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.

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.

Plasticity in the sensorimotor cortex induced by Music-supported therapy in stroke patients: a TMS study.

Playing a musical instrument demands the engagement of different neural systems. Recent studies about the musician"s brain and musical training highlight that this activity requires the close interaction between motor and somatosensory systems. Moreover, neuroplastic changes have been reported in motor-related areas after short and long-term musical training. Because of its capacity to promote neuroplastic changes, music has been used in the context of stroke neurorehabilitation. The majority of patients suffering from a stroke have motor impairments, preventing them to live independently. Thus, there is an increasing demand for effective restorative interventions for neurological deficits. Music-supported Therapy (MST) has been recently developed to restore motor deficits. We report data of a selected sample of stroke patients who have been enrolled in a MST program (1 month intense music learning). Prior to and after the therapy, patients were evaluated with different behavioral motor tests. Transcranial Magnetic Stimulation (TMS) was applied to evaluate changes in the sensorimotor representations underlying the motor gains observed. Several parameters of excitability of the motor cortex were assessed as well as the cortical somatotopic representation of a muscle in the affected hand. Our results revealed that participants obtained significant motor improvements in the paretic hand and those changes were accompanied by changes in the excitability of the motor cortex. Thus, MST leads to neuroplastic changes in the motor cortex of stroke patients which may explain its efficacy.

Plasticity in the sensorimotor cortex induced by Music-supported therapy in stroke patients: a TMS study.

Playing a musical instrument demands the engagement of different neural systems. Recent studies about the musician"s brain and musical training highlight that this activity requires the close interaction between motor and somatosensory systems. Moreover, neuroplastic changes have been reported in motor-related areas after short and long-term musical training. Because of its capacity to promote neuroplastic changes, music has been used in the context of stroke neurorehabilitation. The majority of patients suffering from a stroke have motor impairments, preventing them to live independently. Thus, there is an increasing demand for effective restorative interventions for neurological deficits. Music-supported Therapy (MST) has been recently developed to restore motor deficits. We report data of a selected sample of stroke patients who have been enrolled in a MST program (1 month intense music learning). Prior to and after the therapy, patients were evaluated with different behavioral motor tests. Transcranial Magnetic Stimulation (TMS) was applied to evaluate changes in the sensorimotor representations underlying the motor gains observed. Several parameters of excitability of the motor cortex were assessed as well as the cortical somatotopic representation of a muscle in the affected hand. Our results revealed that participants obtained significant motor improvements in the paretic hand and those changes were accompanied by changes in the excitability of the motor cortex. Thus, MST leads to neuroplastic changes in the motor cortex of stroke patients which may explain its efficacy.

Plasticity in the sensorimotor cortex induced by Music-supported therapy in stroke patients: a TMS study.

Playing a musical instrument demands the engagement of different neural systems. Recent studies about the musician"s brain and musical training highlight that this activity requires the close interaction between motor and somatosensory systems. Moreover, neuroplastic changes have been reported in motor-related areas after short and long-term musical training. Because of its capacity to promote neuroplastic changes, music has been used in the context of stroke neurorehabilitation. The majority of patients suffering from a stroke have motor impairments, preventing them to live independently. Thus, there is an increasing demand for effective restorative interventions for neurological deficits. Music-supported Therapy (MST) has been recently developed to restore motor deficits. We report data of a selected sample of stroke patients who have been enrolled in a MST program (1 month intense music learning). Prior to and after the therapy, patients were evaluated with different behavioral motor tests. Transcranial Magnetic Stimulation (TMS) was applied to evaluate changes in the sensorimotor representations underlying the motor gains observed. Several parameters of excitability of the motor cortex were assessed as well as the cortical somatotopic representation of a muscle in the affected hand. Our results revealed that participants obtained significant motor improvements in the paretic hand and those changes were accompanied by changes in the excitability of the motor cortex. Thus, MST leads to neuroplastic changes in the motor cortex of stroke patients which may explain its efficacy.

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.

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.

Phenotypic plasticity in the Caribbean sponge Callyspongia vaginalis (Porifera: Haplosclerida)

Sponge morphological plasticity has been a long-standing source of taxonomic difficulty. In the Caribbean, several morphotypes of the sponge Callyspongia vaginalis have been observed. To determine the taxonomic status of three of these morphotypes and their relationship with the congeneric species C. plicifera and C. fallax, we compared the spicule composition, spongin fiber skeleton and sequenced fragments of the mitochondrial genes 16S and COI and nuclear genes 28S and 18S ribosomal RNA. Phylogenetic analyses with ribosomal markers 18S and 28S rRNA confirmed the position of our sequences within the Callyspongiidae. None of the genetic markers provided evidence for consistent differentiation among the three morphotypes of C. vaginalis and C. fallax, and only C. plicifera stood as a distinct species. The 16S mtDNA gene was the most variable molecular marker for this group, presenting a nucleotide variability (π = 0.024) higher than that reported for COI. Unlike recent studies for other sponge genera, our results indicate that species in the genus Callyspongia maintain a high degree of phenotypic plasticity, and that morphological characteristics may not reflect reproductive boundaries in C. vaginalis.

Regulation of GABA(A) and glutamate receptor expression, synaptic facilitation and long-term potentiation in the hippocampus of prion mutant mice

Background: Prionopathies are characterized by spongiform brain degeneration, myoclonia, dementia, and periodic electroencephalographic (EEG) disturbances. The hallmark of prioniopathies is the presence of an abnormal conformational isoform (PrP(sc)) of the natural cellular prion protein (PrP(c)) encoded by the Prnp gene. Although several roles have been attributed to PrP(c), its putative functions in neuronal excitability are unknown. Although early studies of the behavior of Prnp knockout mice described minor changes, later studies report altered behavior. To date, most functional PrP(c) studies on synaptic plasticity have been performed in vitro. To our knowledge, only one electrophysiological study has been performed in vivo in anesthetized mice, by Curtis and coworkers. They reported no significant differences in paired-pulse facilitation or LTP in the CA1 region after Schaffer collateral/commissural pathway stimulation. Principal Findings: Here we explore the role of PrP(c) expression in neurotransmission and neural excitability using wild-type, Prnp -/- and PrP(c)-overexpressing mice (Tg20 strain). By correlating histopathology with electrophysiology in living behaving mice, we demonstrate that both Prnp -/- mice but, more relevantly Tg20 mice show increased susceptibility to KA, leading to significant cell death in the hippocampus. This finding correlates with enhanced synaptic facilitation in paired-pulse experiments and hippocampal LTP in living behaving mutant mice. Gene expression profiling using Illumina microarrays and Ingenuity pathways analysis showed that 129 genes involved in canonical pathways such as Ubiquitination or Neurotransmission were co-regulated in Prnp -/- and Tg20 mice. Lastly, RT-qPCR of neurotransmission-related genes indicated that subunits of GABA(A) and AMPA-kainate receptors are co-regulated in both Prnp -/- and Tg20 mice. Conclusions/Significance: Present results demonstrate that PrP(c) is necessary for the proper homeostatic functioning of hippocampal circuits, because of its relationships with GABA(A) and AMPA-Kainate neurotransmission. New PrP(c) functions have recently been described, which point to PrP(c) as a target for putative therapies in Alzheimer's disease. However, our results indicate that a "gain of function" strategy in Alzheimer's disease, or a "loss of function" in prionopathies, may impair PrP(c) function, with devastating effects. In conclusion, we believe that present data should be taken into account in the development of future therapies.

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.