273 resultados para Thalamus


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This study was undertaken to investigate the effect of emotional stress on humoral immunoactivity and to examine whether the sympathetic nervous system was involved in the immunomodulation. In the present study, two types of emotional stressors were used. One was footshock apparatus used to cause the rats which were given footshock before, emotional stressed; the other was an empty water bottle used to cause the rats which were trained to drink water at two set times each day, emotional stressed. The effect of emotional stress on the primary immune function (anti-ovallum antibody level and spleen index), the endocrine response (corticosterone level, epinephrine and norepinephrine level), the behavioral changes (freezing, defecation, grooming and attacking behavior) were investigated. The main results were: 1. Two types of emotional stress significantly increased the level of plasma corticosterone, norepinephrine and epinephrine, as well as freezing, defecation and attacking behavior. 2. Two types of emotional stress significantly decreased the level of anti-ovallum antibody. A negative correlation between catecholamine level (epinephrine and norepinephrine) and antibody level or spleen index was found. 3. β-adrenergic receptor antagonist propranolol could reverse the immunomodulation induced by emotional stress. 4. After two types of emotional stress, c-fos expression was observed in the following brain areas or nucleus; arcuate nucleus, anterior commissure nucleus, diffuse part of dorsalmedial nucleus hypothalamus, lateral dorsal nucleus thalamus, medial nucleus amygdala, solitary nucleus, frontal cortex and cingulum. These brain areas and nucleus are involved in the central modulation of the autonomic nervous system. Taken together, these findings demonstrate that emotional stress can suppress humoral immunity and the activation of the sympathetic nervous system is involved in the humoral immunomodulation induced by emotional stress.

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The cognition and memory functions of the Basal Ganglia have been the focus of contemporary cognitive neuroscience researches. This study, from neuroanatomical and neurophysiological point of view, thoroughly surveyed the recent relevant research progress, carefully examined the evidences of the neurological basis for the Basal Ganglia possessing or participating cognition or memory functions. Moreover, it reviewed recent achievements on the cognitive functions of the basal ganglia based on researches on rodent animals, primate animals and human beings. Then it presented a series of experiments conducted, by neuropsychological and cognitive psychological methods, on neurological patients with focal lesions to the basal ganglia or combining with bilateral hippocampus or thalamus impaired to explore what the role of the basal ganglia play in human explicit and implicit memory. It was found that the lesions to the basal ganglia partially handicapped explicit verbal memory and completely impaired perceptual priming. It was also found that right cerebral cortex dysplasia but basal ganglia spared had no effects on priming tasks performances. The results suggested that the basal ganglia contain or accommodate higher cognitive functions and further suggested that priming be irrelevant to right cerebral cortex. It was posited that the basal ganglia, on the basis of interaction with prefrontal or temporal cortices, mediate movement function as well as cognition and memory functions.

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The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is consistent with recent data on cholinergic interneurons of the striatum are tonically active neurons (TANs) that respond with characteristic pauses to novel events and to appetitive and aversive conditioned stimuli. Fluctuations in acetylcholine release by TANs modulate performance- and learning- related dynamics in the striatum. Whereas tonic activity emerges from intrinsic properties of these neurons, glutamatergic inputs from thalamic centromedian-parafascicular nuclei, and dopaminergic inputs from midbrain are required for the generation of pause responses. No prior computational models encompass both intrinsic and synaptically-gated dynamics. We present a mathematical model that robustly accounts for behavior-related electrophysiological properties of TANs in terms of their intrinsic physiological properties and known afferents. In the model balanced intrinsic hyperpolarizing and depolarizing currents engender tonic firing, and glutamatergic inputs from thalamus (and cortex) both directly excite and indirectly inhibit TANs. If the latter inhibition, probably mediated by GABAergic NOS interneurons, exceeds a threshold, its effect is amplified by a KIR current to generate a prolongued pause. In the model, the intrinsic mechanisms and external inputs are both modulated by learning-dependent dopamine (DA) signals and our simulations revealed that many learning-dependent behaviors of TANs are explicable without recourse to learning-dependent changes in synapses onto TANs.

