Sensory Consequences Of Action Research Articles

Intention tremor and deficits of sensory feedback control in multiple sclerosis: a pilot study.

BackgroundIntention tremor and dysmetria are leading causes of upper extremity disability in Multiple Sclerosis (MS). The development of effective therapies to reduce tremor and dysmetria is hampered by insufficient understanding of how the distributed, multi-focal lesions associated with MS impact sensorimotor control in the brain. Here we describe a systems-level approach to characterizing sensorimotor control and use this approach to examine how sensory and motor processes are differentially impacted by MS.MethodsEight subjects with MS and eight age- and gender-matched healthy control subjects performed visually-guided flexion/extension tasks about the elbow to characterize a sensory feedback control model that includes three sensory feedback pathways (one for vision, another for proprioception and a third providing an internal prediction of the sensory consequences of action). The model allows us to characterize impairments in sensory feedback control that contributed to each MS subject’s tremor.ResultsModels derived from MS subject performance differed from those obtained for control subjects in two ways. First, subjects with MS exhibited markedly increased visual feedback delays, which were uncompensated by internal adaptive mechanisms; stabilization performance in individuals with the longest delays differed most from control subject performance. Second, subjects with MS exhibited misestimates of arm dynamics in a way that was correlated with tremor power. Subject-specific models accurately predicted kinematic performance in a reach and hold task for neurologically-intact control subjects while simulated performance of MS patients had shorter movement intervals and larger endpoint errors than actual subject responses. This difference between simulated and actual performance is consistent with a strategic compensatory trade-off of movement speed for endpoint accuracy.ConclusionsOur results suggest that tremor and dysmetria may be caused by limitations in the brain’s ability to adapt sensory feedback mechanisms to compensate for increases in visual information processing time, as well as by errors in compensatory adaptations of internal estimates of arm dynamics.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-170) contains supplementary material, which is available to authorized users.

Neural correlates of sensory prediction errors in monkeys: evidence for internal models of voluntary self-motion in the cerebellum.

During self-motion, the vestibular system makes essential contributions to postural stability and self-motion perception. To ensure accurate perception and motor control, it is critical to distinguish between vestibular sensory inputs that are the result of externally applied motion (exafference) and that are the result of our own actions (reafference). Indeed, although the vestibular sensors encode vestibular afference and reafference with equal fidelity, neurons at the first central stage of sensory processing selectively encode vestibular exafference. The mechanism underlying this reafferent suppression compares the brain's motor-based expectation of sensory feedback with the actual sensory consequences of voluntary self-motion, effectively computing the sensory prediction error (i.e., exafference). It is generally thought that sensory prediction errors are computed in the cerebellum, yet it has been challenging to explicitly demonstrate this. We have recently addressed this question and found that deep cerebellar nuclei neurons explicitly encode sensory prediction errors during self-motion. Importantly, in everyday life, sensory prediction errors occur in response to changes in the effector or world (muscle strength, load, etc.), as well as in response to externally applied sensory stimulation. Accordingly, we hypothesize that altering the relationship between motor commands and the actual movement parameters will result in the updating in the cerebellum-based computation of exafference. If our hypothesis is correct, under these conditions, neuronal responses should initially be increased--consistent with a sudden increase in the sensory prediction error. Then, over time, as the internal model is updated, response modulation should decrease in parallel with a reduction in sensory prediction error, until vestibular reafference is again suppressed. The finding that the internal model predicting the sensory consequences of motor commands adapts for new relationships would have important implications for understanding how responses to passive stimulation endure despite the cerebellum's ability to learn new relationships between motor commands and sensory feedback.

Moving time: the influence of action on duration perception.

