and vitamin B12-dependent homocysteine metabolism. The methylenetetrahydrofolate reductase (MTHFR) 677C>T and 1298A>C polymorphisms cause elevated homocysteine concentration and are associated with an increased risk of NTD. Additionally, low concentration of vitamin B12 (cobalamin) or transcobalamin that delivers vitamin B12 to the cells of the body leads to hyperhomocysteinemia and is associated with NTD. This effect involves the transcobalamin (TC) 776C>G polymorphism. Importantly, the biochemical consequences of these polymorphisms can be modified by folate and vitamin B12 supplementation. In this review, I focus on recent studies on the role of hyperhomocysteinemia-associated polymorphisms in the pathogenesis of human spontaneous abortion and discuss the possibility that periconceptional supplementation with folate and vitamin B12 might lower the incidence of miscarriage in women planning a pregnancy. PMID:14969589

Methylenetetrahydrofolate reductase and transcobalamin genetic polymorphisms in human spontaneous abortion: biological and clinical implications.

PubMed

Zetterberg, Henrik

2004-02-17

The pathogenesis of human spontaneous abortion involves a complex interaction of several genetic and environmental factors. The firm association between increased homocysteine concentration and neural tube defects (NTD) has led to the hypothesis that high concentrations of homocysteine might be embryotoxic and lead to decreased fetal viability. There are several genetic polymorphisms that are associated with defects in folate- and vitamin B12-dependent homocysteine metabolism. The methylenetetrahydrofolate reductase (MTHFR) 677C>T and 1298A>C polymorphisms cause elevated homocysteine concentration and are associated with an increased risk of NTD. Additionally, low concentration of vitamin B12 (cobalamin) or transcobalamin that delivers vitamin B12 to the cells of the body leads to hyperhomocysteinemia and is associated with NTD. This effect involves the transcobalamin (TC) 776C>G polymorphism. Importantly, the biochemical consequences of these polymorphisms can be modified by folate and vitamin B12 supplementation. In this review, I focus on recent studies on the role of hyperhomocysteinemia-associated polymorphisms in the pathogenesis of human spontaneous abortion and discuss the possibility that periconceptional supplementation with folate and vitamin B12 might lower the incidence of miscarriage in women planning a pregnancy.

Sequential and parallel image restoration: neural network implementations.

PubMed

Figueiredo, M T; Leitao, J N

1994-01-01

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

Understanding human aggression: New insights from neuroscience.

PubMed

Siegel, Allan; Victoroff, Jeff

2009-01-01

The present paper reviews and summarizes the basic findings concerning the nature of the neurobiological and behavioral characteristics of aggression and rage. For heuristic purposes, the types of aggression will be reduced to two categories - defensive rage (affective defense) and predatory attack. This approach helps explain both the behavioral properties of aggression as well as the underlying neural substrates and mechanisms of aggression both in animals and humans. Defensive rage behavior is activated by a threatening stimulus that is real or perceived and is associated with marked sympathetic output. This yields impulsivity with minimal cortical involvement. Predatory attack behavior in both animals and humans is generally planned, taking minutes, hours, days, weeks, months, or even years (with respect to humans) for it to occur and is directed upon a specific individual target; it reflects few outward sympathetic signs and is believed to require cortical involvement for its expression. Predatory attack requires activation of the lateral hypothalamus, while defensive rage requires activation of the medial hypothalamus and midbrain periaqueductal gray (PAG). Both forms of aggressive behavior are controlled by components of the limbic system, a region of the forebrain that is influenced by sensory inputs from the cerebral cortex and monoaminergic inputs from the brainstem reticular formation. Control of aggressive tendencies is partly modifiable through conditioning and related learning principles generated through the cerebral cortex.

The N170 component is sensitive to face-like stimuli: a study of Chinese Peking opera makeup.

PubMed

Liu, Tiantian; Mu, Shoukuan; He, Huamin; Zhang, Lingcong; Fan, Cong; Ren, Jie; Zhang, Mingming; He, Weiqi; Luo, Wenbo

2016-12-01

The N170 component is considered a neural marker of face-sensitive processing. In the present study, the face-sensitive N170 component of event-related potentials (ERPs) was investigated with a modified oddball paradigm using a natural face (the standard stimulus), human- and animal-like makeup stimuli, scrambled control images that mixed human- and animal-like makeup pieces, and a grey control image. Nineteen participants were instructed to respond within 1000 ms by pressing the ' F ' or ' J ' key in response to the standard or deviant stimuli, respectively. We simultaneously recorded ERPs, response accuracy, and reaction times. The behavioral results showed that the main effect of stimulus type was significant for reaction time, whereas there were no significant differences in response accuracies among stimulus types. In relation to the ERPs, N170 amplitudes elicited by human-like makeup stimuli, animal-like makeup stimuli, scrambled control images, and a grey control image progressively decreased. A right hemisphere advantage was observed in the N170 amplitudes for human-like makeup stimuli, animal-like makeup stimuli, and scrambled control images but not for grey control image. These results indicate that the N170 component is sensitive to face-like stimuli and reflect configural processing in face recognition.

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening

PubMed Central

Rupp, Andre; Celikel, Tansu

2018-01-01

Abstract Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration. PMID:29662943

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening.

PubMed

Górska, Urszula; Rupp, Andre; Boubenec, Yves; Celikel, Tansu; Englitz, Bernhard

2018-01-01

Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration.

Neural interface of mirror therapy in chronic stroke patients: a functional magnetic resonance imaging study.

PubMed

Bhasin, Ashu; Padma Srivastava, M V; Kumaran, Senthil S; Bhatia, Rohit; Mohanty, Sujata

2012-01-01

Recovery in stroke is mediated by neural plasticity. Neuro-restorative therapies improve recovery after stroke by promoting repair and function. Mirror neuron system (MNS) has been studied widely in humans in stroke and phantom sensations. Study subjects included 20 patients with chronic stroke and 10 healthy controls. Patients had clinical disease-severity scores, functional magnetic resonance imaging (fMRI) and diffuse tensor imaging (DTI) at baseline, 8 and at 24 weeks. Block design with alternate baseline and activation cycles was used with a total of 90 whole brain echo planar imaging (EPI) measurements (timed repetition (TR) = 4520 ms, timed echo (TE) = 44 ms, slices = 31, slice thickness = 4 mm, EPI factor 127, matrix = 128 × 128, FOV = 230 mm). Whole brain T1-weighted images were acquired using 3D sequence (MPRage) with 120 contiguous slices of 1.0 mm thickness. The mirror therapy was aimed via laptop system integrated with web camera, mirroring the movement of the unaffected hand. This therapy was administered for 5 days in a week for 60-90 min for 8 weeks. All the patients showed statistical significant improvement in Fugl Meyer and modified Barthel Index (P < 0.05) whereas the change in Medical Research Council (MRC) power grade was not significant post-therapy (8 weeks). There was an increase in the laterality index (LI) of ipsilesional BA 4 and BA 6 at 8 weeks exhibiting recruitment and focusing principles of neural plasticity. Mirror therapy simulated the "action-observation" hypothesis exhibiting recovery in patients with chronic stroke. Therapy induced cortical reorganization was also observed from our study.

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence

PubMed Central

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

2016-01-01

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain. PMID:27282108

Comparison of deep neural networks to spatio-temporal cortical dynamics of human visual object recognition reveals hierarchical correspondence.

PubMed

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

2016-06-10

The complex multi-stage architecture of cortical visual pathways provides the neural basis for efficient visual object recognition in humans. However, the stage-wise computations therein remain poorly understood. Here, we compared temporal (magnetoencephalography) and spatial (functional MRI) visual brain representations with representations in an artificial deep neural network (DNN) tuned to the statistics of real-world visual recognition. We showed that the DNN captured the stages of human visual processing in both time and space from early visual areas towards the dorsal and ventral streams. Further investigation of crucial DNN parameters revealed that while model architecture was important, training on real-world categorization was necessary to enforce spatio-temporal hierarchical relationships with the brain. Together our results provide an algorithmically informed view on the spatio-temporal dynamics of visual object recognition in the human visual brain.

Absence of visual experience modifies the neural basis of numerical thinking

PubMed Central

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

2016-01-01

In humans, the ability to reason about mathematical quantities depends on a frontoparietal network that includes the intraparietal sulcus (IPS). How do nature and nurture give rise to the neurobiology of numerical cognition? We asked how visual experience shapes the neural basis of numerical thinking by studying numerical cognition in congenitally blind individuals. Blind (n = 17) and blindfolded sighted (n = 19) participants solved math equations that varied in difficulty (e.g., 27 − 12 = x vs. 7 − 2 = x), and performed a control sentence comprehension task while undergoing fMRI. Whole-cortex analyses revealed that in both blind and sighted participants, the IPS and dorsolateral prefrontal cortices were more active during the math task than the language task, and activity in the IPS increased parametrically with equation difficulty. Thus, the classic frontoparietal number network is preserved in the total absence of visual experience. However, surprisingly, blind but not sighted individuals additionally recruited a subset of early visual areas during symbolic math calculation. The functional profile of these “visual” regions was identical to that of the IPS in blind but not sighted individuals. Furthermore, in blindness, number-responsive visual cortices exhibited increased functional connectivity with prefrontal and IPS regions that process numbers. We conclude that the frontoparietal number network develops independently of visual experience. In blindness, this number network colonizes parts of deafferented visual cortex. These results suggest that human cortex is highly functionally flexible early in life, and point to frontoparietal input as a mechanism of cross-modal plasticity in blindness. PMID:27638209

Dietary folate, but not choline, modifies neural tube defect risk in Shmt1 knockout mice.

PubMed

Beaudin, Anna E; Abarinov, Elena V; Malysheva, Olga; Perry, Cheryll A; Caudill, Marie; Stover, Patrick J

2012-01-01

Low dietary choline intake has been proposed to increase the risk of neural tube defects (NTDs) in human populations. Mice with reduced Shmt1 expression exhibit a higher frequency of NTDs when placed on a folate- and choline-deficient diet and may represent a model of human NTDs. The individual contribution of dietary folate and choline deficiency to NTD incidence in this mouse model is not known. To dissociate the effects of dietary folate and choline deficiency on Shmt1-related NTD sensitivity, we determined NTD incidence in embryos from Shmt1-null dams fed diets deficient in either folate or choline. Shmt1(+/+) and Shmt1(-/-) dams were maintained on a standard AIN93G diet (Dyets), an AIN93G diet lacking folate (FD), or an AIN93G diet lacking choline (CD). Virgin Shmt1(+/+) and Shmt1(-/-) dams were crossed with Shmt1(+/-) males, and embryos were examined for the presence of NTDs at embryonic day (E) 11.5 or E12.5. Exencephaly was observed only in Shmt1(-/-) embryos isolated from dams maintained on the FD diet (P = 0.004). Approximately 33% of Shmt1(-/-)embryos (n = 18) isolated from dams maintained on the FD diet exhibited exencephaly. NTDs were not observed in any embryos isolated from dams maintained on the CD (n = 100) or control (n = 152) diets or in any Shmt1(+/+) (n = 78) or Shmt1(+/-) embryos (n = 182). Maternal folate deficiency alone is sufficient to induce NTDs in response to embryonic Shmt1 disruption.

Synthesizing animal and human behavior research via neural network learning theory.

PubMed

Tryon, W W

1995-12-01

Animal and human research have been "divorced" since approximately 1968. Several recent articles have tried to persuade behavior therapists of the merits of animal research. Three reasons are given concerning why disinterest in animal research is so widespread: (1) functional explanations are given for animals, and cognitive explanations are given for humans; (2) serial symbol manipulating models are used to explain human behavior; and (3) human learning was assumed, thereby removing it as something to be explained. Brain-inspired connectionist neural networks, collectively referred to as neural network learning theory (NNLT), are briefly described, and a spectrum of their accomplishments from simple conditioning through speech is outlined. Five benefits that behavior therapists can derive from NNLT are described. They include (a) enhanced professional identity derived from a comprehensive learning theory, (b) improved interdisciplinary collaboration both clinically and scientifically, (c) renewed perceived relevance of animal research, (d) access to plausible proximal causal mechanisms capable of explaining operant conditioning, and (e) an inherently developmental perspective.

Face Recognition in Humans and Machines

NASA Astrophysics Data System (ADS)

O'Toole, Alice; Tistarelli, Massimo

The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

Face processing in adolescents with positive and negative threat bias.

PubMed

Sylvester, C M; Petersen, S E; Luby, J L; Barch, D M

2017-04-01

Individuals with anxiety disorders exhibit a 'vigilance-avoidance' pattern of attention to threatening stimuli when threatening and neutral stimuli are presented simultaneously, a phenomenon referred to as 'threat bias'. Modifying threat bias through cognitive retraining during adolescence reduces symptoms of anxiety, and so elucidating neural mechanisms of threat bias during adolescence is of high importance. We explored neural mechanisms by testing whether threat bias in adolescents is associated with generalized or threat-specific differences in the neural processing of faces. Subjects were categorized into those with (n = 25) and without (n = 27) threat avoidance based on a dot-probe task at average age 12.9 years. Threat avoidance in this cohort has previously been shown to index threat bias. Brain response to individually presented angry and neutral faces was assessed in a separate session using functional magnetic resonance imaging. Adolescents with threat avoidance exhibited lower activity for both angry and neutral faces relative to controls in several regions in the occipital, parietal, and temporal lobes involved in early visual and facial processing. Results generalized to happy, sad, and fearful faces. Adolescents with a prior history of depression and/or an anxiety disorder had lower activity for all faces in these same regions. A subset of results replicated in an independent dataset. Threat bias is associated with generalized, rather than threat-specific, differences in the neural processing of faces in adolescents. Findings may aid in the development of novel treatments for anxiety disorders that use attention training to modify threat bias.

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

NASA Astrophysics Data System (ADS)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Spike-timing dependent plasticity in primate corticospinal connections induced during free behavior

PubMed Central

Nishimura, Yukio; Perlmutter, Steve I.; Eaton, Ryan W.; Fetz, Eberhard E.

2014-01-01

Motor learning and functional recovery from brain damage involve changes in the strength of synaptic connections between neurons. Relevant in vivo evidence on the underlying cellular mechanisms remains limited and indirect. We found that the strength of neural connections between motor cortex and spinal cord in monkeys can be modified with an autonomous recurrent neural interface that delivers electrical stimuli in the spinal cord triggered by action potentials of corticospinal cells during free behavior. The activity-dependent stimulation modified the strength of the terminal connections of single corticomotoneuronal cells, consistent with a bidirectional spike-timing dependent plasticity rule previously derived from in vitro experiments. For some cells the changes lasted for days after the end of conditioning, but most effects eventually reverted to preconditioning levels. These results provide the first direct evidence of corticospinal synaptic plasticity in vivo at the level of single neurons induced by normal firing patterns during free behavior. PMID:24210907

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

PubMed

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

2016-11-01

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

Detecting phase transitions in a neural network and its application to classification of syndromes in traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Chen, J.; Xi, G.; Wang, W.

2008-02-01

Detecting phase transitions in neural networks (determined or random) presents a challenging subject for phase transitions play a key role in human brain activity. In this paper, we detect numerically phase transitions in two types of random neural network(RNN) under proper parameters.

The anatomy of the intralingual neural interconnections.

PubMed

Păduraru, Dumitru; Rusu, Mugurel Constantin

2013-08-01

The intrinsic lingual neural interconnections are overlooked. It was hypothesized that intralingual anatomically well defined anastomoses interconnect the somatic and autonomic neural systems of the tongue. It was thus aimed to evaluate the intralingual neural scaffold in human tongues. Human tongue samples (ten adult and one pediatric) were microdissected (4.5 magnification). In the interstitium between the genioglossus and hyoglossus muscles, the branches of the lingual nerve (LN) and the medial trunk of the hypoglossal nerve (HN) had a layered disposition of the outer and inner side, respectively, of the lingual artery with its periarterial plexus. Anastomoses of these three distinctive neural suppliers of tongue were recorded, as also were those of the LN with the lateral trunk of the HN and the anastomoses between successive terminal branches of the LN. Successive ansae linguales were joining the LN branches and the medial trunk of the HN. The intrinsic neural system of the tongue supports integrative functions and allows a better retrospective understanding of various experimental studies. The topographical pattern is useful for an accurate diagnosis of intralingual nerves on microscopic slides.

Making an Effort to Feel Positive: Insecure Attachment in Infancy Predicts the Neural Underpinnings of Emotion Regulation in Adulthood

ERIC Educational Resources Information Center

Moutsiana, Christina; Fearon, Pasco; Murray, Lynne; Cooper, Peter; Goodyer, Ian; Johnstone, Tom; Halligan, Sarah

2014-01-01

Background: Animal research indicates that the neural substrates of emotion regulation may be persistently altered by early environmental exposures. If similar processes operate in human development then this is significant, as the capacity to regulate emotional states is fundamental to human adaptation. Methods: We utilised a 22-year longitudinal…

Hydrogel scaffolds promote neural gene expression and structural reorganization in human astrocyte cultures.