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A full understanding of consciouness requires that we identify the brain processes from which conscious experiences emerge. What are these processes, and what is their utility in supporting successful adaptive behaviors? Adaptive Resonance Theory (ART) predicted a functional link between processes of Consciousness, Learning, Expectation, Attention, Resonance, and Synchrony (CLEARS), includes the prediction that "all conscious states are resonant states." This connection clarifies how brain dynamics enable a behaving individual to autonomously adapt in real time to a rapidly changing world. The present article reviews theoretical considerations that predicted these functional links, how they work, and some of the rapidly growing body of behavioral and brain data that have provided support for these predictions. The article also summarizes ART models that predict functional roles for identified cells in laminar thalamocortical circuits, including the six layered neocortical circuits and their interactions with specific primary and higher-order specific thalamic nuclei and nonspecific nuclei. These prediction include explanations of how slow perceptual learning can occur more frequently in superficial cortical layers. ART traces these properties to the existence of intracortical feedback loops, and to reset mechanisms whereby thalamocortical mismatches use circuits such as the one from specific thalamic nuclei to nonspecific thalamic nuclei and then to layer 4 of neocortical areas via layers 1-to-5-to-6-to-4.

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The giant cholinergic interneurons of the striatum are tonically active neurons (TANs) that respond with characteristic pauses to novel events and to appetitive and aversive conditioned stimuli. Fluctuations in acetylcholine release by TANs modulate performance- and learning-related dynamics in the striatum. Whereas tonic activity emerges from intrinsic properties of these neurons, glutamatergic inputs from thalamic centromedian-parafascicular nuclei, and dopaminergic inputs from midbrain, are required for the generation of pause responses. No prior computational models encompass both intrinsic and synaptically-gated dynamics. We present a mathematical model that robustly accounts for behavior-related electrophysiological properties of TANs in terms of their intrinsic physiological properties and known afferents. In the model, balanced intrinsic hyperpolarizing and depolarizing currents engender tonic firing, and glutamatergic inputs from thalamus (and cortex) both directly excite and indirectly inhibit TANs. If the latter inhibition, presumably mediated by GABAergic interneurons, exceeds a threshold, its effect is amplified by a KIR current to generate a prolonged pause. In the model, the intrinsic mechanisms and external inputs are both modulated by learning-dependent dopamine (DA) signals and our simulations revealed that many learning-dependent behaviors of TANs are explicable without recourse to learning-dependent changes in synapses onto TANs. The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is consistent with recent data on cholinergic control of LTD of cortical synapses onto striatal spiny projection neurons.

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A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal cells, and NMDA receptors. This circuit forms part of a model neural system for the coordinated control of recognition learning, reinforcement learning, and motor learning, whose properties clarify how an animal can learn to acquire a delayed reward. Behavioral and neural data are summarized in support of each processing stage of the system. The relevant anatomical sites are in thalamus, neocortex, hippocampus, hypothalamus, amygdala, and cerebellum. Cerebellar influences on motor learning are distinguished from hippocampal influences on adaptive timing of reinforcement learning. The model simulates how damage to the hippocampal formation disrupts adaptive timing, eliminates attentional blocking, and causes symptoms of medial temporal amnesia. It suggests how normal acquisition of subcortical emotional conditioning can occur after cortical ablation, even though extinction of emotional conditioning is retarded by cortical ablation. The model simulates how increasing the duration of an unconditioned stimulus increases the amplitude of emotional conditioning, but does not change adaptive timing; and how an increase in the intensity of a conditioned stimulus "speeds up the clock", but an increase in the intensity of an unconditioned stimulus does not. Computer simulations of the model fit parametric conditioning data, including a Weber law property and an inverted U property. Both primary and secondary adaptively timed conditioning are simulated, as are data concerning conditioning using multiple interstimulus intervals (ISIs), gradually or abruptly changing ISis, partial reinforcement, and multiple stimuli that lead to time-averaging of responses. Neurobiologically testable predictions are made to facilitate further tests of the model.

