Cortical dynamics and Sensory integration in the awake mouse : impact of the behavioral context

La perception menant à une prise de décision implique de multiples aires corticales. Il a été proposé que l'information sensorielle se propage des aires sensorielles primaires, codant principalement la nature du stimulus, aux aires de haut-niveau - plus frontales - codant d'avantage la valence du stimulus ou la décision. Pour mieux comprendre l'intégration corticale des signaux sensoriels, nous avons enregistré les réponses sensorielles évoquées (RSE) simultanément dans différentes aires corticales, tandis que des souris apprenaient une tâche de détection sensorielle. Chez les souris ayant appris la tâche, une RSE est observée dans toutes les aires enregistrées suivant la stimulation de la vibrisse, avec des latences croissantes des aires somatosensorielles primaire (vS1) et secondaire (vS2), vers le cortex moteur primaire des vibrisses (vM1), le cortex pariétal associatif (PtA), l'hippocampe dorsal (dCA1) et enfin le cortex préfrontal médian (mPFC). Nous avons constaté une réduction des RSEs lors des échecs par rapport aux essais réussis dans toutes les aires, sauf vS1. Toutefois, seule l'inactivation de vS1, vS2 ou mPFC affecte significativement la performance des souris. Pendant l'apprentissage de la tâche, une augmentation sélective de la RSE est observée dans le mPFC en corrélation avec la performance. Des enregistrements unitaires dans le mPFC démontrent la nature excitatrice de la réponse sensorielle chez les souris entrainées. Nos résultats confirment ainsi que la réponse sensorielle dans le mPFC reflète l'importance comportementale du stimulus et corrèle avec la prise de décision, tandis que la réponse des aires sensorielles reflète plutôt la nature du stimulusSensory perception leading to goal-directed behavior involves multiple, spatially-distributed cortical areas. It has been hypothesized that sensory information flows from primary sensory areas encoding mainly the nature of the stimulus, to higher-order, more frontal, areas encoding the valence of the stimulus or the decision. To further understand the cortical integration of sensory signals, we recorded sensory evoked potentials (SEPs) simultaneously from different areas while mice learned a whisker-based sensory detection task. In mice that have learned the task, the whisker stimulus evoked SEP in all recorded areas with latencies increasing from the whisker primary (wS1) to the secondary somatosensory area (wS2), the whisker motor area (wM1), the parietal area (PtA), the dorsal hippocampus (dCA1) and the medial prefrontal cortex (mPFC). We found a reduction of SEPs during Miss trials compared with Hit trials in all areas except wS1. However, only the local inactivation of either wS1, wS2 or mPFC significantly impaired the mice performance. During training to the detection task, we observed a selective increase of the SEPs in mPFC that correlated with performance. Finally, using high-density extracellular recordings in mPFC, we found that whisker stimulation in trained mice evoked an early increase in the firing rate of putative excitatory neurons (regular spiking units) that was positively correlated with behavioral outcome. Our results support the idea that mPFC could signal the relevance of a sensory stimulus in the context of a well-defined behavior, whereas sensory areas would be more constrained by the nature of the stimulu

Highly Dynamic Spatiotemporal Organization of Low-Frequency Activities During Behavioral States in the Mouse Cerebral Cortex

Although low-frequency (LF < 10 Hz) activities have been considered as a hallmark of nonrapid eye movement (NREM) sleep, several studies have recently reported LF activities in the membrane potential of cortical neurons from different areas in awake mice. However, little is known about the spatiotemporal organization of LF activities across cortical areas during wakefulness and to what extent it differs during NREM sleep. We have thus investigated the dynamics of LF activities across cortical areas in awake and sleeping mice using chronic simultaneous local field potential recordings. We found that LF activities had higher amplitude in somatosensory and motor areas during quiet wakefulness and decreased in most areas during active wakefulness, resulting in a global state change that was overall correlated with motor activity. However, we also observed transient desynchronization of cortical states between areas, indicating a more local state regulation. During NREM sleep, LF activities had higher amplitude in all areas but slow-wave activity was only poorly correlated across cortical areas. Despite a maximal amplitude during NREM sleep, the coherence of LF activities between areas that are not directly connected dropped from wakefulness to NREM sleep, potentially reflecting a breakdown of long-range cortical integration associated with loss of consciousness

Reward-Based Learning Drives Rapid Sensory Signals in Medial Prefrontal Cortex and Dorsal Hippocampus Necessary for Goal-Directed Behavior

International audienceHighlights d Sensory-evoked responses in mPFC and dCA1 develop during learning d Sensory processing in mPFC and dCA1 is fast, beginning within 50 ms of stimulus d Sensory responses in mPFC and dCA1 correlate trial by trial with performance d mPFC and dCA1 are necessary for execution of a sensory detection tas

Identification of distinct immune activation profiles in adult humans

International audienceLatent infectious agents, microbial translocation, some metabolites and immune cell subpopulations, as well as senescence modulate the level and quality of activation of our immune system. Here, we tested whether various in vivo immune activation profiles may be distinguished in a general population. We measured 43 markers of immune activation by 8-color flow cytometry and ELISA in 150 adults, and performed a double hierarchical clustering of biomarkers and volunteers. We identified five different immune activation profiles. Profile 1 had a high proportion of naïve T cells. By contrast, Profiles 2 and 3 had an elevated percentage of terminally differentiated and of senescent CD4+ T cells and CD8+ T cells, respectively. The fourth profile was characterized by NK cell activation, and the last profile, Profile 5, by a high proportion of monocytes. In search for etiologic factors that could determine these profiles, we observed a high frequency of naïve Treg cells in Profile 1, contrasting with a tendency to a low percentage of Treg cells in Profiles 2 and 3. Moreover, Profile 5 tended to have a high level of 16s ribosomal DNA, a direct marker of microbial translocation. These data are compatible with a model in which specific causes, as the frequency of Treg or the level of microbial translocation, shape specific profiles of immune activation. It will be of interest to analyze whether some of these profiles drive preferentially some morbidities known to be fueled by immune activation, as insulin resistance, atherothrombosis or liver steatosis

Esr1+ hypothalamic-habenula neurons shape aversive states

Excitatory projections from the lateral hypothalamic area (LHA) to the lateral habenula (LHb) drive aversive responses. We used patch-sequencing (Patch-seq) guided multimodal classification to define the structural and functional heterogeneity of the LHA–LHb pathway. Our classification identified six glutamatergic neuron types with unique electrophysiological properties, molecular profiles and projection patterns. We found that genetically defined LHA–LHb neurons signal distinct aspects of emotional or naturalistic behaviors, such as estrogen receptor 1-expressing (Esr1+) LHA–LHb neurons induce aversion, whereas neuropeptide Y-expressing (Npy+) LHA–LHb neurons control rearing behavior. Repeated optogenetic drive of Esr1+ LHA–LHb neurons induces a behaviorally persistent aversive state, and large-scale recordings showed a region-specific neural representation of the aversive signals in the prelimbic region of the prefrontal cortex. We further found that exposure to unpredictable mild shocks induced a sex-specific sensitivity to develop a stress state in female mice, which was associated with a specific shift in the intrinsic properties of bursting-type Esr1+ LHA–LHb neurons. In summary, we describe the diversity of LHA–LHb neuron types and provide evidence for the role of Esr1+ neurons in aversion and sexually dimorphic stress sensitivity