PubMed

Knight, V Bleu; Serrano, Elba E

2017-01-01

Biomaterial scaffolds have the potential to enhance neuronal development and regeneration. Understanding the genetic responses of astrocytes and neurons to biomaterials could facilitate the development of synthetic environments that enable the specification of neural tissue organization with engineered scaffolds. In this study, we used high throughput transcriptomic and imaging methods to determine the impact of a hydrogel, PuraMatrix™, on human glial cells in vitro . Parallel studies were undertaken with cells grown in a monolayer environment on tissue culture polystyrene. When the Normal Human Astrocyte (NHA) cell line is grown in a hydrogel matrix environment, the glial cells adopt a structural organization that resembles that of neuronal-glial cocultures, where neurons form clusters that are distinct from the surrounding glia. Statistical analysis of next generation RNA sequencing data uncovered a set of genes that are differentially expressed in the monolayer and matrix hydrogel environments. Functional analysis demonstrated that hydrogel-upregulated genes can be grouped into three broad categories: neuronal differentiation and/or neural plasticity, response to neural insult, and sensory perception. Our results demonstrate that hydrogel biomaterials have the potential to transform human glial cell identity, and may have applications in the repair of damaged brain tissue.

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

PubMed

Sameiro-Barbosa, Catia M; Geiser, Eveline

2016-01-01

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

Modified DCTNet for audio signals classification

NASA Astrophysics Data System (ADS)

Xian, Yin; Pu, Yunchen; Gan, Zhe; Lu, Liang; Thompson, Andrew

2016-10-01

In this paper, we investigate DCTNet for audio signal classification. Its output feature is related to Cohen's class of time-frequency distributions. We introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature extraction. The A-DCTNet applies the idea of constant-Q transform, with its center frequencies of filterbanks geometrically spaced. The A-DCTNet is adaptive to different acoustic scales, and it can better capture low frequency acoustic information that is sensitive to human audio perception than features such as Mel-frequency spectral coefficients (MFSC). We use features extracted by the A-DCTNet as input for classifiers. Experimental results show that the A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art performance in bird song classification rate, and improve artist identification accuracy in music data. They demonstrate A-DCTNet's applicability to signal processing problems.

Multi-focus image fusion algorithm using NSCT and MPCNN

NASA Astrophysics Data System (ADS)

Liu, Kang; Wang, Lianli

2018-04-01

Based on nonsubsampled contourlet transform (NSCT) and modified pulse coupled neural network (MPCNN), the paper proposes an effective method of image fusion. Firstly, the paper decomposes the source image into the low-frequency components and high-frequency components using NSCT, and then processes the low-frequency components by regional statistical fusion rules. For high-frequency components, the paper calculates the spatial frequency (SF), which is input into MPCNN model to get relevant coefficients according to the fire-mapping image of MPCNN. At last, the paper restructures the final image by inverse transformation of low-frequency and high-frequency components. Compared with the wavelet transformation (WT) and the traditional NSCT algorithm, experimental results indicate that the method proposed in this paper achieves an improvement both in human visual perception and objective evaluation. It indicates that the method is effective, practical and good performance.

Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

NASA Astrophysics Data System (ADS)

Simeral, J. D.; Kim, S.-P.; Black, M. J.; Donoghue, J. P.; Hochberg, L. R.

2011-04-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor.

Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array

PubMed Central

Simeral, J D; Kim, S-P; Black, M J; Donoghue, J P; Hochberg, L R

2013-01-01

The ongoing pilot clinical trial of the BrainGate neural interface system aims in part to assess the feasibility of using neural activity obtained from a small-scale, chronically implanted, intracortical microelectrode array to provide control signals for a neural prosthesis system. Critical questions include how long implanted microelectrodes will record useful neural signals, how reliably those signals can be acquired and decoded, and how effectively they can be used to control various assistive technologies such as computers and robotic assistive devices, or to enable functional electrical stimulation of paralyzed muscles. Here we examined these questions by assessing neural cursor control and BrainGate system characteristics on five consecutive days 1000 days after implant of a 4 × 4 mm array of 100 microelectrodes in the motor cortex of a human with longstanding tetraplegia subsequent to a brainstem stroke. On each of five prospectively-selected days we performed time-amplitude sorting of neuronal spiking activity, trained a population-based Kalman velocity decoding filter combined with a linear discriminant click state classifier, and then assessed closed-loop point-and-click cursor control. The participant performed both an eight-target center-out task and a random target Fitts metric task which was adapted from a human-computer interaction ISO standard used to quantify performance of computer input devices. The neural interface system was further characterized by daily measurement of electrode impedances, unit waveforms and local field potentials. Across the five days, spiking signals were obtained from 41 of 96 electrodes and were successfully decoded to provide neural cursor point-and-click control with a mean task performance of 91.3% ± 0.1% (mean ± s.d.) correct target acquisition. Results across five consecutive days demonstrate that a neural interface system based on an intracortical microelectrode array can provide repeatable, accurate point-and-click control of a computer interface to an individual with tetraplegia 1000 days after implantation of this sensor. PMID:21436513

Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system

NASA Astrophysics Data System (ADS)

Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

2017-10-01

Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

Silicon synaptic transistor for hardware-based spiking neural network and neuromorphic system.

PubMed

Kim, Hyungjin; Hwang, Sungmin; Park, Jungjin; Park, Byung-Gook

2017-10-06

Brain-inspired neuromorphic systems have attracted much attention as new computing paradigms for power-efficient computation. Here, we report a silicon synaptic transistor with two electrically independent gates to realize a hardware-based neural network system without any switching components. The spike-timing dependent plasticity characteristics of the synaptic devices are measured and analyzed. With the help of the device model based on the measured data, the pattern recognition capability of the hardware-based spiking neural network systems is demonstrated using the modified national institute of standards and technology handwritten dataset. By comparing systems with and without inhibitory synapse part, it is confirmed that the inhibitory synapse part is an essential element in obtaining effective and high pattern classification capability.

Human and animal cognition: Continuity and discontinuity

PubMed Central

Premack, David

2007-01-01

Microscopic study of the human brain has revealed neural structures, enhanced wiring, and forms of connectivity among nerve cells not found in any animal, challenging the view that the human brain is simply an enlarged chimpanzee brain. On the other hand, cognitive studies have found animals to have abilities once thought unique to the human. This suggests a disparity between brain and mind. The suggestion is misleading. Cognitive research has not kept pace with neural research. Neural findings are based on microscopic study of the brain and are primarily cellular. Because cognition cannot be studied microscopically, we need to refine the study of cognition by using a different approach. In examining claims of similarity between animals and humans, one must ask: What are the dissimilarities? This approach prevents confusing similarity with equivalence. We follow this approach in examining eight cognitive cases—teaching, short-term memory, causal reasoning, planning, deception, transitive inference, theory of mind, and language—and find, in all cases, that similarities between animal and human abilities are small, dissimilarities large. There is no disparity between brain and mind. PMID:17717081

Faith-based perspectives on the use of chimeric organisms for medical research.

PubMed

Degeling, Chris; Irvine, Rob; Kerridge, Ian

2014-04-01

Efforts to advance our understanding of neurodegenerative diseases involve the creation chimeric organisms from human neural stem cells and primate embryos--known as prenatal chimeras. The existence of potential mentally complex beings with human and non-human neural apparatus raises fundamental questions as to the ethical permissibility of chimeric research and the moral status of the creatures it creates. Even as bioethicists find fewer reasons to be troubled by most types of chimeric organisms, social attitudes towards the non-human world are often influenced by religious beliefs. In this paper scholars representing eight major religious traditions provide a brief commentary on a hypothetical case concerning the development and use of prenatal human-animal chimeric primates in medical research. These commentaries reflect the plurality and complexity within and between religious discourses of our relationships with other species. Views on the moral status and permissibility of research on neural human animal chimeras vary. The authors provide an introduction to those who seek a better understanding of how faith-based perspectives might enter into biomedical ethics and public discourse towards forms of biomedical research that involves chimeric organisms.

Adaptation of the phase of the human linear vestibulo-ocular reflex (LVOR) and effects on the oculomotor neural integrator

NASA Technical Reports Server (NTRS)

Hegemann, S.; Shelhamer, M.; Kramer, P. D.; Zee, D. S.

2000-01-01

The phase of the translational linear VOR (LVOR) can be adaptively modified by exposure to a visual-vestibular mismatch. We extend here our earlier work on LVOR phase adaptation, and discuss the role of the oculomotor neural integrator. Ten subjects were oscillated laterally at 0.5 Hz, 0.3 g peak acceleration, while sitting upright on a linear sled. LVOR was assessed before and after adaptation with subjects tracking the remembered location of a target at 1 m in the dark. Phase and gain were measured by fitting sine waves to the desaccaded eye movements, and comparing sled and eye position. To adapt LVOR phase, the subject viewed a computer-generated stereoscopic visual display, at a virtual distance of 1 m, that moved so as to require either a phase lead or a phase lag of 53 deg. Adaptation lasted 20 min, during which subjects were oscillated at 0.5 Hz/0.3 g. Four of five subjects produced an adaptive change in the lag condition (range 4-45 deg), and each of five produced a change in the lead condition (range 19-56 deg), as requested. Changes in drift on eccentric gaze suggest that the oculomotor velocity-to-position integrator may be involved in the phase changes.

Characterization of pulse amplitude and pulse rate modulation for a human vestibular implant during acute electrical stimulation

NASA Astrophysics Data System (ADS)

Nguyen, T. A. K.; DiGiovanna, J.; Cavuscens, S.; Ranieri, M.; Guinand, N.; van de Berg, R.; Carpaneto, J.; Kingma, H.; Guyot, J.-P.; Micera, S.; Perez Fornos, A.

2016-08-01

Objective. The vestibular system provides essential information about balance and spatial orientation via the brain to other sensory and motor systems. Bilateral vestibular loss significantly reduces quality of life, but vestibular implants (VIs) have demonstrated potential to restore lost function. However, optimal electrical stimulation strategies have not yet been identified in patients. In this study, we compared the two most common strategies, pulse amplitude modulation (PAM) and pulse rate modulation (PRM), in patients. Approach. Four subjects with a modified cochlear implant including electrodes targeting the peripheral vestibular nerve branches were tested. Charge-equivalent PAM and PRM were applied after adaptation to baseline stimulation. Vestibulo-ocular reflex eye movement responses were recorded to evaluate stimulation efficacy during acute clinical testing sessions. Main results. PAM evoked larger amplitude eye movement responses than PRM. Eye movement response axes for lateral canal stimulation were marginally better aligned with PRM than with PAM. A neural network model was developed for the tested stimulation strategies to provide insights on possible neural mechanisms. This model suggested that PAM would consistently cause a larger ensemble firing rate of neurons and thus larger responses than PRM. Significance. Due to the larger magnitude of eye movement responses, our findings strongly suggest PAM as the preferred strategy for initial VI modulation.

How instructions modify perception: An fMRI study investigating brain areas involved in attributing human agency

PubMed Central

Stanley, James; Gowen, Emma; Miall, R. Christopher

2010-01-01

Behavioural studies suggest that the processing of movement stimuli is influenced by beliefs about the agency behind these actions. The current study examined how activity in social and action related brain areas differs when participants were instructed that identical movement stimuli were either human or computer generated. Participants viewed a series of point-light animation figures derived from motion-capture recordings of a moving actor, while functional magnetic resonance imaging (fMRI) was used to monitor patterns of neural activity. The stimuli were scrambled to produce a range of stimulus realism categories; furthermore, before each trial participants were told that they were about to view either a recording of human movement or a computer-simulated pattern of movement. Behavioural results suggested that agency instructions influenced participants' perceptions of the stimuli. The fMRI analysis indicated different functions within the paracingulate cortex: ventral paracingulate cortex was more active for human compared to computer agency instructed trials across all stimulus types, whereas dorsal paracingulate cortex was activated more highly in conflicting conditions (human instruction, low realism or vice versa). These findings support the hypothesis that ventral paracingulate encodes stimuli deemed to be of human origin, whereas dorsal paracingulate cortex is involved more in the ascertainment of human or intentional agency during the observation of ambiguous stimuli. Our results highlight the importance of prior instructions or beliefs on movement processing and the role of the paracingulate cortex in integrating prior knowledge with bottom-up stimuli. PMID:20398769

Direct electrical stimulation of human cortex evokes high gamma activity that predicts conscious somatosensory perception

NASA Astrophysics Data System (ADS)

Muller, Leah; Rolston, John D.; Fox, Neal P.; Knowlton, Robert; Rao, Vikram R.; Chang, Edward F.

2018-04-01

Objective. Direct electrical stimulation (DES) is a clinical gold standard for human brain mapping and readily evokes conscious percepts, yet the neurophysiological changes underlying these percepts are not well understood. Approach. To determine the neural correlates of DES, we stimulated the somatosensory cortex of ten human participants at frequency-amplitude combinations that both elicited and failed to elicit conscious percepts, meanwhile recording neural activity directly surrounding the stimulation site. We then compared the neural activity of perceived trials to that of non-perceived trials. Main results. We found that stimulation evokes distributed high gamma activity, which correlates with conscious perception better than stimulation parameters themselves. Significance. Our findings suggest that high gamma activity is a reliable biomarker for perception evoked by both natural and electrical stimuli.

Decoding Spontaneous Emotional States in the Human Brain

PubMed Central

Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.

2016-01-01

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

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.

Monkey Prefrontal Neurons Reflect Logical Operations for Cognitive Control in a Variant of the AX Continuous Performance Task (AX-CPT)

PubMed Central

Blackman, Rachael K.; Crowe, David A.; DeNicola, Adele L.; Sakellaridi, Sofia; MacDonald, Angus W.

2016-01-01

Cognitive control is the ability to modify the behavioral response to a stimulus based on internal representations of goals or rules. We sought to characterize neural mechanisms in prefrontal cortex associated with cognitive control in a context that would maximize the potential for future translational relevance to human neuropsychiatric disease. To that end, we trained monkeys to perform a dot-pattern variant of the AX continuous performance task that is used to measure cognitive control impairment in patients with schizophrenia (MacDonald, 2008; Jones et al., 2010). Here we describe how information processing for cognitive control in this task is related to neural activity patterns in prefrontal cortex of monkeys, to advance our understanding of how behavioral flexibility is implemented by prefrontal neurons in general, and to model neural signals in the healthy brain that may be disrupted to produce cognitive control deficits in schizophrenia. We found that the neural representation of stimuli in prefrontal cortex is strongly biased toward stimuli that inhibit prepotent or automatic responses. We also found that population signals encoding different stimuli were modulated to overlap in time specifically in the case that information from multiple stimuli had to be integrated to select a conditional response. Finally, population signals relating to the motor response were biased toward less frequent and therefore less automatic actions. These data relate neuronal activity patterns in prefrontal cortex to logical information processing operations required for cognitive control, and they characterize neural events that may be disrupted in schizophrenia. SIGNIFICANCE STATEMENT Functional imaging studies have demonstrated that cognitive control deficits in schizophrenia are associated with reduced activation of the dorsolateral prefrontal cortex (MacDonald et al., 2005). However, these data do not reveal how the disease has disrupted the function of prefrontal neurons to produce the observed deficits in cognitive control. Relating cognitive control to neurophysiological signals at a cellular level in prefrontal cortex is a necessary first step toward understanding how disruption of these signals could lead to cognitive control failure in neuropsychiatric disease. To that end, we translated a task that measures cognitive control deficits in patients with schizophrenia to monkeys and describe here how neural signals in prefrontal cortex relate to performance. PMID:27053213

The human body odor compound androstadienone increases neural conflict coupled to higher behavioral costs during an emotional Stroop task.

PubMed

Hornung, Jonas; Kogler, Lydia; Erb, Michael; Freiherr, Jessica; Derntl, Birgit

2018-05-01

The androgen derivative androstadienone (AND) is a substance found in human sweat and thus may act as human chemosignal. With the current experiment, we aimed to explore in which way AND affects interference processing during an emotional Stroop task which used human faces as target and emotional words as distractor stimuli. This was complemented by functional magnetic resonance imaging (fMRI) to unravel the neural mechanism of AND-action. Based on previous accounts we expected AND to increase neural activation in areas commonly implicated in evaluation of emotional face processing and to change neural activation in brain regions linked to interference processing. For this aim, a total of 80 healthy individuals (oral contraceptive users, luteal women, men) were tested twice on two consecutive days with an emotional Stroop task using fMRI. Our results suggest that AND increases interference processing in brain areas that are heavily recruited during emotional conflict. At the same time, correlation analyses revealed that this neural interference processing was paralleled by higher behavioral costs (response times) with higher interference related brain activation under AND. Furthermore, AND elicited higher activation in regions implicated in emotional face processing including right fusiform gyrus, inferior frontal gyrus and dorsomedial cortex. In this connection, neural activation was not coupled to behavioral outcome. Furthermore, despite previous accounts of increased hypothalamic activation under AND, we were not able to replicate this finding and discuss possible reasons for this discrepancy. To conclude, AND increased interference processing in regions heavily recruited during emotional conflict which was coupled to higher costs in resolving emotional conflicts with stronger interference-related brain activation under AND. At the moment it remains unclear whether these effects are due to changes in conflict detection or resolution. However, evidence most consistently suggests that AND does not draw attention to the most potent socio-emotional information (human faces) but rather highlights representations of emotional words. Copyright © 2018 Elsevier Inc. All rights reserved.

