Imaging of experience-dependent structural plasticity in the mouse neocortex in vivo

The functionality of adult neocortical circuits can be altered by novel experiences or learning. This functional plasticity appears to rely on changes in the strength of neuronal connections that were established during development. Here we will describe some of our studies in which we have addressed whether structural changes, including the remodeling of axons and dendrites with synapse formation and elimination, could underlie experience-dependent plasticity in the adult neocortex. Using 2-photon laser-scanning microscopes and transgenic mice expressing GFP in a subset of pyramidal cells, we have observed that a small subset of dendritic spines continuously appear and disappear on a daily basis, whereas the majority of spines persists for months. Axonal boutons from different neuronal classes displayed similar behavior, although the extent of remodeling varied. Under baseline conditions, new spines in the barrel cortex were mostly transient and rarely survived for more than a week. However, when every other whisker was trimmed, the generation and loss of persistent spines was enhanced. Ultrastructural reconstruction of previously imaged spines and boutons showed that new spines slowly form synapses. New spines persisting for a few days always had synapses, whereas very young spines often lacked synapses. New synapses were predominantly found on large, multi-synapse boutons, suggesting that spine growth is followed by synapse formation, preferentially on existing boutons. Altogether our data indicate that novel sensory experience drives the stabilization of new spines on subclasses of cortical neurons and promotes the formation of new synapses. These synaptic changes likely underlie experience-dependent functional remodeling of specific neocortical circuits.

Effects of unilateral motor cortex lesion on ipsilesional hand's reach and grasp performance in monkeys: relationship with recovery in the contralesional hand.

Manual dexterity, a prerogative of primates, is under the control of the corticospinal (CS) tract. Because 90-95% of CS axons decussate, it is assumed that this control is exerted essentially on the contralateral hand. Consistently, unilateral lesion of the hand representation in the motor cortex is followed by a complete loss of dexterity of the contralesional hand. During the months following lesion, spontaneous recovery of manual dexterity takes place to a highly variable extent across subjects, although largely incomplete. In the present study, we tested the hypothesis that after a significant postlesion period, manual performance in the ipsilesional hand is correlated with the extent of functional recovery in the contralesional hand. To this aim, ten adult macaque monkeys were subjected to permanent unilateral motor cortex lesion. Monkeys' manual performance was assessed for each hand during several months postlesion, using our standard behavioral test (modified Brinkman board task) that provides a quantitative measure of reach and grasp ability. The ipsilesional hand's performance was found to be significantly enhanced over the long term (100-300 days postlesion) in six of ten monkeys, with the six exhibiting the best, though incomplete, recovery of the contralesional hand. There was a statistically significant correlation (r = 0.932; P < 0.001) between performance in the ipsilesional hand after significant postlesion period and the extent of recovery of the contralesional hand. This observation is interpreted in terms of different possible mechanisms of recovery, dependent on the recruitment of motor areas in the lesioned and/or intact hemispheres.

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

Sleep disorders in children with cerebral palsy.

To determine the frequency and predictors of sleep disorders in children with cerebral palsy (CP) we analyzed the responses of 173 parents who had completed the Sleep Disturbance Scale for Children. The study population included 100 males (57.8%) and 73 females (42.2%; mean age 8y 10mo [SD 1y 11mo]; range 6y-11y 11mo). Eighty-three children (48.0%) had spastic diplegia, 59 (34.1%) congenital hemiplegia, 18 (10.4%) spastic quadriplegia, and 13 (7.5%) dystonic/dyskinetic CP. Seventy-three children (42.2%) were in Gross Motor Function Classification System Level I, 33 (19.1%) in Level II, 30 (17.3%) in Level III, 23 (13.3%) in Level IV, and 14 (8.1%) in Level V. Thirty children (17.3%) had epilepsy. A total sleep problem score and six factors indicative of the most common areas of sleep disorder in childhood were obtained. Of the children in our study, 23% had a pathological total sleep score, in comparison with 5% of children in the general population. Difficulty in initiating and maintaining sleep, sleep-wake transition, and sleep breathing disorders were the most frequently identified problems. Active epilepsy was associated with the presence of a sleep disorder (odds ratio [OR]=17.1, 95% confidence interval [CI] 2.5-115.3), as was being the child of a single-parent family (OR=3.9, 95% CI 1.3-11.6). Disorders of initiation and maintenance of sleep were more frequent in children with spastic quadriplegia (OR=12.9, 95% CI 1.9-88.0), those with dyskinetic CP (OR=20.6, 95% CI 3.1-135.0), and those with severe visual impairment (OR=12.5, 95% CI 2.5-63.1). Both medical and environmental factors seem to contribute to the increased frequency of chronic sleep disorders in children with CP.

Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

Homer1a is a core brain molecular correlate of sleep loss.

Sleep is regulated by a homeostatic process that determines its need and by a circadian process that determines its timing. By using sleep deprivation and transcriptome profiling in inbred mouse strains, we show that genetic background affects susceptibility to sleep loss at the transcriptional level in a tissue-dependent manner. In the brain, Homer1a expression best reflects the response to sleep loss. Time-course gene expression analysis suggests that 2,032 brain transcripts are under circadian control. However, only 391 remain rhythmic when mice are sleep-deprived at four time points around the clock, suggesting that most diurnal changes in gene transcription are, in fact, sleep-wake-dependent. By generating a transgenic mouse line, we show that in Homer1-expressing cells specifically, apart from Homer1a, three other activity-induced genes (Ptgs2, Jph3, and Nptx2) are overexpressed after sleep loss. All four genes play a role in recovery from glutamate-induced neuronal hyperactivity. The consistent activation of Homer1a suggests a role for sleep in intracellular calcium homeostasis for protecting and recovering from the neuronal activation imposed by wakefulness.

Consequences of sleep deprivation on neurotransmitter receptor expression and function.

Several pieces of evidence suggest that sleep deprivation causes marked alterations in neurotransmitter receptor function in diverse neuronal cell types. To date, this has been studied mainly in wake- and sleep-promoting areas of the brain and in the hippocampus, which is implicated in learning and memory. This article reviews findings linking sleep deprivation to modifications in neurotransmitter receptor function, including changes in receptor subunit expression, ligand affinity and signal transduction mechanisms. We focus on studies using sleep deprivation procedures that control for side-effects such as stress. We classify the changes with respect to their functional consequences on the activity of wake-promoting and/or sleep-promoting systems. We suggest that elucidation of how sleep deprivation affects neurotransmitter receptor function will provide functional insight into the detrimental effects of sleep loss.

MENTAL IMAGERY IN PERCEPTUAL LEARNING

L'imagerie mentale est définie comme une expérience similaire à la perception mais se déroulant en l'absence d'une stimulation physique. Des recherches antérieures ont montré que l'imagerie mentale améliore la performance dans certains domaines, comme par exemple le domaine moteur. Cependant, son rôle dans l'apprentissage perceptif n'a pas encore été étudié. L'apprentissage perceptif correspond à l'amélioration permanente des performances suite à la répétition de la même tâche. Cette thèse présente une série des résultats empiriques qui montrent que l'apprentissage perceptif peut aussi être achevé en l'absence des stimuli physiques. En effet, imaginer des stimuli visuels amène à une meilleure performance avec les stimuli réels. Donc, les processus sous-jacents l'apprentissage perceptif ne sont pas uniquement déclenchés par les stimuli sensoriels, mais également par des signaux internes. En plus, l'apprentissage perceptif à travers l'imagerie mentale ne se réalise que seule-ment quand les stimuli ne sont pas (complètement) présents, mais gaiement quand les stimuli montrés ne sont pas utiles quant à la résolution de la tâche. - Mental imagery is described as an experience that resembles pereeptnal ex-perience but which occurs in the absence ef a physical stimulation. Despite its beneficial effects in, among others, motor performance, the role of mental imagery m perceptual learning has not yet been addressed. Here we focus on a specific sensory modality: vision. Perceptual learning is the ability to improve perception in a stable way through the repetition of a given task Here I demonstrate by a series of empirical results that a perceptual improve¬ment can also occur in the absence of a stimulation. Imagining visual stimuli is sufficient for successful perceptual learning. Hence, processes underlying perceptual learning are not only stimulus-driven but can also be driven by internally generated signals. Moreover, I also show that perceptual learning via mental imagery can occur not only when physical stimuli are (partially) absent, but also in conditions where stimuli are uninformative with respect to the task that has to be learned.

