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This project will investigate the development of large-scale neural networks in infancy. We will collect longitudinal data from infants at 8, 12, 18, and 24 months of age using functional near-infrared spectroscopy (fNIRS). Infants will engage in two tasks so that we can measure brain activity at rest (i.e., resting-state functional connectivity) and when infants are actively engaged in learning (i.e., task-based functional connectivity).

The central aim of this study is to investigate the relationship between neural reward sensitivity and cognitive control across adolescent development. To examine this relationship, we plan to use the longitudinal fMRI imaging and behavioral data provided by the Adolescent Brain Cognitive Development Study database. The analyses described here are designed to test the following questions: 1) Does neural reward sensitivity predict cognitive control during development from 9 to 14 years old? 2) Does the development of neural reward sensitivity predict cortical-subcortical functional connectivity supporting cognitive control? 3) Does cognitive control-related cortical-subcortical connectivity mediate the relationship between neural reward sensitivity and cognitive control? These findings will deepen our understanding of the adaptive significance of reward sensitivity and help differentiate between neural models explaining adolescent behavior.

Face processing has been shown to have a fundamental role to learn social skills and attend to social information (Rajhans et al., 2016). Facial emotion processing is critical to social cognitive ability, and previous research has suggested that language plays a role in the development of social cognitive skills, including non-verbal emotion recognition tasks. Bigelow et al. (2022) showed that several ERP components were correlated with language development during childhood, and that it depends on facial expression. They found that P100 latency for negative expressions increased with language, while Late Positive Potential (LPP) amplitude increased with language for negative and neutral expressions. Several Event-related Potential (ERP) components have shown to reflect these abilities. ERPs are defined as very small voltages generated in the brain structures in response to specific events or stimuli. Furthermore, N290 has been shown to reflect facial emotion processing in young children, with smaller amplitude in response to fearful expressions, compared to happy or neutral ones. Additionally, N290 amplitudes are reduced in young compared to older children; this is thought to be due to the high-level cognition that has been developed across time (van den Boomen; Xie et al., 2019). However, controversial findings for N290 amplitudes and latencies have been found. For instance, Rajhans et al. (2016) showed that no effects were observed for face-sensitive processing as reflected in the N290, thought to be involved in face encoding in infants. Therefore, the current study will provide insights about the neural correlates of infant facial emotion processing in the second year of life and will have the potential to serve as a reference on the typical development of the neural mechanisms underlying infant facial emotion processing. Therefore, using baseline visit data from the Kia Tīmata Pai (KTP) study, we aim to conduct cross-sectional analysis to investigate how N290 amplitude and latency 1) associate with age in early development 2) differ in response to different emotional stimuli (angry, fearful, happy faces). We will assess a total of 200 children, between 13 and 30 months old. EEG data were collected while infants were viewing images of angry, happy, and neutral faces. Furthermore, we will 3) investigate the relationship between N290 amplitudes and latencies, and oral language development. We expect to see greater amplitude and later latency to be associated with better performance in the oral language measures. The novelty of this study is the combination of EEG and oral language measures. Not many studies investigated the associations between these two variables across early development.

Face processing has been shown to have a fundamental role to learn social skills and attend to social information (Rajhans et al., 2016). Facial emotion processing is critical to social cognitive ability, and previous research has suggested that language plays a role in the development of social cognitive skills, including non-verbal emotion recognition tasks. Bigelow et al. (2022) showed that several ERP components were correlated with language development during childhood, and that it depends on facial expression. They found that P100 latency for negative expressions increased with language, while Late Positive Potential (LPP) amplitude increased with language for negative and neutral expressions. Several Event-related Potential (ERP) components have shown to reflect these abilities. ERPs are defined as very small voltages generated in the brain structures in response to specific events or stimuli. Furthermore, N290 has been shown to reflect facial emotion processing in young children, with smaller amplitude in response to fearful expressions, compared to happy or neutral ones. Additionally, N290 amplitudes are reduced in young compared to older children; this is thought to be due to the high-level cognition that has been developed across time (van den Boomen; Xie et al., 2019). However, controversial findings for N290 amplitudes and latencies have been found. For instance, Rajhans et al. (2016) showed that no effects were observed for face-sensitive processing as reflected in the N290, thought to be involved in face encoding in infants. Therefore, the current study will provide insights about the neural correlates of infant facial emotion processing in the second year of life and will have the potential to serve as a reference on the typical development of the neural mechanisms underlying infant facial emotion processing. Therefore, using baseline visit data from the Kia Tīmata Pai (KTP) study, we aim to conduct cross-sectional analysis to investigate how N290 amplitude and latency 1) associate with age in early development 2) differ in response to different emotional stimuli (angry, fearful, happy faces). We will assess a total of 200 children, between 13 and 30 months old. EEG data were collected while infants were viewing images of angry, happy, and neutral faces. Furthermore, we will 3) investigate the relationship between N290 amplitudes and latencies, and oral language development. We expect to see greater amplitude and later latency to be associated with better performance in the oral language measures. The novelty of this study is the combination of EEG and oral language measures. Not many studies investigated the associations between these two variables across early development.