Neural correlate of human reciprocity in social interactions

PubMed Central

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

2013-01-01

Reciprocity plays a key role maintaining cooperation in society. However, little is known about the neural process that underpins human reciprocity during social interactions. Our neuroimaging study manipulated partner identity (computer, human) and strategy (random, tit-for-tat) in repeated prisoner's dilemma games and investigated the neural correlate of reciprocal interaction with humans. Reciprocal cooperation with humans but exploitation of computers by defection was associated with activation in the left amygdala. Amygdala activation was also positively and negatively correlated with a preference change for human partners following tit-for-tat and random strategies, respectively. The correlated activation represented the intensity of positive feeling toward reciprocal and negative feeling toward non-reciprocal partners, and so reflected reciprocity in social interaction. Reciprocity in social interaction, however, might plausibly be misinterpreted and so we also examined the neural coding of insight into the reciprocity of partners. Those with and without insight revealed differential brain activation across the reward-related circuitry (i.e., the right middle dorsolateral prefrontal cortex and dorsal caudate) and theory of mind (ToM) regions [i.e., ventromedial prefrontal cortex (VMPFC) and precuneus]. Among differential activations, activation in the precuneus, which accompanied deactivation of the VMPFC, was specific to those without insight into human partners who were engaged in a tit-for-tat strategy. This asymmetric (de)activation might involve specific contributions of ToM regions to the human search for reciprocity. Consequently, the intensity of emotion attached to human reciprocity was represented in the amygdala, whereas insight into the reciprocity of others was reflected in activation across the reward-related and ToM regions. This suggests the critical role of mentalizing, which was not equated with reward expectation during social interactions. PMID:24381534

Neural correlate of human reciprocity in social interactions.

PubMed

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

2013-01-01

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

Prototype-Incorporated Emotional Neural Network.

PubMed

Oyedotun, Oyebade K; Khashman, Adnan

2017-08-15

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

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.

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.

Method for neural network control of motion using real-time environmental feedback

NASA Technical Reports Server (NTRS)

Buckley, Theresa M. (Inventor)

1997-01-01

A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.

Frameworking memory and serotonergic markers.

PubMed

Meneses, Alfredo

2017-07-26

The evidence for neural markers and memory is continuously being revised, and as evidence continues to accumulate, herein, we frame earlier and new evidence. Hence, in this work, the aim is to provide an appropriate conceptual framework of serotonergic markers associated with neural activity and memory. Serotonin (5-hydroxytryptamine [5-HT]) has multiple pharmacological tools, well-characterized downstream signaling in mammals' species, and established 5-HT neural markers showing new insights about memory functions and dysfunctions, including receptors (5-HT1A/1B/1D, 5-HT2A/2B/2C, and 5-HT3-7), transporter (serotonin transporter [SERT]) and volume transmission present in brain areas involved in memory. Bidirectional influence occurs between 5-HT markers and memory/amnesia. A growing number of researchers report that memory, amnesia, or forgetting modifies neural markers. Diverse approaches support the translatability of using neural markers and cerebral functions/dysfunctions, including memory formation and amnesia. At least, 5-HT1A, 5-HT4, 5-HT6, and 5-HT7 receptors and SERT seem to be useful neural markers and therapeutic targets. Hence, several mechanisms cooperate to achieve synaptic plasticity or memory, including changes in the expression of neurotransmitter receptors and transporters.

“Theory of Food” as a Neurocognitive Adaptation

PubMed Central

Allen, John S.

2011-01-01

Human adult cognition emerges over the course of development via the interaction of multiple critical neurocognitive networks. These networks evolved in response to various selection pressures, many of which were modified or intensified by the intellectual, technological, and socio-cultural environments that arose in connection with the evolution of genus Homo. Networks related to language and theory of mind clearly play an important role in adult cognition. Given the critical importance of food to both basic survival and cultural interaction, a “theory of food” (analogous to theory of mind) may represent another complex network essential for normal cognition. I propose that theory of food evolved as an internal, cognitive representation of our diets in our minds. Like other complex cognitive abilities, it relies on complex and overlapping dedicated neural networks that develop in childhood under familial and cultural influences. Normative diets are analogous to first languages in that they are acquired without overt teaching; they are also difficult to change or modify once a critical period in development is passed. Theory of food suggests that cognitive activities related to food may be cognitive enhancers, which could have implications for maintaining healthy brain function in aging. PMID:22262561

"Theory of food" as a neurocognitive adaptation.

PubMed

Allen, John S

2012-01-01

Human adult cognition emerges over the course of development via the interaction of multiple critical neurocognitive networks. These networks evolved in response to various selection pressures, many of which were modified or intensified by the intellectual, technological, and sociocultural environments that arose in connection with the evolution of genus Homo. Networks related to language and theory of mind clearly play an important role in adult cognition. Given the critical importance of food to both basic survival and cultural interaction, a "theory of food" (analogous to theory of mind) may represent another complex network essential for normal cognition. I propose that theory of food evolved as an internal, cognitive representation of our diets in our minds. Like other complex cognitive abilities, it relies on complex and overlapping dedicated neural networks that develop in childhood under familial and cultural influences. Normative diets are analogous to first languages in that they are acquired without overt teaching; they are also difficult to change or modify once a critical period in development is passed. Theory of food suggests that cognitive activities related to food may be cognitive enhancers, which could have implications for maintaining healthy brain function in aging. Copyright © 2012 Wiley Periodicals, Inc.

Neural Networks

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

Smith, Patrick I.

2003-09-23

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neuralmore » networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing information [2]. Each one of these cells acts as a simple processor. When individual cells interact with one another, the complex abilities of the brain are made possible. In neural networks, the input or data are processed by a propagation function that adds up the values of all the incoming data. The ending value is then compared with a threshold or specific value. The resulting value must exceed the activation function value in order to become output. The activation function is a mathematical function that a neuron uses to produce an output referring to its input value. [8] Figure 1 depicts this process. Neural networks usually have three components an input, a hidden, and an output. These layers create the end result of the neural network. A real world example is a child associating the word dog with a picture. The child says dog and simultaneously looks a picture of a dog. The input is the spoken word ''dog'', the hidden is the brain processing, and the output will be the category of the word dog based on the picture. This illustration describes how a neural network functions.« less

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

PubMed

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

2016-09-15

Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune different neuronal subtypes in 3-D differentiation from hiPSCs and the differential cellular responses of region-specific neuronal subtypes to various biomolecules have not been fully investigated. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog signaling, this study provides knowledge on the differential susceptibility of region-specific neuronal subtypes derived from hiPSCs to different biomolecules in extracellular matrix remodeling and neurotoxicity. The findings are significant for understanding 3-D neural patterning of hiPSCs for the applications in brain organoid formation, neurological disease modeling, and drug discovery. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Transcriptional response of Hoxb genes to retinoid signalling is regionally restricted along the neural tube rostrocaudal axis.

PubMed

Carucci, Nicoletta; Cacci, Emanuele; Nisi, Paola S; Licursi, Valerio; Paul, Yu-Lee; Biagioni, Stefano; Negri, Rodolfo; Rugg-Gunn, Peter J; Lupo, Giuseppe

2017-04-01

During vertebrate neural development, positional information is largely specified by extracellular morphogens. Their distribution, however, is very dynamic due to the multiple roles played by the same signals in the developing and adult neural tissue. This suggests that neural progenitors are able to modify their competence to respond to morphogen signalling and autonomously maintain positional identities after their initial specification. In this work, we take advantage of in vitro culture systems of mouse neural stem/progenitor cells (NSPCs) to show that NSPCs isolated from rostral or caudal regions of the mouse neural tube are differentially responsive to retinoic acid (RA), a pivotal morphogen for the specification of posterior neural fates. Hoxb genes are among the best known RA direct targets in the neural tissue, yet we found that RA could promote their transcription only in caudal but not in rostral NSPCs. Correlating with these effects, key RA-responsive regulatory regions in the Hoxb cluster displayed opposite enrichment of activating or repressing histone marks in rostral and caudal NSPCs. Finally, RA was able to strengthen Hoxb chromatin activation in caudal NSPCs, but was ineffective on the repressed Hoxb chromatin of rostral NSPCs. These results suggest that the response of NSPCs to morphogen signalling across the rostrocaudal axis of the neural tube may be gated by the epigenetic configuration of target patterning genes, allowing long-term maintenance of intrinsic positional values in spite of continuously changing extrinsic signals.

Neural Circuitry of the Bilingual Mental Lexicon: Effect of Age of Second Language Acquisition

ERIC Educational Resources Information Center

Isel, Frederic; Baumgaertner, Annette; Thran, Johannes; Meisel, Jurgen M.; Buchel, Christian

2010-01-01

Numerous studies have proposed that changes of the human language faculty caused by neural maturation can explain the substantial differences in ultimate attainment of grammatical competences between first language (L1) acquirers and second language (L2) learners. However, little evidence on the effect of neural maturation on the attainment of…

Generation of H1 PAX6WT/EGFP reporter cells to purify PAX6 positive neural stem/progenitor cells.

PubMed

Wu, Wei; Liu, Juli; Su, Zhenghui; Li, Zhonghao; Ma, Ning; Huang, Ke; Zhou, Tiancheng; Wang, Linli

2018-08-25

Neural conversion from human pluripotent cells (hPSCs) is a potential therapy to neurological disease in the future. However, this is still limited by efficiency and stability of existed protocols used for neural induction from hPSCs. To overcome this obstacle, we developed a reporter system to screen PAX6 + neural progenitor/stem cells using transcription activator like effector nuclease (TALEN). We found that knock-in 2 A-EGFP cassette into PAX6 exon of human embryonic stem cells H1 with TALEN-based homology recombination could establish PAX6 WT/EGFP H1 reporter cell line fast and efficiently. This reporter cell line could differentiate into PAX6 and EGFP double positive neural progenitor/stem cells (NPCs/NSCs) after neural induction. Those PAX6 WT/EGFP NPCs could be purified, expanded and specified to post-mitotic neurons in vitro efficiently. With this reporter cell line, we also screened out 1 NPC-specific microRNA, hsa-miR-99a-5p, and 3 ESCs-enriched miRNAs, hsa-miR-302c-5p, hsa-miR-512-3p and hsa-miR-518 b. In conclusion, the TALEN-based neural stem cell screening system is safe and efficient and could help researcher to acquire adequate and pure neural progenitor cells for further application. Copyright © 2018 Elsevier Inc. All rights reserved.

Applying cybernetic technology to diagnose human pulmonary sounds.

PubMed

Chen, Mei-Yung; Chou, Cheng-Han

2014-06-01

Chest auscultation is a crucial and efficient method for diagnosing lung disease; however, it is a subjective process that relies on physician experience and the ability to differentiate between various sound patterns. Because the physiological signals composed of heart sounds and pulmonary sounds (PSs) are greater than 120 Hz and the human ear is not sensitive to low frequencies, successfully making diagnostic classifications is difficult. To solve this problem, we constructed various PS recognition systems for classifying six PS classes: vesicular breath sounds, bronchial breath sounds, tracheal breath sounds, crackles, wheezes, and stridor sounds. First, we used a piezoelectric microphone and data acquisition card to acquire PS signals and perform signal preprocessing. A wavelet transform was used for feature extraction, and the PS signals were decomposed into frequency subbands. Using a statistical method, we extracted 17 features that were used as the input vectors of a neural network. We proposed a 2-stage classifier combined with a back-propagation (BP) neural network and learning vector quantization (LVQ) neural network, which improves classification accuracy by using a haploid neural network. The receiver operating characteristic (ROC) curve verifies the high performance level of the neural network. To expand traditional auscultation methods, we constructed various PS diagnostic systems that can correctly classify the six common PSs. The proposed device overcomes the lack of human sensitivity to low-frequency sounds and various PS waves, characteristic values, and a spectral analysis charts are provided to elucidate the design of the human-machine interface.

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

PubMed

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

2017-12-01

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

Effects of acids on neural activity elicited by other taste stimuli in the rat Chorda tympani.

PubMed

Sakurai, N; Kanemura, F; Watanabe, K; Shimizu, Y; Tonosaki, K

2000-03-24

The purpose of this study is whether the gustatory neural response of taste cell to a binary mixture with threshold concentration of acid becomes synergistic or antagonistic can be estimated from the whole chorda tympani (CT) nerve in the rat. The present data demonstrate that acids are synergistic enhancer for sugars, and suppressor for NaCl and QHCl, but no effect to glycine and alanine. These results suggest that the acid was modifying the interaction of the other stimulus with its transduction mechanism.

Modification of existing human motor memories is enabled by primary cortical processing during memory reactivation.

PubMed

Censor, Nitzan; Dimyan, Michael A; Cohen, Leonardo G

2010-09-14

One of the most challenging tasks of the brain is to constantly update the internal neural representations of existing memories. Animal studies have used invasive methods such as direct microfusion of protein inhibitors to designated brain areas, in order to study the neural mechanisms underlying modification of already existing memories after their reactivation during recall [1-4]. Because such interventions are not possible in humans, it is not known how these neural processes operate in the human brain. In a series of experiments we show here that when an existing human motor memory is reactivated during recall, modification of the memory is blocked by virtual lesion [5] of the related primary cortical human brain area. The virtual lesion was induced by noninvasive repetitive transcranial magnetic stimulation guided by a frameless stereotactic brain navigation system and each subject's brain image. The results demonstrate that primary cortical processing in the human brain interacting with pre-existing reactivated memory traces is critical for successful modification of the existing related memory. Modulation of reactivated memories by noninvasive cortical stimulation may have important implications for human memory research and have far-reaching clinical applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

The Human Central Pattern Generator for Locomotion.

PubMed

Minassian, Karen; Hofstoetter, Ursula S; Dzeladini, Florin; Guertin, Pierre A; Ijspeert, Auke

2017-03-01

The ability of dedicated spinal circuits, referred to as central pattern generators (CPGs), to produce the basic rhythm and neural activation patterns underlying locomotion can be demonstrated under specific experimental conditions in reduced animal preparations. The existence of CPGs in humans is a matter of debate. Equally elusive is the contribution of CPGs to normal bipedal locomotion. To address these points, we focus on human studies that utilized spinal cord stimulation or pharmacological neuromodulation to generate rhythmic activity in individuals with spinal cord injury, and on neuromechanical modeling of human locomotion. In the absence of volitional motor control and step-specific sensory feedback, the human lumbar spinal cord can produce rhythmic muscle activation patterns that closely resemble CPG-induced neural activity of the isolated animal spinal cord. In this sense, CPGs in humans can be defined by the activity they produce. During normal locomotion, CPGs could contribute to the activation patterns during specific phases of the step cycle and simplify supraspinal control of step cycle frequency as a feedforward component to achieve a targeted speed. Determining how the human CPGs operate will be essential to advance the theory of neural control of locomotion and develop new locomotor neurorehabilitation paradigms.

Relaxed genetic control of cortical organization in human brains compared with chimpanzees

PubMed Central

Gómez-Robles, Aida; Hopkins, William D.; Schapiro, Steven J.; Sherwood, Chet C.

2015-01-01

The study of hominin brain evolution has focused largely on the neocortical expansion and reorganization undergone by humans as inferred from the endocranial fossil record. Comparisons of modern human brains with those of chimpanzees provide an additional line of evidence to define key neural traits that have emerged in human evolution and that underlie our unique behavioral specializations. In an attempt to identify fundamental developmental differences, we have estimated the genetic bases of brain size and cortical organization in chimpanzees and humans by studying phenotypic similarities between individuals with known kinship relationships. We show that, although heritability for brain size and cortical organization is high in chimpanzees, cerebral cortical anatomy is substantially less genetically heritable than brain size in humans, indicating greater plasticity and increased environmental influence on neurodevelopment in our species. This relaxed genetic control on cortical organization is especially marked in association areas and likely is related to underlying microstructural changes in neural circuitry. A major result of increased plasticity is that the development of neural circuits that underlie behavior is shaped by the environmental, social, and cultural context more intensively in humans than in other primate species, thus providing an anatomical basis for behavioral and cognitive evolution. PMID:26627234

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.

Monocrotophos Induces the Expression of Xenobiotic Metabolizing Cytochrome P450s (CYP2C8 and CYP3A4) and Neurotoxicity in Human Brain Cells.

PubMed

Tripathi, Vinay Kumar; Kumar, Vivek; Pandey, Ankita; Vatsa, Pankhi; Dhasmana, Anupam; Singh, Rajat Pratap; Appikonda, Sri Hari Chandan; Hwang, Inho; Lohani, Mohtashim

2017-07-01

Expression of various cytochrome P450s (CYPs) in mammalian brain cells is well documented. However, such studies are hampered in neural/glial cells of human origin due to nonavailability of human brain cells. To address this issue, we investigated the expression and inducibility of CYP2C8 and CYP3A4 and their responsiveness against cyclophosphamide (CPA) and organophosphorus pesticide monocrotophos (MCP), a known developmental neurotoxicant in human neural (SH-SY5Y) and glial (U373-MG) cell lines. CPA induced significant expression of CYP2C8 and CYP3A4 in both types of cells in a time-dependent manner. Neural cell line exhibited relatively higher constitutive and inducible expression of CYPs than the glial cell line. MCP exposure alone could not induce the significant expression of CYPs, whereas the cells preexposed to CPA showed a significant response to MCP. Similar to the case of CPA induced expressions, neural cells were found to be more vulnerable than glial cells. Our data indicate differential expressions of CYPs in cultured human neural and glial cell lines. The findings were synchronized with protein ligand docking studies, which showed a significant modulatory capacity of MCP by strong interaction with CYP regulators-CAR and PXR. Similarly, the known CYP inducer CPA has also shown significant high docking scores with the two studied CYP regulators. We also observed a significant induction in reactive oxygen species (ROS), lipid peroxides (LPO), micronucleus (MN), chromosomal aberration (CA), and reduction in reduced glutathione (GSH) and catalase following the exposure of MCP. Moreover, the expressions of apoptotic markers such as caspase-3, caspase-9, Bax, and p53 were significantly upregulated, whereas the levels of antiapoptotic marker, Bcl2, was downregulated after the exposure of MCP in both cell lines. These findings confirm the involvement of ROS-mediated oxidative stress, which subsequently triggers apoptosis pathways in both human neural (SH-SY5Y) and glial (U373-MG) cell lines following the exposure of MCP.