Perceiving the sensory consequences of action accurately is essential for appropriate interaction with our physical and social environments. Prediction mechanisms are considered necessary for fine-tuned sensory control of action, yet paradoxically may distort perception. Here, we examine this paradox by addressing how movement influences the perceived duration of sensory outcomes congruent with action. Experiment 1 required participants to make judgments about the duration of vibrations applied to a moving or stationary finger. In Experiments 2 and 3, participants judged observed finger movements that were congruent or incongruent with their own actions. In all experiments, target events were perceived to be longer when congruent with movement. Interestingly, this temporal dilation did not differ as a function of stimulus perspective (1st or 3rd person) or spatial location. We propose that this bias may reflect the operation of an adaptive mechanism for sensorimotor selection and control that preactivates anticipated outcomes of action. The bias itself may have surprising implications for both action control and perception of others: we may be in contact with grasped objects for less time than we realize, and others’ reactions to us may be briefer than we believe.

The Motor System Contributes to Comprehension of Abstract Language

If language comprehension requires a sensorimotor simulation, how can abstract language be comprehended? We show that preparation to respond in an upward or downward direction affects comprehension of the abstract quantifiers “more and more” and “less and less” as indexed by an N400-like component. Conversely, the semantic content of the sentence affects the motor potential measured immediately before the upward or downward action is initiated. We propose that this bidirectional link between motor system and language arises because the motor system implements forward models that predict the sensory consequences of actions. Because the same movement (e.g., raising the arm) can have multiple forward models for different contexts, the models can make different predictions depending on whether the arm is raised, for example, to place an object or raised as a threat. Thus, different linguistic contexts invoke different forward models, and the predictions constitute different understandings of the language.

Modelling mental rotation in cognitive robots

Mental rotation concerns the cognitive processes that allow an agent mentally to rotate the image of an object in order to solve a given task, for example to say if two objects with different orientations are the same or different. Here we present a system-level bio-constrained model, developed within a neurorobotics framework, that provides an embodied account of mental rotation processes relying on neural mechanisms involving motor affordance encoding, motor simulation and the anticipation of the sensory consequences of actions (both visual and proprioceptive). This model and methodology are in agreement with the most recent theoretical and empirical research on mental rotation. The model was validated through experiments with a simulated humanoid robot (iCub) engaged in solving a classical mental rotation test. The results of the test show that the robot is able to solve the task and, in agreement with data from psychology experiments, exhibits response times linearly dependent on the angular disparity between the objects. This model represents a novel detailed operational account of the embodied brain mechanisms that may underlie mental rotation.

Coupling internal cerebellar models enhances online adaptation and supports offline consolidation in sensorimotor tasks

The cerebellum is thought to mediate sensorimotor adaptation through the acquisition of internal models of the body-environment interaction. These representations can be of two types, identified as forward and inverse models. The first predicts the sensory consequences of actions, while the second provides the correct commands to achieve desired state transitions. In this paper, we propose a composite architecture consisting of multiple cerebellar internal models to account for the adaptation performance of humans during sensorimotor learning. The proposed model takes inspiration from the cerebellar microcomplex circuit, and employs spiking neurons to process information. We investigate the intrinsic properties of the cerebellar circuitry subserving efficient adaptation properties, and we assess the complementary contributions of internal representations by simulating our model in a procedural adaptation task. Our simulation results suggest that the coupling of internal models enhances learning performance significantly (compared with independent forward and inverse models), and it allows for the reproduction of human adaptation capabilities. Furthermore, we provide a computational explanation for the performance improvement observed after one night of sleep in a wide range of sensorimotor tasks. We predict that internal model coupling is a necessary condition for the offline consolidation of procedural memories.

