11 resultados para Schnitzler

em Aston University Research Archive


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Humans imitate biological movements faster than non-biological movements. The faster response has been attributed to an activation of the human mirror neuron system, which is thought to match observation and execution of actions. However, it is unclear which cortical areas are responsible for this behavioural advantage. Also, little is known about the timing of activations. Using whole-head magnetoencephalography we recorded neuronal responses to single biological finger movements and non-biological dot movements while the subjects were required to perform an imitation task or an observation task, respectively. Previous imaging studies on the human mirror neurone system suggested that activation in response to biological movements would be stronger in ventral premotor, parietal and superior temporal regions. In accordance with previous studies, reaction times to biological movements were faster than those to dot movements in all subjects. The analysis of evoked magnetic fields revealed that the reaction time benefit was paralleled by stronger and earlier activation of the left temporo-occipital cortex, right superior temporal area and right ventral motor/premotor area. The activity patterns suggest that the latter areas mediate the observed behavioural advantage of biological movements and indicate a predominant contribution of the right temporo-frontal hemisphere to action observation–execution matching processes in intransitive movements, which has not been reported previously.

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Our motor and perceptual representations of actions seem to be intimately linked and the human mirror neuron system (MNS) has been proposed as the mediator. In two experiments, we presented biological or non-biological movement stimuli that were either congruent or incongruent to a required response prompted by a tone. When the tone occurred with the onset of the last movement in a series, i.e., it was perceived during the movement presentation, congruent biological stimuli resulted in faster reaction times than congruent non-biological stimuli. The opposite was observed for incongruent stimuli. When the tone was presented after visual movement stimulation, however, no such interaction was present. This implies that biological movement stimuli only affect motor behaviour during visual processing but not thereafter. These data suggest that the MNS is an “online” system; longstanding repetitive visual stimulation (Experiment 1) has no benefit in comparison to only one or two repetitions (Experiment 2).

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The posterior inferior frontal gyrus (pIFG) and anterior inferior parietal lobule (aIPL) form the core regions of the human “mirror neuron system” that matches an observed movement onto its internal motor representation. We used event-related functional MRI to examine whether simple intransitive finger movements evoke “mirror activity” in the pIFG and aIPL. In separate sessions, participants either merely observed visuospatial stimuli or responded to them as quickly as possible with a spatially compatible finger movement. A picture of a relaxed hand with static dots on the tip of the index and little finger was continuously presented as high-level baseline. Four types of stimuli were presented in a pseudorandom order: a color change of a dot, a moving finger, a moving dot, or a simultaneous finger-dot movement. Dot movements were spatially and kinematically matched to finger movements. Participants were faster at imitating a finger movement than performing the same movement in response to a moving dot or a color change of a dot. Though imitative responses were facilitated, fMRI revealed no additional “mirror activity” in the pIFG and aIPL during the observation or imitation of finger movements as opposed to observing or responding to a moving dot. Mere observation of a finger movement alone failed to induce significant activation of the pIFG and aIPL. The lack of a signature of “mirror neuron activity” in the inferior frontoparietal cortex is presumably due to specific features of the task which may have favored stimulus–response mapping based on common spatial coding. We propose that the responsiveness of human frontoparietal mirror neuron areas to simple intransitive movements critically depends on the experimental context.

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Behavioural advantages for imitation of human movements over movements instructed by other visual stimuli are attributed to an ‘action observation-execution matching’ (AOEM) mechanism. Here, we demonstrate that priming/exogenous cueing with a videotaped finger movement stimulus (S1) produces specific congruency effects in reaction times (RTs) of imitative responses to a target movement (S2) at defined stimulus onset asynchronies (SOAs). When contrasted with a moving object at an SOA of 533 ms, only a human movement is capable of inducing an effect reminiscent of ‘inhibition of return’ (IOR), i.e. a significant advantage for imitation of a subsequent incongruent as compared to a congruent movement. When responses are primed by a finger movement at SOAs of 533 and 1,200 ms, inhibition of congruent or facilitation of incongruent responses, respectively, is stronger as compared to priming by a moving object. This pattern does not depend on whether S2 presents a finger movement or a moving object, thus effects cannot be attributed to visual similarity between S1 and S2. We propose that, whereas both priming by a finger movement and a moving object induces processes of spatial orienting, solely observation of a human movement activates AOEM. Thus, S1 immediately elicits an imitative response tendency. As an overt imitation of S1 is inadequate in the present setting, the response is inhibited which, in turn, modulates congruency effects.