Strategies to improve electrode positioning and safety in cochlear implants.

PubMed

Rebscher, S J; Heilmann, M; Bruszewski, W; Talbot, N H; Snyder, R L; Merzenich, M M

1999-03-01

An injection-molded internal supporting rib has been produced to control the flexibility of silicone rubber encapsulated electrodes designed to electrically stimulate the auditory nerve in human subjects with severe to profound hearing loss. The rib molding dies, and molds for silicone rubber encapsulation of the electrode, were designed and machined using AutoCad and MasterCam software packages in a PC environment. After molding, the prototype plastic ribs were iteratively modified based on observations of the performance of the rib/silicone composite insert in a clear plastic model of the human scala tympani cavity. The rib-based electrodes were reliably inserted farther into these models, required less insertion force and were positioned closer to the target auditory neural elements than currently available cochlear implant electrodes. With further design improvements the injection-molded rib may also function to accurately support metal stimulating contacts and wire leads during assembly to significantly increase the manufacturing efficiency of these devices. This method to reliably control the mechanical properties of miniature implantable devices with multiple electrical leads may be valuable in other areas of biomedical device design.

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

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

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

A cone-shaped 3D carbon nanotube probe for neural recording.

PubMed

Su, Huan-Chieh; Lin, Chia-Min; Yen, Shiang-Jie; Chen, Yung-Chan; Chen, Chang-Hsiao; Yeh, Shih-Rung; Fang, Weileun; Chen, Hsin; Yao, Da-Jeng; Chang, Yen-Chung; Yew, Tri-Rung

2010-09-15

A novel cone-shaped 3D carbon nanotube (CNT) probe is proposed as an electrode for applications in neural recording. The electrode consists of CNTs synthesized on the cone-shaped Si (cs-Si) tip by catalytic thermal chemical vapor deposition (CVD). This probe exhibits a larger CNT surface area with the same footprint area and higher spatial resolution of neural recording compared to planar-type CNT electrodes. An approach to improve CNT characteristics by O(2) plasma treatment to modify the CNT surface will be also presented. Electrochemical characterization of O(2) plasma-treated 3D CNT (OT-CNT) probes revealed low impedance per unit area (∼64.5 Ω mm(-2)) at 1 kHz and high specific capacitance per unit area (∼2.5 mF cm(-2)). Furthermore, the OT-CNT probes were employed to record the neural signals of a crayfish nerve cord. Our findings suggest that OT-CNT probes have potential advantages as high spatial resolution and superb electrochemical properties which are suitable for neural recording applications. Copyright 2010 Elsevier B.V. All rights reserved.

Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

NASA Astrophysics Data System (ADS)

Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

2009-04-01

θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

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

PubMed

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

2017-12-01

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

Devices and circuits for nanoelectronic implementation of artificial neural networks

NASA Astrophysics Data System (ADS)

Turel, Ozgur

Biological neural networks perform complicated information processing tasks at speeds better than conventional computers based on conventional algorithms. This has inspired researchers to look into the way these networks function, and propose artificial networks that mimic their behavior. Unfortunately, most artificial neural networks, either software or hardware, do not provide either the speed or the complexity of a human brain. Nanoelectronics, with high density and low power dissipation that it provides, may be used in developing more efficient artificial neural networks. This work consists of two major contributions in this direction. First is the proposal of the CMOL concept, hybrid CMOS-molecular hardware [1-8]. CMOL may circumvent most of the problems in posed by molecular devices, such as low yield, vet provide high active device density, ˜1012/cm 2. The second contribution is CrossNets, artificial neural networks that are based on CMOL. We showed that CrossNets, with their fault tolerance, exceptional speed (˜ 4 to 6 orders of magnitude faster than biological neural networks) can perform any task any artificial neural network can perform. Moreover, there is a hope that if their integration scale is increased to that of human cerebral cortex (˜ 1010 neurons and ˜ 1014 synapses), they may be capable of performing more advanced tasks.

Artificial intelligence: Deep neural reasoning

NASA Astrophysics Data System (ADS)

Jaeger, Herbert

2016-10-01

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

Engineering the Brain: Ethical Issues and the Introduction of Neural Devices.

PubMed

Klein, Eran; Brown, Tim; Sample, Matthew; Truitt, Anjali R; Goering, Sara

2015-01-01

Neural devices now under development stand to interact with and alter the human brain in ways that may challenge standard notions of identity, normality, authority, responsibility, privacy and justice.

Wireless, High-Bandwidth Recordings from Non-Human Primate Motor Cortex using a Scalable 16-Ch Implantable Microsystem

PubMed Central

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

2013-01-01

A multitude of neuroengineering challenges exist today in creating practical, chronic multichannel neural recording systems for primate research and human clinical application. Specifically, a) the persistent wired connections limit patient mobility from the recording system, b) the transfer of high bandwidth signals to external (even distant) electronics normally forces premature data reduction, and c) the chronic susceptibility to infection due to the percutaneous nature of the implants all severely hinder the success of neural prosthetic systems. Here we detail one approach to overcome these limitations: an entirely implantable, wirelessly communicating, integrated neural recording microsystem, dubbed the Brain Implantable Chip (BIC). PMID:19964128

Neural autonomic control in orthostatic intolerance.

PubMed

Furlan, Raffaello; Barbic, Franca; Casella, Francesco; Severgnini, Giorgio; Zenoni, Luca; Mercieri, Angelo; Mangili, Ruggero; Costantino, Giorgio; Porta, Alberto

2009-10-01

Inability to maintain the upright position is manifested by a number of symptoms shared by either human pathophysiology and conditions following weightlessness or bed rest. Alterations of the neural sympathetic cardiovascular control have been suggested to be one of the potential underlying etiopathogenetic mechanisms in these conditions. We hypothesize that the study of the autonomic profile of human orthostatic intolerance syndromes may furnish a valuable insight into the complexity of the sympathetic alterations leading to a reduced gravitational tolerance. In the present paper we describe abnormalities both in the magnitude and in the pattern of the sympathetic neural firing observed in patients affected by orthostatic intolerance, attending the upright position. Also, we discuss similarity and differences in the neural sympathetic mechanisms regulating the cardiovascular system during the gravitational stimulus both in clinical syndromes and in subjects returning from space.

Non-invasive neural stimulation

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Neural tube defects in Waardenburg syndrome: A case report and review of the literature.

PubMed

Hart, Joseph; Miriyala, Kalpana

2017-09-01

Waardenburg syndrome type 1 (WS1) is an autosomal dominant genetic condition characterized by sensorineural deafness and pigment abnormalities, and is caused by variants in the PAX3 homeodomain. PAX3 variants have been associated with severe neural tube defects in mice and humans, but the frequency and clinical manifestations of this symptom remain largely unexplored in humans. Consequently, the role of PAX3 in human neural tube formation remains a study of interest, for clinical as well as research purposes. Though the association between spina bifida and WS1 is now well-documented, no study has attempted to characterize the range of spina bifida phenotypes seen in WS. Spina bifida encompasses several diagnoses with a wide scope of clinical severity, ranging from spina bifida occulta to myelomeningocele. We present a patient with Waardenburg syndrome type 1 caused by a novel missense variant in PAX3, presenting with myelomeningocele, Arnold-Chiari malformation, and hydrocephalus at birth. Additionally, we review 32 total cases of neural tube defects associated with WS. Including this report, there have been 15 published cases of myelomeningocele, 10 cases of unspecified spina bifida, 3 cases of sacral dimples, 0 cases of meningocele, and 4 cases of miscellaneous other neural tube defects. Though the true frequency of each phenotype cannot be determined from this collection of cases, these results demonstrate that Waardenburg syndrome type 1 carries a notable risk of severe neural tube defects, which has implications in prenatal and genetic counseling. © 2017 Wiley Periodicals, Inc.

Human-like brain hemispheric dominance in birdsong learning.

PubMed

Moorman, Sanne; Gobes, Sharon M H; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A; Bolhuis, Johan J

2012-07-31

Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca's area in the frontal lobe and Wernicke's area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke's area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms.

Use of a probabilistic neural network to reduce costs of selecting construction rock

USGS Publications Warehouse

Singer, Donald A.; Bliss, James D.

2003-01-01

Rocks used as construction aggregate in temperate climates deteriorate to differing degrees because of repeated freezing and thawing. The magnitude of the deterioration depends on the rock's properties. Aggregate, including crushed carbonate rock, is required to have minimum geotechnical qualities before it can be used in asphalt and concrete. In order to reduce chances of premature and expensive repairs, extensive freeze-thaw tests are conducted on potential construction rocks. These tests typically involve 300 freeze-thaw cycles and can take four to five months to complete. Less time consuming tests that (1) predict durability as well as the extended freeze-thaw test or that (2) reduce the number of rocks subject to the extended test, could save considerable amounts of money. Here we use a probabilistic neural network to try and predict durability as determined by the freeze-thaw test using four rock properties measured on 843 limestone samples from the Kansas Department of Transportation. Modified freeze-thaw tests and less time consuming specific gravity (dry), specific gravity (saturated), and modified absorption tests were conducted on each sample. Durability factors of 95 or more as determined from the extensive freeze-thaw tests are viewed as acceptable—rocks with values below 95 are rejected. If only the modified freeze-thaw test is used to predict which rocks are acceptable, about 45% are misclassified. When 421 randomly selected samples and all four standardized and scaled variables were used to train aprobabilistic neural network, the rate of misclassification of 422 independent validation samples dropped to 28%. The network was trained so that each class (group) and each variable had its own coefficient (sigma). In an attempt to reduce errors further, an additional class was added to the training data to predict durability values greater than 84 and less than 98, resulting in only 11% of the samples misclassified. About 43% of the test data was classed by the neural net into the middle group—these rocks should be subject to full freeze-thaw tests. Thus, use of the probabilistic neural network would meanthat the extended test would only need be applied to 43% of the samples, and 11% of the rocks classed as acceptable would fail early.

Neural decoding of collective wisdom with multi-brain computing.

PubMed

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

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally, our methods highlight the potential of multi-brain computing as a technique to rapidly and in parallel gather increased information about the environment as well as to access collective perceptual/cognitive choices and mental states. Copyright © 2011 Elsevier Inc. All rights reserved.

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

An Exploratory Application of Neural Networks to the Sortie Generation Forecasting Problem

DTIC Science & Technology

1991-09-01

modifiable--a configuration clearly inspired by neurophysiology . Rosenblatt and others effectively demonstrated that in using such an architectural...different perspectives (i.e., longitudinally and cross-sectionally), significance testing between prediction results may promote more enlightened network

An Automation Framework for Neural Nets that Learn

ERIC Educational Resources Information Center

Kilmer, W. L.; Arbib, M. A.

1973-01-01

A discussion of several types of formal neurons, many of whose functions are modifiable by their own input stimuli. The language of finite automata is used to mathematicize the problem of adaptation sufficiently to remove some ambiguities of Brindley's approach. (Author)

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography.

PubMed

Muller, Leah; Hamilton, Liberty S; Edwards, Erik; Bouchard, Kristofer E; Chang, Edward F

2016-10-01

Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

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

PubMed Central

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

2016-01-01

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

Spatial resolution dependence on spectral frequency in human speech cortex electrocorticography

NASA Astrophysics Data System (ADS)

Muller, Leah; Hamilton, Liberty S.; Edwards, Erik; Bouchard, Kristofer E.; Chang, Edward F.

2016-10-01

Objective. Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach. Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results. The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Human adenovirus serotypes 4p and 11p are efficiently expressed in cell lines of neural tumour origin.

PubMed

Skog, Johan; Mei, Ya-Fang; Wadell, Göran

2002-06-01

Most currently used adenovirus vectors are based upon adenovirus serotypes 2 and 5 (Ad2 and Ad5), which have limited efficiencies for gene transfer to human neural cells. Both serotypes bind to the known adenovirus receptor, CAR (coxsackievirus and adenovirus receptor), and have restricted cell tropism. The purpose of this study was to find vector candidates that are superior to Ad5 in infecting human neural tumours. Using flow cytometry, the vector candidates Ad4p, Ad11p and Ad17p were compared to the commonly used adenovirus vector Ad5v for their binding capacity to neural cell lines derived from glioblastoma, medulloblastoma and neuroblastoma cell lines. The production of viral structural proteins and the CAR-binding properties of the different serotypes were also assessed in these cells. Computer-based models of the fibre knobs of Ad4p and Ad17 were created based upon the crystallized fibre knob structure of adenoviruses and analysed for putative receptor-interacting regions that differed from the fibre knob of Ad5. The non CAR-binding vector candidate Ad11p showed clearly the best binding capacity to all of the neural cell lines, binding more than 90% of cells of all of the neural cell lines tested, in contrast to 20% or less for the commonly used vector Ad5v. Ad4p and Ad11p were also internalized and produced viral proteins more successfully than Ad5. Ad4p showed a low binding ability but a very efficient capacity for infection in cell culture. Ad17p virions neither bound or efficiently infected any of the neural cell lines studied.

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

NASA Astrophysics Data System (ADS)

Tanohata, Naoki; Seki, Hirokazu

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

Classification of time-of-flight secondary ion mass spectrometry spectra from complex Cu-Fe sulphides by principal component analysis and artificial neural networks.

PubMed

Kalegowda, Yogesh; Harmer, Sarah L

2013-01-08

Artificial neural network (ANN) and a hybrid principal component analysis-artificial neural network (PCA-ANN) classifiers have been successfully implemented for classification of static time-of-flight secondary ion mass spectrometry (ToF-SIMS) mass spectra collected from complex Cu-Fe sulphides (chalcopyrite, bornite, chalcocite and pyrite) at different flotation conditions. ANNs are very good pattern classifiers because of: their ability to learn and generalise patterns that are not linearly separable; their fault and noise tolerance capability; and high parallelism. In the first approach, fragments from the whole ToF-SIMS spectrum were used as input to the ANN, the model yielded high overall correct classification rates of 100% for feed samples, 88% for conditioned feed samples and 91% for Eh modified samples. In the second approach, the hybrid pattern classifier PCA-ANN was integrated. PCA is a very effective multivariate data analysis tool applied to enhance species features and reduce data dimensionality. Principal component (PC) scores which accounted for 95% of the raw spectral data variance, were used as input to the ANN, the model yielded high overall correct classification rates of 88% for conditioned feed samples and 95% for Eh modified samples. Copyright © 2012 Elsevier B.V. All rights reserved.

Electrospun Fibers for Spinal Cord Injury Research and Regeneration

PubMed Central

Schaub, Nicholas J.; Johnson, Christopher D.; Cooper, Blair

2016-01-01

Abstract Electrospinning is the process by which a scaffold containing micrometer and nanometer diameter fibers are drawn from a polymer solution or melt using a large voltage gradient between a polymer emitting source and a grounded collector. Ramakrishna and colleagues first investigated electrospun fibers for neural applications in 2004. After this initial study, electrospun fibers are increasingly investigated for neural tissue engineering applications. Electrospun fibers robustly support axonal regeneration within in vivo rodent models of spinal cord injury. These findings suggest the possibility of their eventual use within patients. Indeed, both spinal cord and peripheral nervous system regeneration research over the last several years shows that physical guidance cues induce recovery of limb, respiration, or bladder control in rodent models. Electrospun fibers may be an alternative to the peripheral nerve graft (PNG), because PNG autografts injure the patient and are limited in supply, and allografts risk host rejection. In addition, electrospun fibers can be engineered easily to confront new therapeutic challenges. Fibers can be modified to release therapies locally or can be physically modified to direct neural stem cell differentiation. This review summarizes the major findings and trends in the last decade of research, with a particular focus on spinal cord injury. This review also demonstrates how electrospun fibers can be used to study the central nervous system in vitro. PMID:26650778

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.

Inhibition of Excessive Monoamine Oxidase A/B Activity Protects Against Stress-induced Neuronal Death in Huntington Disease.

PubMed

Ooi, Jolene; Hayden, Michael R; Pouladi, Mahmoud A

2015-12-01

Monoamine oxidases (MAO) are important components of the homeostatic machinery that maintains the levels of monoamine neurotransmitters, including dopamine, in balance. Given the imbalance in dopamine levels observed in Huntington disease (HD), the aim of this study was to examine MAO activity in a mouse striatal cell model of HD and in human neural cells differentiated from control and HD patient-derived induced pluripotent stem cell (hiPSC) lines. We show that mouse striatal neural cells expressing mutant huntingtin (HTT) exhibit increased MAO expression and activity. We demonstrate using luciferase promoter assays that the increased MAO expression reflects enhanced epigenetic activation in striatal neural cells expressing mutant HTT. Using cellular stress paradigms, we further demonstrate that the increase in MAO activity in mutant striatal neural cells is accompanied by enhanced susceptibility to oxidative stress and impaired viability. Treatment of mutant striatal neural cells with MAO inhibitors ameliorated oxidative stress and improved cellular viability. Finally, we demonstrate that human HD neural cells exhibit increased MAO-A and MAO-B expression and activity. Altogether, this study demonstrates abnormal MAO expression and activity and suggests a potential use for MAO inhibitors in HD.