Prolonged rock climbing activity induces structural changes in cerebellum and parietal lobe

This article analyzes whether climbing, a motor activity featured by upward movements by using both feet and hands, generation of new strategies of motor control, maintenance of not stable equilibrium and adoption of long-lasting quadrupedal posture, is able to modify specific brain areas. MRI data of 10 word-class mountain climbers (MC) and 10 age-matched controls, with no climbing experience were acquired. Combining region-of-interest analyses and voxel-based morphometry we investigated cerebellar volumes and correlation between cerebellum and whole cerebral gray matter. In comparison to controls, world-class MC showed significantly larger vermian lobules I-V volumes, with no significant difference in other cerebellar vermian lobules or hemispheres. The cerebellar enlargement was associated with an enlargement of right medial posterior parietal area. The specific features of the motor climbing skills perfectly fit with the plastic anatomical changes we found. The enlargement of the vermian lobules I-V seems to be related to highly dexterous hand movements and to eye-hand coordination in the detection of and correction of visuomotor errors. The concomitant enlargement of the parietal area is related to parallel work in predicting sensory consequences of action to make movement corrections. Motor control and sensory-motor prediction of actions make the difference between survive or not at extreme altitude.

Cerebellar Contributions to Reach Adaptation and Learning Sensory Consequences of Action

When we use a novel tool, the motor commands may not produce the expected outcome. In healthy individuals, with practice the brain learns to alter the motor commands. This change depends critically on the cerebellum as damage to this structure impairs adaptation. However, it is unclear precisely what the cerebellum contributes to the process of adaptation in human motor learning. Is the cerebellum crucial for learning to associate motor commands with novel sensory consequences, called forward model, or is the cerebellum important for learning to associate sensory goals with novel motor commands, called inverse model? Here, we compared performance of cerebellar patients and healthy controls in a reaching task with a gradual perturbation schedule. This schedule allowed both groups to adapt their motor commands. Following training, we measured two kinds of behavior: in one case, people were presented with reach targets near the direction in which they had trained. The resulting generalization patterns of patients and controls were similar, suggesting comparable inverse models. In the second case, participants reached without a target and reported the location of their hand. In controls, the pattern of change in reported hand location was consistent with simulation results of a forward model that had learned to associate motor commands with new sensory consequences. In patients, this change was significantly smaller. Therefore, in our sample of patients, we observed that while adaptation of motor commands can take place despite cerebellar damage, cerebellar integrity appears critical for learning to predict visual sensory consequences of motor commands.

Perception-action in children with ASD

How do disturbances to perception and action relate to the deficiencies expressed by children with autism? The ability to predict what is going to happen next is crucial for the construction of all actions and children develop these predictive abilities early in development. Children with autism, however, are deficient in the ability to foresee future events and to plan movements and movement sequences. They are also deficient in the understanding of other people's actions. This includes communicative actions as they are ultimately based on movements. Today there are two promising neurobiological interpretation of Autism Spectrum Disorder (ASD). First, there is strong evidence that the Mirror Neuron System (MNS) is impaired. As stated by this hypothesis, action production and action understanding are intimately related. Both these functions rely on predictive models of the sensory consequences of actions and depend on connectivity between the parietal and premotor areas. Secondly, action prediction is accomplished through a system that includes a loop from the posterior parietal cortex (PPC) through the cerebellum and back to the premotor and motor areas of the brain. Impairment of this loop is probably also part of the explanation of the prediction problems in children with ASD. Both the cortico-cerebellar loop and the MNS rely on distant neural connections. There are multiple evidence that such connections are weak in children with autism.

Unravelling cerebellar pathways with high temporal precision targeting motor and extensive sensory and parietal networks

Increasing evidence has implicated the cerebellum in providing forward models of motor plants predicting the sensory consequences of actions. Assuming that cerebellar input to the cerebral cortex contributes to the cerebro-cortical processing by adding forward model signals, we would expect to find projections emphasising motor and sensory cortical areas. However, this expectation is only partially met by studies of cerebello-cerebral connections. Here we show that by electrically stimulating the cerebellar output and imaging responses with functional magnetic resonance imaging, evoked blood oxygen level-dependant activity is observed not only in the classical cerebellar projection target, the primary motor cortex, but also in a number of additional areas in insular, parietal and occipital cortex, including sensory cortical representations. Further probing of the responses reveals a projection system that has been optimized to mediate fast and temporarily precise information. In conclusion, both the topography of the stimulation effects and its emphasis on temporal precision are in full accordance with the concept of cerebellar forward model information modulating cerebro-cortical processing.

