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Background: Cerebral Cavernous Malformations (CCMs) are neurovascular abnormalities in the central nervous system (CNS) caused by loss of function mutations in KRIT1 (CCM1), CCM2, or PDCD10 (CCM3) genes. One of the most common symptoms in CCM patients is associated with motor disability, weakness, seizures, stress, and anxiety, and the extent of the symptom or symptoms may be due to the location of the lesion within the CNS or whether multiple lesions are present. Previous studies have primarily focused on understanding the pathology of CCM using animal models. However, more research has yet to explore the potential impact of CCM lesions on behavioral deficits in animal models, including effects on short-term and long-term memory, motor coordination, and function. Methods: We used the accelerating RotaRod test to assess motor and coordination deficits. We also used the open field test to assess locomotor activity and pathology-related behavior and Pavlovian fear conditioning to assess short-and long-term memory deficits. Our behavioral studies were complemented by proteomics, histology, immunofluorescence, and imaging techniques. We found that neuroinflammation is crucial in behavioral deficits in male and female mice with neurovascular CCM lesions (Slco1c1-iCreERT2; Pdcd10 fl/fl ; Pdcd10 BECKO ). Results: Functional behavior tests in male and female Pdcd10 BECKO mice revealed that CCM lesions cause sudden motor coordination deficits associated with the manifestation of profound neuroinflammatory lesions. Our findings indicate that maturation of CCM lesions in Pdcd10 BECKO mice also experienced a significant change in short- and long-term memory compared to their littermate controls, Pdcd10 fl/fl mice. Proteomic experiments reveal that as CCM lesions mature, there is an increase in pathways associated with inflammation, coagulation, and angiogenesis, and a decrease in pathways associated with learning and plasticity. Therefore, our study shows that Pdcd10 BECKO mice display a wide range of behavioral deficits due to significant lesion formation in their central nervous system and that signaling pathways associated with neuroinflammation and learning impact behavioral outcomes. Conclusions: Our study found that CCM animal models exhibited behavioral impairments such as decreased motor coordination and amnesia. These impairments were associated with the maturation of CCM lesions that displayed a neuroinflammatory pattern.
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How complex is the memory structure that honeybees use to navigate? Recently, an insect-inspired parsimonious spiking neural network model was proposed that enabled simulated ground-moving agents to follow learned routes. We adapted this model to flying insects and evaluate the route following performance in three different worlds with gradually decreasing object density. In addition, we propose an extension to the model to enable the model to associate sensory input with a behavioral context, such as foraging or homing. The spiking neural network model makes use of a sparse stimulus representation in the mushroom body and reward-based synaptic plasticity at its output synapses. In our experiments, simulated bees were able to navigate correctly even when panoramic cues were missing. The context extension we propose enabled agents to successfully discriminate partly overlapping routes. The structure of the visual environment, however, crucially determines the success rate. We find that the model fails more often in visually rich environments due to the overlap of features represented by the Kenyon cell layer. Reducing the landmark density improves the agents route following performance. In very sparse environments, we find that extended landmarks, such as roads or field edges, may help the agent stay on its route, but often act as strong distractors yielding poor route following performance. We conclude that the presented model is valid for simple route following tasks and may represent one component of insect navigation. Additional components might still be necessary for guidance and action selection while navigating along different memorized routes in complex natural environments.
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Potenciais de Ação/fisiologia , Voo Animal/fisiologia , Modelos Neurológicos , Corpos Pedunculados/citologia , Neurônios/fisiologia , Reconhecimento Psicológico/fisiologia , Animais , Abelhas , Simulação por Computador , Redes Neurais de Computação , Vias Neurais/fisiologia , Reforço Psicológico , Comportamento Espacial , Sinapses/fisiologiaRESUMO
This article describes the cellular sources for tyramine and the cellular targets of tyramine via the Tyramine Receptor 1 (AmTyr1) in the olfactory learning and memory neuropils of the honey bee brain. Clusters of approximately 160 tyramine immunoreactive neurons are the source of tyraminergic fibers with small varicosities in the optic lobes, antennal lobes, lateral protocerebrum, mushroom body (calyces and gamma lobes), tritocerebrum and subesophageal ganglion (SEG). Our tyramine mapping study shows that the primary sources of tyramine in the antennal lobe and calyx of the mushroom body are from at least two Ventral Unpaired Median neurons (VUMmd and VUMmx) with cell bodies in the SEG. To reveal AmTyr1 receptors in the brain, we used newly characterized anti-AmTyr1 antibodies. Immunolocalization studies in the antennal lobe with anti-AmTyr1 antibodies showed that the AmTyr1 expression pattern is mostly in the presynaptic sites of olfactory receptor neurons (ORNs). In the mushroom body calyx, anti-AmTyr1 mapped the presynaptic sites of uniglomerular Projection Neurons (PNs) located primarily in the microglomeruli of the lip and basal ring calyx area. Release of tyramine/octopamine from VUM (md and mx) neurons in the antennal lobe and mushroom body calyx would target AmTyr1 expressed on ORN and uniglomerular PN presynaptic terminals. The presynaptic location of AmTyr1, its structural similarity with vertebrate alpha-2 adrenergic receptors, and previous pharmacological evidence suggests that it has an important role in the presynaptic inhibitory control of neurotransmitter release.