Pattern recognition of sleep in rodents using piezoelectric signals generated by gross body movements.

Current research on sleep using experimental animals is limited by the expense and time-consuming nature of traditional EEG/EMG recordings. We present here an alternative, noninvasive approach utilizing piezoelectric films configured as highly sensitive motion detectors. These film strips attached to the floor of the rodent cage produce an electrical output in direct proportion to the distortion of the material. During sleep, movement associated with breathing is the predominant gross body movement and, thus, output from the piezoelectric transducer provided an accurate respiratory trace during sleep. During wake, respiratory movements are masked by other motor activities. An automatic pattern recognition system was developed to identify periods of sleep and wake using the piezoelectric generated signal. Due to the complex and highly variable waveforms that result from subtle postural adjustments in the animals, traditional signal analysis techniques were not sufficient for accurate classification of sleep versus wake. Therefore, a novel pattern recognition algorithm was developed that successfully distinguished sleep from wake in approximately 95% of all epochs. This algorithm may have general utility for a variety of signals in biomedical and engineering applications. This automated system for monitoring sleep is noninvasive, inexpensive, and may be useful for large-scale sleep studies including genetic approaches towards understanding sleep and sleep disorders, and the rapid screening of the efficacy of sleep or wake promoting drugs.

Motor overactivity and loss of motor circadian rhythm in fatal familial insomnia: an actigraphic study.

The 24-hour rest-activity pattern and the amount of motor activity was studied in a patient with fatal familial insomnia (FFI) by means of wrist actigraphy. During the study, the patient underwent indirect calorimetry. The 52-day recording showed severe disruption of the 24-hour rest-activity pattern with increased motor activity up to 80%. The 24-hour energy expenditure, assayed in a respiration chamber, was strikingly elevated by 60%. Chronic motor overactivity and loss of circadian rest-activity rhythm may play a role in the progressive metabolic exhaustion leading to death in FFI patients.

The Ca(V)3.3 calcium channel is the major sleep spindle pacemaker in thalamus.

Low-threshold (T-type) Ca(2+) channels encoded by the Ca(V)3 genes endow neurons with oscillatory properties that underlie slow waves characteristic of the non-rapid eye movement (NREM) sleep EEG. Three Ca(V)3 channel subtypes are expressed in the thalamocortical (TC) system, but their respective roles for the sleep EEG are unclear. Ca(V)3.3 protein is expressed abundantly in the nucleus reticularis thalami (nRt), an essential oscillatory burst generator. We report the characterization of a transgenic Ca(V)3.3(-/-) mouse line and demonstrate that Ca(V)3.3 channels are indispensable for nRt function and for sleep spindles, a hallmark of natural sleep. The absence of Ca(V)3.3 channels prevented oscillatory bursting in the low-frequency (4-10 Hz) range in nRt cells but spared tonic discharge. In contrast, adjacent TC neurons expressing Ca(V)3.1 channels retained low-threshold bursts. Nevertheless, the generation of synchronized thalamic network oscillations underlying sleep-spindle waves was weakened markedly because of the reduced inhibition of TC neurons via nRt cells. T currents in Ca(V)3.3(-/-) mice were <30% compared with those in WT mice, and the remaining current, carried by Ca(V)3.2 channels, generated dendritic [Ca(2+)](i) signals insufficient to provoke oscillatory bursting that arises from interplay with Ca(2+)-dependent small conductance-type 2 K(+) channels. Finally, naturally sleeping Ca(V)3.3(-/-) mice showed a selective reduction in the power density of the σ frequency band (10-12 Hz) at transitions from NREM to REM sleep, with other EEG waves remaining unaltered. Together, these data identify a central role for Ca(V)3.3 channels in the rhythmogenic properties of the sleep-spindle generator and provide a molecular target to elucidate the roles of sleep spindles for brain function and development.

