Disruption of embryonic blood-CSF barrier in chick embryos reveals the actual importance of this barrier to control E-CSF composition and homeostasis in early brain development

In vertebrates, early brain development takes place at the expanded anterior end of the neural tube. After closure of the anterior neuropore, the brain wall forms a physiologically sealed cavity that encloses embryonic cerebrospinal fluid (E-CSF), a complex and protein-rich fluid that is initially composed of trapped amniotic fluid. E-CSF has several crucial roles in brain anlagen development. Recently, we reported the presence of transient blood-CSF barrier located in the brain stem lateral to the ventral midline, at the mesencephalon and prosencephalon level, in chick and rat embryos by transporting proteins, water, ions and glucose in a selective manner via transcellular routes. To test the actual relevance of the control of E-CSF composition and homeostasis on early brain development by this embryonic blood-CSF barrier, we block the activity of this barrier by treating the embryos with 6-aminonicotinamide gliotoxin (6-AN). We demonstrate that 6-AN treatment in chick embryos blocks protein transport across the embryonic blood-CSF barrier, and that the disruption of the barrier properties is due to the cease transcellular caveolae transport, as detected by CAV-1 expression cease. We also show that the lack of protein transport across the embryonic blood-CSF barrier influences neuroepithelial cell survival, proliferation and neurogenesis, as monitored by neurepithelial progenitor cells survival, proliferation and neurogenesis. The blockage of embryonic blood-CSF transport also disrupts water influx to the E-CSF, as revealed by an abnormal increase in brain anlagen volume. These experiments contribute to delineate the actual extent of this blood-CSF embryonic barrier controlling E-CSF composition and homeostasis and the actual important of this control for early brain development, as well as to elucidate the mechanism by which proteins and water are transported thought transcellular routes across the neuroectoderm, reinforcing the crucial role of E-CSF for brain development.

The embryonic blood-CSF barrier has molecular elements for specific glucose transport and for the general transport of molecules via transcellular routes.

In vertebrates, early brain development takes place at the expanded anterior end of the neural tube, which is filled with embryonic cerebrospinal fluid (E-CSF). We have recently identified a transient blood-CSF barrier that forms between embryonic days E3 and E4 in chick embryos and that is responsible for the transport of proteins and control of E-CSF homeostasis, including osmolarity. Here we examined the presence of glucose transporter GLUT-1 as well the presence of caveolae-structural protein Caveolin1 (CAV-1) in the embryonic blood-CSF barrier which may be involved in the transport of glucose and of proteins, water and ions respectively across the neuroectoderm. In this paper we demonstrate the presence of GLUT-1 and CAV-1 in endothelial cells of blood vessels as well as in adjacent neuroectodermal cells, located in the embryonic blood-CSF barrier. In blood vessels, these proteins were detected as early as E4 in chick embryos and E12.7 in rat embryos, i.e. the point at which the embryonic blood-CSF barrier acquires this function. In the neuroectoderm of the embryonic blood-CSF barrier, GLUT-1 was also detected at E4 and E12.7 respectively, and CAV-1 was detected shortly thereafter in both experimental models. These experiments contribute to delineating the extent to which the blood-CSF embryonic barrier controls E-CSF composition and homeostasis during early stages of brain development in avians and mammals. Our results suggest the regulation of glucose transport to the E-CSF by means of GLUT-1 and also suggest a mechanism by which proteins are transported via transcellular routes across the neuroectoderm, thus reinforcing the crucial role of E-CSF in brain development.

Implementación y entrenamiento de un modelo clasificatorio de red neural sobre la base de datos IGBADAT para la clasificación de las rocas basálticas de acuerdo a las clases del sistema de clasificación tradicional de Yoder and Tiller.

Aquest treball vol implementar un projecte de mineria de dades en l'àrea de la petrologia ígnia, especialitat englobada dins la geologia clàssica.

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

Volatility smile extrapolation with an artificial neural network

I use a multi-layer feedforward perceptron, with backpropagation learning implemented via stochastic gradient descent, to extrapolate the volatility smile of Euribor derivatives over low-strikes by training the network on parametric prices.