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Recently, a number of investigators have examined the neural loci of psychological processes enabling the control of visual spatial attention using cued-attention paradigms in combination with event-related functional magnetic resonance imaging. Findings from these studies have provided strong evidence for the involvement of a fronto-parietal network in attentional control. In the present study, we build upon this previous work to further investigate these attentional control systems. In particular, we employed additional controls for nonattentional sensory and interpretative aspects of cue processing to determine whether distinct regions in the fronto-parietal network are involved in different aspects of cue processing, such as cue-symbol interpretation and attentional orienting. In addition, we used shorter cue-target intervals that were closer to those used in the behavioral and event-related potential cueing literatures. Twenty participants performed a cued spatial attention task while brain activity was recorded with functional magnetic resonance imaging. We found functional specialization for different aspects of cue processing in the lateral and medial subregions of the frontal and parietal cortex. In particular, the medial subregions were more specific to the orienting of visual spatial attention, while the lateral subregions were associated with more general aspects of cue processing, such as cue-symbol interpretation. Additional cue-related effects included differential activations in midline frontal regions and pretarget enhancements in the thalamus and early visual cortical areas.

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Mechanisms for the evolution of convergent behavioral traits are largely unknown. Vocal learning is one such trait that evolved multiple times and is necessary in humans for the acquisition of spoken language. Among birds, vocal learning is evolved in songbirds, parrots, and hummingbirds. Each time similar forebrain song nuclei specialized for vocal learning and production have evolved. This finding led to the hypothesis that the behavioral and neuroanatomical convergences for vocal learning could be associated with molecular convergence. We previously found that the neural activity-induced gene dual specificity phosphatase 1 (dusp1) was up-regulated in non-vocal circuits, specifically in sensory-input neurons of the thalamus and telencephalon; however, dusp1 was not up-regulated in higher order sensory neurons or motor circuits. Here we show that song motor nuclei are an exception to this pattern. The song nuclei of species from all known vocal learning avian lineages showed motor-driven up-regulation of dusp1 expression induced by singing. There was no detectable motor-driven dusp1 expression throughout the rest of the forebrain after non-vocal motor performance. This pattern contrasts with expression of the commonly studied activity-induced gene egr1, which shows motor-driven expression in song nuclei induced by singing, but also motor-driven expression in adjacent brain regions after non-vocal motor behaviors. In the vocal non-learning avian species, we found no detectable vocalizing-driven dusp1 expression in the forebrain. These findings suggest that independent evolutions of neural systems for vocal learning were accompanied by selection for specialized motor-driven expression of the dusp1 gene in those circuits. This specialized expression of dusp1 could potentially lead to differential regulation of dusp1-modulated molecular cascades in vocal learning circuits.

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OBJECTIVE: The authors sought to increase understanding of the brain mechanisms involved in cigarette addiction by identifying neural substrates modulated by visual smoking cues in nicotine-deprived smokers. METHOD: Event-related functional magnetic resonance imaging (fMRI) was used to detect brain activation after exposure to smoking-related images in a group of nicotine-deprived smokers and a nonsmoking comparison group. Subjects viewed a pseudo-random sequence of smoking images, neutral nonsmoking images, and rare targets (photographs of animals). Subjects pressed a button whenever a rare target appeared. RESULTS: In smokers, the fMRI signal was greater after exposure to smoking-related images than after exposure to neutral images in mesolimbic dopamine reward circuits known to be activated by addictive drugs (right posterior amygdala, posterior hippocampus, ventral tegmental area, and medial thalamus) as well as in areas related to visuospatial attention (bilateral prefrontal and parietal cortex and right fusiform gyrus). In nonsmokers, no significant differences in fMRI signal following exposure to smoking-related and neutral images were detected. In most regions studied, both subject groups showed greater activation following presentation of rare target images than after exposure to neutral images. CONCLUSIONS: In nicotine-deprived smokers, both reward and attention circuits were activated by exposure to smoking-related images. Smoking cues are processed like rare targets in that they activate attentional regions. These cues are also processed like addictive drugs in that they activate mesolimbic reward regions.