Face processing has been shown to have a fundamental role to learn social skills and attend to social information (Rajhans et al., 2016). Facial emotion processing is critical to social cognitive ability, and previous research has suggested that language plays a role in the development of social cognitive skills, including non-verbal emotion recognition tasks. Bigelow et al. (2022) showed that several ERP components were correlated with language development during childhood, and that it depends on facial expression. They found that P100 latency for negative expressions increased with language, while Late Positive Potential (LPP) amplitude increased with language for negative and neutral expressions. Several Event-related Potential (ERP) components have shown to reflect these abilities. ERPs are defined as very small voltages generated in the brain structures in response to specific events or stimuli. Furthermore, N290 has been shown to reflect facial emotion processing in young children, with smaller amplitude in response to fearful expressions, compared to happy or neutral ones. Additionally, N290 amplitudes are reduced in young compared to older children; this is thought to be due to the high-level cognition that has been developed across time (van den Boomen; Xie et al., 2019). However, controversial findings for N290 amplitudes and latencies have been found. For instance, Rajhans et al. (2016) showed that no effects were observed for face-sensitive processing as reflected in the N290, thought to be involved in face encoding in infants. Therefore, the current study will provide insights about the neural correlates of infant facial emotion processing in the second year of life and will have the potential to serve as a reference on the typical development of the neural mechanisms underlying infant facial emotion processing. Therefore, using baseline visit data from the Kia Tīmata Pai (KTP) study, we aim to conduct cross-sectional analysis to investigate how N290 amplitude and latency 1) associate with age in early development 2) differ in response to different emotional stimuli (angry, fearful, happy faces). We will assess a total of 200 children, between 13 and 30 months old. EEG data were collected while infants were viewing images of angry, happy, and neutral faces. Furthermore, we will 3) investigate the relationship between N290 amplitudes and latencies, and oral language development. We expect to see greater amplitude and later latency to be associated with better performance in the oral language measures. The novelty of this study is the combination of EEG and oral language measures. Not many studies investigated the associations between these two variables across early development.

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This article is from PLoS ONE , volume 9 . Abstract Background: Adar2 deaminates selective adenosines to inosines (A-to-I RNA editing) in the double-stranded region of nuclear transcripts. Although the functions of mouse Adar2 and its biologically most important substrate gria2, encoding the GluA2 subunit of AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor, have been extensively studied, the substrates and functions of zebrafish Adar2 remain elusive. Methods/Principal Findings: Expression of Adar2 was perturbed in the adar2 morphant (adar2MO), generated by antisense morpholio oligonucleotides. The Q/R editing of gria2α was reduced in the adar2MO and was enhanced by overexpression of Adar2, demonstrating an evolutionarily conserved activity between zebrafish and mammalian Adar2 in editing the Q/R site of gria2. To delineate the role of Q/R editing of gria2α in the developmental defects observed in the adar2MO, the Q/R editing of gria2α was specifically perturbed in the gria2αQRMO, generated by a morpholio oligonucleotide complementary to the exon complementary sequence (ECS) required for the Q/R editing. Analogous to the adar2-deficient and Q/R-editing deficient mice displaying identical neurological defects, the gria2αQRMO and adar2MO displayed identical developmental defects in the nervous system and cranial cartilages. Knockdown p53 abolished apoptosis and partially suppressed the loss of spinal cord motor neurons in these morphants. However, reducing p53 activity neither replenished the brain neuronal populations nor rescued the developmental defects. The expressions of crestin and sox9b in the neural crest cells were reduced in the adar2MO and gria2αQRMO. Overexpressing the edited GluA2αR in the adar2MO restored normal expressions of cresting and sox9b. Moreover, overexpressing the unedited GluA2αQ in the wild type embryos resulted in reduction of crestin and sox9b expressions. These results argue that an elevated GluA2αQ level is sufficient for generating the cranial neural crest defects observed in the adar2MO. Our results present a link between dysfunction of AMPA receptors and defective development of the nervous system and cranial neural crest in the zebrafish.

This article is from Neural Regeneration Research , volume 9 . Abstract None

Orientation selectivity is a remarkable feature of the neurons located in the primary visual cortex. Provided that the visual neurons acquire orientation selectivity through activity-dependent Hebbian learning, the development process could be understood as a kind of symmetry breaking phenomenon in the view of physics. The key mechanisms of the development process are examined here in a neural system. Found is that there are at least two different mechanisms which lead to the development of orientation selectivity through breaking the radial symmetry in receptive fields. The first, a simultaneous symmetry breaking mechanism, bases on the competition between neighboring neurons, and the second, a spontaneous one, bases on the nonlinearity in interactions. It turns out that only the second mechanism leads to the formation of a columnar pattern which characteristics accord with those observed in an animal experiment.

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

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

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This article is from EvoDevo , volume 4 . Abstract Background: Arthropod and vertebrate appendages appear to have evolved via parallel co-option of a plesiomorphic gene regulatory network. Our previous work implies that annelids evolved unrelated appendage-forming mechanisms; we therefore found no support for homology of parapodia and arthropodia at the level of the whole appendage. We expand on that study here by asking whether expression of the LIM homeobox (Lhx) genes apterous and lim1 in the annelid Neanthes arenaceodentata supports homology of the dorsal branches as well as the proximodistal axes of parapodia and arthropodia. In addition, we explore whether the neural expression of apterous and lim1 in Neanthes supports the putative ancestral function of the Lhx gene family in regulating the differentiation and maintenance of neuronal subtypes. Results: Both genes exhibit continuous expression in specific portions of the developing central nervous system, from hatching to at least the 13-chaetiger stage. For example, nerve cord expression occurs in segmentally iterated patterns consisting of diffuse sets of many lim1-positive cells and comparatively fewer, clustered pairs of apterous-positive cells. Additionally, continuous apterous expression is observed in presumed neurosecretory ganglia of the posterior brain, while lim1 is continuously expressed in stomatogastric ganglia of the anterior brain. apterous is also expressed in the jaw sacs, dorsal parapodial muscles, and a presumed pair of cephalic sensory organs, whereas lim1 is expressed in multiple pharyngeal ganglia, the segmental peripheral nervous system, neuropodial chaetal sac muscles, and parapodial ligules. Conclusions: The early and persistent nervous system expression of apterous and lim1 in Neanthes juveniles supports conservation of Lhx function in bilaterian neural differentiation and maintenance. Our results also suggest that diversification of parapodial muscle precursors involves a complementary LIM code similar to those generating distinct neuronal identities in fly and mouse nerve cords. Expression of apterous and lim1 in discrete components of developing parapodia is intriguing but does not map to comparable expression of these genes in developing arthropod appendages. Thus, annelid and arthropod appendage development apparently evolved, in part, via distinct co-option of the neuronal regulatory architecture. These divergent patterns of apterous and lim1 activity seemingly reflect de novo origins of parapodia and arthropodia, although we discuss alternative hypotheses.