Cerebellar lesions alter performance monitoring on the antisaccade task—An event-related potentials study

Error processing is associated with distinct event-related potential components (ERPs), i.e. the error-related negativity (ERN) which occurs within approximately 150 ms and is typically more pronounced than the correct-response negativity (CRN), and the error positivity (Pe) emerging from about 200 to 400 ms after an erroneous response. The short latency of the ERN suggests that the internal error monitoring system acts on rapidly available central information such as an efference copy signal rather than slower peripheral feedback. The cerebellum has been linked to an internal forward-model which enables online performance monitoring by predicting the sensory consequences of actions, most probably by making use of efference copies. In the present study it was hypothesized that the cerebellum is involved in the fast evaluation of saccadic response accuracy as reflected by the ERN. Error processing on an antisaccade task was investigated in eight patients with focal vascular lesions to the cerebellum and 22 control subjects using ERPs. While error rates were comparable between groups, saccadic reaction times (SRTs) were enhanced in the patients, and the error-correct difference waveforms showed reduced amplitudes for patients relative to controls in the ERN time window. Notably, this effect was mainly driven by an increased CRN in the patients. In the later Pe time window, the difference signal yielded higher amplitudes in patients compared to controls mainly because of smaller Pe amplitudes on correct trials in patients. The altered ERN/CRN pattern suggests that the cerebellum is critically involved in fast classification of saccadic accuracy. Largely intact performance accuracy together with increased SRTs and the altered Pe pattern may indicate a compensatory mechanism presumably related to slower, more conscious aspects of error processing in the patients.

Beside the point: motor adaptation without feedback-based error correction in task-irrelevant conditions

Adaptation of movement may be driven by the difference between planned and actual motor performance, or the difference between expected and actual sensory consequences of movement. To identify how the nervous system differentially uses these signals, we asked: does motor adaptation occur when movement errors are irrelevant to the task goal? Participants reached on a digitizing tablet from a fixed start location to one of three targets: a point, an arc, or a ray. For the arc, reaches could be in any direction, but to a specific extent. For the ray, reaches could be to any distance, but in a targeted direction. After baseline reaching to the point, the direction or extent of continuous visual feedback was perturbed during training with either a cursor rotation or gain, respectively, while reaching to either the ray (goal = direction) or the arc (goal = extent). The perturbation, therefore, was either relevant or irrelevant to the task goal, depending on target type. During interspersed catch trials, the perturbation was removed and the target switched back to the point, identical to baseline. Although the goal of baseline and catch trials was the same, significant aftereffects in catch trials indicated behavioral adaptation in response to the perturbation. Adaptation occurred regardless of whether the perturbation was relevant to the task, and it was independent of feedback control. The presence of adaptation orthogonal to task demands supports the hypothesis that the nervous system can rely on sensory prediction to drive motor learning that can generalize across tasks.

Human Supplementary Motor Area Contribution to Predictive Motor Planning

ABSTRACT The supplementary motor area (SMA) is involved in planning limb movements. An important component of such planning is the prediction of the sensory consequences of action. The authors used transcranial magnetic stimulation (TMS) to probe the contribution of SMA to motor planning during a predictive load-bearing task. Single TMS pulses were delivered over the SMA after a cue instructing the participant to release a platform supporting his or her right hand, which in turn held a 2 kg mass. Participants were less able to bear the load successfully when TMS was delivered 400–500 ms prior to the response. This result suggests that the SMA contributes to the prediction of the sensory consequences of movement well before movement onset.

