Le décours temporel de l'utilisation des fréquences spatiales dans les troubles du spectre autistique

Notre système visuel extrait d'ordinaire l'information en basses fréquences spatiales (FS) avant celles en hautes FS. L'information globale extraite tôt peut ainsi activer des hypothèses sur l'identité de l'objet et guider l'extraction d'information plus fine spécifique par la suite. Dans les troubles du spectre autistique (TSA), toutefois, la perception des FS est atypique. De plus, la perception des individus atteints de TSA semble être moins influencée par leurs a priori et connaissances antérieures. Dans l'étude décrite dans le corps de ce mémoire, nous avions pour but de vérifier si l'a priori de traiter l'information des basses aux hautes FS était présent chez les individus atteints de TSA. Nous avons comparé le décours temporel de l'utilisation des FS chez des sujets neurotypiques et atteints de TSA en échantillonnant aléatoirement et exhaustivement l'espace temps x FS. Les sujets neurotypiques extrayaient les basses FS avant les plus hautes: nous avons ainsi pu répliquer le résultat de plusieurs études antérieures, tout en le caractérisant avec plus de précision que jamais auparavant. Les sujets atteints de TSA, quant à eux, extrayaient toutes les FS utiles, basses et hautes, dès le début, indiquant qu'ils ne possédaient pas l'a priori présent chez les neurotypiques. Il semblerait ainsi que les individus atteints de TSA extraient les FS de manière purement ascendante, l'extraction n'étant pas guidée par l'activation d'hypothèses.

Mechanisms underlying activation of neural stem cells in the adult central nervous system

À la fin du 19e siècle, Dr. Ramón y Cajal, un pionnier scientifique, a découvert les éléments cellulaires individuels, appelés neurones, composant le système nerveux. Il a également remarqué la complexité de ce système et a mentionné l’impossibilité de ces nouveaux neurones à être intégrés dans le système nerveux adulte. Une de ses citations reconnues : “Dans les centres adultes, les chemins nerveux sont fixes, terminés, immuables. Tout doit mourir, rien ne peut être régénérer” est représentative du dogme de l’époque (Ramón y Cajal 1928). D’importantes études effectuées dans les années 1960-1970 suggèrent un point de vue différent. Il a été démontré que les nouveaux neurones peuvent être générés à l’âge adulte, mais cette découverte a créé un scepticisme omniprésent au sein de la communauté scientifique. Il a fallu 30 ans pour que le concept de neurogenèse adulte soit largement accepté. Cette découverte, en plus de nombreuses avancées techniques, a ouvert la porte à de nouvelles cibles thérapeutiques potentielles pour les maladies neurodégénératives. Les cellules souches neurales (CSNs) adultes résident principalement dans deux niches du cerveau : la zone sous-ventriculaire des ventricules latéraux et le gyrus dentelé de l’hippocampe. En condition physiologique, le niveau de neurogenèse est relativement élevé dans la zone sous-ventriculaire contrairement à l’hippocampe où certaines étapes sont limitantes. En revanche, la moelle épinière est plutôt définie comme un environnement en quiescence. Une des principales questions qui a été soulevée suite à ces découvertes est : comment peut-on activer les CSNs adultes afin d’augmenter les niveaux de neurogenèse ? Dans l’hippocampe, la capacité de l’environnement enrichi (incluant la stimulation cognitive, l’exercice et les interactions sociales) à promouvoir la neurogenèse hippocampale a déjà été démontrée. La plasticité de cette région est importante, car elle peut jouer un rôle clé dans la récupération de déficits au niveau de la mémoire et l’apprentissage. Dans la moelle épinière, des études effectuées in vitro ont démontré que les cellules épendymaires situées autour du canal central ont des capacités d’auto-renouvellement et de multipotence (neurones, astrocytes, oligodendrocytes). Il est intéressant de noter qu’in vivo, suite à une lésion de la moelle épinière, les cellules épendymaires sont activées, peuvent s’auto-renouveller, mais peuvent seulement ii donner naissance à des cellules de type gliale (astrocytes et oligodendrocytes). Cette nouvelle fonction post-lésion démontre que la plasticité est encore possible dans un environnement en quiescence et peut être exploité afin de développer des stratégies de réparation endogènes dans la moelle épinière. Les CSNs adultes jouent un rôle important dans le maintien des fonctions physiologiques du cerveau sain et dans la réparation neuronale suite à une lésion. Cependant, il y a peu de données sur les mécanismes qui permettent l'activation des CSNs en quiescence permettant de maintenir ces fonctions. L'objectif général est d'élucider les mécanismes sous-jacents à l'activation des CSNs dans le système nerveux central adulte. Pour répondre à cet objectif, nous avons mis en place deux approches complémentaires chez les souris adultes : 1) L'activation des CSNs hippocampales par l'environnement enrichi (EE) et 2) l'activation des CSNs de la moelle épinière par la neuroinflammation suite à une lésion. De plus, 3) afin d’obtenir plus d’information sur les mécanismes moléculaires de ces modèles, nous utiliserons des approches transcriptomiques afin d’ouvrir de nouvelles perspectives. Le premier projet consiste à établir de nouveaux mécanismes cellulaires et moléculaires à travers lesquels l’environnement enrichi module la plasticité du cerveau adulte. Nous avons tout d’abord évalué la contribution de chacune des composantes de l’environnement enrichi à la neurogenèse hippocampale (Chapitre II). L’exercice volontaire promeut la neurogenèse, tandis que le contexte social augmente l’activation neuronale. Par la suite, nous avons déterminé l’effet de ces composantes sur les performances comportementales et sur le transcriptome à l’aide d’un labyrinthe radial à huit bras afin d’évaluer la mémoire spatiale et un test de reconnaissante d’objets nouveaux ainsi qu’un RNA-Seq, respectivement (Chapitre III). Les coureurs ont démontré une mémoire spatiale de rappel à court-terme plus forte, tandis que les souris exposées aux interactions sociales ont eu une plus grande flexibilité cognitive à abandonner leurs anciens souvenirs. Étonnamment, l’analyse du RNA-Seq a permis d’identifier des différences claires dans l’expression des transcripts entre les coureurs de courte et longue distance, en plus des souris sociales (dans l’environnement complexe). iii Le second projet consiste à découvrir comment les cellules épendymaires acquièrent les propriétés des CSNs in vitro ou la multipotence suite aux lésions in vivo (Chapitre IV). Une analyse du RNA-Seq a révélé que le transforming growth factor-β1 (TGF-β1) agit comme un régulateur, en amont des changements significatifs suite à une lésion de la moelle épinière. Nous avons alors confirmé la présence de cette cytokine suite à la lésion et caractérisé son rôle sur la prolifération, différentiation, et survie des cellules initiatrices de neurosphères de la moelle épinière. Nos résultats suggèrent que TGF-β1 régule l’acquisition et l’expression des propriétés de cellules souches sur les cellules épendymaires provenant de la moelle épinière.

