Yprel networks, classification and incremental learning

This paperpresents a neural network methodology called « yprel networks ». After relating the main characteristics of the approach, we shall detail the incremental learning methodology used to improve the performances, which is based on the relearning phases from the classification errors . The results obtained on a characters recognition problem are then discussed .L'article présente un type de réseaux neuro-mimétiques appelé «réseaux d'yprels ». Après avoir rappelé quelques caractéristiques essentielles de ces réseaux, on précise la méthode d'apprentissage incrémental permettant d'améliorer les performances par reprise des erreurs de classification. Les résultats obtenus pour un problème de reconnaissance de caractères sont alors présentés

Document interpretation using perceptive cycles to build coherent objects. Application to the french cadastral maps

The methodology we have used for the interpretation of the French cadastral documents focuses on a number of studied results of the visual perception and a hierarchical description of the document. The strategy used has been based on the « model » document, employing a mixed approach including various « points of view » about the image to be processed. The results of this mixed analysis reveal the appearance of non-interpretable objects on the cadasrer, due to the presence of incoherent semantics. Thanks to the return cycles between the high and low level processing, an analytical strategy is proposed and allows, in order to independently cure the incoherence, thus to attain the most reliable interpretation of the cadastral map.Notre méthodologie d'interprétation des documents cadastraux français s'appuie sur un certain nombre de résultats d'études sur la perception visuelle ainsi que sur une description hiérarchisée du document. La stratégie utilisée, basée sur le « modèle » du document, repose sur une approche mixte comportant différents « points de vue » de l'image à traiter. Les résultats de cette analyse mixte mettent en évidence l'apparition d'objets non interprétables au sens du cadastre, du fait de la présence d'incohérences sémantiques. Une stratégie d'analyse est alors proposée et permet, grâce à des cycles d'aller-retours entre les traitements hauts et bas niveaux, de résoudre les incohérences de façon autonome, ceci afin d'interpréter au plus sûr la planche cadastrale

Geographic map understanding : Algorithms for hydrographic and road networks reconstruction

The French Institut Géographique National (IGN) wants to develop an automated map understanding system, for the geographical maps at scale 1/25000. The aim is to automatically convert the 2000 cartographic paper-maps in a geographical objects database, directly usable by a GIS. This paper describes a high-level method for the automated reconstruction of the network graphs, represented on the French geographic maps . This method is applied to the hydrographic and road networks, symbolized with dashed lines, interrupted solid lines and fragmented textured areas . The graph theory paradigm is used, which allows to naturally model those networks by graphs, and to formalize the constraints for their reconstruction . A priori knowledges on natural and cartographic networks are directly used in the reconstruction process, and translated either as invariants the networks must verify during the reconstruction, either as quality criterion for the likely considered connexions .L'Institut Géographique National (IGN) a pour objectif de développer sur la carte IGN au 1/25000 un système d'interprétation totalement automatique et complet de la carte. Le but est de convertir automatiquement le fond de cartes existant sous forme papier, en une base de données d'objets géographiques directement manipulables par un SIG. Cet article décrit une méthode générale de haut niveau pour la reconstruction automatique des graphes des réseaux représentés sur les cartes géographiques. Elle a été appliquée aux réseaux hydrographiques et routiers qui sont essentiellement composés de lignes tiretées, de traits pleins interrompus et d'objets surfaciques interrompus. Le formalisme utilisé est celui de la théorie des graphes, qui permet de modéliser naturellement ces réseaux et d'expliciter les contraintes liées à leur reconstruction. Les connaissances a priori sur les réseaux réels et cartographiques sont directement intégrées dans le processus de reconstruction, et traduites soit comme des invariants que doivent vérifier les réseaux en cours de reconstruction, soit comme des mesures de qualité sur les connexions vraissemblables envisagées

Neurodevelopmental Disruption of Cortico-Striatal Function Caused by Degeneration of Habenula Neurons

