955 resultados para Stimuli complexe


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Existing in vitro models of human skeletal muscle cannot recapitulate the organization and function of native muscle, limiting their use in physiological and pharmacological studies. Here, we demonstrate engineering of electrically and chemically responsive, contractile human muscle tissues ('myobundles') using primary myogenic cells. These biomimetic constructs exhibit aligned architecture, multinucleated and striated myofibers, and a Pax7(+) cell pool. They contract spontaneously and respond to electrical stimuli with twitch and tetanic contractions. Positive correlation between contractile force and GCaMP6-reported calcium responses enables non-invasive tracking of myobundle function and drug response. During culture, myobundles maintain functional acetylcholine receptors and structurally and functionally mature, evidenced by increased myofiber diameter and improved calcium handling and contractile strength. In response to diversely acting drugs, myobundles undergo dose-dependent hypertrophy or toxic myopathy similar to clinical outcomes. Human myobundles provide an enabling platform for predictive drug and toxicology screening and development of novel therapeutics for muscle-related disorders.

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The intensity and valence of 30 emotion terms, 30 events typical of those emotions, and 30 autobiographical memories cued by those emotions were each rated by different groups of 40 undergraduates. A vector model gave a consistently better account of the data than a circumplex model, both overall and in the absence of high-intensity, neutral valence stimuli. The Positive Activation - Negative Activation (PANA) model could be tested at high levels of activation, where it is identical to the vector model. The results replicated when ratings of arousal were used instead of ratings of intensity for the events and autobiographical memories. A reanalysis of word norms gave further support for the vector and PANA models by demonstrating that neutral valence, high-arousal ratings resulted from the averaging of individual positive and negative valence ratings. Thus, compared to a circumplex model, vector and PANA models provided overall better fits.

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Previous functional neuroimaging studies of temporal-order memory have investigated memory for laboratory stimuli that are causally unrelated and poor in sensory detail. In contrast, the present functional magnetic resonance imaging (fMRI) study investigated temporal-order memory for autobiographical events that were causally interconnected and rich in sensory detail. Participants took photographs at many campus locations over a period of several hours, and the following day they were scanned while making temporal-order judgments to pairs of photographs from different locations. By manipulating the temporal lag between the two locations in each trial, we compared the neural correlates associated with reconstruction processes, which we hypothesized depended on recollection and contribute mainly to short lags, and distance processes, which we hypothesized to depend on familiarity and contribute mainly to longer lags. Consistent with our hypotheses, parametric fMRI analyses linked shorter lags to activations in regions previously associated with recollection (left prefrontal, parahippocampal, precuneus, and visual cortices), and longer lags with regions previously associated with familiarity (right prefrontal cortex). The hemispheric asymmetry in prefrontal cortex activity fits very well with evidence and theories regarding the contributions of the left versus right prefrontal cortex to memory (recollection vs. familiarity processes) and cognition (systematic vs. heuristic processes). In sum, using a novel photo-paradigm, this study provided the first evidence regarding the neural correlates of temporal-order for autobiographical events.

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Behavior, neuropsychology, and neuroimaging suggest that episodic memories are constructed from interactions among the following basic systems: vision, audition, olfaction, other senses, spatial imagery, language, emotion, narrative, motor output, explicit memory, and search and retrieval. Each system has its own well-documented functions, neural substrates, processes, structures, and kinds of schemata. However, the systems have not been considered as interacting components of episodic memory, as is proposed here. Autobiographical memory and oral traditions are used to demonstrate the usefulness of the basic-systems model in accounting for existing data and predicting novel findings, and to argue that the model, or one similar to it, is the only way to understand episodic memory for complex stimuli routinely encountered outside the laboratory.