This article is from Human Molecular Genetics , volume 23 . Abstract Urofacial syndrome (UFS; previously Ochoa syndrome) is an autosomal recessive disease characterized by incomplete bladder emptying during micturition. This is associated with a dyssynergia in which the urethral walls contract at the same time as the detrusor smooth muscle in the body of the bladder. UFS is also characterized by an abnormal facial expression upon smiling, and bilateral weakness in the distribution of the facial nerve has been reported. Biallelic mutations in HPSE2 occur in UFS. This gene encodes heparanase 2, a protein which inhibits the activity of heparanase. Here, we demonstrate, for the first time, an in vivo developmental role for heparanase 2. We identified the Xenopus orthologue of heparanase 2 and showed that the protein is localized to the embryonic ventrolateral neural tube where motor neurons arise. Morpholino-induced loss of heparanase 2 caused embryonic skeletal muscle paralysis, and morphant motor neurons had aberrant morphology including less linear paths and less compactly-bundled axons than normal. Biochemical analyses demonstrated that loss of heparanase 2 led to upregulation of fibroblast growth factor 2/phosphorylated extracellular signal-related kinase signalling and to alterations in levels of transcripts encoding neural- and muscle-associated molecules. Thus, a key role of heparanase 2 is to buffer growth factor signalling in motor neuron development. These results shed light on the pathogenic mechanisms underpinning the clinical features of UFS and support the contention that congenital peripheral neuropathy is a key feature of this disorder.

This article is from Human Molecular Genetics , volume 23 . Abstract Urofacial syndrome (UFS; previously Ochoa syndrome) is an autosomal recessive disease characterized by incomplete bladder emptying during micturition. This is associated with a dyssynergia in which the urethral walls contract at the same time as the detrusor smooth muscle in the body of the bladder. UFS is also characterized by an abnormal facial expression upon smiling, and bilateral weakness in the distribution of the facial nerve has been reported. Biallelic mutations in HPSE2 occur in UFS. This gene encodes heparanase 2, a protein which inhibits the activity of heparanase. Here, we demonstrate, for the first time, an in vivo developmental role for heparanase 2. We identified the Xenopus orthologue of heparanase 2 and showed that the protein is localized to the embryonic ventrolateral neural tube where motor neurons arise. Morpholino-induced loss of heparanase 2 caused embryonic skeletal muscle paralysis, and morphant motor neurons had aberrant morphology including less linear paths and less compactly-bundled axons than normal. Biochemical analyses demonstrated that loss of heparanase 2 led to upregulation of fibroblast growth factor 2/phosphorylated extracellular signal-related kinase signalling and to alterations in levels of transcripts encoding neural- and muscle-associated molecules. Thus, a key role of heparanase 2 is to buffer growth factor signalling in motor neuron development. These results shed light on the pathogenic mechanisms underpinning the clinical features of UFS and support the contention that congenital peripheral neuropathy is a key feature of this disorder.

We study how modularity of the human brain changes as children develop into adults. Theory suggests that modularity can enhance the response function of a networked system subject to changing external stimuli. Thus, greater cognitive performance might be achieved for more modular neural activity, and modularity might likely increase as children develop. The value of modularity calculated from fMRI data is observed to increase during childhood development and peak in young adulthood. Head motion is deconvolved from the fMRI data, and it is shown that the dependence of modularity on age is independent of the magnitude of head motion. A model is presented to illustrate how modularity can provide greater cognitive performance at short times, i.e.\ task switching. A fitness function is extracted from the model. Quasispecies theory is used to predict how the average modularity evolves with age, illustrating the increase of modularity during development from children to adults that arises from selection for rapid cognitive function in young adults. Experiments exploring the effect of modularity on cognitive performance are suggested. Modularity may be a potential biomarker for injury, rehabilitation, or disease.

The distribution of the geometric distances of connected neurons is a practical factor underlying neural networks in the brain. It can affect the brain\'s dynamic properties at the ground level. Karbowski derived a power-law decay distribution that has not yet been verified by experiment. In this work, we check its validity using simulations with a phenomenological model. Based on the in vitro two-dimensional development of neural networks in culture vessels by Ito, we match the synapse number saturation time to obtain suitable parameters for the development process, then determine the distribution of distances between connected neurons under such conditions. Our simulations obtain a clear exponential distribution instead of a power-law one, which indicates that Karbowski's conclusion is invalid, at least for the case of in vitro neural network development in two-dimensional culture vessels.

We present a model of decentralized growth for Artificial Neural Networks (ANNs) inspired by the development and the physiology of real nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates modeled by a simple artificial chemistry. Gene expression is manifested as axon and dendrite growth, cell division and differentiation, substrate production and cell stimulation. We demonstrate the model's power with a hand-written genome that leads to the growth of a simple network which performs classical conditioning. To evolve more complex structures, we implemented a platform-independent, asynchronous, distributed Genetic Algorithm (GA) that allows users to participate in evolutionary experiments via the World Wide Web.