Endothelial dependant coronary vasoreactivity measured by 82Rb cardiac PET in obstructive sleep apnea patients before and after CPAP treatment

Introduction: Obstructive sleep apnea (OSA) is associated with an increased risk of cardiovascular diseases. Endothelial dysfunction is believed to be one of the pathophysiological mechanism underlying this association. Our aim was to compare endothelial dependent coronary vasoreactivity in obstructive sleep apnea (OSA) patients and controls by quantifying myocardial blood flow (MBF) response to cold pressure testing (CPT) with 82Rb cardiac PET/CT. Methods: Twenty-four OSA patients (2W/22M, mean age 58 yo, mean BMI 28.6 kg/m2) with an apnea-hypopnea index (AHI) >30/h and 9 healthy volunteers (AHI <10/h) underwent a full night sleep recording (PSG) and a dynamic 82 Rb cardiac PET/CT scan at rest, during CPT and adenosine stress. In OSA patients the same measurements (PSG and PET/CT) were respeated 6 weeks after initiating continuous positive airway pressure (autoCPAP) treatment. To reflect differences in baseline cardiac work, values were normalized according to ratepressure product (RPP). Results: At baseline, untreated OSA patients had a mean AHI of 48.8/h and showed a lower MBF response to CPT than controls (1.1 ± 0.2 mL/min/g vs. 1.3 ± 0.4 mL/min/g, P = 0.048). When treated with CPAP, CPT-MBF was not different between controls and well-treated OSA patients (1.2 ± 0.3 mL/min/g vs 1.3 ± 0.4 mL/min/g, P = 0.68), but it was significantly lower for insufficiently treated patients (n = 10) with a residual AHI >10/h (0.9 ± 0.2 mL/min/g vs 1.3 ± 0.4 mL/min/g, P = 0.03). There was also a trend toward a difference in CPT-MBF between insufficiently and well-treated OSA patients (1.2 ± 0.3 mL/min/g vs 0.9 ± 0.2 mL/min/g, P = 0.15). Conclusion: Untreated OSA patients have an impaired coronary endothelial function as measured by MBF response to CPT compared to control subjects. This difference disappears after 6 weeks of autoCPAP therapy but only in OSA patients showing a good response to CPAP (AHI <10/h). Further studies are needed to determine by which mechanism OSA and CPAP treatment influence coronary vasoreactivity.

On optimal learning schedules and the marginal value of cumulative cultural evolution.

The age-dependent choice between expressing individual learning (IL) or social learning (SL) affects cumulative cultural evolution. A learning schedule in which SL precedes IL is supportive of cumulative culture because the amount of nongenetically encoded adaptive information acquired by previous generations can be absorbed by an individual and augmented. Devoting time and energy to learning, however, reduces the resources available for other life-history components. Learning schedules and life history thus coevolve. Here, we analyze a model where individuals may have up to three distinct life stages: "infants" using IL or oblique SL, "juveniles" implementing IL or horizontal SL, and adults obtaining material resources with learned information. We study the dynamic allocation of IL and SL within life stages and how this coevolves with the length of the learning stages. Although no learning may be evolutionary stable, we find conditions where cumulative cultural evolution can be selected for. In that case, the evolutionary stable learning schedule causes individuals to use oblique SL during infancy and a mixture between IL and horizontal SL when juvenile. We also find that the selected pattern of oblique SL increases the amount of information in the population, but horizontal SL does not do so.

Interregional compensatory mechanisms of motor functioning in progressing preclinical neurodegeneration.