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Very long-term memory for popular music was investigated. Older and younger adults listened to 20-sec excerpts of popular songs drawn from across the 20th century. The subjects gave emotionality and preference ratings and tried to name the title, artist, and year of popularity for each excerpt. They also performed a cued memory test for the lyrics. The older adults' emotionality ratings were highest for songs from their youth; they remembered more about these songs, as well. However, the stimuli failed to cue many autobiographical memories of specific events. Further analyses revealed that the older adults were less likely than the younger adults to retrieve multiple attributes of a song together (i.e., title and artist) and that there was a significant positive correlation between emotion and memory, especially for the older adults. These results have implications for research on long-term memory, as well as on the relationship between emotion and memory.

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Line drawings were presented in either a spatial or a nonspatial format. Subjects recalled each of four sets of 24 items in serial order. Amount recalled in the correct serial order and sequencing errors were scored. In Experiment 1 items appeared either in consecutive locations of a matrix or in one central location. Subjects who saw the items in different locations made fewer sequencing errors than those who saw each item in a central location, but serial recall levels for these two conditions did not differ. When items appeared in nonconsecutive locations in Experiment 2, the advantage of the spatial presentation on sequencing errors disappeared. Experiment 3 included conditions in which both the consecutive and nonconsecutive spatial formats were paired with retrieval cues that either did or did not indicate the sequence of locations in which the items had appeared. Spatial imagery aided sequencing when, and only when, the order of locations in which the stimuli appeared could be reconstructed at retrieval.

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Recent studies have shown that in addition to the transcriptional circadian clock, many organisms, including Arabidopsis, have a circadian redox rhythm driven by the organism's metabolic activities. It has been hypothesized that the redox rhythm is linked to the circadian clock, but the mechanism and the biological significance of this link have only begun to be investigated. Here we report that the master immune regulator NPR1 (non-expressor of pathogenesis-related gene 1) of Arabidopsis is a sensor of the plant's redox state and regulates transcription of core circadian clock genes even in the absence of pathogen challenge. Surprisingly, acute perturbation in the redox status triggered by the immune signal salicylic acid does not compromise the circadian clock but rather leads to its reinforcement. Mathematical modelling and subsequent experiments show that NPR1 reinforces the circadian clock without changing the period by regulating both the morning and the evening clock genes. This balanced network architecture helps plants gate their immune responses towards the morning and minimize costs on growth at night. Our study demonstrates how a sensitive redox rhythm interacts with a robust circadian clock to ensure proper responsiveness to environmental stimuli without compromising fitness of the organism.

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INTRODUCTION: We previously reported models that characterized the synergistic interaction between remifentanil and sevoflurane in blunting responses to verbal and painful stimuli. This preliminary study evaluated the ability of these models to predict a return of responsiveness during emergence from anesthesia and a response to tibial pressure when patients required analgesics in the recovery room. We hypothesized that model predictions would be consistent with observed responses. We also hypothesized that under non-steady-state conditions, accounting for the lag time between sevoflurane effect-site concentration (Ce) and end-tidal (ET) concentration would improve predictions. METHODS: Twenty patients received a sevoflurane, remifentanil, and fentanyl anesthetic. Two model predictions of responsiveness were recorded at emergence: an ET-based and a Ce-based prediction. Similarly, 2 predictions of a response to noxious stimuli were recorded when patients first required analgesics in the recovery room. Model predictions were compared with observations with graphical and temporal analyses. RESULTS: While patients were anesthetized, model predictions indicated a high likelihood that patients would be unresponsive (> or = 99%). However, after termination of the anesthetic, models exhibited a wide range of predictions at emergence (1%-97%). Although wide, the Ce-based predictions of responsiveness were better distributed over a percentage ranking of observations than the ET-based predictions. For the ET-based model, 45% of the patients awoke within 2 min of the 50% model predicted probability of unresponsiveness and 65% awoke within 4 min. For the Ce-based model, 45% of the patients awoke within 1 min of the 50% model predicted probability of unresponsiveness and 85% awoke within 3.2 min. Predictions of a response to a painful stimulus in the recovery room were similar for the Ce- and ET-based models. DISCUSSION: Results confirmed, in part, our study hypothesis; accounting for the lag time between Ce and ET sevoflurane concentrations improved model predictions of responsiveness but had no effect on predicting a response to a noxious stimulus in the recovery room. These models may be useful in predicting events of clinical interest but large-scale evaluations with numerous patients are needed to better characterize model performance.