On this grant research was conducted in three directions to make progress towards the goal of implementing large scale learning neural networks on compact optoelectronic multichip modules. (1) Refinement of the Fuzzy ARTMAP neural network algorithm. The algorithm is very well suited to hardware implementation, but previously did not perform well on most real problems. (2) Design, fabrication, and characterization of birefringent computer generated holograms to implement the OTIS optical system for reflective modulators. This optical system provides a k-shuffle interconnection pattern that may be used to implement a backpropagation neural network. (3) Development of a single, compact, efficient optical system (OTIS-VE) compatible with surface-normal transmitters (such as VCSELs) implementing the k-shuffle interconnection pattern.

This article is from Acta Neuropathologica Communications , volume 2 . Abstract Background: Axon degeneration is a characteristic feature of multiple neuropathologic states and is also a mechanism of physiological neurodevelopmental pruning. The vast majority of in vivo studies looking at axon degeneration have relied on the use of classical silver degeneration stains, which have many limitations including lack of molecular specificity and incompatibility with immunolabeling methods. Because Wallerian degeneration is well known to involve cytoskeletal disassembly and because caspases are recently implicated in aspects of this process, we asked whether antibodies directed at caspase-generated neoepitopes of beta-actin and alpha-tubulin would be useful immunohistochemical markers of pathological and developmental axon degeneration. Results: Here we demonstrate that several forms of axon degeneration involve caspase-mediated cleavage of these cytoskeletal elements and are well-visualized using this approach. We demonstrate the generation of caspase-induced neoepitopes in a) an in vitro neuronal culture model using nerve growth factor-deprivation-induced degeneration and b) an in vivo model using ethanol-induced neuronal apoptosis, and c) during normal developmental pruning and physiological turnover of neurons. Conclusions: Our findings support recent experimental data that suggests caspase-3 and caspase-6 have specific non-redundant roles in developmental pruning. Finally, these findings may have clinical utility, as these markers highlight degenerating neurites in human hypoxic-ischemic injury. Our work not only confirms a common downstream mechanism involved in axon degeneration, but also illuminates the potential utility of caspase-cleavage-neoepitope antibodies as markers of neurodegeneration.

This article is from PLoS ONE , volume 9 . Abstract Heparan sulfate proteoglycans (HSPGs) play critical roles in the development and adult physiology of all metazoan organisms. Most of the known molecular interactions of HSPGs are attributed to the structurally highly complex heparan sulfate (HS) glycans. However, whether a specific HSPG (such as syndecan) contains HS modifications that differ from another HSPG (such as glypican) has remained largely unresolved. Here, a neural model in C. elegans is used to demonstrate for the first time the relationship between specific HSPGs and HS modifications in a defined biological process in vivo. HSPGs are critical for the migration of hermaphrodite specific neurons (HSNs) as genetic elimination of multiple HSPGs leads to 80% defect of HSN migration. The effects of genetic elimination of HSPGs are additive, suggesting that multiple HSPGs, present in the migrating neuron and in the matrix, act in parallel to support neuron migration. Genetic analyses suggest that syndecan/sdn-1 and HS 6-O-sulfotransferase, hst-6, function in a linear signaling pathway and glypican/lon-2 and HS 2-O-sulfotransferase, hst-2, function together in a pathway that is parallel to sdn-1 and hst-6. These results suggest core protein specific HS modifications that are critical for HSN migration. In C. elegans, the core protein specificity of distinct HS modifications may be in part regulated at the level of tissue specific expression of genes encoding for HSPGs and HS modifying enzymes. Genetic analysis reveals that there is a delicate balance of HS modifications and eliminating one HS modifying enzyme in a compromised genetic background leads to significant changes in the overall phenotype. These findings are of importance with the view of HS as a critical regulator of cell signaling in normal development and disease.

This article is from Redox Biology , volume 2 . Abstract Glutaredoxin 2 is a vertebrate specific oxidoreductase of the thioredoxin family of proteins modulating the intracellular thiol pool. Thereby, glutaredoxin 2 is important for specific redox signaling and regulates embryonic development of brain and vasculature via reversible oxidative posttranslational thiol modifications. Here, we describe that glutaredoxin 2 is also required for successful heart formation. Knock-down of glutaredoxin 2 in zebrafish embryos inhibits the invasion of cardiac neural crest cells into the primary heart field. This leads to impaired heart looping and subsequent obstructed blood flow. Glutaredoxin 2 specificity of the observed phenotype was confirmed by rescue experiments. Active site variants of glutaredoxin 2 revealed that the (de)-glutathionylation activity is required for proper heart formation. Our data suggest that actin might be one target during glutaredoxin 2 regulated cardiac neural crest cell migration and embryonic heart development. In summary, this work represents further evidence for the general importance of redox signaling in embryonic development and highlights additionally the importance of glutaredoxin 2 during embryogenesis.

This article is from Genome Research , volume 23 . Abstract The neural crest is an excellent model system for the study of cell type diversification during embryonic development due to its multipotency, motility, and ability to form a broad array of derivatives ranging from neurons and glia, to cartilage, bone, and melanocytes. As a uniquely vertebrate cell population, it also offers important clues regarding vertebrate origins. In the past 30 yr, introduction of recombinant DNA technology has facilitated the dissection of the genetic program controlling neural crest development and has provided important insights into gene regulatory mechanisms underlying cell migration and differentiation. More recently, new genomic approaches have provided a platform and tools that are changing the depth and breadth of our understanding of neural crest development at a “systems” level. Such advances provide an insightful view of the regulatory landscape of neural crest cells and offer a new perspective on developmental as well as stem cell and cancer biology.