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The main impetus for a mini-symposium on corticothalamic interrelationships was the recent number of studies highlighting the role of the thalamus in aspects of cognition beyond sensory processing. The thalamus contributes to a range of basic cognitive behaviors that include learning and memory, inhibitory control, decision-making, and the control of visual orienting responses. Its functions are deeply intertwined with those of the better studied cortex, although the principles governing its coordination with the cortex remain opaque, particularly in higher-level aspects of cognition. How should the thalamus be viewed in the context of the rest of the brain? Although its role extends well beyond relaying of sensory information from the periphery, the main function of many of its subdivisions does appear to be that of a relay station, transmitting neural signals primarily to the cerebral cortex from a number of brain areas. In cognition, its main contribution may thus be to coordinate signals between diverse regions of the telencephalon, including the neocortex, hippocampus, amygdala, and striatum. This central coordination is further subject to considerable extrinsic control, for example, inhibition from the basal ganglia, zona incerta, and pretectal regions, and chemical modulation from ascending neurotransmitter systems. What follows is a brief review on the role of the thalamus in aspects of cognition and behavior, focusing on a summary of the topics covered in a mini-symposium held at the Society for Neuroscience meeting, 2014.

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Cognitive neuroscience, as a discipline, links the biological systems studied by neuroscience to the processing constructs studied by psychology. By mapping these relations throughout the literature of cognitive neuroscience, we visualize the semantic structure of the discipline and point to directions for future research that will advance its integrative goal. For this purpose, network text analyses were applied to an exhaustive corpus of abstracts collected from five major journals over a 30-month period, including every study that used fMRI to investigate psychological processes. From this, we generate network maps that illustrate the relationships among psychological and anatomical terms, along with centrality statistics that guide inferences about network structure. Three terms--prefrontal cortex, amygdala, and anterior cingulate cortex--dominate the network structure with their high frequency in the literature and the density of their connections with other neuroanatomical terms. From network statistics, we identify terms that are understudied compared with their importance in the network (e.g., insula and thalamus), are underspecified in the language of the discipline (e.g., terms associated with executive function), or are imperfectly integrated with other concepts (e.g., subdisciplines like decision neuroscience that are disconnected from the main network). Taking these results as the basis for prescriptive recommendations, we conclude that semantic analyses provide useful guidance for cognitive neuroscience as a discipline, both by illustrating systematic biases in the conduct and presentation of research and by identifying directions that may be most productive for future research.

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Fear conditioning is an established model for investigating posttraumatic stress disorder (PTSD). However, symptom triggers may vaguely resemble the initial traumatic event, differing on a variety of sensory and affective dimensions. We extended the fear-conditioning model to assess generalization of conditioned fear on fear processing neurocircuitry in PTSD. Military veterans (n=67) consisting of PTSD (n=32) and trauma-exposed comparison (n=35) groups underwent functional magnetic resonance imaging during fear conditioning to a low fear-expressing face while a neutral face was explicitly unreinforced. Stimuli that varied along a neutral-to-fearful continuum were presented before conditioning to assess baseline responses, and after conditioning to assess experience-dependent changes in neural activity. Compared with trauma-exposed controls, PTSD patients exhibited greater post-study memory distortion of the fear-conditioned stimulus toward the stimulus expressing the highest fear intensity. PTSD patients exhibited biased neural activation toward high-intensity stimuli in fusiform gyrus (P<0.02), insula (P<0.001), primary visual cortex (P<0.05), locus coeruleus (P<0.04), thalamus (P<0.01), and at the trend level in inferior frontal gyrus (P=0.07). All regions except fusiform were moderated by childhood trauma. Amygdala-calcarine (P=0.01) and amygdala-thalamus (P=0.06) functional connectivity selectively increased in PTSD patients for high-intensity stimuli after conditioning. In contrast, amygdala-ventromedial prefrontal cortex (P=0.04) connectivity selectively increased in trauma-exposed controls compared with PTSD patients for low-intensity stimuli after conditioning, representing safety learning. In summary, fear generalization in PTSD is biased toward stimuli with higher emotional intensity than the original conditioned-fear stimulus. Functional brain differences provide a putative neurobiological model for fear generalization whereby PTSD symptoms are triggered by threat cues that merely resemble the index trauma.