Understanding brain reserve in preclinical stages of neurodegenerative disorders allows determination of which brain regions contribute to normal functioning despite accelerated neuronal loss. Besides the recruitment of additional regions, a reorganisation and shift of relevance between normally engaged regions are a suggested key mechanism. Thus, network analysis methods seem critical for investigation of changes in directed causal interactions between such candidate brain regions. To identify core compensatory regions, fifteen preclinical patients carrying the genetic mutation leading to Huntington's disease and twelve controls underwent fMRI scanning. They accomplished an auditory paced finger sequence tapping task, which challenged cognitive as well as executive aspects of motor functioning by varying speed and complexity of movements. To investigate causal interactions among brain regions a single Dynamic Causal Model (DCM) was constructed and fitted to the data from each subject. The DCM parameters were analysed using statistical methods to assess group differences in connectivity, and the relationship between connectivity patterns and predicted years to clinical onset was assessed in gene carriers. In preclinical patients, we found indications for neural reserve mechanisms predominantly driven by bilateral dorsal premotor cortex, which increasingly activated superior parietal cortices the closer individuals were to estimated clinical onset. This compensatory mechanism was restricted to complex movements characterised by high cognitive demand. Additionally, we identified task-induced connectivity changes in both groups of subjects towards pre- and caudal supplementary motor areas, which were linked to either faster or more complex task conditions. Interestingly, coupling of dorsal premotor cortex and supplementary motor area was more negative in controls compared to gene mutation carriers. Furthermore, changes in the connectivity pattern of gene carriers allowed prediction of the years to estimated disease onset in individuals. Our study characterises the connectivity pattern of core cortical regions maintaining motor function in relation to varying task demand. We identified connections of bilateral dorsal premotor cortex as critical for compensation as well as task-dependent recruitment of pre- and caudal supplementary motor area. The latter finding nicely mirrors a previously published general linear model-based analysis of the same data. Such knowledge about disease specific inter-regional effective connectivity may help identify foci for interventions based on transcranial magnetic stimulation designed to stimulate functioning and also to predict their impact on other regions in motor-associated networks.

Cellular and molecular mechanisms underlying the effects of sleep loss on hippocampal synaptic plasticity