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© 2015 Young, Smith, Coutlee and Huettel.Individuals with autistic spectrum disorders exhibit distinct personality traits linked to attentional, social, and affective functions, and those traits are expressed with varying levels of severity in the neurotypical and subclinical population. Variation in autistic traits has been linked to reduced functional and structural connectivity (i.e., underconnectivity, or reduced synchrony) with neural networks modulated by attentional, social, and affective functions. Yet, it remains unclear whether reduced synchrony between these neural networks contributes to autistic traits. To investigate this issue, we used functional magnetic resonance imaging to record brain activation while neurotypical participants who varied in their subclinical scores on the Autism-Spectrum Quotient (AQ) viewed alternating blocks of social and nonsocial stimuli (i.e., images of faces and of landscape scenes). We used independent component analysis (ICA) combined with a spatiotemporal regression to quantify synchrony between neural networks. Our results indicated that decreased synchrony between the executive control network (ECN) and a face-scene network (FSN) predicted higher scores on the AQ. This relationship was not explained by individual differences in head motion, preferences for faces, or personality variables related to social cognition. Our findings build on clinical reports by demonstrating that reduced synchrony between distinct neural networks contributes to a range of subclinical autistic traits.

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The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.

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Successful interaction with the world depends on accurate perception of the timing of external events. Neurons at early stages of the primate visual system represent time-varying stimuli with high precision. However, it is unknown whether this temporal fidelity is maintained in the prefrontal cortex, where changes in neuronal activity generally correlate with changes in perception. One reason to suspect that it is not maintained is that humans experience surprisingly large fluctuations in the perception of time. To investigate the neuronal correlates of time perception, we recorded from neurons in the prefrontal cortex and midbrain of monkeys performing a temporal-discrimination task. Visual time intervals were presented at a timescale relevant to natural behavior (<500 ms). At this brief timescale, neuronal adaptation--time-dependent changes in the size of successive responses--occurs. We found that visual activity fluctuated with timing judgments in the prefrontal cortex but not in comparable midbrain areas. Surprisingly, only response strength, not timing, predicted task performance. Intervals perceived as longer were associated with larger visual responses and shorter intervals with smaller responses, matching the dynamics of adaptation. These results suggest that the magnitude of prefrontal activity may be read out to provide temporal information that contributes to judging the passage of time.

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The image on the retina may move because the eyes move, or because something in the visual scene moves. The brain is not fooled by this ambiguity. Even as we make saccades, we are able to detect whether visual objects remain stable or move. Here we test whether this ability to assess visual stability across saccades is present at the single-neuron level in the frontal eye field (FEF), an area that receives both visual input and information about imminent saccades. Our hypothesis was that neurons in the FEF report whether a visual stimulus remains stable or moves as a saccade is made. Monkeys made saccades in the presence of a visual stimulus outside of the receptive field. In some trials, the stimulus remained stable, but in other trials, it moved during the saccade. In every trial, the stimulus occupied the center of the receptive field after the saccade, thus evoking a reafferent visual response. We found that many FEF neurons signaled, in the strength and timing of their reafferent response, whether the stimulus had remained stable or moved. Reafferent responses were tuned for the amount of stimulus translation, and, in accordance with human psychophysics, tuning was better (more prevalent, stronger, and quicker) for stimuli that moved perpendicular, rather than parallel, to the saccade. Tuning was sometimes present as well for nonspatial transaccadic changes (in color, size, or both). Our results indicate that FEF neurons evaluate visual stability during saccades and may be general purpose detectors of transaccadic visual change.