Generating Discriminative Objective Proposals via Submodular Ranking

Object recognition has long been a core problem in computer vision. To improve object spatial support and speed up object localization for object recognition, generating high-quality category-independent object proposals as the input for object recognition system has drawn attention recently. Given an image, we generate a limited number of high-quality and category-independent object proposals in advance and used as inputs for many computer vision tasks. We present an efficient dictionary-based model for image classification task. We further extend the work to a discriminative dictionary learning method for tensor sparse coding. In the first part, a multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale. Object proposals are obtained by selecting a subset from the multi-scale segment pool via maximizing a submodular objective function, which consists of a weighted coverage term, a single-scale diversity term and a multi-scale reward term. The weighted coverage term forces the selected set of object proposals to be representative and compact; the single-scale diversity term encourages choosing segments from different exemplar clusters so that they will cover as many object patterns as possible; the multi-scale reward term encourages the selected proposals to be discriminative and selected from multiple layers generated by the hierarchical image segmentation. The experimental results on the Berkeley Segmentation Dataset and PASCAL VOC2012 segmentation dataset demonstrate the accuracy and efficiency of our object proposal model. Additionally, we validate our object proposals in simultaneous segmentation and detection and outperform the state-of-art performance. To classify the object in the image, we design a discriminative, structural low-rank framework for image classification. We use a supervised learning method to construct a discriminative and reconstructive dictionary. By introducing an ideal regularization term, we perform low-rank matrix recovery for contaminated training data from all categories simultaneously without losing structural information. A discriminative low-rank representation for images with respect to the constructed dictionary is obtained. With semantic structure information and strong identification capability, this representation is good for classification tasks even using a simple linear multi-classifier.