SUMMARY : The function of sleep for the organism is one of the most persistent and perplexing questions in biology. Current findings lead to the conclusion that sleep is primarily for the brain. In particular, a role for sleep in cognitive aspects of brain function is supported by behavioral evidence both in humans and animals. However, in spite of remarkable advancement in the understanding of the mechanisms underlying sleep generation and regulation, it has been proven difficult to determine the neurobiological mechanisms underlying the beneficial effect of sleep, and the detrimental impact of sleep loss, on learning and memory processes. In my thesis, I present results that lead to several critical steps forward in the link between sleep and cognitive function. My major result is the molecular identification and physiological analysis of a protein, the NR2A subunit of NMDA receptor (NMDAR), that confers sensitivity to sleep loss to the hippocampus, a brain structure classically involved in mnemonic processes. Specifically, I used a novel behavioral approach to achieve sleep deprivation in adult C57BL6/J mice, yet minimizing the impact of secondary factors associated with the procedure,.such as stress. By using in vitro electrophysiological analysis, I show, for the first time, that sleep loss dramatically affects bidirectional plasticity at CA3 to CA1 synapses in the hippocampus, a well established cellular model of learning and memory. 4-6 hours of sleep loss elevate the modification threshold for bidirectional synaptic plasticity (MT), thereby promoting long-term depression of CA3 to CA 1 synaptic strength after stimulation in the theta frequency range (5 Hz), and rendering long-term potentiation induction.more difficult. Remarkably, 3 hours of recovery sleep, after the deprivation, reset the MT at control values, thus re-establishing the normal proneness of synapses to undergo long-term plastic changes. At the molecular level, these functional changes are paralleled by a change in the NMDAR subunit composition. In particular, the expression of the NR2A subunit protein of NMDAR at CA3 to CA1 synapses is selectively and rapidly increased by sleep deprivation, whereas recovery sleep reset NR2A synaptic content to control levels. By using an array of genetic, pharmacological and computational approaches, I demonstrate here an obligatory role for NR2A-containing NMDARs in conveying the effect of sleep loss on CA3 to CAl MT. Moreover, I show that a genetic deletion of the NR2A subunit fully preserves hippocampal plasticity from the impact of sleep loss, whereas it does not alter sleepwake behavior and homeostatic response to sleep deprivation. As to the mechanism underlying the effects of the NR2A subunit on hippocampal synaptic plasticity, I show that the increased NR2A expression after sleep loss distinctly affects the contribution of synaptic and more slowly recruited NMDAR pools activated during plasticity-induction protocols. This study represents a major step forward in understanding the mechanistic basis underlying sleep's role for the brain. By showing that sleep and sleep loss affect neuronal plasticity by regulating the expression and function of a synaptic neurotransmitter receptor, I propose that an important aspect of sleep function could consist in maintaining and regulating protein redistribution and ion channel trafficking at central synapses. These findings provide a novel starting point for investigations into the connections between sleep and learning, and they may open novel ways for pharmacological control over hippocampal .function during periods of sleep restriction. RÉSUMÉ DU PROJET La fonction du sommeil pour l'organisme est une des questions les plus persistantes et difficiles dans la biologie. Les découvertes actuelles mènent à la conclusion que le sommeil est essentiel pour le cerveau. En particulier, le rôle du sommeil dans les aspects cognitifs est soutenu par des études comportementales tant chez les humains que chez les animaux. Cependant, malgré l'avancement remarquable dans la compréhension des mécanismes sous-tendant la génération et la régulation du sommeil, les mécanismes neurobiologiques qui pourraient expliquer l'effet favorable du sommeil sur l'apprentissage et la mémoire ne sont pas encore clairs. Dans ma thèse, je présente des résultats qui aident à clarifier le lien entre le sommeil et la fonction cognitive. Mon résultat le plus significatif est l'identification moléculaire et l'analyse physiologique d'une protéine, la sous-unité NR2A du récepteur NMDA, qui rend l'hippocampe sensible à la perte de sommeil. Dans cette étude, nous avons utilisé une nouvelle approche expérimentale qui nous a permis d'induire une privation de sommeil chez les souris C57BL6/J adultes, en minimisant l'impact de facteurs confondants comme, par exemple, le stress. En utilisant les techniques de l'électrophysiologie in vitro, j'ai démontré, pour la première fois, que la perte de sommeil est responsable d'affecter radicalement la plasticité bidirectionnelle au niveau des synapses CA3-CA1 de l'hippocampe. Cela correspond à un mécanisme cellulaire de l'apprentissage et de la mémoire bien établi. En particulier, 4-6 heures de privation de sommeil élèvent le seuil de modification pour la plasticité synaptique bidirectionnelle (SM). Comme conséquence, la dépression à long terme de la transmission synaptique est induite par la stimulation des fibres afférentes dans la bande de fréquences thêta (5 Hz), alors que la potentialisation à long terme devient plus difficile. D'autre part, 3 heures de sommeil de récupération sont suffisant pour rétablir le SM aux valeurs contrôles. Au niveau moléculaire, les changements de la plasticité synaptiques sont associés à une altération de la composition du récepteur NMDA. En particulier, l'expression synaptique de la protéine NR2A du récepteur NMDA est rapidement augmentée de manière sélective par la privation de sommeil, alors que le sommeil de récupération rétablit l'expression de la protéine au niveau contrôle. En utilisant des approches génétiques, pharmacologiques et computationnelles, j'ai démontré que les récepteurs NMDA qui expriment la sous-unité NR2A sont responsables de l'effet de la privation de sommeil sur le SM. De plus, nous avons prouvé qu'une délétion génétique de la sous-unité NR2A préserve complètement la plasticité synaptique hippocampale de l'impact de la perte de sommeil, alors que cette manipulation ne change pas les mécanismes de régulation homéostatique du sommeil. En ce qui concerne les mécanismes, j'ai .découvert que l'augmentation de l'expression de la sous-unité NR2A au niveau synaptique modifie les propriétés de la réponse du récepteur NMDA aux protocoles de stimulations utilisés pour induire la plasticité. Cette étude représente un pas en avant important dans la compréhension de la base mécaniste sous-tendant le rôle du sommeil pour le cerveau. En montrant que le sommeil et la perte de sommeil affectent la plasticité neuronale en régulant l'expression et la fonction d'un récepteur de la neurotransmission, je propose qu'un aspect important de la fonction du sommeil puisse être finalisé au règlement de la redistribution des protéines et du tracking des récepteurs aux synapses centraux. Ces découvertes fournissent un point de départ pour mieux comprendre les liens entre le sommeil et l'apprentissage, et d'ailleurs, ils peuvent ouvrir des voies pour des traitements pharmacologiques dans le .but de préserver la fonction hippocampale pendant les périodes de restriction de sommeil.