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

PubMed

Censor, Nitzan; Cohen, Leonardo G

2011-01-01

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

Simbrain 3.0: A flexible, visually-oriented neural network simulator.

PubMed

Tosi, Zachary; Yoshimi, Jeffrey

2016-11-01

Simbrain 3.0 is a software package for neural network design and analysis, which emphasizes flexibility (arbitrarily complex networks can be built using a suite of basic components) and a visually rich, intuitive interface. These features support both students and professionals. Students can study all of the major classes of neural networks in a familiar graphical setting, and can easily modify simulations, experimenting with networks and immediately seeing the results of their interventions. With the 3.0 release, Simbrain supports models on the order of thousands of neurons and a million synapses. This allows the same features that support education to support research professionals, who can now use the tool to quickly design, run, and analyze the behavior of large, highly customizable simulations. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

The Future of Contextual Fear Learning for PTSD Research: A Methodological Review of Neuroimaging Studies.

PubMed

Glenn, Daniel E; Risbrough, Victoria B; Simmons, Alan N; Acheson, Dean T; Stout, Daniel M

2017-10-21

There has been a great deal of recent interest in human models of contextual fear learning, particularly due to the use of such paradigms for investigating neural mechanisms related to the etiology of posttraumatic stress disorder. However, the construct of "context" in fear conditioning research is broad, and the operational definitions and methods used to investigate contextual fear learning in humans are wide ranging and lack specificity, making it difficult to interpret findings about neural activity. Here we will review neuroimaging studies of contextual fear acquisition in humans. We will discuss the methodology associated with four broad categories of how contextual fear learning is manipulated in imaging studies (colored backgrounds, static picture backgrounds, virtual reality, and configural stimuli) and highlight findings for the primary neural circuitry involved in each paradigm. Additionally, we will offer methodological recommendations for human studies of contextual fear acquisition, including using stimuli that distinguish configural learning from discrete cue associations and clarifying how context is experimentally operationalized.

Nuclear translocation of PKCα isoenzyme is involved in neurogenic commitment of human neural crest-derived periodontal ligament stem cells.

PubMed

Trubiani, Oriana; Guarnieri, Simone; Diomede, Francesca; Mariggiò, Maria A; Merciaro, Ilaria; Morabito, Caterina; Cavalcanti, Marcos F X B; Cocco, Lucio; Ramazzotti, Giulia

2016-11-01

Stem cells isolated from human adult tissue niche represent a promising source for neural differentiation. Human Periodontal Ligament Stem Cells (hPDLSCs) originating from the neural crest are particularly suitable for induction of neural commitment. In this study, under xeno-free culture conditions, in undifferentiated hPDLSCs and in hPDLSCs induced to neuronal differentiation by basic Fibroblast Growth Factor, the level of some neural markers have been analyzed. The hPDLSCs spontaneously express Nestin, a neural progenitor marker. In these cells, the neurogenic process induced to rearrange the cytoskeleton, form neurospheres and express higher levels of Nestin and Tyrosine Hydroxylase, indicating neural induction. Protein Kinase C (PKC) is highly expressed in neural tissue and has a key role in neuronal functions. In particular the Ca(2+) and diacylglycerol-dependent activation of PKCα isozyme is involved in the regulation of neuronal differentiation. Another main component of the pathways controlling neuronal differentiation is the Growth Associated Protein-43 (GAP-43), whose activity is strictly regulated by PKC. The aim of this study is to investigate the role of PKCα/GAP-43 nuclear signal transduction pathway during neuronal commitment of hPDLSCs. During hPDLSCs neurogenic commitment the levels of p-PKC and p-GAP-43 increased both in cytoplasmic and nuclear compartment. PKCα nuclear translocation induced GAP-43 movement to the cytoplasm, where it is known to regulate growth cone dynamics and neuronal differentiation. Moreover, the degree of cytosolic Ca(2+) mobilization appeared to be more pronounced in differentiated hPDLSCs than in undifferentiated cells. This study provides evidences of a new PKCα/GAP-43 nuclear signalling pathway that controls neuronal differentiation in hPDLSCs, leading the way to a potential use of these cells in cell-based therapy in neurodegenerative diseases. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

What can stimulus polarity and interphase gap tell us about auditory nerve function in cochlear-implant recipients?

PubMed

Hughes, Michelle L; Choi, Sangsook; Glickman, Erin

2018-03-01

Modeling studies suggest that differences in neural responses between polarities might reflect underlying neural health. Specifically, large differences in electrically evoked compound action potential (eCAP) amplitudes and amplitude-growth-function (AGF) slopes between polarities might reflect poorer peripheral neural health, whereas more similar eCAP responses between polarities might reflect better neural health. The interphase gap (IPG) has also been shown to relate to neural survival in animal studies. Specifically, healthy neurons exhibit larger eCAP amplitudes, lower thresholds, and steeper AGF slopes for increasing IPGs. In ears with poorer neural survival, these changes in neural responses are generally less apparent with increasing IPG. The primary goal of this study was to examine the combined effects of stimulus polarity and IPG within and across subjects to determine whether both measures represent similar underlying mechanisms related to neural health. With the exception of one measure in one group of subjects, results showed that polarity and IPG effects were generally not correlated in a systematic or predictable way. This suggests that these two effects might represent somewhat different aspects of neural health, such as differences in site of excitation versus integrative membrane characteristics, for example. Overall, the results from this study suggest that the underlying mechanisms that contribute to polarity and IPG effects in human CI recipients might be difficult to determine from animal models that do not exhibit the same anatomy, variance in etiology, electrode placement, and duration of deafness as humans. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

A Brain for Speech. Evolutionary Continuity in Primate and Human Auditory-Vocal Processing

PubMed Central

Aboitiz, Francisco

2018-01-01

In this review article, I propose a continuous evolution from the auditory-vocal apparatus and its mechanisms of neural control in non-human primates, to the peripheral organs and the neural control of human speech. Although there is an overall conservatism both in peripheral systems and in central neural circuits, a few changes were critical for the expansion of vocal plasticity and the elaboration of proto-speech in early humans. Two of the most relevant changes were the acquisition of direct cortical control of the vocal fold musculature and the consolidation of an auditory-vocal articulatory circuit, encompassing auditory areas in the temporoparietal junction and prefrontal and motor areas in the frontal cortex. This articulatory loop, also referred to as the phonological loop, enhanced vocal working memory capacity, enabling early humans to learn increasingly complex utterances. The auditory-vocal circuit became progressively coupled to multimodal systems conveying information about objects and events, which gradually led to the acquisition of modern speech. Gestural communication accompanies the development of vocal communication since very early in human evolution, and although both systems co-evolved tightly in the beginning, at some point speech became the main channel of communication. PMID:29636657

Long-term hydrocephalus alters the cytoarchitecture of the adult subventricular zone.

PubMed

Campos-Ordoñez, Tania; Herranz-Pérez, Vicente; Chaichana, Kaisorn L; Rincon-Torroella, Jordina; Rigamonti, Daniele; García-Verdugo, Jose M; Quiñones-Hinojosa, Alfredo; Gonzalez-Perez, Oscar

2014-11-01

Hydrocephalus can develop secondarily to a disturbance in production, flow and/or absorption of cerebrospinal fluid. Experimental models of hydrocephalus, especially subacute and chronic hydrocephalus, are few and limited, and the effects of hydrocephalus on the subventricular zone are unclear. The aim of this study was to analyze the effects of long-term obstructive hydrocephalus on the subventricular zone, which is the neurogenic niche lining the lateral ventricles. We developed a new method to induce hydrocephalus by obstructing the aqueduct of Sylvius in the mouse brain, thus simulating aqueductal stenosis in humans. In 120-day-old rodents (n=18 per group), the degree of ventricular dilatation and cellular composition of the subventricular zone were studied by immunofluorescence and transmission electron microscopy. In adult patients (age>18years), the sizes of the subventricular zone, corpus callosum, and internal capsule were analyzed by magnetic resonance images obtained from patients with and without aqueductal stenosis (n=25 per group). Mice with 60-day hydrocephalus had a reduced number of Ki67+ and doublecortin+cells on immunofluorescence, as well as decreased number of neural progenitors and neuroblasts in the subventricular zone on electron microscopy analysis as compared to non-hydrocephalic mice. Remarkably, a number of extracellular matrix structures (fractones) contacting the ventricular lumen and blood vessels were also observed around the subventricular zone in mice with hydrocephalus. In humans, the widths of the subventricular zone, corpus callosum, and internal capsule in patients with aqueductal stenosis were significantly smaller than age and gender-matched patients without aqueductal stenosis. In summary, supratentorial hydrocephalus reduces the proliferation rate of neural progenitors and modifies the cytoarchitecture and extracellular matrix compounds of the subventricular zone. In humans, this similar process reduces the subventricular niche as well as the width of corpus callosum and internal capsule. Copyright © 2014 Elsevier Inc. All rights reserved.

Efficient stage-specific differentiation of human pluripotent stem cells toward retinal photoreceptor cells.

PubMed

Mellough, Carla B; Sernagor, Evelyne; Moreno-Gimeno, Inmaculada; Steel, David H W; Lako, Majlinda

2012-04-01

Recent successes in the stem cell field have identified some of the key chemical and biological cues which drive photoreceptor derivation from human embryonic stem cells (hESC) and human induced pluripotent stem cells (hiPSC); however, the efficiency of this process is variable. We have designed a three-step photoreceptor differentiation protocol combining previously published methods that direct the differentiation of hESC and hiPSC toward a retinal lineage, which we further modified with additional supplements selected on the basis of reports from the eye field and retinal development. We report that hESC and hiPSC differentiating under our regimen over a 60 day period sequentially acquire markers associated with neural, retinal field, retinal pigmented epithelium and photoreceptor cells, including mature photoreceptor markers OPN1SW and RHODOPSIN with a higher efficiency than previously reported. In addition, we report the ability of hESC and hiPSC cultures to generate neural and retinal phenotypes under minimal culture conditions, which may be linked to their ability to endogenously upregulate the expression of a range of factors important for retinal cell type specification. However, cultures that were differentiated with full supplementation under our photoreceptor-induction regimen achieve this within a significantly shorter time frame and show a substantial increase in the expression of photoreceptor-specific markers in comparison to cultures differentiated under minimal conditions. Interestingly, cultures supplemented only with B27 and/or N2 displayed comparable differentiation efficiency to those under full supplementation, indicating a key role for B27 and N2 during the differentiation process. Furthermore, our data highlight an important role for Dkk1 and Noggin in enhancing the differentiation of hESC and hiPSC toward retinal progenitor cells and photoreceptor precursors during the early stages of differentiation, while suggesting that further maturation of these cells into photoreceptors may not require additional factors and can ensue under minimal culture conditions. Copyright © 2012 AlphaMed Press.

Human motor cortical activity recorded with Micro-ECoG electrodes, during individual finger movements.

PubMed

Wang, W; Degenhart, A D; Collinger, J L; Vinjamuri, R; Sudre, G P; Adelson, P D; Holder, D L; Leuthardt, E C; Moran, D W; Boninger, M L; Schwartz, A B; Crammond, D J; Tyler-Kabara, E C; Weber, D J

2009-01-01

In this study human motor cortical activity was recorded with a customized micro-ECoG grid during individual finger movements. The quality of the recorded neural signals was characterized in the frequency domain from three different perspectives: (1) coherence between neural signals recorded from different electrodes, (2) modulation of neural signals by finger movement, and (3) accuracy of finger movement decoding. It was found that, for the high frequency band (60-120 Hz), coherence between neighboring micro-ECoG electrodes was 0.3. In addition, the high frequency band showed significant modulation by finger movement both temporally and spatially, and a classification accuracy of 73% (chance level: 20%) was achieved for individual finger movement using neural signals recorded from the micro-ECoG grid. These results suggest that the micro-ECoG grid presented here offers sufficient spatial and temporal resolution for the development of minimally-invasive brain-computer interface applications.

Nonequilibrium landscape theory of neural networks.

PubMed

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

2013-11-05

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

Nonequilibrium landscape theory of neural networks

PubMed Central

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

2013-01-01

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

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

PubMed Central

Jackson, Stuart; Blake, Randolph

2010-01-01

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

Neural correlates for perception of companion animal photographs.

PubMed

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

2016-05-01

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

Growth kinetics of borided layers: Artificial neural network and least square approaches

NASA Astrophysics Data System (ADS)

Campos, I.; Islas, M.; Ramírez, G.; VillaVelázquez, C.; Mota, C.

2007-05-01

The present study evaluates the growth kinetics of the boride layer Fe 2B in AISI 1045 steel, by means of neural networks and the least square techniques. The Fe 2B phase was formed at the material surface using the paste boriding process. The surface boron potential was modified considering different boron paste thicknesses, with exposure times of 2, 4 and 6 h, and treatment temperatures of 1193, 1223 and 1273 K. The neural network and the least square models were set by the layer thickness of Fe 2B phase, and assuming that the growth of the boride layer follows a parabolic law. The reliability of the techniques used is compared with a set of experiments at a temperature of 1223 K with 5 h of treatment time and boron potentials of 2, 3, 4 and 5 mm. The results of the Fe 2B layer thicknesses show a mean error of 5.31% for the neural network and 3.42% for the least square method.

Can beneficial ends justify lying? Neural responses to the passive reception of lies and truth-telling with beneficial and harmful monetary outcomes

PubMed Central

Weber, Bernd

2016-01-01

Can beneficial ends justify morally questionable means? To investigate how monetary outcomes influence the neural responses to lying, we used a modified, cheap talk sender–receiver game in which participants were the direct recipients of lies and truthful statements resulting in either beneficial or harmful monetary outcomes. Both truth-telling (vs lying) as well as beneficial (vs harmful) outcomes elicited higher activity in the nucleus accumbens. Lying (vs truth-telling) elicited higher activity in the supplementary motor area, right inferior frontal gyrus, superior temporal sulcus and left anterior insula. Moreover, the significant interaction effect was found in the left amygdala, which showed that the monetary outcomes modulated the neural activity in the left amygdala only when truth-telling rather than lying. Our study identified a neural network associated with the reception of lies and truth, including the regions linked to the reward process, recognition and emotional experiences of being treated (dis)honestly. PMID:26454816

Adaptively combined FIR and functional link artificial neural network equalizer for nonlinear communication channel.

PubMed

Zhao, Haiquan; Zhang, Jiashu

2009-04-01

This paper proposes a novel computational efficient adaptive nonlinear equalizer based on combination of finite impulse response (FIR) filter and functional link artificial neural network (CFFLANN) to compensate linear and nonlinear distortions in nonlinear communication channel. This convex nonlinear combination results in improving the speed while retaining the lower steady-state error. In addition, since the CFFLANN needs not the hidden layers, which exist in conventional neural-network-based equalizers, it exhibits a simpler structure than the traditional neural networks (NNs) and can require less computational burden during the training mode. Moreover, appropriate adaptation algorithm for the proposed equalizer is derived by the modified least mean square (MLMS). Results obtained from the simulations clearly show that the proposed equalizer using the MLMS algorithm can availably eliminate various intensity linear and nonlinear distortions, and be provided with better anti-jamming performance. Furthermore, comparisons of the mean squared error (MSE), the bit error rate (BER), and the effect of eigenvalue ratio (EVR) of input correlation matrix are presented.

Evolving RBF neural networks for adaptive soft-sensor design.

PubMed

Alexandridis, Alex

2013-12-01

This work presents an adaptive framework for building soft-sensors based on radial basis function (RBF) neural network models. The adaptive fuzzy means algorithm is utilized in order to evolve an RBF network, which approximates the unknown system based on input-output data from it. The methodology gradually builds the RBF network model, based on two separate levels of adaptation: On the first level, the structure of the hidden layer is modified by adding or deleting RBF centers, while on the second level, the synaptic weights are adjusted with the recursive least squares with exponential forgetting algorithm. The proposed approach is tested on two different systems, namely a simulated nonlinear DC Motor and a real industrial reactor. The results show that the produced soft-sensors can be successfully applied to model the two nonlinear systems. A comparison with two different adaptive modeling techniques, namely a dynamic evolving neural-fuzzy inference system (DENFIS) and neural networks trained with online backpropagation, highlights the advantages of the proposed methodology.

Stochastic Spiking Neural Networks Enabled by Magnetic Tunnel Junctions: From Nontelegraphic to Telegraphic Switching Regimes

NASA Astrophysics Data System (ADS)

Liyanagedera, Chamika M.; Sengupta, Abhronil; Jaiswal, Akhilesh; Roy, Kaushik

2017-12-01

Stochastic spiking neural networks based on nanoelectronic spin devices can be a possible pathway to achieving "brainlike" compact and energy-efficient cognitive intelligence. The computational model attempt to exploit the intrinsic device stochasticity of nanoelectronic synaptic or neural components to perform learning or inference. However, there has been limited analysis on the scaling effect of stochastic spin devices and its impact on the operation of such stochastic networks at the system level. This work attempts to explore the design space and analyze the performance of nanomagnet-based stochastic neuromorphic computing architectures for magnets with different barrier heights. We illustrate how the underlying network architecture must be modified to account for the random telegraphic switching behavior displayed by magnets with low barrier heights as they are scaled into the superparamagnetic regime. We perform a device-to-system-level analysis on a deep neural-network architecture for a digit-recognition problem on the MNIST data set.