Implication of GluR2 subunit of AMPA receptor in RGS14(414)-mediated memory enhancement

Ongoing quest for finding treatment against memory loss seen in aging and in many neurological and neurodegenerative diseases, so far has been unsuccessful and memory enhancers are seen as a potential remedy against this brain dysfunction. Recently, we showed that gene corresponding to a protein called regulator of G-protein signaling 14 of 414 amino acids (RGS14414) is a robust memory enhancer (Lopez-Aranda et al. 2009: Science). RGS14414-treatment in area V2 of visual cortex caused memory enhancement to such extent that it converted short-term object recognition memory (ORM) of 45min into long lasting long-term memory that could be traced even after many months. Now, through targeting of multiple receptors and molecules known to be involved in memory processing, we found that GluR2 subunit of AMPA receptor might be key to memory enhancement in RGS-animals. RGS14-animals showed a progressive increase in GluR2 protein expression while processing an object information which reached to highest level after 60min of object exposure, a time period required for conversion of short-term ORM into long-term memory in our laboratory set up. Normal rats could retain an object information in brain for 45min (short-term) and not for 60min. However, RGS-treated rats are able to retain the same information for 24h or longer (long-term). Therefore, highest expression of GluR2 subunit seen at 60min suggests that this protein might be key in memory enhancement and conversion to long-term memory in RGS-animals. In addition, we will also discuss the implication of Hebbian plasticity and interaction of brain circuits in memory enhancement.

Behavioral traits predicting cocaine-conditioned place reference in mice: role of anxiety adn the basolateral amygdala

Aims. The individual susceptibility to cocaine addiction, a factor of interest in the understanding and prevention of this disorder, may be predicted by certain behavioral traits. However, these are not usually taken into account in research, making it difficult to identify whether they are a cause or a consequence of drug use. Methods. Male C57BL/6J mice underwent a battery of behavioral tests (elevated plus maze, hole-board, novelty preference in the Y maze, episodic-like object recognition memory and forced swimming test), followed by a cocaine-conditioned place preference (CPP) training to assess the reinforcing effect of the drug. In a second study, we aimed to determine the existence of neurobiological differences between the mice expressing high or low CPP by studying the number of neurons in certain addiction-related structures: the medial prefrontal cortex, the basolateral amygdala and the ventral tegmental area. Results. Anxiety-like behaviors in the elevated plus maze successfully predicted the cocaine-CPP behavior, so that the most anxious mice were also more likely to search for cocaine in a CPP paradigm. In addition, these mice exhibited an increased number of neurons in the basolateral amygdala, a key structure in emotional response including anxiety expression, without differences in the others regions analyzed. Conclusions. Our results suggest a relevant role of anxiety as a psychological risk factor for cocaine vulnerability, with the basolateral amygdala as potential common neural center for both anxiety and addiction.

Characterization of the behavioural phenotype of calpain-knockout mice

Dissertação de Mestrado, Ciências Biomédicas, Departamento de Ciências Biomédicas e Medicina, Universidade do Algarve, 2016

Cultural Heritage and Mobile Robotics Technologies

This paper reviews current research works at the authors’ Institutions to illustrate how mobile robotics and related technologies can be used to enhance economical fruition, control, protection and social impact of the cultural heritage. Robots allow experiencing on-line, from remote locations, tours at museums, archaeological areas and monuments. These solutions avoid travelling costs, increase beyond actual limits the number of simultaneous visitors, and prevent possible damages that can arise by over-exploitation of fragile environments. The same tools can be used for exploration and monitoring of cultural artifacts located in difficult to reach or dangerous areas. Examples are provided by the use of underwater robots in the exploration of deeply submerged archaeological areas. Besides, technologies commonly employed in robotics can be used to help exploring, monitoring and preserving cultural artifacts. Examples are provided by the development of procedures for data acquisition and mapping and by object recognition and monitoring algorithms.

Epothilone-d rescues cognition and attenuates alzheimer’s disease-like pathology in APP/PS1 mice

AIMS: Cognitive decline in Alzheimer's disease (AD) patients has been linked to synaptic damage and neuronal loss. Hyperphosphorylation of tau protein destabilizes microtubules leading to the accumulation of autophagy/vesicular material and the generation of dystrophic neurites, thus contributing to axonal/synaptic dysfunction. In this study, we analyzed the effect of a microtubule-stabilizing compound in the progression of the disease in the hippocampus of APP751SL/PS1M146L transgenic model. METHODS: APP/PS1 mice (3 month-old) were treated with a weekly intraperitoneal injection of 2 mg/kg epothilone-D (Epo-D) for 3 months. Vehicle-injected animals were used as controls. Mice were tested on the Morris water maze, Y-maze and object-recognition tasks for memory performance. Abeta, AT8, ubiquitin and synaptic markers levels were analyzed by Western-blots. Hippocampal plaque, synaptic and dystrophic loadings were quantified by image analysis after immunohistochemical stainings. RESULTS: Epo-D treated mice exhibited a significant improvement in the memory tests compared to controls. The rescue of cognitive deficits was associated to a significant reduction in the AD-like hippocampal pathology. Levels of Abeta, APP and ubiquitin were significantly reduced in treated animals. This was paralleled by a decrease in the amyloid burden, and more importantly, in the plaque-associated axonal dystrophy pathology. Finally, synaptic levels were significantly restored in treated animals compared to controls. CONCLUSION: Epo-D treatment promotes synaptic and spatial memory recovery, reduces the accumulation of extracellular Abeta and the associated neuritic pathology in the hippocampus of APP/PS1 model. Therefore, microtubule stabilizing drugs could be considered therapeutical candidates to slow down AD progression. Supported by FIS-PI12/01431 and PI15/00796 (AG),FIS-PI12/01439 and PI15/00957(JV)