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Everyday human behaviour relies on our ability to predict outcomes on the basis of moment by moment information. Long-range neural phase synchronization has been hypothesized as a mechanism by which ‘predictions’ can exert an effect on the processing of incoming sensory events. Using magnetoencephalography (MEG) we have studied the relationship between the modulation of phase synchronization in a cerebral network of areas involved in visual target processing and the predictability of target occurrence. Our results reveal a striking increase in the modulation of phase synchronization associated with an increased probability of target occurrence. These observations are consistent with the hypothesis that long-range phase synchronization plays a critical functional role in humans' ability to effectively employ predictive heuristics.

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The present report reviews behavioural, electroencephalographic, and especially magnetoencephalographic findings on the cortical mechanisms underlying attentional processes that separate targets from distractors and that ensure durable target representations for goal-directed action. A common way of investigation is to observe the system’s overt and covert behaviour when capacity limitations are reached. Here we focus on the aspect of temporally enhanced processing load, namely on performance deficits occurring under rapid-serial-visual-presentation (RSVP) conditions. The most prominent of these deficits is the so-called “attentional blink” (AB) effect. We first report MEG findings with respect to the time course of activation that shows modulations around 300 ms after target onset which reflect demands and success of target consolidation. Then, findings regarding long-range inter-area phase synchronization are reported that are hypothesized to mediate communication within the attentional network. Changes in synchronization reflect changes in the attentional demands of the task and are directly related to behavioural performance. Furthermore, enhanced vigilance of the system elicits systematically increased synchronization indices. A hypothetical framework is sketched out that aims at explaining limitations in multiple target consolidation under RSVP conditions.

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When people monitor a visual stream of rapidly presented stimuli for two targets (T1 and T2), they often miss T2 if it falls into a time window of about half a second after T1 onset—the attentional blink (AB). We provide an overview of recent neuroscientific studies devoted to analyze the neural processes underlying the AB and their temporal dynamics. The available evidence points to an attentional network involving temporal, right-parietal and frontal cortex, and suggests that the components of this neural network interact by means of synchronization and stimulus-induced desynchronization in the beta frequency range. We set up a neurocognitive scenario describing how the AB might emerge and why it depends on the presence of masks and the other event(s) the targets are embedded in. The scenario supports the idea that the AB arises from ‘‘biased competition’’, with the top–down bias being generated by parietal–frontal interactions and the competition taking place between stimulus codes in temporal cortex.

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The human mirror neuron system (MNS) has recently been a major topic of research in cognitive neuroscience. As a very basic reflection of the MNS, human observers are faster at imitating a biological as compared with a non-biological movement. However, it is unclear which cortical areas and their interactions (synchronization) are responsible for this behavioural advantage. We investigated the time course of long-range synchronization within cortical networks during an imitation task in 10 healthy participants by means of whole-head magnetoencephalography (MEG). Extending previous work, we conclude that left ventrolateral premotor, bilateral temporal and parietal areas mediate the observed behavioural advantage of biological movements in close interaction with the basal ganglia and other motor areas (cerebellum, sensorimotor cortex). Besides left ventrolateral premotor cortex, we identified the right temporal pole and the posterior parietal cortex as important junctions for the integration of information from different sources in imitation tasks that are controlled for movement (biological vs. non-biological) and that involve a certain amount of spatial orienting of attention. Finally, we also found the basal ganglia to participate at an early stage in the processing of biological movement, possibly by selecting suitable motor programs that match the stimulus.

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We investigated the nature of resource limitations during visual target processing by imposing high temporal processing demands on the cognitive system. This was achieved by embedding target stimuli into rapid-serial-visual-presentation-streams (RSVP). In RSVP streams, it is difficult to report the second of two targets (T2) if the second follows the first (T1) within 500 ms. This effect is known as the attentional blink (AB). For the AB to occur, it is essential that T1 is followed by a mask, as without such a stimulus, the AB is significantly attenuated. Usually, it is thought that T1 processing is delayed by the mask, which in turn delays T2 processing, increasing the likelihood for T2 failures (AB). Predictions regarding amplitudes and latencies of cortical responses (M300, the magnetic counterpart to the P300) to targets were tested by investigating the neurophysiological effects of the post-T1 item (mask) by means of magnetoencephalography (MEG). Cortical M300 responses to targets drawn from prefrontal sources – areas associated with working memory – revealed accelerated T1 yet delayed T2 processing with an intervening mask. The explanation we are proposing assumes that “protection” of ongoing T1 processing necessitated by the occurrence of the mask suppresses other activation patterns, which boosts T1 yet also hinders further processing. Our data shed light on the mechanisms employed by the human brain for ensuring visual target processing under high temporal processing demands, which is hypothesized to occur at the expense of subsequently presented information.