Cortical Coupling Reflects Bayesian Belief Updating in the Deployment of Spatial Attention.

PubMed

Vossel, Simone; Mathys, Christoph; Stephan, Klaas E; Friston, Karl J

2015-08-19

The deployment of visuospatial attention and the programming of saccades are governed by the inferred likelihood of events. In the present study, we combined computational modeling of psychophysical data with fMRI to characterize the computational and neural mechanisms underlying this flexible attentional control. Sixteen healthy human subjects performed a modified version of Posner's location-cueing paradigm in which the percentage of cue validity varied in time and the targets required saccadic responses. Trialwise estimates of the certainty (precision) of the prediction that the target would appear at the cued location were derived from a hierarchical Bayesian model fitted to individual trialwise saccadic response speeds. Trial-specific model parameters then entered analyses of fMRI data as parametric regressors. Moreover, dynamic causal modeling (DCM) was performed to identify the most likely functional architecture of the attentional reorienting network and its modulation by (Bayes-optimal) precision-dependent attention. While the frontal eye fields (FEFs), intraparietal sulcus, and temporoparietal junction (TPJ) of both hemispheres showed higher activity on invalid relative to valid trials, reorienting responses in right FEF, TPJ, and the putamen were significantly modulated by precision-dependent attention. Our DCM results suggested that the precision of predictability underlies the attentional modulation of the coupling of TPJ with FEF and the putamen. Our results shed new light on the computational architecture and neuronal network dynamics underlying the context-sensitive deployment of visuospatial attention. Spatial attention and its neural correlates in the human brain have been studied extensively with the help of fMRI and cueing paradigms in which the location of targets is pre-cued on a trial-by-trial basis. One aspect that has so far been neglected concerns the question of how the brain forms attentional expectancies when no a priori probability information is available but needs to be inferred from observations. This study elucidates the computational and neural mechanisms under which probabilistic inference governs attentional deployment. Our results show that Bayesian belief updating explains changes in cortical connectivity; in that directional influences from the temporoparietal junction on the frontal eye fields and the putamen were modulated by (Bayes-optimal) updates. Copyright © 2015 Vossel et al.

The cognitive neuroscience of prehension: recent developments.

PubMed

Grafton, Scott T

2010-08-01

Prehension, the capacity to reach and grasp, is the key behavior that allows humans to change their environment. It continues to serve as a remarkable experimental test case for probing the cognitive architecture of goal-oriented action. This review focuses on recent experimental evidence that enhances or modifies how we might conceptualize the neural substrates of prehension. Emphasis is placed on studies that consider how precision grasps are selected and transformed into motor commands. Then, the mechanisms that extract action relevant information from vision and touch are considered. These include consideration of how parallel perceptual networks within parietal cortex, along with the ventral stream, are connected and share information to achieve common motor goals. On-line control of grasping action is discussed within a state estimation framework. The review ends with a consideration about how prehension fits within larger action repertoires that solve more complex goals and the possible cortical architectures needed to organize these actions.

Extracellular vesicles are independent metabolic units with asparaginase activity

PubMed Central

Leonardi, Tommaso; Costa, Ana S. H.; Cossetti, Chiara; Peruzzotti-Jametti, Luca; Bernstock, Joshua D.; Saini, Harpreet K.; Gelati, Maurizio; Vescovi, Angelo Luigi; Bastos, Carlos; Faria, Nuno; Occhipinti, Luigi G.; Enright, Anton J.; Frezza, Christian; Pluchino, Stefano

2017-01-01

Extracellular vesicles (EVs) are membrane particles involved in the exchange of a broad range of bioactive molecules between cells and the microenvironment. While it has been shown that cells can traffic metabolic enzymes via EVs much remains to be elucidated with regard to their intrinsic metabolic activity. Accordingly, herein we assessed the ability of neural stem/progenitor cell (NSC)-derived EVs to consume and produce metabolites. Both our metabolomics and functional analyses revealed that EVs harbour L-asparaginase activity catalysed by the enzyme Asparaginase-like protein 1 (Asrgl1). Critically, we show that Asrgl1 activity is selective for asparagine and is devoid of glutaminase activity. We found that mouse and human NSC-derived EVs traffic ASRGL1. Our results demonstrate for the first time that NSC EVs function as independent, extracellular metabolic units able to modify the concentrations of critical nutrients, with the potential to affect the physiology of their microenvironment. PMID:28671681

Neural Correlates of Intentional Communication

PubMed Central

Noordzij, Matthijs L.; Newman-Norlund, Sarah E.; de Ruiter, Jan Peter; Hagoort, Peter; Levinson, Stephen C.; Toni, Ivan

2010-01-01

We know a great deal about the neurophysiological mechanisms supporting instrumental actions, i.e., actions designed to alter the physical state of the environment. In contrast, little is known about our ability to select communicative actions, i.e., actions directly designed to modify the mental state of another agent. We have recently provided novel empirical evidence for a mechanism in which a communicator selects his actions on the basis of a prediction of the communicative intentions that an addressee is most likely to attribute to those actions. The main novelty of those findings was that this prediction of intention recognition is cerebrally implemented within the intention recognition system of the communicator, is modulated by the ambiguity in meaning of the communicative acts, and not by their sensorimotor complexity. The characteristics of this predictive mechanism support the notion that human communicative abilities are distinct from both sensorimotor and linguistic processes. PMID:21151781

Long-term control of olfactory neuroblastoma in a dog treated with surgery and radiation therapy.

PubMed

Gumpel, E; Moore, A S; Simpson, D J; Hoffmann, K L; Taylor, D P

2017-07-01

Olfactory neuroblastoma is a rare malignancy of the nasal cavity in dogs that is thought to arise from specialised sensory neuroendocrine olfactory cells derived from the neural crest. An 8-year-old dog was presented for reclusiveness and pacing. On CT and MRI, a contract-enhancing mass was disclosed within the rostral fossa, extending caudally from the cribriform plate into the left nasal sinus. Surgical excision was performed and the diagnosis was histological grade III (Hyams grading scheme) olfactory neuroblastoma. Based on human CT criteria this was high stage (modified Kadish stage C). Surgical excision was incomplete and was followed by curative-intent radiation therapy using a linear accelerator to a total dose of 48 Gy. The dog survived 20 months after diagnosis. Although olfactory neuroblastoma is a rare tumour in dogs, aggressive local therapy may allow for prolonged survival, even when the tumour is advanced. © 2017 Australian Veterinary Association.

Nervous system excitability and joint stiffness following short-term dynamic ankle immobilization.

PubMed

Stirling, Alyssa M; McBride, Jeffrey M; Merritt, Edward K; Needle, Alan R

2018-01-01

Joint immobilization has been demonstrated to modify neural excitability in subsets of healthy populations, leading to disinhibition of cortical and reflexive pathways. However, these findings may have limited clinical application as most models have investigated casting and rigid immobilization, while many musculoskeletal injuries often utilize dynamic immobilization devices such as boot immobilizers and pneumatic splints that allow for modified ambulation. We therefore aimed to determine the short-term effects of ambulation in ankle immobilization devices on nervous system excitability and stiffness in able-bodied individuals. A repeated-measures design was implemented where 12 healthy individuals were tested for cortical excitability to the ankle musculature using transcranial magnetic stimulation, reflexive excitability using the Hoffmann reflex, and ankle joint stiffness using arthrometry before and after 30min of ambulation with a boot immobilizer, pneumatic leg splint, or barefoot. Motor evoked potential (MEP), cortical silent period (CSP), H max to M max ratio, and ankle joint displacement were extracted as dependent variables. Results indicated that despite the novel motor demands of walking in immobilization devices, no significant changes in cortical excitability (F≥0.335, P≥0.169), reflexive excitability (F≥0.027, P≥0.083), or joint stiffness (F≥0.558, P≥0.169) occurred. These findings indicate that short-term ambulation in dynamic immobilization devices does not modify neural excitability despite forced constraints on the sensorimotor system. We may therefore conclude that modifications to neural excitability in previous immobilization models are mediated by long-term nervous system plasticity rather than acute mechanisms, and there appear to be no robust changes in corticomotor or spinal excitability acutely posed by ambulation with immobilization devices. Copyright © 2017 Elsevier B.V. All rights reserved.

3D printing of layered brain-like structures using peptide modified gellan gum substrates.

PubMed

Lozano, Rodrigo; Stevens, Leo; Thompson, Brianna C; Gilmore, Kerry J; Gorkin, Robert; Stewart, Elise M; in het Panhuis, Marc; Romero-Ortega, Mario; Wallace, Gordon G

2015-10-01

The brain is an enormously complex organ structured into various regions of layered tissue. Researchers have attempted to study the brain by modeling the architecture using two dimensional (2D) in vitro cell culturing methods. While those platforms attempt to mimic the in vivo environment, they do not truly resemble the three dimensional (3D) microstructure of neuronal tissues. Development of an accurate in vitro model of the brain remains a significant obstacle to our understanding of the functioning of the brain at the tissue or organ level. To address these obstacles, we demonstrate a new method to bioprint 3D brain-like structures consisting of discrete layers of primary neural cells encapsulated in hydrogels. Brain-like structures were constructed using a bio-ink consisting of a novel peptide-modified biopolymer, gellan gum-RGD (RGD-GG), combined with primary cortical neurons. The ink was optimized for a modified reactive printing process and developed for use in traditional cell culturing facilities without the need for extensive bioprinting equipment. Furthermore the peptide modification of the gellan gum hydrogel was found to have a profound positive effect on primary cell proliferation and network formation. The neural cell viability combined with the support of neural network formation demonstrated the cell supportive nature of the matrix. The facile ability to form discrete cell-containing layers validates the application of this novel printing technique to form complex, layered and viable 3D cell structures. These brain-like structures offer the opportunity to reproduce more accurate 3D in vitro microstructures with applications ranging from cell behavior studies to improving our understanding of brain injuries and neurodegenerative diseases. Copyright © 2015 Elsevier Ltd. All rights reserved.

Advances in color science: from retina to behavior

PubMed Central

Chatterjee, Soumya; Field, Greg D.; Horwitz, Gregory D.; Johnson, Elizabeth N.; Koida, Kowa; Mancuso, Katherine

2010-01-01

Color has become a premier model system for understanding how information is processed by neural circuits, and for investigating the relationships among genes, neural circuits and perception. Both the physical stimulus for color and the perceptual output experienced as color are quite well characterized, but the neural mechanisms that underlie the transformation from stimulus to perception are incompletely understood. The past several years have seen important scientific and technical advances that are changing our understanding of these mechanisms. Here, and in the accompanying minisymposium, we review the latest findings and hypotheses regarding color computations in the retina, primary visual cortex and higher-order visual areas, focusing on non-human primates, a model of human color vision. PMID:21068298

A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.

PubMed

Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

2016-01-01

We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment

PubMed Central

Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

2016-01-01

We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot’s performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks. PMID:27806074

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.

Embedding Task-Based Neural Models into a Connectome-Based Model of the Cerebral Cortex.

PubMed

Ulloa, Antonio; Horwitz, Barry

2016-01-01

A number of recent efforts have used large-scale, biologically realistic, neural models to help understand the neural basis for the patterns of activity observed in both resting state and task-related functional neural imaging data. An example of the former is The Virtual Brain (TVB) software platform, which allows one to apply large-scale neural modeling in a whole brain framework. TVB provides a set of structural connectomes of the human cerebral cortex, a collection of neural processing units for each connectome node, and various forward models that can convert simulated neural activity into a variety of functional brain imaging signals. In this paper, we demonstrate how to embed a previously or newly constructed task-based large-scale neural model into the TVB platform. We tested our method on a previously constructed large-scale neural model (LSNM) of visual object processing that consisted of interconnected neural populations that represent, primary and secondary visual, inferotemporal, and prefrontal cortex. Some neural elements in the original model were "non-task-specific" (NS) neurons that served as noise generators to "task-specific" neurons that processed shapes during a delayed match-to-sample (DMS) task. We replaced the NS neurons with an anatomical TVB connectome model of the cerebral cortex comprising 998 regions of interest interconnected by white matter fiber tract weights. We embedded our LSNM of visual object processing into corresponding nodes within the TVB connectome. Reciprocal connections between TVB nodes and our task-based modules were included in this framework. We ran visual object processing simulations and showed that the TVB simulator successfully replaced the noise generation originally provided by NS neurons; i.e., the DMS tasks performed with the hybrid LSNM/TVB simulator generated equivalent neural and fMRI activity to that of the original task-based models. Additionally, we found partial agreement between the functional connectivities using the hybrid LSNM/TVB model and the original LSNM. Our framework thus presents a way to embed task-based neural models into the TVB platform, enabling a better comparison between empirical and computational data, which in turn can lead to a better understanding of how interacting neural populations give rise to human cognitive behaviors.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating.

PubMed

Knips, Guido; Zibner, Stephan K U; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.

A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

PubMed Central

Knips, Guido; Zibner, Stephan K. U.; Reimann, Hendrik; Schöner, Gregor

2017-01-01

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp. PMID:28303100

Human-like brain hemispheric dominance in birdsong learning

PubMed Central

Moorman, Sanne; Gobes, Sharon M. H.; Kuijpers, Maaike; Kerkhofs, Amber; Zandbergen, Matthijs A.; Bolhuis, Johan J.

2012-01-01

Unlike nonhuman primates, songbirds learn to vocalize very much like human infants acquire spoken language. In humans, Broca’s area in the frontal lobe and Wernicke’s area in the temporal lobe are crucially involved in speech production and perception, respectively. Songbirds have analogous brain regions that show a similar neural dissociation between vocal production and auditory perception and memory. In both humans and songbirds, there is evidence for lateralization of neural responsiveness in these brain regions. Human infants already show left-sided dominance in their brain activation when exposed to speech. Moreover, a memory-specific left-sided dominance in Wernicke’s area for speech perception has been demonstrated in 2.5-mo-old babies. It is possible that auditory-vocal learning is associated with hemispheric dominance and that this association arose in songbirds and humans through convergent evolution. Therefore, we investigated whether there is similar song memory-related lateralization in the songbird brain. We exposed male zebra finches to tutor or unfamiliar song. We found left-sided dominance of neuronal activation in a Broca-like brain region (HVC, a letter-based name) of juvenile and adult zebra finch males, independent of the song stimulus presented. In addition, juvenile males showed left-sided dominance for tutor song but not for unfamiliar song in a Wernicke-like brain region (the caudomedial nidopallium). Thus, left-sided dominance in the caudomedial nidopallium was specific for the song-learning phase and was memory-related. These findings demonstrate a remarkable neural parallel between birdsong and human spoken language, and they have important consequences for our understanding of the evolution of auditory-vocal learning and its neural mechanisms. PMID:22802637

Coculture with endothelial cells reduces the population of cycling LeX neural precursors but increases that of quiescent cells with a side population phenotype

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

Mathieu, Celine; Fouchet, Pierre; Gauthier, Laurent R.

2006-04-01

Neural stem cell proliferation and differentiation are regulated by external cues from their microenvironment. As endothelial cells are closely associated with neural stem cell in brain germinal zones, we investigated whether endothelial cells may interfere with neurogenesis. Neural precursor cells (NPC) from telencephalon of EGFP mouse embryos were cocultured in direct contact with endothelial cells. Endothelial cells did not modify the overall proliferation and apoptosis of neural cells, albeit they transiently delayed spontaneous apoptosis. These effects appeared to be specific to endothelial cells since a decrease in proliferation and a raise in apoptosis were observed in cocultures with fibroblasts. Endothelialmore » cells stimulated the differentiation of NPC into astrocytes and into neurons, whereas they reduced differentiation into oligodendrocytes in comparison to adherent cultures on polyornithine. Determination of NPC clonogenicity and quantification of LeX expression, a marker for NPC, showed that endothelial cells decreased the number of cycling NPC. On the other hand, the presence of endothelial cells increased the number of neural cells having 'side population' phenotype, another marker reported on NPC, which we have shown to contain quiescent cells. Thus, we show that endothelial cells may regulate neurogenesis by acting at different level of NPC differentiation, proliferation and quiescence.« less

Risk-taking on the road and in the mind: behavioural and neural patterns of decision making between risky and safe drivers.

PubMed

Ba, Yutao; Zhang, Wei; Peng, QiJia; Salvendy, Gavriel; Crundall, David

2016-01-01

Drivers' risk-taking is a key issue of road safety. This study explored individual differences in drivers' decision-making, linking external behaviours to internal neural activity, to reveal the cognitive mechanisms of risky driving. Twenty-four male drivers were split into two groups (risky vs. safe drivers) via the Drivier Behaviour Questionnaire-violation. The risky drivers demonstrated higher preference for the risky choices in the paradigms of Iowa Gambling Task and Balloon Analogue Risk Task. More importantly, the risky drivers showed lower amplitudes of feedback-related negativity (FRN) and loss-minus-gain FRN in both paradigms, which indicated their neural processing of error-detection. A significant difference of P300 amplitudes was also reported between groups, which indicated their neural processing of reward-evaluation and were modified by specific paradigm and feedback. These results suggested that the neural basis of risky driving was the decision patterns less revised by losses and more motivated by rewards. Risk-taking on the road is largely determined by inherent cognitive mechanisms, which can be indicated by the behavioural and neural patterns of decision-making. In this regard, it is feasible to quantize drivers’ riskiness in the cognitive stage before actual risky driving or accidents, and intervene accordingly.