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UNLABELLED: Response inhibition is a key component of executive control, but its relation to other cognitive processes is not well understood. We recently documented the "inhibition-induced forgetting effect": no-go cues are remembered more poorly than go cues. We attributed this effect to central-resource competition, whereby response inhibition saps attention away from memory encoding. However, this proposal is difficult to test with behavioral means alone. We therefore used fMRI in humans to test two neural predictions of the "common resource hypothesis": (1) brain regions associated with response inhibition should exhibit greater resource demands during encoding of subsequently forgotten than remembered no-go cues; and (2) this higher inhibitory resource demand should lead to memory encoding regions having less resources available during encoding of subsequently forgotten no-go cues. Participants categorized face stimuli by gender in a go/no-go task and, following a delay, performed a surprise recognition memory test for those faces. Replicating previous findings, memory was worse for no-go than for go stimuli. Crucially, forgetting of no-go cues was predicted by high inhibitory resource demand, as quantified by the trial-by-trial ratio of activity in neural "no-go" versus "go" networks. Moreover, this index of inhibitory demand exhibited an inverse trial-by-trial relationship with activity in brain regions responsible for the encoding of no-go cues into memory, notably the ventrolateral prefrontal cortex. This seesaw pattern between the neural resource demand of response inhibition and activity related to memory encoding directly supports the hypothesis that response inhibition temporarily saps attentional resources away from stimulus processing. SIGNIFICANCE STATEMENT: Recent behavioral experiments showed that inhibiting a motor response to a stimulus (a "no-go cue") impairs subsequent memory for that cue. Here, we used fMRI to test whether this "inhibition-induced forgetting effect" is caused by competition for neural resources between the processes of response inhibition and memory encoding. We found that trial-by-trial variations in neural inhibitory resource demand predicted subsequent forgetting of no-go cues and that higher inhibitory demand was furthermore associated with lower concurrent activation in brain regions responsible for successful memory encoding of no-go cues. Thus, motor inhibition and stimulus encoding appear to compete with each other: when more resources have to be devoted to inhibiting action, less are available for encoding sensory stimuli.

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All of us are taxed with juggling our inner mental lives with immediate external task demands. For many years, the temporary maintenance of internal information was considered to be handled by a dedicated working memory (WM) system. It has recently become increasingly clear, however, that such short-term internal activation interacts with attention focused on external stimuli. It is unclear, however, exactly why these two interact, at what level of processing, and to what degree. Because our internal maintenance and external attention processes co-occur with one another, the manner of their interaction has vast implications for functioning in daily life. The work described here has employed original experimental paradigms combining WM and attention task elements, functional magnetic resonance imaging (fMRI) to illuminate the associated neural processes, and transcranial magnetic stimulation (TMS) to clarify the causal substrates of attentional brain function. These studies have examined a mechanism that might explain why (and when) the content of WM can involuntarily capture visual attention. They have, furthermore, tested whether fundamental attentional selection processes operate within WM, and whether they are reciprocal with attention. Finally, they have illuminated the neural consequences of competing attentional demands. The findings indicate that WM shares representations, operating principles, and cognitive resources with externally-oriented attention.

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Modulatory descending neurons (DNs) that link the brain to body motor circuits, including dopaminergic DNs (DA-DNs), are thought to contribute to the flexible control of behavior. Dopamine elicits locomotor-like outputs and influences neuronal excitability in isolated body motor circuits over tens of seconds to minutes, but it remains unknown how and over what time scale DA-DN activity relates to movement in behaving animals. To address this question, we identified DA-DNs in the Drosophila brain and developed an electrophysiological preparation to record and manipulate the activity of these cells during behavior. We find that DA-DN spike rates are rapidly modulated during a subset of leg movements and scale with the total speed of ongoing leg movements, whether occurring spontaneously or in response to stimuli. However, activating DA-DNs does not elicit leg movements in intact flies, nor do acute bidirectional manipulations of DA-DN activity affect the probability or speed of leg movements over a time scale of seconds to minutes. Our findings indicate that in the context of intact descending control, changes in DA-DN activity are not sufficient to influence ongoing leg movements and open the door to studies investigating how these cells interact with other descending and local neuromodulatory inputs to influence body motor output.