This article is from Genome Research , volume 23 . Abstract The neural crest is an excellent model system for the study of cell type diversification during embryonic development due to its multipotency, motility, and ability to form a broad array of derivatives ranging from neurons and glia, to cartilage, bone, and melanocytes. As a uniquely vertebrate cell population, it also offers important clues regarding vertebrate origins. In the past 30 yr, introduction of recombinant DNA technology has facilitated the dissection of the genetic program controlling neural crest development and has provided important insights into gene regulatory mechanisms underlying cell migration and differentiation. More recently, new genomic approaches have provided a platform and tools that are changing the depth and breadth of our understanding of neural crest development at a “systems” level. Such advances provide an insightful view of the regulatory landscape of neural crest cells and offer a new perspective on developmental as well as stem cell and cancer biology.

This article is from Genome Research , volume 23 . Abstract The neural crest is an excellent model system for the study of cell type diversification during embryonic development due to its multipotency, motility, and ability to form a broad array of derivatives ranging from neurons and glia, to cartilage, bone, and melanocytes. As a uniquely vertebrate cell population, it also offers important clues regarding vertebrate origins. In the past 30 yr, introduction of recombinant DNA technology has facilitated the dissection of the genetic program controlling neural crest development and has provided important insights into gene regulatory mechanisms underlying cell migration and differentiation. More recently, new genomic approaches have provided a platform and tools that are changing the depth and breadth of our understanding of neural crest development at a “systems” level. Such advances provide an insightful view of the regulatory landscape of neural crest cells and offer a new perspective on developmental as well as stem cell and cancer biology.

Bipolar Disorder (BD) is a highly hereditary and severe disorder. Large genome-wide association studies have identified CACNA1C, a calcium channel gene crucial for brain development and neural function, as a major genetic risk factor for BD. The strongest association is with a SNP located in the third intronic region of the gene, however, the underlying molecular mechanisms of the pathogenesis have not been elucidated yet completely so it restrains efficient treatment and worsens the prognosis. In this project, we provide an integrative approach combining patient-derived stem cells, CRISPR-engineered isogenic lines, and advanced 3D brain organoids to understand the characteristics of the neurodevelopmental disease comprehensively.

This article is from Biology Open , volume 3 . Abstract We previously found that the small GTPase Ras-dva1 is essential for the telencephalic development in Xenopus laevis because Ras-dva1 controls the Fgf8-mediated induction of FoxG1 expression, a key telencephalic regulator. In this report, we show, however, that Ras-dva1 and FoxG1 are expressed in different groups of cells; whereas Ras-dva1 is expressed in the outer layer of the anterior neural fold, FoxG1 and Fgf8 are activated in the inner layer from which the telencephalon is derived. We resolve this paradox by demonstrating that Ras-dva1 is involved in the transduction of Fgf8 signal received by cells in the outer layer, which in turn send a feedback signal that stimulates FoxG1 expression in the inner layer. We show that this feedback signal is transmitted by secreted Agr proteins, the expression of which is activated in the outer layer by mediation of Ras-dva1 and the homeodomain transcription factor Otx2. In turn, Agrs are essential for maintaining Fgf8 and FoxG1 expression in cells at the anterior neural plate border. Our finding reveals a novel feedback loop mechanism based on the exchange of Fgf8 and Agr signaling between neural and non-neural compartments at the anterior margin of the neural plate and demonstrates a key role of Ras-dva1 in this mechanism.

This document describes the development of an artificial neural-network-based algorithm for classifying soil behavior type from cone penetrometer strain gauge data. The network input consists of the two standard cone penetration test parameters: the logarithm of cone pressure and the percentage of sleeve friction to cone pressure (friction ratio). Network output is a one-of-n coding of 12 soil classifications. Three- and four-layer backpropagation networks are trained to associate 11,000 data points with the appropriate soil type. The best recall performance is obtained from a four-layer, 2 x 15 x 15 x 12 network with a tested accuracy rate of 98.2%. All classification errors occur at the decision boundaries between class regions. The network was incorporated into the data collection software of the prototype SCAPS vehicle in October 1993. The C source code is included as appendix A.

One problem in robot control is how to obtain accurate high speed trajectory tracking when the payload varies throughout the performance of the task. A solution to the problem is one requirement for realizing a manipulator capable of duplicating human performance. A manipulator with the ability to emulate human performance is one prerequisite for achieving Air Force Robotic Telepresence program objectives. A new form of adaptive model-based control is proposed and experimentally evaluated. An Adaptive Model-Based Neural Network Controller (AMBNNC) uses multilayer perceptron artificial neural networks to estimate the payload during high speed manipulator motion. The payload estimate adapts the feedforward compensator to unmodeled system dynamics and payload variations. The neural nets are trained through repetitive training on trajectory tracking error data. The AMBNNC is experimentally evaluated on the third link of a PUMA-560 manipulator. Tracking performance is evaluated for a wide range of payload and trajectory conditions and compared to a non-adaptive model-based controller. The superior tracking accuracy of the AMBNNC demonstrates the potential of the proposed technique. Keywords: Robot, Robotics, Robot control, Adaptive control, Pattern recognition, Parameter estimation, Theses. (AW)

During the second year of the DARPA ANNT Program contact, new neural network architectures were developed to carry out autonomous real-time preprocessing, segmentation, recognition, timing, and control of both spatial and temporal inputs. These architectures contribute to: (1) preprocessing of visual form and motion signals; (2) preprocessing of acoustic signals; (3) adaptive pattern recognition and categorization in an unsupervised learning context; (4) adaptive pattern recognition and prediction in a supervised learning context; (5) processing of temporal patterns using working memory networks, with applications to 3-D object recognition; (6) adaptive timing for task scheduling; (7) adaptive sensory-motor control using head-centered spatial representations of 3-D target position.