Functional Comparison of Neuronal Cells Differentiated from Human Induced Pluripotent Stem Cell-Derived Neural Stem Cells under Different Oxygen and Medium Conditions.

PubMed

Yamazaki, Kazuto; Fukushima, Kazuyuki; Sugawara, Michiko; Tabata, Yoshikuni; Imaizumi, Yoichi; Ishihara, Yasuharu; Ito, Masashi; Tsukahara, Kappei; Kohyama, Jun; Okano, Hideyuki

2016-12-01

Because neurons are difficult to obtain from humans, generating functional neurons from human induced pluripotent stem cells (hiPSCs) is important for establishing physiological or disease-relevant screening systems for drug discovery. To examine the culture conditions leading to efficient differentiation of functional neural cells, we investigated the effects of oxygen stress (2% or 20% O 2 ) and differentiation medium (DMEM/F12:Neurobasal-based [DN] or commercial [PhoenixSongs Biologicals; PS]) on the expression of genes related to neural differentiation, glutamate receptor function, and the formation of networks of neurons differentiated from hiPSCs (201B7) via long-term self-renewing neuroepithelial-like stem (lt-NES) cells. Expression of genes related to neural differentiation occurred more quickly in PS and/or 2% O 2 than in DN and/or 20% O 2 , resulting in high responsiveness of neural cells to glutamate, N-methyl-d-aspartate (NMDA), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate (AMPA), and ( S)-3,5-dihydroxyphenylglycine (an agonist for mGluR 1/5 ), as revealed by calcium imaging assays. NMDA receptors, AMPA receptors, mGluR 1 , and mGluR 5 were functionally validated by using the specific antagonists MK-801, NBQX, JNJ16259685, and 2-methyl-6-(phenylethynyl)-pyridine, respectively. Multielectrode array analysis showed that spontaneous firing occurred earlier in cells cultured in 2% O 2 than in 20% O 2 . Optimization of O 2 tension and culture medium for neural differentiation of hiPSCs can efficiently generate physiologically relevant cells for screening systems.

Sound Waves Induce Neural Differentiation of Human Bone Marrow-Derived Mesenchymal Stem Cells via Ryanodine Receptor-Induced Calcium Release and Pyk2 Activation.

PubMed

Choi, Yura; Park, Jeong-Eun; Jeong, Jong Seob; Park, Jung-Keug; Kim, Jongpil; Jeon, Songhee

2016-10-01

Mesenchymal stem cells (MSCs) have shown considerable promise as an adaptable cell source for use in tissue engineering and other therapeutic applications. The aims of this study were to develop methods to test the hypothesis that human MSCs could be differentiated using sound wave stimulation alone and to find the underlying mechanism. Human bone marrow (hBM)-MSCs were stimulated with sound waves (1 kHz, 81 dB) for 7 days and the expression of neural markers were analyzed. Sound waves induced neural differentiation of hBM-MSC at 1 kHz and 81 dB but not at 1 kHz and 100 dB. To determine the signaling pathways involved in the neural differentiation of hBM-MSCs by sound wave stimulation, we examined the Pyk2 and CREB phosphorylation. Sound wave induced an increase in the phosphorylation of Pyk2 and CREB at 45 min and 90 min, respectively, in hBM-MSCs. To find out the upstream activator of Pyk2, we examined the intracellular calcium source that was released by sound wave stimulation. When we used ryanodine as a ryanodine receptor antagonist, sound wave-induced calcium release was suppressed. Moreover, pre-treatment with a Pyk2 inhibitor, PF431396, prevented the phosphorylation of Pyk2 and suppressed sound wave-induced neural differentiation in hBM-MSCs. These results suggest that specific sound wave stimulation could be used as a neural differentiation inducer of hBM-MSCs.

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

PubMed

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

2013-01-01

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

Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

PubMed

Calvin, Olivia L; McDowell, J J

2016-06-01

The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this experiment, neural networks were developed from the theory to extend the unified theory of reinforcement to operant behavior on single-alternative variable-interval schedules. This area of operant research was selected because previously developed neural networks could be applied to it without significant alteration. Previous research with humans and animals indicates that the pattern of their steady-state behavior is hyperbolic when plotted against the obtained rate of reinforcement (Herrnstein, 1970). A genetic algorithm was used in the first part of the experiment to determine parameter values for the neural networks, because values that were used in previous research did not result in a hyperbolic pattern of behavior. After finding these parameters, hyperbolic and other similar functions were fitted to the behavior produced by the neural networks. The form of the neural network's behavior was best described by an exponentiated hyperbola (McDowell, 1986; McLean and White, 1983; Wearden, 1981), which was derived from the generalized matching law (Baum, 1974). In post-hoc analyses the addition of a baseline rate of behavior significantly improved the fit of the exponentiated hyperbola and removed systematic residuals. The form of this function was consistent with human and animal behavior, but the estimated parameter values were not. Copyright © 2016 Elsevier B.V. All rights reserved.

High-frequency neural activity and human cognition: past, present and possible future of intracranial EEG research

PubMed Central

Lachaux, Jean-Philippe; Axmacher, Nikolai; Mormann, Florian; Halgren, Eric; Crone, Nathan E.

2013-01-01

Human intracranial EEG (iEEG) recordings are primarily performed in epileptic patients for presurgical mapping. When patients perform cognitive tasks, iEEG signals reveal high-frequency neural activities (HFA, between around 40 Hz and 150 Hz) with exquisite anatomical, functional and temporal specificity. Such HFA were originally interpreted in the context of perceptual or motor binding, in line with animal studies on gamma-band (‘40Hz’) neural synchronization. Today, our understanding of HFA has evolved into a more general index of cortical processing: task-induced HFA reveals, with excellent spatial and time resolution, the participation of local neural ensembles in the task-at-hand, and perhaps the neural communication mechanisms allowing them to do so. This review promotes the claim that studying HFA with iEEG provides insights into the neural bases of cognition that cannot be derived as easily from other approaches, such as fMRI. We provide a series of examples supporting that claim, drawn from studies on memory, language and default-mode networks, and successful attempts of real-time functional mapping. These examples are followed by several guidelines for HFA research, intended for new groups interested by this approach. Overall, iEEG research on HFA should play an increasing role in cognitive neuroscience in humans, because it can be explicitly linked to basic research in animals. We conclude by discussing the future evolution of this field, which might expand that role even further, for instance through the use of multi-scale electrodes and the fusion of iEEG with MEG and fMRI. PMID:22750156

Augmentation-related brain plasticity

PubMed Central

Di Pino, Giovanni; Maravita, Angelo; Zollo, Loredana; Guglielmelli, Eugenio; Di Lazzaro, Vincenzo

2014-01-01

Today, the anthropomorphism of the tools and the development of neural interfaces require reconsidering the concept of human-tools interaction in the framework of human augmentation. This review analyses the plastic process that the brain undergoes when it comes into contact with augmenting artificial sensors and effectors and, on the other hand, the changes that the use of external augmenting devices produces in the brain. Hitherto, few studies investigated the neural correlates of augmentation, but clues on it can be borrowed from logically-related paradigms: sensorimotor training, cognitive enhancement, cross-modal plasticity, sensorimotor functional substitution, use and embodiment of tools. Augmentation modifies function and structure of a number of areas, i.e., primary sensory cortices shape their receptive fields to become sensitive to novel inputs. Motor areas adapt the neuroprosthesis representation firing-rate to refine kinematics. As for normal motor outputs, the learning process recruits motor and premotor cortices and the acquisition of proficiency decreases attentional recruitment, focuses the activity on sensorimotor areas and increases the basal ganglia drive on the cortex. Augmentation deeply relies on the frontoparietal network. In particular, premotor cortex is involved in learning the control of an external effector and owns the tool motor representation, while the intraparietal sulcus extracts its visual features. In these areas, multisensory integration neurons enlarge their receptive fields to embody supernumerary limbs. For operating an anthropomorphic neuroprosthesis, the mirror system is required to understand the meaning of the action, the cerebellum for the formation of its internal model and the insula for its interoception. In conclusion, anthropomorphic sensorized devices can provide the critical sensory afferences to evolve the exploitation of tools through their embodiment, reshaping the body representation and the sense of the self. PMID:24966816

Infrared neural stimulation of human spinal nerve roots in vivo.

PubMed

Cayce, Jonathan M; Wells, Jonathon D; Malphrus, Jonathan D; Kao, Chris; Thomsen, Sharon; Tulipan, Noel B; Konrad, Peter E; Jansen, E Duco; Mahadevan-Jansen, Anita

2015-01-01

Infrared neural stimulation (INS) is a neurostimulation modality that uses pulsed infrared light to evoke artifact-free, spatially precise neural activity with a noncontact interface; however, the technique has not been demonstrated in humans. The objective of this study is to demonstrate the safety and efficacy of INS in humans in vivo. The feasibility of INS in humans was assessed in patients ([Formula: see text]) undergoing selective dorsal root rhizotomy, where hyperactive dorsal roots, identified for transection, were stimulated in vivo with INS on two to three sites per nerve with electromyogram recordings acquired throughout the stimulation. The stimulated dorsal root was removed and histology was performed to determine thermal damage thresholds of INS. Threshold activation of human dorsal rootlets occurred in 63% of nerves for radiant exposures between 0.53 and [Formula: see text]. In all cases, only one or two monitored muscle groups were activated from INS stimulation of a hyperactive spinal root identified by electrical stimulation. Thermal damage was first noted at [Formula: see text] and a [Formula: see text] safety ratio was identified. These findings demonstrate the success of INS as a fresh approach for activating human nerves in vivo and providing the necessary safety data needed to pursue clinically driven therapeutic and diagnostic applications of INS in humans.

Effects of hypoxia on sympathetic neural control in humans

NASA Technical Reports Server (NTRS)

Smith, M. L.; Muenter, N. K.

2000-01-01

This special issue is principally focused on the time domain of the adaptive mechanisms of ventilatory responses to short-term, long-term and intermittent hypoxia. The purpose of this review is to summarize the limited literature on the sympathetic neural responses to sustained or intermittent hypoxia in humans and attempt to discern the time domain of these responses and potential adaptive processes that are evoked during short and long-term exposures to hypoxia.

Deliberate or unintended: Intentions modulate empathic responses to others' economic payoffs in social interactions.

PubMed

Ma, Qingguo; Meng, Liang; Shen, Qiang

2017-12-01

Previous studies examining empathy have revealed the neural substrates of how the physical pain of others is represented in the human brain. However, little is known about the empathic modulation of behavioral and neural responses to others' economic payoffs, especially in the social context. In the present study, we engaged participants in a revised Dictator Game as observers who observe the powerless players receiving varied offers proposed by the dominant players, establishing the link between empathy and fairness perception. Results showed that unfair division schemes elicited a more pronounced FRN than fair ones only if a human agent proposed the initial offer. In addition, observers sacrificed their own payments to adjust unfair proposals, especially when a human agent proposed the offer. Thus, results of the current study demonstrated that perceived intention modulates behavioral and neural responses to others' economic payoffs in social interactions.

Mirror neurons and the social nature of language: the neural exploitation hypothesis.

PubMed

Gallese, Vittorio

2008-01-01

This paper discusses the relevance of the discovery of mirror neurons in monkeys and of the mirror neuron system in humans to a neuroscientific account of primates' social cognition and its evolution. It is proposed that mirror neurons and the functional mechanism they underpin, embodied simulation, can ground within a unitary neurophysiological explanatory framework important aspects of human social cognition. In particular, the main focus is on language, here conceived according to a neurophenomenological perspective, grounding meaning on the social experience of action. A neurophysiological hypothesis--the "neural exploitation hypothesis"--is introduced to explain how key aspects of human social cognition are underpinned by brain mechanisms originally evolved for sensorimotor integration. It is proposed that these mechanisms were later on adapted as new neurofunctional architecture for thought and language, while retaining their original functions as well. By neural exploitation, social cognition and language can be linked to the experiential domain of action.

Combining Patient-Reprogrammed Neural Cells and Proteomics as a Model to Study Psychiatric Disorders.

PubMed

Zuccoli, Giuliana S; Martins-de-Souza, Daniel; Guest, Paul C; Rehen, Stevens K; Nascimento, Juliana Minardi

2017-01-01

The mechanisms underlying the pathophysiology of psychiatric disorders are still poorly known. Most of the studies about these disorders have been conducted on postmortem tissue or in limited preclinical models. The development of human induced pluripotent stem cells (iPSCs) has helped to increase the translational capacity of molecular profiling studies of psychiatric disorders through provision of human neuronal-like tissue. This approach consists of generation of pluripotent cells by genetically reprogramming somatic cells to produce the multiple neural cell types as observed within the nervous tissue. The finding that iPSCs can recapitulate the phenotype of the donor also affords the possibility of using this approach to study both the disease and control states in a given medical area. Here, we present a protocol for differentiation of human pluripotent stem cells to neural progenitor cells followed by subcellular fractionation which allows the study of specific cellular organelles and proteomic analysis.

Investigation of automated task learning, decomposition and scheduling

NASA Technical Reports Server (NTRS)

Livingston, David L.; Serpen, Gursel; Masti, Chandrashekar L.

1990-01-01

The details and results of research conducted in the application of neural networks to task planning and decomposition are presented. Task planning and decomposition are operations that humans perform in a reasonably efficient manner. Without the use of good heuristics and usually much human interaction, automatic planners and decomposers generally do not perform well due to the intractable nature of the problems under consideration. The human-like performance of neural networks has shown promise for generating acceptable solutions to intractable problems such as planning and decomposition. This was the primary reasoning behind attempting the study. The basis for the work is the use of state machines to model tasks. State machine models provide a useful means for examining the structure of tasks since many formal techniques have been developed for their analysis and synthesis. It is the approach to integrate the strong algebraic foundations of state machines with the heretofore trial-and-error approach to neural network synthesis.

Generation of inner ear sensory cells from bone marrow-derived human mesenchymal stem cells.

PubMed

Durán Alonso, M Beatriz; Feijoo-Redondo, Ana; Conde de Felipe, Magnolia; Carnicero, Estela; García, Ana Sánchez; García-Sancho, Javier; Rivolta, Marcelo N; Giráldez, Fernando; Schimmang, Thomas

2012-11-01

Hearing loss is the most common sensory disorder in humans, its main cause being the loss of cochlear hair cells. We studied the potential of human mesenchymal stem cells (hMSCs) to differentiate towards hair cells and auditory neurons. hMSCs were first differentiated to neural progenitors and subsequently to hair cell- or auditory neuron-like cells using in vitro culture methods. Differentiation of hMSCs to an intermediate neural progenitor stage was critical for obtaining inner ear sensory lineages. hMSCs generated hair cell-like cells only when neural progenitors derived from nonadherent hMSC cultures grown in serum-free medium were exposed to EGF and retinoic acid. Auditory neuron-like cells were obtained when treated with retinoic acid, and in the presence of defined growth factor combinations containing Sonic Hedgehog. The results show the potential of hMSCs to give rise to inner ear sensory cells.

Combined effect of pulsed electromagnetic field and sound wave on In vitro and In vivo neural differentiation of human mesenchymal stem cells.

PubMed

Choi, Yun-Kyong; Urnukhsaikhan, Enerelt; Yoon, Hee-Hoon; Seo, Young-Kwon; Cho, Hyunjin; Jeong, Jong-Seob; Kim, Soo-Chan; Park, Jung-Keug

2017-01-01

Biophysical wave stimulus has been used as an effective tool to promote cellular maturation and differentiation in the construction of engineered tissue. Pulsed electromagnetic fields (PEMFs) and sound waves have been selected as effective stimuli that can promote neural differentiation. The aim of this study was to investigate the synergistic effect of PEMFs and sound waves on the neural differentiation potential in vitro and in vivo using human bone marrow mesenchymal stem cells (hBM-MSCs). In vitro, neural-related genes in hBM-MSCs were accelerated by the combined exposure to both waves more than by individual exposure to PEMFs or sound waves. The combined wave also up-regulated the expression of neural and synaptic-related proteins in a three-dimensional (3-D) culture system through the phosphorylation of extracellular signal-related kinase. In a mouse model of photochemically induced ischemia, exposure to the combined wave reduced the infarction volume and improved post-injury behavioral activity. These results indicate that a combined stimulus of biophysical waves, PEMFs and sound can enhance and possibly affect the differentiation of MSCs into neural cells. Our study is meaningful for highlighting the potential of combined wave for neurogenic effects and providing new therapeutic approaches for neural cell therapy. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 33:201-211, 2017. © 2016 American Institute of Chemical Engineers.

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

PubMed

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

2016-04-01

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

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.

Flexible body control using neural networks

NASA Technical Reports Server (NTRS)

Mccullough, Claire L.

1992-01-01

Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

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.

Microneurography as a tool in clinical neurophysiology to investigate peripheral neural traffic in humans.