Sox genes in C. elegans: sox-2 role in postembryonic development

Report for the scientific sojourn carried out at the Columbia University, United States, from 2010 to 2012. Expression of SoxB genes correlates with the commitment of cells to a neural fate; however, the relevance of SoxB proteins in early vertebrate neurogenesis has been difficult to prove genetically due to embryonic lethality and presumed redundant functions. The nematode C. Elegants has only 5 sox genes: sox-2 and sox-3 form the SoxB group while sem-2, sox-4 and egl-13 belong to other Sox groups. Our results show that sox-2 and sem-2 are the sox genes expressed earliest and in a broader manner during embryogenesis, being expressed in several neuronal progenitors. sox-3, sox-4 and egl-13 are expressed in few cells during late embryogenesis, when most neurons are already born. Both sox-2 and sem-2 null mutants are early larval lethal but do not show neuronal specification defects during embryonic development as indicated by quantification of a panneuronal reporter. Potential redundancy or compensatory mechanisms between different sox genes have been ruled out, strongly suggesting that sox genes are not required for specification of embryonically-derived neurons. However, at the first larval stage there are still several blast cells that will give rise to different postembryonic lineages, which generate several neurons amongst other cell types. nterestingly, sox-2 is expressed in many of these progenitor cells. Using mosaic analysis we have so far identified neurons derived from two different postembryonic lineages which fail to be generated in C. elegans sox-2 mutants. These results support the idea that postembryonic progenitor competence is compromised in the absence of sox-2.

Cannabinoid addiction: behavioral models and neural correlates

The use of cannabis sativa preparations as recreational drugs can be traced back to the earliest civilizations. However, animal models of cannabinoid addiction allowing the exploration of neural correlates of cannabinoid abuse have been developed only recently. We review these models and the role of the CB1 cannabinoid receptor, the main target of natural cannabinoids, and its interaction with opioid and dopamine transmission in reward circuits. Extensive reviews on the molecular basis of cannabinoid action are available elsewhere (Piomelli et al., 2000;Schlicker and Kathmann, 2001).

What can spike train distances tell us about the neural code?

Time scale parametric spike train distances like the Victor and the van Rossum distancesare often applied to study the neural code based on neural stimuli discrimination.Different neural coding hypotheses, such as rate or coincidence coding,can be assessed by combining a time scale parametric spike train distance with aclassifier in order to obtain the optimal discrimination performance. The time scalefor which the responses to different stimuli are distinguished best is assumed to bethe discriminative precision of the neural code. The relevance of temporal codingis evaluated by comparing the optimal discrimination performance with the oneachieved when assuming a rate code.We here characterize the measures quantifying the discrimination performance,the discriminative precision, and the relevance of temporal coding. Furthermore,we evaluate the information these quantities provide about the neural code. Weshow that the discriminative precision is too unspecific to be interpreted in termsof the time scales relevant for encoding. Accordingly, the time scale parametricnature of the distances is mainly an advantage because it allows maximizing thediscrimination performance across a whole set of measures with different sensitivitiesdetermined by the time scale parameter, but not due to the possibility toexamine the temporal properties of the neural code.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Podocalyxin is a novel polysialylated neural adhesion protein with multiple roles in neural development and synapse formation

Neural development and plasticity are regulated by neural adhesion proteins, including the polysialylated form of NCAM (PSA-NCAM). Podocalyxin (PC) is a renal PSA-containing protein that has been reported to function as an anti-adhesin in kidney podocytes. Here we show that PC is widely expressed in neurons during neural development. Neural PC interacts with the ERM protein family, and with NHERF1/2 and RhoA/G. Experiments in vitro and phenotypic analyses of podxl-deficient mice indicate that PC is involved in neurite growth, branching and axonal fasciculation, and that PC loss-of-function reduces the number of synapses in the CNS and in the neuromuscular system. We also show that whereas some of the brain PC functions require PSA, others depend on PC per se. Our results show that PC, the second highly sialylated neural adhesion protein, plays multiple roles in neural development.

Quality coding by neural populations in the early olfactory pathway: analysis using information theory

In this article, we analyze the ability of the early olfactory system to detect and discriminate different odors by means of information theory measurements applied to olfactory bulb activity images. We have studied the role that the diversity and number of receptor neuron types play in encoding chemical information. Our results show that the olfactory receptors of the biological system are low correlated and present good coverage of the input space. The coding capacity of ensembles of olfactory receptors with the same receptive range is maximized when the receptors cover half of the odor input space - a configuration that corresponds to receptors that are not particularly selective. However, the ensemble's performance slightly increases when mixing uncorrelated receptors of different receptive ranges. Our results confirm that the low correlation between sensors could be more significant than the sensor selectivity for general purpose chemo-sensory systems, whether these are biological or biomimetic.