It was (not) me: Causal Inference of Agency in goal-directed actions

AbstractSummary:The perception of one’s own actions depends on both sensory information and predictions derived from internal forward models [1]. The integration of these information sources depends critically on whether perceptual consequences are associated with one’s own action (sense of agency) or with changes in the external world that are not related to the action. The perceived effects of actions should thus critically depend on the consistency between the predicted and the actual sensory consequences of actions. To test this idea, we used a virtual-reality setup to manipulate the consistency between pointing movements and their visual consequences and investigated the influence of this manipulation on self-action perception. We then asked whether a Bayesian causal inference model, which assumes a latent agency variable controlling the attributed influence of the own action on perceptual consequences [2,3], would account for the empirical data: if the percept was attributed to the own action, visual and internal information should fuse in a Bayesian optimal manner, while this should not be the case if the visual stimulus was attributed to external influences. The model correctly fits the data, showing that small deviations between predicted and actual sensory information were still attributed to one’s own action, while this was not the case for large deviations when subjects relied more on internal information. We discuss the performance of this causal inference model in comparison to alternative biologically feasible statistical models applying methods for Bayesian model comparison.Experiment:Participants were seated in front of a horizontal board on which their right hand was placed with the index finger on a haptic marker, representing the starting point for each trial. Participants were instructed to execute straight, fast (quasi-ballistic) pointing movements of fixed amplitude, but without an explicit visual target. The hand was obstructed from the view of the participants, and visual feedback about the peripheral part of the movement was provided by a cursor. Feedback was either veridical or rotated against the true direction of the hand movement by predefined angles. After each trial participants were asked to report the subjectively experienced direction of the executed hand movement by placing a mouse-cursor into that direction.Model:We compared two probabilistic models: Both include a binary random gating variable (agency) that models the sense of ‘agency’; that is the belief that the visual feedback is influenced by the subject’s motor action. The first model assumes that both the visual feedback xv and the internal motor state estimate xe are directly caused by the (unobserved) real motor state xt (Fig. 1). The second model assumes instead that the expected visual feedback depends on the perceived direction of the own motor action xe (Fig. 2). Results: Both models are in good agreement with the data. Fig. A shows the model fit for Model 1 superpositioned to the data from a single subject. Fig. B shows the belief that the visual stimulus was influenced by the own action, which decreases for large deviations between predicted and real visual feedback. Bayesian model comparison shows a better fit for model 1.Citations[1] Wolpert D.M, Ghahramani, Z, Jordan, M. (1995) Science, 269, 1880-1882.[2] Körding KP, Beierholm E, Ma WJ, Quartz S, Tenenbaum JB, et al (2007) PLoS ONE 2(9): e943.[3] Shams, L., Beierholm, U. (2010) TiCS, 14: 425-432.Acknowledgements This work was supported by the BCCN Tübingen (FKZ: 01GQ1002), the CIN Tübingen, the European Union (FP7-ICT-215866 project SEARISE), the DFG and the Hermann and Lilly Schilling Foundation.