KAU Faculty of Medicine 3rd year CNS MODULE Anatomy lecture

Falls are dangerous and contribute to over 80% of injury-related hospitalization especially amongst the elderly. Hence, fall detection is important for preventing severe injuries and accidental deaths. Meanwhile, recognizing human activity is important for monitoring health status and quality of life as it can be applied in geriatric care and healthcare in general. This research presents the development of a fall detection and human activity recognition system using Threshold Based Method (TBM) and Neural Network (NN). Intentional forward fall and six other activities of daily living (ADLs), which include running, jumping, walking, sitting, lying, and standing are performed by 15 healthy volunteers in a series of experiments. There are four important stages involved in fall detection and ADL recognition, which are signal filtering, segmentation, features extraction and classification. For classification, TBM achieved an accuracy of 98.41% and 95.40% for fall detection and activity recognition respectively whereas NN achieved an accuracy of 97.78% and 96.77% for fall detection and activity recognition respectively. 

The proposed article described the basics of developing an artificial neural network as one of the components of a hybrid expert system for antifault control. The functioning of neurons, their reaction under various operating conditions are considered. A multilayer recurrent artificial neural network is also represented, using the method of back propagation of the error, in general form, and its training is shown. In addition, the application of such a network for analyzing and predicting the state of health of a complex technical system is described.

The proposed article described the basics of developing an artificial neural network as one of the components of a hybrid expert system for antifault control. The functioning of neurons, their reaction under various operating conditions are considered. A multilayer recurrent artificial neural network is also represented, using the method of back propagation of the error, in general form, and its training is shown. In addition, the application of such a network for analyzing and predicting the state of health of a complex technical system is described.

Study plan for "Explaining the link between dyslexia susceptibility genes DYX1C1, DCDC2, and KIAA0319 and neural development in healthy adolescents – a DTI – fMRI study". The study is part of the Cognitive development in adolescence: Towards neurogenetic markers and naturalistic experimental design -project.

Study plan for "Explaining the link between dyslexia susceptibility genes DYX1C1, DCDC2, and KIAA0319 and neural development in healthy adolescents – a DTI – fMRI study". The study is part of the Cognitive development in adolescence: Towards neurogenetic markers and naturalistic experimental design -project.

Study plan for "Explaining the link between dyslexia susceptibility genes DYX1C1, DCDC2, and KIAA0319 and neural development in healthy adolescents – a DTI – fMRI study". The study is part of the Cognitive development in adolescence: Towards neurogenetic markers and naturalistic experimental design -project.

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

Conventionally programmed digital computers can process numbers with great speed and precision, but do not easily recognize patterns or imprecise or contradictory data. Instead of being programmed in the conventional sense, artificial neural networks are capable of self-learning through exposure to repeated examples. However, the training of an ANN can be a time consuming and unpredictable process. A general method is being developed to mate the adaptability of the ANN with the speed and precision of the digital computer. This method was successful in building feedforward networks that can approximate functions and their partial derivatives from examples in a single iteration. The general method also allows the formation of feedforward networks that can approximate the solution to nonlinear ordinary and partial differential equations to desired accuracy without the need of examples. It is believed that continued research will produce artificial neural networks that can be used with confidence in practical scientific computing and engineering applications.

This article is from PLoS ONE , volume 9 . Abstract During mouse neocortical development, the Wnt–β-catenin signaling pathway plays essential roles in various phenomena including neuronal differentiation and proliferation of neural precursor cells (NPCs). Production of the appropriate number of neurons without depletion of the NPC population requires precise regulation of the balance between differentiation and maintenance of NPCs. However, the mechanism that suppresses Wnt signaling to prevent premature neuronal differentiation of NPCs is poorly understood. We now show that the HMG box transcription factor Tcf3 (also known as Tcf7l1) contributes to this mechanism. Tcf3 is highly expressed in undifferentiated NPCs in the mouse neocortex, and its expression is reduced in intermediate neuronal progenitors (INPs) committed to the neuronal fate. We found Tcf3 to be a repressor of Wnt signaling in neocortical NPCs in a reporter gene assay. Tcf3 bound to the promoter of the proneural bHLH gene Neurogenin1 (Neurog1) and repressed its expression. Consistent with this, Tcf3 repressed neuronal differentiation and increased the self-renewal activity of NPCs. We also found that Wnt signal stimulation reduces the level of Tcf3, and increases those of Tcf1 (also known as Tcf7) and Lef1, positive mediators of Wnt signaling, in NPCs. Together, these results suggest that Tcf3 antagonizes Wnt signaling in NPCs, thereby maintaining their undifferentiated state in the neocortex and that Wnt signaling promotes the transition from Tcf3-mediated repression to Tcf1/Lef1-mediated enhancement of Wnt signaling, constituting a positive feedback loop that facilitates neuronal differentiation.

Parenting behaviors are critical in shaping youths’ socioemotional and cognitive development, especially throughout childhood and during the transition to adolescence. Positive and supportive parenting behaviors both socialize effective emotion regulation and promote top-down executive functions such as working memory (Kerr et al., 2017; Schroeder & Kelly, 2009). Throughout late childhood and adolescence, emotion regulation and working memory undergo significant changes, not only as a result of the rearing environment but also due to ongoing brain development. Whereas some adolescents will follow normative trajectories of cognitive and emotional development, others may exhibit neurobiological vulnerabilities underlying processes that lead to later psychopathology (Beauchaine & McNulty, 2013). This data-driven study aims to: 1) derive latent profiles of neural function during working memory and implicit emotion processing in relevant ROIs, 2) identify transitions of profile membership across 24 months (Mage, baseline = 11, Mage, T2 = 13), and 3) characterize environmental predictors and socioemotional distal outcomes associated wth transitions between profiles. We will use longitudinal data from the ABCD project (NW1 = 11,854; NW5 = 10,414, NW7 = 6,251), including assessments of parenting at baseline, functional imaging at baseline and wave 5 (24 months post baseline), and psychopathology at baseline, wave 5, and wave 7 (36 months post baseline).