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Many neurons in the frontal eye field (FEF) exhibit visual responses and are thought to play important roles in visuosaccadic behavior. The FEF, however, is far removed from striate cortex. Where do the FEF's visual signals come from? Usually they are reasonably assumed to enter the FEF through afferents from extrastriate cortex. Here we show that, surprisingly, visual signals also enter the FEF through a subcortical route: a disynaptic, ascending pathway originating in the intermediate layers of the superior colliculus (SC). We recorded from identified neurons at all three stages of this pathway (n=30-40 in each sample): FEF recipient neurons, orthodromically activated from the SC; mediodorsal thalamus (MD) relay neurons, antidromically activated from FEF and orthodromically activated from SC; and SC source neurons, antidromically activated from MD. We studied the neurons while monkeys performed delayed saccade tasks designed to temporally resolve visual responses from presaccadic discharges. We found, first, that most neurons at every stage in the pathway had visual responses, presaccadic bursts, or both. Second, we found marked similarities between the SC source neurons and MD relay neurons: in both samples, about 15% of the neurons had only a visual response, 10% had only a presaccadic burst, and 75% had both. In contrast, FEF recipient neurons tended to be more visual in nature: 50% had only a visual response, none had only a presaccadic burst, and 50% had both a visual response and a presaccadic burst. This suggests that in addition to their subcortical inputs, these FEF neurons also receive other visual inputs, e.g. from extrastriate cortex. We conclude that visual activity in the FEF results not only from cortical afferents but also from subcortical inputs. Intriguingly, this implies that some of the visual signals in FEF are pre-processed by the SC.

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We perceive a stable visual world even though saccades often move our retinas. One way the brain may achieve a stable visual percept is through predictive remapping of visual receptive fields: just before a saccade, the receptive field of many neurons moves from its current location ("current receptive field") to the location it is expected to occupy after the saccade ("future receptive field"). Goldberg and colleagues found such remapping in cortical areas, e.g. in the frontal eye field (FEF), as well as in the intermediate layers of the superior colliculus (SC). In the present study we investigated the source of the SC's remapped visual signals. Do some of them come from the FEF? We identified FEF neurons that project to the SC using antidromic stimulation. For neurons with a visual response, we tested whether the receptive field shifted just prior to making a saccade. Saccadic amplitudes were chosen to be as small as possible while clearly separating the current and future receptive fields; they ranged from 5-30 deg. in amplitude and were directed contraversively. The saccadic target was a small red spot. We probed visual responsiveness at the current and future receptive field locations using a white spot flashed at various times before or after the saccade. Predictive remapping was indicated by a visual response to a probe flashed in the future receptive field just before the saccade began. We found that many FEF neurons projecting to the SC exhibited predictive remapping. Moreover, the remapping was as fast and strong as any previously reported for FEF or SC. It is clear, therefore, that remapped visual signals are sent from FEF to SC, providing direct evidence that the FEF is one source of the SC's remapped visual signals. Because remapping requires information about an imminent saccade, we hypothesize that remapping in FEF depends on corollary discharge signals such as those ascending from the SC through MD thalamus (Sommer and Wurtz 2002).

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One way we keep track of our movements is by monitoring corollary discharges or internal copies of movement commands. This study tested a hypothesis that the pathway from superior colliculus (SC) to mediodorsal thalamus (MD) to frontal eye field (FEF) carries a corollary discharge about saccades made into the contralateral visual field. We inactivated the MD relay node with muscimol in monkeys and measured corollary discharge deficits using a double-step task: two sequential saccades were made to the locations of briefly flashed targets. To make second saccades correctly, monkeys had to internally monitor their first saccades; therefore deficits in the corollary discharge representation of first saccades should disrupt second saccades. We found, first, that monkeys seemed to misjudge the amplitudes of their first saccades; this was revealed by systematic shifts in second saccade end points. Thus corollary discharge accuracy was impaired. Second, monkeys were less able to detect trial-by-trial variations in their first saccades; this was revealed by reduced compensatory changes in second saccade angles. Thus corollary discharge precision also was impaired. Both deficits occurred only when first saccades went into the contralateral visual field. Single-saccade generation was unaffected. Additional deficits occurred in reaction time and overall performance, but these were bilateral. We conclude that the SC-MD-FEF pathway conveys a corollary discharge used for coordinating sequential saccades and possibly for stabilizing vision across saccades. This pathway is the first elucidated in what may be a multilevel chain of corollary discharge circuits extending from the extraocular motoneurons up into cerebral cortex.