The habenula plays an important role on cognitive and affective functions by regulating monoamines transmission such as the dopamine and serotonin, such that its dysfunction is thought to underlie a number of psychiatric conditions. Given that the monoamine systems are highly vulnerable to neurodevelopmental insults, damages in the habenula during early neurodevelopment may cause devastating effects on the wide-spread brain areas targeted by monoamine innervations.Using a battery of behavioral, anatomical, and biochemical assays, we examined the impacts of neonatal damage in the habenula on neurodevelopmental sequelae of the prefrontal cortex (PFC) and nucleus accumbens (NAcc) and associated behavioral deficits in rodents. Neonatal lesion of the medial and lateral habenula by ibotenic acid produced an assortment of behavioral manifestations consisting of hyper-locomotion, impulsivity, and attention deficit, with hyper-locomotion and impulsivity being observed only in the juvenile period, whereas attention deficit was sustained up until adulthood. Moreover, these behavioral alterations were also improved by amphetamine. Our study further revealed that impulsivity and attention deficit were associated with disruption of PFC volume and dopamine (DA) receptor expression, respectively. In contrast, hyper-locomotion was associated with decreased DA transporter expression in the NAcc. We also found that neonatal administration of nicotine into the habenula of neonatal brains produced selective lesion of the medial habenula. Behavioral deficits with neonatal nicotine administration were similar to those caused by ibotenic acid lesion of both medial and lateral habenula during the juvenile period, whereas they were different in adulthood.Because of similarity between behavioral and brain alterations caused by neonatal insults in the habenula and the symptoms and suggested neuropathology in attention deficit/hyperactivity disorder (ADHD), these results suggest that neurodevelopmental deficits in the habenula and the consequent cortico-striatal dysfunctions may be involved in the pathogenesis and pathophysiology of ADHD

Input-specific control of reward and aversion in the ventral tegmental area

Ventral tegmental area (VTA) dopamine neurons have important roles in adaptive and pathological brain functions related to reward and motivation. However, it is unknown whether subpopulations of VTA dopamine neurons participate in distinct circuits that encode different motivational signatures, and whether inputs to the VTA differentially modulate such circuits. Here we show that, because of differences in synaptic connectivity, activation of inputs to the VTA from the laterodorsal tegmentum and the lateral habenula elicit reward and aversion in mice, respectively. Laterodorsal tegmentum neurons preferentially synapse on dopamine neurons projecting to the nucleus accumbens lateral shell, whereas lateral habenula neurons synapse primarily on dopamine neurons projecting to the medial prefrontal cortex as well as on GABAergic (γ-aminobutyric-acid-containing) neurons in the rostromedial tegmental nucleus. These results establish that distinct VTA circuits generate reward and aversion, and thereby provide a new framework for understanding the circuit basis of adaptive and pathological motivated behaviours.National Institutes of Health (U.S.) (Grant NIH NS069375)JPB FoundationNational Institute of Mental Health (U.S.

Stimulation of Midbrain Dopaminergic Structures Modifies Firing Rates of Rat Lateral Habenula Neurons

Ventral tegmental area (VTA) and substantia nigra pars compacta (SNpc) are midbrain structures known to be involved in mediating reward in rodents. Lateral habenula (LHb) is considered as a negative reward source and it is reported that stimulation of the LHb rapidly induces inhibition of firing in midbrain dopamine neurons. Interestingly, the phasic fall in LHb neuronal activity may follow the excitation of dopamine neurons in response to reward-predicting stimuli. The VTA and SNpc give rise to dopaminergic projections that innervate the LHb, which is also known to be involved in processing painful stimuli. But it's unclear what physiological effects these inputs have on habenular function. In this study we distinguished the LHb pain-activated neurons of the Wistar rats and assessed their electrophysiological responsiveness to the stimulation of the VTA and SNpc with either single-pulse stimulation (300 µA, 0.5 Hz) or tetanic stimulation (80 µA, 25 Hz). Single-pulse stimulation that was delivered to either midbrain structure triggered transient inhibition of firing of ∼90% of the LHb pain-activated neurons. However, tetanic stimulation of the VTA tended to evoke an elevation in neuronal firing rate. We conclude that LHb pain-activated neurons can receive diverse reward-related signals originating from midbrain dopaminergic structures, and thus participate in the regulation of the brain reward system via both positive and negative feedback mechanisms

Quelques problèmes posés par l'analyse spectrale basse frequence (Application à l'étude des oscillateurs)

L'étude des oscillateurs a montré la nécessité de définir une stabilité à court terme. Ce problème est lié à l'élimination des basses fréquences. En cherchant à optimiser cette opération, nous obtenons un filtrage simple nettement plus efficace que ceux utilisés jusqu'à ce jour dans ces études. Nous examinons par ailleurs le problème de l'analyse spectrale en basse fréquence en temps fini. La première étape consiste à rechercher le filtre numérique dont le gain G(v) soit "le plus étroit" centré sur une fréquence réglable f. Notre travail a consisté à comparer entre eux quelques critères d'optimisation. Une estimation de la densité spectrale est donnée par celle du moment du 2d ordre du processus filtré. Nous avons enfin envisagé la possibilité de regrouper dans un même traitement l'élimination des basses fréquences et l'analyse spectrale en vue d'obtenir une pseudo densité spectrale pour des processus dont la variance est infinie