It was (not) me: Causal Inference of Agency in goal-directed actions

AbstractSummary:The perception of one's own actions depends on both sensory information and predictions derived from internal forward models [1]. The integration of these information sources depends critically on whether perceptual consequences are associated with one’s own action (sense of agency) or with changes in the external world that are not related to the action. The perceived effects of actions should thus critically depend on the consistency between the predicted and the actual sensory consequences of actions. To test this idea, we used a virtual-reality setup to manipulate the consistency between pointing movements and their visual consequences and investigated the influence of this manipulation on self-action perception. We then asked whether a Bayesian causal inference model, which assumes a latent agency variable controlling the attributed influence of the own action on perceptual consequences [2,3], would account for the empirical data: if the percept was attributed to the own action, visual and internal information should fuse in a Bayesian optimal manner, while this should not be the case if the visual stimulus was attributed to external influences. The model correctly fits the data, showing that small deviations between predicted and actual sensory information were still attributed to one’s own action, while this was not the case for large deviations when subjects relied more on internal information. We discuss the performance of this causal inference model in comparison to alternative biologically feasible statistical models applying methods for Bayesian model comparison. Experiment: Participants were seated in front of a horizontal board on which their right hand was placed with the index finger on a haptic marker, representing the starting point for each trial. Participants were instructed to execute straight, fast (quasi-ballistic) pointing movements of fixed amplitude, but without an explicit visual target. The hand was obstructed from the view of the participants, and visual feedback about the peripheral part of the movement was provided by a cursor. Feedback was either veridical or rotated against the true direction of the hand movement by predefined angles. After each trial participants were asked to report the subjectively experienced direction of the executed hand movement by placing a mouse-cursor into that direction. Model: We compared two probabilistic models: Both include a binary random gating variable (agency) that models the sense of ‘agency’; that is the belief that the visual feedback is influenced by the subject’s motor action. The first model assumes that both the visual feedback xv and the internal motor state estimate xe are directly caused by the (unobserved) real motor state xt (Fig. 1). The second model assumes instead that the expected visual feedback depends on the perceived direction of the own motor action xe (Fig. 2). Results: Both models are in good agreement with the data. Fig. A shows the model fit for Model 1 superpositioned to the data from a single subject. Fig. B shows the belief that the visual stimulus was influenced by the own action, which decreases for large deviations between predicted and real visual feedback. Bayesian model comparison shows a better fit for model 1. Citations [1] Wolpert D.M, Gharamani, Z, Jordan, M. (1995) Science, 269, 1880-1882.[2] Körding KP, Beierholm E, Ma WJ, Quartz S, Tenenbaum JB, et al (2007) PLoS ONE 2(9): e943.[3] Shams, L., Beierholm, U. (2010) TiCS, 14: 425-432.Acknowledgements This work was supported by the BCCN Tübingen (FKZ: 01GQ1002), the CIN Tübingen, the European Union (FP7-ICT-215866 project SEARISE), the DFG and the Hermann and Lilly Schilling Foundation.

Action Preparation Helps and Hinders Perception of Action

Several theories of the mechanisms linking perception and action require that the links are bidirectional, but there is a lack of consensus on the effects that action has on perception. We investigated this by measuring visual event-related brain potentials to observed hand actions while participants prepared responses that were spatially compatible (e.g., both were on the left side of the body) or incompatible and action type compatible (e.g., both were finger taps) or incompatible, with observed actions. An early enhanced processing of spatially compatible stimuli was observed, which is likely due to spatial attention. This was followed by an attenuation of processing for both spatially and action type compatible stimuli, likely to be driven by efference copy signals that attenuate processing of predicted sensory consequences of actions. Attenuation was not response-modality specific; it was found for manual stimuli when participants prepared manual and vocal responses, in line with the hypothesis that action control is hierarchically organized. These results indicate that spatial attention and forward model prediction mechanisms have opposite, but temporally distinct, effects on perception. This hypothesis can explain the inconsistency of recent findings on action-perception links and thereby supports the view that sensorimotor links are bidirectional. Such effects of action on perception are likely to be crucial, not only for the control of our own actions but also in sociocultural interaction, allowing us to predict the reactions of others to our own actions.

The case for the comparator model as an explanation of the sense of agency and its breakdowns

I compare Frith and colleagues' influential comparator account of how the sense of agency is elicited to the multifactorial weighting model advocated by Synofzik and colleagues. I defend the comparator model from the common objection that the actual sensory consequences of action are not needed to elicit the sense of agency. I examine the comparator model's ability to explain the performance of healthy subjects and those suffering from delusions of alien control on various self-attribution tasks. It transpires that the comparator model needs case-by-case adjustment to deal with problematic data. In response to this, the multifactorial weighting model of Synofzik and colleagues is introduced. Although this model is incomplete, it is more naturally constrained by the cases that are problematic for the comparator model. However, this model may be untestable. I conclude that currently the comparator model approach has stronger support than the multifactorial weighting model approach.