This study uses DTI and eye-tracking data to examine the potential neural networks involved in fear bias in infants. The main aim of the current study is to identify whether there is an association between White Matter (WM) tract integrity involved in amygdala-cortical connections and early emotional development in infants. Specifically, is this association present in the development of an attentional bias towards fearful faces?

Supporting Materials for Impact of Shared Genes and Family Environment in Theory of Mind Development (MSc Project)

This article is from Frontiers in Genetics , volume 5 . Abstract Alcohol intoxicated cells broadly alter their metabolites – among them methyl and acetic acid can alter the DNA and histone epigenetic codes. Together with the promiscuous effect of alcohol on enzyme activities (including DNA methyltransferases) and the downstream effect on microRNA and transposable elements, alcohol is well placed to affect intrinsic transcriptional programs of developing cells. Considering that the developmental consequences of early alcohol exposure so profoundly affect neural systems, it is not unfounded to reason that alcohol exploits transcriptional regulators to challenge canonical gene expression and in effect, intrinsic developmental pathways to achieve widespread damage in the developing nervous system. To fully evaluate the role of epigenetic regulation in alcohol-related developmental disease, it is important to first gather the targets of epigenetic players in neurodevelopmental models. Here, we attempt to review the cellular and genomic windows of opportunity for alcohol to act on intrinsic neurodevelopmental programs. We also discuss some established targets of fetal alcohol exposure and propose pathways for future study. Overall, this review hopes to illustrate the known epigenetic program and its alterations in normal neural stem cell development and further, aims to depict how alcohol, through neuroepigenetics, may lead to neurodevelopmental deficits observed in fetal alcohol spectrum disorders.

With this three-wave annual longitudinal study, we aim to examine changes in trust behavior involving an uncooperative interaction partner and their neural correlates across early adolescence.

Childhood adversity exposure is common and is associated with unfavorable physical and mental health outcomes (Cicchetti & Toth, 1995; McLaughlin et al., 2012). While cumulative risk models of adversity have been instrumental in demonstrating that children with more adversity exposure are at greatest risk for unfavorable outcomes (Felitti et al., 1998), they do not elucidate the mechanisms by which adversity confers this risk. The Dimensional Model of Adversity and Psychopathology (DMAP) proposes two dimensions of adversity exposure – deprivation and threat – which differentially impact developmental outcomes through separate neurodevelopmental pathways (McLaughlin, Sheridan, & Lambert, 2014; Sheridan & McLaughlin, 2014). The model proposes that deprivation is associated with neural structure in areas of the brain that support complex cognitive functions (e.g., executive function, language, associative learning), like the frontoparietal control and dorsal attention networks. Another recent conceptual model proposes that early deprivation exposure may impact early-developing visual regions in the ventral visual stream that may scaffold the development of higher-order cognitive skills (Rosen et al., 2019). The DMAP further proposes that threat exposures are associated with structure in areas of the brain that support fear learning, emotion regulation, and threat perception like the limbic network, salience network, default mode network, amygdala, and hippocampus. Previous hypothesis-driven work has supported that deprivation and threat exposures differentially predict neural structure separately in childhood and adolescence (Busso et al., 2017; McLaughlin et al., 2016; 2019; McLaughlin, Sheridan, Winter, et al., 2014; Rosen et al., 2018; Sheridan, Copeland, et al., 2019). There is, however, a lack of consistent longitudinal evidence supporting the association between adversity exposures and neurodevelopmental trajectories. Furthermore, data-driven tests of the DMAP could support its relevance in understanding developmental outcomes following adversity exposures relative to cumulative risk models (e.g., Sheridan, Shi, et al., 2019). In the present study, we will take a network analytical approach to examine clusters of adversity exposures and structural neural development in a longitudinal neuroimaging sample of children and adolescents. The study involved two study visits starting with youth aged 8-16 years in the Seattle area. Participants were recruited for increased likelihood of maltreatment exposure. At the first visit, participants reported on lifetime deprivation and threat exposures and underwent structural magnetic resonance imaging (MRI). Approximately two years later, subjects completed a follow-up neuroimaging assessment using the same scanner.

Parents and peers are two reference groups that are particularly salient and important for the type of risk attitudes that are learned and adopted as one’s one (i.e., internalized) throughout adolescence. However, less is known about the extent to which adolescents differentially integrate the perceived risk attitudes of their parents vs. peers into constructing their own risk attitudes over time. Given ongoing functional changes that occur in social and motivational brain systems during adolescence (Crone & Dahl, 2012), it is important to understand how age-related changes in brain systems associated with social influence may constrain the extent to which the brain encodes and integrates the perceived risk attitudes of others in the development of risk attitudes across adolescence. The proposed study has two goals: (1) Examine age-related changes in the extent to which adolescents internalize the perceived risk attitudes of their parents vs. peers when constructing their own risk attitudes; and (2) Examine whether trajectories of adolescents’ risk attitudes are shaped by the extent to which the adolescent brain differentially utilizes internalized perceptions of their parents’ or peers’ risk attitudes over time, with a focus on brain systems implicated in social decision making (vmPFC, mPFC, dmPFC, dACC).

LibriVox volunteers bring you 11 recordings of <em>To a Fish</em> by (James) Leigh Hunt. This was the weekly poetry project for the week of October 19th, 2008.