PubMed

Mano, Tadaaki; Iwase, Satoshi; Toma, Shinobu

2006-11-01

Microneurography is a method using metal microelectrodes to investigate directly identified neural traffic in myelinated as well as unmyelinated efferent and afferent nerves leading to and coming from muscle and skin in human peripheral nerves in situ. The present paper reviews how this technique has been used in clinical neurophysiology to elucidate the neural mechanisms of autonomic regulation, motor control and sensory functions in humans under physiological and pathological conditions. Microneurography is particularly important to investigate efferent and afferent neural traffic in unmyelinated C fibers. The recording of efferent discharges in postganglionic sympathetic C efferent fibers innervating muscle and skin (muscle sympathetic nerve activity; MSNA and skin sympathetic nerve activity; SSNA) provides direct information about neural control of autonomic effector organs including blood vessels and sweat glands. Sympathetic microneurography has become a potent tool to reveal neural functions and dysfunctions concerning blood pressure control and thermoregulation. This recording has been used not only in wake conditions but also in sleep to investigate changes in sympathetic neural traffic during sleep and sleep-related events such as sleep apnea. The same recording was also successfully carried out by astronauts during spaceflight. Recordings of afferent discharges from muscle mechanoreceptors have been used to understand the mechanisms of motor control. Muscle spindle afferent information is particularly important for the control of fine precise movements. It may also play important roles to predict behavior outcomes during learning of a motor task. Recordings of discharges in myelinated afferent fibers from skin mechanoreceptors have provided not only objective information about mechanoreceptive cutaneous sensation but also the roles of these signals in fine motor control. Unmyelinated mechanoreceptive afferent discharges from hairy skin seem to be important to convey cutaneous sensation to the central structures related to emotion. Recordings of afferent discharges in thin myelinated and unmyelinated fibers from nociceptors in muscle and skin have been used to provide information concerning pain. Recordings of afferent discharges of different types of cutaneous C-nociceptors identified by marking method have become an important tool to reveal the neural mechanisms of cutaneous sensations such as an itch. No direct microneurographic evidence has been so far proved regarding the effects of sympathoexcitation on sensitization of muscle and skin sensory receptors at least in healthy humans.

Neural Responses to Injury: Prevention, Protection, and Repair.

DTIC Science & Technology

1998-10-01

opioid-sensitive circuitry by electroacupuncture can suppress c-fos expression (21). Anesthetic agents and system- ically administered morphine can...ders Co., 1995, pp 397-460. 21. Lee JH, Beitz AJ: Electroacupuncture modifies the expression of c-fos in the spinal cord induced by noxious

A knowledge-base generating hierarchical fuzzy-neural controller.

PubMed

Kandadai, R M; Tien, J M

1997-01-01

We present an innovative fuzzy-neural architecture that is able to automatically generate a knowledge base, in an extractable form, for use in hierarchical knowledge-based controllers. The knowledge base is in the form of a linguistic rule base appropriate for a fuzzy inference system. First, we modify Berenji and Khedkar's (1992) GARIC architecture to enable it to automatically generate a knowledge base; a pseudosupervised learning scheme using reinforcement learning and error backpropagation is employed. Next, we further extend this architecture to a hierarchical controller that is able to generate its own knowledge base. Example applications are provided to underscore its viability.

Improving ECG Classification Accuracy Using an Ensemble of Neural Network Modules

PubMed Central

Javadi, Mehrdad; Ebrahimpour, Reza; Sajedin, Atena; Faridi, Soheil; Zakernejad, Shokoufeh

2011-01-01

This paper illustrates the use of a combined neural network model based on Stacked Generalization method for classification of electrocardiogram (ECG) beats. In conventional Stacked Generalization method, the combiner learns to map the base classifiers' outputs to the target data. We claim adding the input pattern to the base classifiers' outputs helps the combiner to obtain knowledge about the input space and as the result, performs better on the same task. Experimental results support our claim that the additional knowledge according to the input space, improves the performance of the proposed method which is called Modified Stacked Generalization. In particular, for classification of 14966 ECG beats that were not previously seen during training phase, the Modified Stacked Generalization method reduced the error rate for 12.41% in comparison with the best of ten popular classifier fusion methods including Max, Min, Average, Product, Majority Voting, Borda Count, Decision Templates, Weighted Averaging based on Particle Swarm Optimization and Stacked Generalization. PMID:22046232

Discrete Circuits Support Generalized versus Context-Specific Vocal Learning in the Songbird.

PubMed

Tian, Lucas Y; Brainard, Michael S

2017-12-06

Motor skills depend on the reuse of individual gestures in multiple sequential contexts (e.g., a single phoneme in different words). Yet optimal performance requires that a given gesture be modified appropriately depending on the sequence in which it occurs. To investigate the neural architecture underlying such context-dependent modifications, we studied Bengalese finch song, which, like speech, consists of variable sequences of "syllables." We found that when birds are instructed to modify a syllable in one sequential context, learning generalizes across contexts; however, if unique instruction is provided in different contexts, learning is specific for each context. Using localized inactivation of a cortical-basal ganglia circuit specialized for song, we show that this balance between generalization and specificity reflects a hierarchical organization of neural substrates. Primary motor circuitry encodes a core syllable representation that contributes to generalization, while top-down input from cortical-basal ganglia circuitry biases this representation to enable context-specific learning. Copyright © 2017 Elsevier Inc. All rights reserved.

XenoSite: accurately predicting CYP-mediated sites of metabolism with neural networks.

PubMed

Zaretzki, Jed; Matlock, Matthew; Swamidass, S Joshua

2013-12-23

Understanding how xenobiotic molecules are metabolized is important because it influences the safety, efficacy, and dose of medicines and how they can be modified to improve these properties. The cytochrome P450s (CYPs) are proteins responsible for metabolizing 90% of drugs on the market, and many computational methods can predict which atomic sites of a molecule--sites of metabolism (SOMs)--are modified during CYP-mediated metabolism. This study improves on prior methods of predicting CYP-mediated SOMs by using new descriptors and machine learning based on neural networks. The new method, XenoSite, is faster to train and more accurate by as much as 4% or 5% for some isozymes. Furthermore, some "incorrect" predictions made by XenoSite were subsequently validated as correct predictions by revaluation of the source literature. Moreover, XenoSite output is interpretable as a probability, which reflects both the confidence of the model that a particular atom is metabolized and the statistical likelihood that its prediction for that atom is correct.

Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

PubMed Central

Qiao, Lei; Zhang, Lijie

2017-01-01

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion. SIGNIFICANCE STATEMENT Humans can fluently switch between different tasks, reflecting an ability to dynamically configure “task sets,” rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior. PMID:28972126

Proceedings of the Government Neural Network Applications Workshop Held at Wright-Patterson AFB, Ohio on August 24-26, 1992. Volume 1

DTIC Science & Technology

1992-08-01

history trace of input u(t). (b) A common network struc- 1 ture makes use of the feedforward tapped delay line. For this structure the memory depth D...theories and analyses that will be used world- wide for a long time to come. The reason for this contribution has generally been the government’s need to...that emulate the neural reasoning behavior of biological neural systems (e.g. the human brain). As such, they are loosely based on biological neural

Intelligence moderates reinforcement learning: a mini-review of the neural evidence

PubMed Central

2014-01-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. PMID:25185818

Intelligence moderates reinforcement learning: a mini-review of the neural evidence.

PubMed

Chen, Chong

2015-06-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. Copyright © 2015 the American Physiological Society.

Synapse alterations in autism: Review of animal model findings.

PubMed

Zatkova, Martina; Bakos, Jan; Hodosy, Julius; Ostatnikova, Daniela

2016-06-01

Recent research has produced an explosion of experimental data on the complex neurobiological mechanisms of developmental disorders including autism. Animal models are one approach to studying the phenotypic features and molecular basis of autism. In this review, we describe progress in understanding synaptogenesis and alterations to this process with special emphasis on the cell adhesion molecules and scaffolding proteins implicated in autism. Genetic mouse model experiments are discussed in relation to alterations to selected synaptic proteins and consequent behavioral deficits measured in animal experiments. Pubmed databases were used to search for original and review articles on animal and human clinical studies on autism. The cell adhesion molecules, neurexin, neurolignin and the Shank family of proteins are important molecular targets associated with autism. The heterogeneity of the autism spectrum of disorders limits interpretation of information acquired from any single animal model or animal test. We showed synapse-specific/ model-specific defects associated with a given genotype in these models. Characterization of mouse models with genetic variations may help study the mechanisms of autism in humans. However, it will be necessary to apply new analytic paradigms in using genetically modified mice for understanding autism etiology in humans. Further studies are needed to create animal models with mutations that match the molecular and neural bases of autism.

Computed aided system for separation and classification of the abnormal erythrocytes in human blood

NASA Astrophysics Data System (ADS)

Wąsowicz, Michał; Grochowski, Michał; Kulka, Marek; Mikołajczyk, Agnieszka; Ficek, Mateusz; Karpieńko, Katarzyna; Cićkiewicz, Maciej

2017-12-01

The human peripheral blood consists of cells (red cells, white cells, and platelets) suspended in plasma. In the following research the team assessed an influence of nanodiamond particles on blood elements over various periods of time. The material used in the study consisted of samples taken from ten healthy humans of various age, different blood types and both sexes. The markings were leaded by adding to the blood unmodified diamonds and oxidation modified. The blood was put under an impact of two diamond concentrations: 20μl and 100μl. The amount of abnormal cells increased with time. The percentage of echinocytes as a result of interaction with nanodiamonds in various time intervals for individual specimens was scarce. The impact of the two diamond types had no clinical importance on red blood cells. It is supposed that as a result of longlasting exposure a dehydratation of red cells takes place, because of the function of the cells. The analysis of an influence of nanodiamond particles on blood elements was supported by computer system designed for automatic counting and classification of the Red Blood Cells (RBC). The system utilizes advanced image processing methods for RBCs separation and counting and Eigenfaces method coupled with the neural networks for RBCs classification into normal and abnormal cells purposes.

Neuromodulation of lower limb motor control in restorative neurology.

PubMed

Minassian, Karen; Hofstoetter, Ursula; Tansey, Keith; Mayr, Winfried

2012-06-01

One consequence of central nervous system injury or disease is the impairment of neural control of movement, resulting in spasticity and paralysis. To enhance recovery, restorative neurology procedures modify altered, yet preserved nervous system function. This review focuses on functional electrical stimulation (FES) and spinal cord stimulation (SCS) that utilize remaining capabilities of the distal apparatus of spinal cord, peripheral nerves and muscles in upper motor neuron dysfunctions. FES for the immediate generation of lower limb movement along with current rehabilitative techniques is reviewed. The potential of SCS for controlling spinal spasticity and enhancing lower limb function in multiple sclerosis and spinal cord injury is discussed. The necessity for precise electrode placement and appropriate stimulation parameter settings to achieve therapeutic specificity is elaborated. This will lead to our human work of epidural and transcutaneous stimulation targeting the lumbar spinal cord for enhancing motor functions in spinal cord injured people, supplemented by pertinent human research of other investigators. We conclude that the concept of restorative neurology recently received new appreciation by accumulated evidence for locomotor circuits residing in the human spinal cord. Technological and clinical advancements need to follow for a major impact on the functional recovery in individuals with severe damage to their motor system. Copyright © 2012 Elsevier B.V. All rights reserved.

Neuromodulation of lower limb motor control in restorative neurology

PubMed Central

Minassian, Karen; Hofstoetter, Ursula; Tansey, Keith; Mayr, Winfried

2012-01-01

One consequence of central nervous system injury or disease is the impairment of neural control of movement, resulting in spasticity and paralysis. To enhance recovery, restorative neurology procedures modify altered, yet preserved nervous system function. This review focuses on functional electrical stimulation (FES) and spinal cord stimulation (SCS) that utilize remaining capabilities of the distal apparatus of spinal cord, peripheral nerves and muscles in upper motor neuron dysfunctions. FES for the immediate generation of lower limb movement along with current rehabilitative techniques is reviewed. The potential of SCS for controlling spinal spasticity and enhancing lower limb function in multiple sclerosis and spinal cord injury is discussed. The necessity for precise electrode placement and appropriate stimulation parameter settings to achieve therapeutic specificity is elaborated. This will lead to our human work of epidural and transcutaneous stimulation targeting the lumbar spinal cord for enhancing motor functions in spinal cord injured people, supplemented by pertinent human research of other investigators. We conclude that the concept of restorative neurology recently received new appreciation by accumulated evidence for locomotor circuits residing in the human spinal cord. Technological and clinical advancements need to follow for a major impact on the functional recovery in individuals with severe damage to their motor system. PMID:22464657

The Variability of Neural Responses to Naturalistic Videos Change with Age and Sex.

PubMed

Petroni, Agustin; Cohen, Samantha S; Ai, Lei; Langer, Nicolas; Henin, Simon; Vanderwal, Tamara; Milham, Michael P; Parra, Lucas C

2018-01-01

Neural development is generally marked by an increase in the efficiency and diversity of neural processes. In a large sample ( n = 114) of human children and adults with ages ranging from 5 to 44 yr, we investigated the neural responses to naturalistic video stimuli. Videos from both real-life classroom settings and Hollywood feature films were used to probe different aspects of attention and engagement. For all stimuli, older ages were marked by more variable neural responses. Variability was assessed by the intersubject correlation of evoked electroencephalographic responses. Young males also had less-variable responses than young females. These results were replicated in an independent cohort ( n = 303). When interpreted in the context of neural maturation, we conclude that neural function becomes more variable with maturity, at least during the passive viewing of real-world stimuli.

The refined biomimetic NeuroDigm GEL™ model of neuropathic pain in a mature rat

PubMed Central

Hannaman, Mary R.; Fitts, Douglas A.; Doss, Rose M.; Weinstein, David E.; Bryant, Joseph L.

2017-01-01

Background: Many humans suffering with chronic neuropathic pain have no objective evidence of an etiological lesion or disease. Frequently their persistent pain occurs after the healing of a soft tissue injury. Based on clinical observations over time, our hypothesis was that after an injury in mammals the process of tissue repair could cause chronic neural pain. Our objectives were to create the delayed onset of neuropathic pain in rats with minimal nerve trauma using a physiologic hydrogel, and characterize the rats’ responses to known analgesics and a targeted biologic. Methods: In mature male Sprague Dawley rats (age 9.5 months) a percutaneous implant of tissue-derived hydrogel was placed in the musculofascial tunnel of the distal tibial nerve. Subcutaneous morphine (3 mg/kg), celecoxib (10 mg/kg), gabapentin (25 mg/kg) and duloxetine (10 mg/kg) were each screened in the model three times each over 5 months after pain behaviors developed. Sham and control groups were used in all screenings. A pilot study followed in which recombinant human erythropoietin (200 units) was injected by the GEL™ neural procedure site. Results: The GEL group gradually developed mechanical hypersensitivity lasting months. Morphine, initially effective, had less analgesia over time. Celecoxib produced no analgesia, while gabapentin and duloxetine at low doses demonstrated profound analgesia at all times tested. The injected erythropoietin markedly decreased bilateral pain behavior that had been present for over 4 months, p ≤ 0.001. Histology of the GEL group tibial nerve revealed a site of focal neural remodeling, with neural regeneration, as found in nerve biopsies of patients with neuropathic pain. Conclusion: The refined NeuroDigm GEL™ model induces a neural response resulting in robust neuropathic pain behavior. The analgesic responses in this model reflect known responses of humans with neuropathic pain. The targeted recombinant human erythropoietin at the ectopic neural lesion appears to alleviate the persistent pain behavior in the GEL™ model rodents. PMID:28620451

Understanding the Implications of Neural Population Activity on Behavior

NASA Astrophysics Data System (ADS)

Briguglio, John

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

What is reconfigured?. Comment on "The quartet theory of human emotions: An integrative and neurofunctional model" by S. Koelsch et al.

NASA Astrophysics Data System (ADS)

Engelen, Eva-Maria

2015-06-01

The research group around Koelsch presents a neurobiological emotion theory that is supposed to have the following plus factors: (1) Interdisciplinary approach towards understanding human emotions and their neural correlates, (2) concentration on human emotions, (3) interaction between language and emotion, (4) allows research on short-term emotional phenomena and takes long-term emotional phenomena into account, as well as the differences of the neural correlates underlying short-term and long-term emotions [5]. This is a very ambitious program. My comment will focus on (3) and (4).

Optimal feature selection using a modified differential evolution algorithm and its effectiveness for prediction of heart disease.

PubMed

Vivekanandan, T; Sriman Narayana Iyengar, N Ch

2017-11-01

Enormous data growth in multiple domains has posed a great challenge for data processing and analysis techniques. In particular, the traditional record maintenance strategy has been replaced in the healthcare system. It is vital to develop a model that is able to handle the huge amount of e-healthcare data efficiently. In this paper, the challenging tasks of selecting critical features from the enormous set of available features and diagnosing heart disease are carried out. Feature selection is one of the most widely used pre-processing steps in classification problems. A modified differential evolution (DE) algorithm is used to perform feature selection for cardiovascular disease and optimization of selected features. Of the 10 available strategies for the traditional DE algorithm, the seventh strategy, which is represented by DE/rand/2/exp, is considered for comparative study. The performance analysis of the developed modified DE strategy is given in this paper. With the selected critical features, prediction of heart disease is carried out using fuzzy AHP and a feed-forward neural network. Various performance measures of integrating the modified differential evolution algorithm with fuzzy AHP and a feed-forward neural network in the prediction of heart disease are evaluated in this paper. The accuracy of the proposed hybrid model is 83%, which is higher than that of some other existing models. In addition, the prediction time of the proposed hybrid model is also evaluated and has shown promising results. Copyright © 2017 Elsevier Ltd. All rights reserved.