Neural conduction delay forces the emergence of predictive function in simulated evolution

Evidence from biological studies suggests that humans are able to predict the sensory consequences of their own actions [1]. Computational studies also demonstrate the advantage of systems that predict sensory consequences of actions over those that predict the value of actions alone [2]. But how could the ability to predict sensory consequences of actions have evolved? One solution suggested by [3] is that prediction mechanisms first evolved to deal with natural sources of delay. Delay is commonly considered to be a purely negative feature of real world systems; however, we argue that delay can actually encourage evolution of the prediction of sensory consequences. We hypothesize that increasing sensory delay to an evolving population of sensory-motor agents will increase reliance on internal prediction of sensory consequences. To test our hypothesis we evolved populations of artificial neural networks at a complex control task (i.e. pole balancing, see figure ​figure1)1) with varied neural conduction delay (Δt) between sensory neurons and input to the control network (see figure ​figure2),2), which estimates the long term cost of applying a specific action. For top fitness networks, hidden unit activations were recorded as well as the true consequent sensory state during several evaluation trials. Each sensory variable was associated with the hidden unit that the sensory variable was maximally correlated with. Taking the average of these correlation values provides a measure of how well an agent can predict the sensory consequences of actions. We expected to find that increasing sensory delay also increases the average correlation measure described above. Figure 1 Cart-Pole Balancing Figure 2 Control network structure The result of the experiment (summarized in figure ​figure3)3) show that with no delay successful agents use a range of strategies, however, as delay increases successful strategies are forced to rely more and more on prediction of the next state to compensate for sensory delay. This seems surprising when considering that under conditions of no delay it is considerably easier to predict the next state than conditions with increased delay. Figure 3 Absolute correlation between hidden until activations and variables of the state at time t+Δt as delay increases. Although the common conception of delay is negative, sensory delay can direct natural selection to favor individuals that are better able to predict the sensory consequences of their actions.

Mental motor imagery and chronic pain: The foot laterality task

Several lines of evidence suggest that mental motor imagery is subserved by the same cognitive operations and brain structures that underlie action. Additionally, motor imagery is informed by the anticipated sensory consequences of action, including pain. We reasoned that motor imagery could provide a useful measure of chronic leg or foot pain. Forty subjects with leg pain (19 bilateral, 11 right, and 10 left leg pain), 42 subjects with chronic pain not involving the legs, and 38 controls were shown 12 different line drawings of the right or left foot and asked to indicate which foot was depicted. Previous work suggests that subjects perform this task by mentally rotating their foot to match the visually presented stimulus. All groups of subjects were slower and less accurate with stimuli that required a greater degree of mental rotation of their foot. Subjects with leg pain were both slower and less accurate than normal and pain control subjects in responding to drawings of a painful extremity. Furthermore, subjects with leg pain exhibited a significantly greater decrement in performance for stimuli that required larger amplitude mental rotations. These data suggest that motor imagery may provide important insights into the nature of the pain experience.

Post-action determinants of the reported time of conscious intentions

The question of whether our behavior is guided by our conscious intentions is gaining momentum within the field of cognitive neuroscience. It has been demonstrated that the subjective experience that conscious intentions are the driving force of our actions, is built partially on a post hoc reconstruction. Our hypothesis was that this reconstructive process is mediated by an action-monitoring system that compares the predicted and the actual sensory consequences of an action. We applied event-related potentials (ERP) to a variant of the Libet's task in which participants were asked to press a button and to report the time of decision – will judgment (W) – to press. We provided delayed auditory feedbacks after participants’ action to signify an action time later than the actual action. We found that auditory feedbacks evoked a negative component in the 250–300 time range, namely action-effect negativity (NAE), that is thought to reflect the activity of a system that detects violation from expectancies. We showed that the amplitude of the NAE was sensitive to the delay of the auditory feedback, with a larger amplitude for more delayed feedbacks. Furthermore, changes in the NAE were also associated with changes in the reported W. These results not only confirm that we infer the time we decided to act from events occurring after the response, but these results also indicate that the subjective experience of when an action is decided is influenced by the activity of an action-monitoring system that detects mismatches between predicted and actual sensory consequences of the actions.