LibriVox volunteers bring you 8 recordings of <em>A Fish Answers</em> by James Leigh Hunt. This was the weekly poetry project for the week of October 26th, 2008.

Dark times for British Catholics hung over England in the days of King Henry VIII. Henry, influenced by the hated Thomas Cromwell, fell into opposition with them, suppressing them, and closing religious houses. In that period a famous shrine, erected centuries earlier at Walsingham and dedicated to our Lady, drew people from far and near for it was a favorite place of pilgrimage and the site of many miracles.<br><br>On their grandmother's and uncle's farm, far removed from this scene of persecution, were Jemmy Reynolds and his sister Joan. For a long time they had been promised the chance to make the pilgrimage to Walsingham, and now at last they were going. Their biggest problem was to find a suitable offering to our Lady, and Joan came upon the idea of presenting a great, fine candle. And so they set out upon a thrilling journey which eventually brings Jem face to face with the crafty Cromwell and King Henry himself.<br><br>What happens when they meet a cunning stranger on the way to the shrine and later when Jem attempts to rescue a friend from Cromwell's power are some of the exciting developments that make A Candle For Our Lady interesting and fast moving. True history and authentic background are woven into this story which provides a taste of the struggles English Catholics knew in a time when cruelty and greed ruled the land. (Summary from original jacket.)

A long poem telling the tragic story of Francesca da Rimini, the duped and adulterous bride, inspired by the character in Dante's Inferno. Published in 1816 and dedicated to Lord Byron, it is considered the pinnacle of Hunt's poetic achievements. Hunt, though having fine artistic sensibilities, was not placed among the first rank of lyric poets, many of whom he championed however. The Story of Rimini was written in prison, where he spent two years for slander of the Prince Regent, and is dramatically and vividly told, with much evocative scene-setting and careful portrayal of emotional conflicts. (Peter Tucker)

Isobel Violet Hunt was a British author renowned for her literary salons, which hosted such notables as H.G. Wells, D.H. Laurence, Henry James, W. Somerset Maugham, Oscar Wilde and Ezra Pound. In White Rose of Weary Leaf (often considered her best work), principal character, Amy, voices many of Hunt's New Woman theories of sexual, financial, and intellectual autonomy. Amy manages to successfully navigate through society in her roles as secretary and governess, until her reputation as an "Adventuress" leads to a supreme test. - summary by Lisa Reichert

James Henry Leigh Hunt, best known as Leigh Hunt, was an English critic, essayist, poet, and writer. - Summary by Wikipedia

An amusing but deeply poignant story, “The Last Ditch” describes the wartime experiences of a British aristocratic family who gradually realize that their old feudal perquisites are passing away in the trenches of the Great War and that unprecedented new forces are pushing out the comfortable old ways. Lady Arles is the matriarch determined to resist to her last breath. Her bohemian young daughter Venice is set on a career as a poet and even dallies with a Socialist lover, but in some ways is the family member who seems the most helpless without her old aristocratic privileges. Another daughter Ilsa brings scandal after scandal to the family because of her endless sexual flings, incorrigible almost to the last page. Audley Bar, beloved by at least two of the Ladies Arles, is the ennui-laden aristocratic adventurer, determined despite his middle age to go forth to war and do his bit, especially after one young friend after another dies on the Western Front. Author Violet Hunt pokes ironical, affectionate fun at her old-fashioned cast of characters, but as an ardent feminist and free-thinker finds ways to show her profound sympathies for the rising poor of England, the previously unprivileged who were finding some new freedoms in the passing of the Old Order. Her novel published while the seemingly endless War was still in full force, Hunt deftly sketches a portrait of a very human family, harrowed by loss and adrift in a new world. - Summary by Expatriate

A travel journal of a year the author spent in Germany. With a preface and two additional chapters by her partner, the novelist Ford Madox Ford (here using the surname Hueffer). - Summary by barbara2

Nine twisty-turny tales of tragic human drama, played out in Victorian parlors, death beds and lonely country roads. This collection of Violet Hunt writings has all the requirements for short story entertainment: flirtatious beauties, mismatched love, ''lung symptoms'', and cruel, cruel fate. Sometimes the horror has a ghostly source, but often the horror is rooted in our very human pathology. - Lisa Reichert

10Captain Sword and Captain Pen: A Poem

By Leigh Hunt

This Poem is the result of a sense of duty, which has taken the Author from quieter studies during a great public crisis. He obeyed the impulse with joy, because it took the shape of verse; but with more pain, on some accounts, than he chooses to express. However, he has done what he conceived himself bound to do; and if every zealous lover of his species were to express his feelings in like manner, to the best of his ability, individual opinions, little in themselves, would soon amount to an overwhelming authority, and hasten the day of reason and beneficence. - Summary by Advertisement

11Peaceful Atom

By Bernice Kohn Hunt

In this children's science book from the early 1960s, the concept of atoms and the science behind them is introduced. The book recounts the history of scientific discoveries related to atoms, radioactivity, and nuclear energy. The author promotes the benefits of atomic power plants and nuclear energy while also exploring other positive uses of radioisotopes. The book pointedly does not discuss the history of nuclear weapons and how the scientific discoveries related to atoms led to the ability to create those weapons. - Summary by Elsie Selwyn

Leigh Hunt was an English poet, essayist and editor best remembered as the host of a literary circle which gathered at his home in Hampstead and attracted many well known writers of the day including Lord Byron, Percy Shelley, John Keats, William Hazlitt, Thomas Moore and Charles Lamb. He wrote many letters to various friends including some Epistles in Verse of which those to Byron, Moore, Hazlitt and Lamb are recorded here. He also made translations from Poets of Antiquity (Homer, Theocritus, Anacreon and Catullus) (Summary by Alan Mapstone)