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Early auditory deprivation has serious neurodevelopmental and cognitive repercussions largely derived from impoverished and delayed language acquisition. These conditions may be associated with early changes in brain connectivity. Vibrotactile stimulation is a sensory substitution method that allows perception and discrimination of sound, and even speech. To clarify the efficacy of this approach, a vibrotactile oddball task with 700 and 900 Hz pure-tones as stimuli [counterbalanced as target (T: 20% of the total) and non-target (NT: 80%)] with simultaneous EEG recording was performed by 14 profoundly deaf and 14 normal-hearing (NH) subjects, before and after a short training period (five 1-h sessions; in 2.5-3 weeks). A small device worn on the right index finger delivered sound-wave stimuli. The training included discrimination of pure tone frequency and duration, and more complex natural sounds. A significant P300 amplitude increase and behavioral improvement was observed in both deaf and normal subjects, with no between group differences. However, a P3 with larger scalp distribution over parietal cortical areas and lateralized to the right was observed in the profoundly deaf. A graph theory analysis showed that brief training significantly increased fronto-central brain connectivity in deaf subjects, but not in NH subjects. Together, ERP tools and graph methods depicted the different functional brain dynamic in deaf and NH individuals, underlying the temporary engagement of the cognitive resources demanded by the task. Our findings showed that the index-fingertip somatosensory mechanoreceptors can discriminate sounds. Further studies are necessary to clarify brain connectivity dynamics associated with the performance of vibrotactile language-related discrimination tasks and the effect of lengthier training programs.
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We have deployed recombinant adeno-associated viruses equipped with tetracycline-controlled genetic switches to manipulate gene expression in mouse brain. Here, we show a combinatorial genetic approach for inducible, cell type-specific gene expression and Cre/loxP mediated gene recombination in different brain regions. Our chemical-genetic approach will help to investigate 'when', 'where', and 'how' gene(s) control neuronal circuit dynamics, and organize, for example, sensory signal processing, learning and memory, and behavior.
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Octopamine (OA) underlies reinforcement during appetitive conditioning in the honey bee and fruit fly, acting via different subtypes of receptors. Recently, antibodies raised against a peptide sequence of one honey bee OA receptor, AmOA1, were used to study the distribution of these receptors in the honey bee brain (Sinakevitch et al., 2011). These antibodies also recognize an isoform of the AmOA1 ortholog in the fruit fly (OAMB, mushroom body OA receptor). Here we describe in detail the distribution of AmOA1 receptors in different types of neurons in the honey bee and fruit fly antennal lobes. We integrate this information into a detailed anatomical analysis of olfactory receptor neurons (ORNs), uni- and multi-glomerular projection neurons (uPNs, and mPNs) and local interneurons (LNs) in glomeruli of the antennal lobe. These neurons were revealed by dye injection into the antennal nerve, antennal lobe, medial and lateral antenno-protocerbral tracts (m-APT and l-APT), and lateral protocerebral lobe (LPL) by use of labeled cell lines in the fruit fly or by staining with anti-GABA. We found that ORN receptor terminals and uPNs largely do not show immunostaining for AmOA1. About seventeen GABAergic mPNs leave the antennal lobe through the ml-APT and branch into the LPL. Many, but not all, mPNs show staining for AmOA1. AmOA1 receptors are also in glomeruli on GABAergic processes associated with LNs. The data suggest that in both species one important action of OA in the antennal lobe involves modulation of different types of inhibitory neurons via AmOA1 receptors. We integrated this new information into a model of circuitry within glomeruli of the antennal lobes of these species.
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In this paper, we present two neural network models - devoted to two specific and widely investigated aspects of multisensory integration - in order to evidence the potentialities of computational models to gain insight into the neural mechanisms underlying organization, development, and plasticity of multisensory integration in the brain. The first model considers visual-auditory interaction in a midbrain structure named superior colliculus (SC). The model is able to reproduce and explain the main physiological features of multisensory integration in SC neurons and to describe how SC integrative capability - not present at birth - develops gradually during postnatal life depending on sensory experience with cross-modal stimuli. The second model tackles the problem of how tactile stimuli on a body part and visual (or auditory) stimuli close to the same body part are integrated in multimodal parietal neurons to form the perception of peripersonal (i.e., near) space. The model investigates how the extension of peripersonal space - where multimodal integration occurs - may be modified by experience such as use of a tool to interact with the far space. The utility of the modeling approach relies on several aspects: (i) The two models, although devoted to different problems and simulating different brain regions, share some common mechanisms (lateral inhibition and excitation, non-linear neuron characteristics, recurrent connections, competition, Hebbian rules of potentiation and depression) that may govern more generally the fusion of senses in the brain, and the learning and plasticity of multisensory integration. (ii) The models may help interpretation of behavioral and psychophysical responses in terms of neural activity and synaptic connections. (iii) The models can make testable predictions that can help guiding future experiments in order to validate, reject, or modify the main assumptions.