Altered oscillatory dynamics of CA1 parvalbumin-basket cells during theta-gamma rhythmopathies of temporal lobe epilepsy

Recent reports in human demonstrate a role of theta– gamma coupling in memory for spatial episodes and a lack of coupling in people experiencing temporal lobe epilepsy, but the mechanisms are unknown. Using multisite silicon probe recordings of epileptic rats engaged in episodic-like object recognition tasks, we sought to evaluate the role of theta– gamma coupling in the absence of epileptiform activities. Our data reveal a specific association between theta– gamma (30 – 60 Hz) coupling at the proximal stratum radiatum of CA1 and spatial memory deficits. We targeted the microcircuit mechanisms with a novel approach to identify putative interneuronal types in tetrode recordings (parvalbumin basket cells in particular) and validated classification criteria in the epileptic context with neurochemical identification of intracellularly recorded cells. In epileptic rats, putative parvalbumin basket cells fired poorly modulated at the falling theta phase, consistent with weaker inputs from Schaffer collaterals and attenuated gamma oscillations, as evaluated by theta-phase decomposition of current–source density signals. We propose that theta– gamma interneuronal rhythmopathies of the temporal lobe are intimately related to episodic memory dysfunction in this condition.

Into the looking glass: Literacy acquisition and mirror invariance in preschool and first-grade children

At what point in reading development does literacy impact object recognition and orientation processing? Is it specific to mirror images? To answer these questions, forty-six 5- to 7-year-old preschoolers and first graders performed two same–different tasks differing in the matching criterion-orientation-based versus shape-based (orientation independent)-on geometric shapes and letters. On orientation-based judgments, first graders out- performed preschoolers who had the strongest difficulty with mirrored pairs. On shape-based judgments, first graders were slower for mirrored than identical pairs, and even slower than preschoolers. This mirror cost emerged with letter knowledge. Only first graders presented worse shape-based judgments for mirrored and rotated pairs of reversible (e.g., b-d; b-q) than nonreversible (e.g., e-ә) letters, indicating readers’ difficulty in ignoring orientation contrasts relevant to letters.

3D Trajectory Recovery for Tracking Multiple Objects and Trajectory Guided Recognition of Actions

A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high-level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliably segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

3D ellipsoid fitting for multi-view gait recognition

Gait recognition approaches continue to struggle with challenges including view-invariance, low-resolution data, robustness to unconstrained environments, and fluctuating gait patterns due to subjects carrying goods or wearing different clothes. Although computationally expensive, model based techniques offer promise over appearance based techniques for these challenges as they gather gait features and interpret gait dynamics in skeleton form. In this paper, we propose a fast 3D ellipsoidal-based gait recognition algorithm using a 3D voxel model derived from multi-view silhouette images. This approach directly solves the limitations of view dependency and self-occlusion in existing ellipse fitting model-based approaches. Voxel models are segmented into four components (left and right legs, above and below the knee), and ellipsoids are fitted to each region using eigenvalue decomposition. Features derived from the ellipsoid parameters are modeled using a Fourier representation to retain the temporal dynamic pattern for classification. We demonstrate the proposed approach using the CMU MoBo database and show that an improvement of 15-20% can be achieved over a 2D ellipse fitting baseline.

GrabCutSFM : how 3D information improves unsupervised object segmentation

In this paper, we present an unsupervised graph cut based object segmentation method using 3D information provided by Structure from Motion (SFM), called Grab- CutSFM. Rather than focusing on the segmentation problem using a trained model or human intervention, our approach aims to achieve meaningful segmentation autonomously with direct application to vision based robotics. Generally, object (foreground) and background have certain discriminative geometric information in 3D space. By exploring the 3D information from multiple views, our proposed method can segment potential objects correctly and automatically compared to conventional unsupervised segmentation using only 2D visual cues. Experiments with real video data collected from indoor and outdoor environments verify the proposed approach.