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If humans monitor streams of rapidly presented (approximately 100-ms intervals) visual stimuli, which are typically specific single letters of the alphabet, for two targets (T1 and T2), they often miss T2 if it follows T1 within an interval of 200-500 ms. If T2 follows T1 directly (within 100 ms; described as occurring at 'Lag 1'), however, performance is often excellent: the so-called 'Lag-1 sparing' phenomenon. Lag-1 sparing might result from the integration of the two targets into the same 'event representation', which fits with the observation that sparing is often accompanied by a loss of T1-T2 order information. Alternatively, this might point to competition between the two targets (implying a trade-off between performance on T1 and T2) and Lag-1 sparing might solely emerge from conditional data analysis (i.e. T2 performance given T1 correct). We investigated the neural correlates of Lag-1 sparing by carrying out magnetoencephalography (MEG) recordings during an attentional blink (AB) task, by presenting two targets with a temporal lag of either 1 or 2 and, in the case of Lag 2, with a nontarget or a blank intervening between T1 and T2. In contrast to Lag 2, where two distinct neural responses were observed, at Lag 1 the two targets produced one common neural response in the left temporo-parieto-frontal (TPF) area but not in the right TPF or prefrontal areas. We discuss the implications of this result with respect to competition and integration hypotheses, and with respect to the different functional roles of the cortical areas considered. We suggest that more than one target can be identified in parallel in left TPF, at least in the absence of intervening nontarget information (i.e. masks), yet identified targets are processed and consolidated as two separate events by other cortical areas (right TPF and PFC, respectively).

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Because of attentional limitations, the human visual system can process for awareness and response only a fraction of the input received. Lesion and functional imaging studies have identified frontal, temporal, and parietal areas as playing a major role in the attentional control of visual processing, but very little is known about how these areas interact to form a dynamic attentional network. We hypothesized that the network communicates by means of neural phase synchronization, and we used magnetoencephalography to study transient long-range interarea phase coupling in a well studied attentionally taxing dual-target task (attentional blink). Our results reveal that communication within the fronto-parieto-temporal attentional network proceeds via transient long-range phase synchronization in the beta band. Changes in synchronization reflect changes in the attentional demands of the task and are directly related to behavioral performance. Thus, we show how attentional limitations arise from the way in which the subsystems of the attentional network interact. The human brain faces an inestimable task of reducing a potentially overloading amount of input into a manageable flow of information that reflects both the current needs of the organism and the external demands placed on it. This task is accomplished via a ubiquitous construct known as “attention,” whose mechanism, although well characterized behaviorally, is far from understood at the neurophysiological level. Whereas attempts to identify particular neural structures involved in the operation of attention have met with considerable success (1-5) and have resulted in the identification of frontal, parietal, and temporal regions, far less is known about the interaction among these structures in a way that can account for the task-dependent successes and failures of attention. The goal of the present research was, thus, to unravel the means by which the subsystems making up the human attentional network communicate and to relate the temporal dynamics of their communication to observed attentional limitations in humans. A prime candidate for communication among distributed systems in the human brain is neural synchronization (for review, see ref. 6). Indeed, a number of studies provide converging evidence that long-range interarea communication is related to synchronized oscillatory activity (refs. 7-14; for review, see ref. 15). To determine whether neural synchronization plays a role in attentional control, we placed humans in an attentionally demanding task and used magnetoencephalography (MEG) to track interarea communication by means of neural synchronization. In particular, we presented 10 healthy subjects with two visual target letters embedded in streams of 13 distractor letters, appearing at a rate of seven per second. The targets were separated in time by a single distractor. This condition leads to the “attentional blink” (AB), a well studied dual-task phenomenon showing the reduced ability to report the second of two targets when an interval <500 ms separates them (16-18). Importantly, the AB does not prevent perceptual processing of missed target stimuli but only their conscious report (19), demonstrating the attentional nature of this effect and making it a good candidate for the purpose of our investigation. Although numerous studies have investigated factors, e.g., stimulus and timing parameters, that manipulate the magnitude of a particular AB outcome, few have sought to characterize the neural state under which “standard” AB parameters produce an inability to report the second target on some trials but not others. We hypothesized that the different attentional states leading to different behavioral outcomes (second target reported correctly or not) are characterized by specific patterns of transient long-range synchronization between brain areas involved in target processing. Showing the hypothesized correspondence between states of neural synchronization and human behavior in an attentional task entails two demonstrations. First, it needs to be demonstrated that cortical areas that are suspected to be involved in visual-attention tasks, and the AB in particular, interact by means of neural synchronization. This demonstration is particularly important because previous brain-imaging studies (e.g., ref. 5) only showed that the respective areas are active within a rather large time window in the same task and not that they are concurrently active and actually create an interactive network. Second, it needs to be demonstrated that the pattern of neural synchronization is sensitive to the behavioral outcome; specifically, the ability to correctly identify the second of two rapidly succeeding visual targets