Sensorimotor prediction is used to direct gaze toward task-relevant locations in a goal-directed throwing task.

Previous research has shown that action effects of self-generated movements are internally predicted before outcome feedback becomes available. To test whether these sensorimotor predictions are used to facilitate visual information uptake for feedback processing, we measured eye movements during the execution of a goal-directed throwing task. Participants could fully observe the effects of their throwing actions (ball trajectory and either hitting or missing a target) in most of the trials. In a portion of the trials, the ball trajectory was not visible, and participants only received static information about the outcome. We observed a large proportion of predictive saccades, shifting gaze toward the goal region before the ball arrived and outcome feedback became available. Fixation locations after predictive saccades systematically covaried with future ball positions in trials with continuous ball flight information, but notably also in trials with static outcome feedback and only efferent and proprioceptive information about the movement that could be used for predictions. Fixation durations at the chosen positions after feedback onset were modulated by action outcome (longer durations for misses than for hits) and outcome uncertainty (longer durations for narrow vs. clear outcomes). Combining both effects, durations were longest for narrow errors and shortest for clear hits, indicating that the chosen locations offer informational value for feedback processing. Thus, humans are able to use sensorimotor predictions to direct their gaze toward task-relevant feedback locations. Outcome-dependent saccade latency differences (miss vs. hit) indicate that also predictive valuation processes are involved in planning predictive saccades.NEW & NOTEWORTHY We elucidate the potential benefits of sensorimotor predictions, focusing on how the system actually uses this information to optimize feedback processing in goal-directed actions. Sensorimotor information is used to predict spatial parameters of movement outcomes, guiding predictive saccades toward future action effects. Saccade latencies and fixation durations are modulated by outcome quality, indicating that predictive valuation processes are considered and that the locations chosen are of high informational value for feedback processing.

Analysis of timing variability in human movements by aligning parameter curves in time.

The analysis of timing in human movements requires a reference with which timing can be quantified. In reactive movements this reference is given by the stimulus. However, many movements do not respond to such an external event. In throwing, for instance, the hand opening for release has to be timed to an acceleration of the throwing arm. A common approach to analyzing release-timing variability is to choose a landmark in the movement that is supposed to have a fixed temporal relation to the release. Such distinct landmarks, however, are not always well definable. Therefore, the present article describes an alternative approach analyzing timing variability on the basis of the alignment of different trials relative to their kinematic shape, by shifting the trials in the time domain. The basic assumption behind this approach is that single throwing movements are one instance of an acquired movement template, and thus show a considerable similarity. In contrast, the location of the temporal moment of release varies from trial to trial, generating imprecision regarding the release timing. In trials synchronized with respect to the release, this variability can be assessed by shifting the kinematic profiles of the throwing movements in time such that they superimpose as closely as possible. As a result, the corresponding time shifts for all trials represent a measure of the release time deviations across trials, and the standard deviation of these deviations represents the timing variability. Aside from timing analyses in such movements as throwing, the approach can be applied to very different tasks with timing demands-for example, to neurophysiological signals.

Metacognitive Domains Are Not Aligned along a Dimension of Internal-External Information Source.

It is still debated whether metacognition, or the ability to monitor our own mental states, relies on processes that are "domain-general" (a single set of processes can account for the monitoring of any mental process) or "domain-specific" (metacognition is accomplished by a collection of multiple monitoring modules, one for each cognitive domain). It has been speculated that two broad categories of metacognitive processes may exist: those that monitor primarily externally generated versus those that monitor primarily internally generated information. To test this proposed division, we measured metacognitive performance (using m-ratio, a signal detection theoretical measure) in four tasks that could be ranked along an internal-external axis of the source of information, namely memory, motor, visuomotor, and visual tasks. We found correlations between m-ratios in visuomotor and motor tasks, but no correlations between m-ratios in visual and visuomotor tasks, or between motor and memory tasks. While we found no correlation in metacognitive ability between visual and memory tasks, and a positive correlation between visuomotor and motor tasks, we found no evidence for a correlation between motor and memory tasks. This pattern of correlations does not support the grouping of domains based on whether the source of information is primarily internal or external. We suggest that other groupings could be more reflective of the nature of metacognition and discuss the need to consider other non-domain task-features when using correlations as a way to test the underlying shared processes between domains.

Motor outcomes congruent with intentions may sharpen metacognitive representations.

We can monitor our intentional movements and form explicit representations about our movements, allowing us to describe how we move our bodies. But it is unclear which information this metacognitive monitoring relies on. For example, when throwing a ball to hit a target, we might use the visual information about how the ball flew to metacognitively assess our performance. Alternatively, we might disregard the ball trajectory - given that it is not directly relevant to our goal - and metacognitively assess our performance based solely on whether we reached the goal of hitting the target. In two experiments we aimed to distinguish between these two alternatives and asked whether the distal outcome of a goal-directed action (hitting or missing a target) informs the metacognitive representations of our own movements. Participants performed a semi-virtual task where they moved their arm to throw a virtual ball at a target. After each throw, participants discriminated which of two ball trajectories displayed on the screen corresponded to the flight path of their throw and then rated their confidence in this decision. The task included two conditions that differed on whether the distal outcome of the two trajectories shown matched (congruent) or differed (incongruent). Participants were significantly more accurate in discriminating between the two trajectories, and responded faster in the incongruent condition and, accordingly, were significantly more confident on these trials. Crucially, we found significant differences in metacognitive performance (measured as meta-d'/d') between the two conditions only on successful trials, where the virtual ball had hit the target. These results indicate that participants successfully incorporated information about the outcome of the movement into both their discrimination and confidence responses. However, information about the outcome selectively sharpened the precision of confidence ratings only when the outcome of their throw matched their intention. We argue that these findings underline the separation between the different levels of information that may contribute to body monitoring, and we provide evidence that intentions might play a central role in metacognitive motor representations.

Relevance of Predictive and Postdictive Error Information in the Course of Motor Learning.

The prediction of the sensory consequences of physical movements is a fundamental feature of the human brain. This function is attributed to a forward model, which generates predictions based on sensory and efferent information. The neural processes underlying such predictions have been studied using the error-related negativity (ERN) as a fronto-central event-related potential in electroencephalogram (EEG) tracings. In this experiment, 16 participants practiced a novel motor task for 4000 trials over ten sessions. Neural correlates of error processing were recorded in sessions one, five, and ten. Along with significant improvements in task performance, the ERN amplitude increased over the sessions. Simultaneously, the feedback-related negativity (FRN), a neural marker corresponding to the processing of movement-outcome feedback, attenuated with learning. The findings suggest that early in learning, the motor control system relies more on information from external feedback about terminal outcome. With increasing task performance, the forward model is able to generate more accurate outcome predictions, which, as a result, increasingly contributes to error processing. The data also suggests a complementary relationship between the ERN and the FRN over motor learning.

Predictability shapes movement kinematics and grip force regulation in human object handovers.

In contrast to a self-generated action, a human-to-human object handover represents a semi-predictable task, due to a lack of exact knowledge about the partner's future movement behavior. Thus far, it has not been determined which behavioral characteristics result from dealing with this prevailing uncertainty, although this distinction would enhance the understanding of underlying motor control strategies in such semi-predictable situations. Behavioral effects of mutual interaction during object handovers were therefore investigated in the current study, by comparing grip force profiles and kinematic data from predictable solo-handovers (between the two hands of one person) with data from semi-predictable partner-handovers. There were significant decreases in passers' mean release rates as well as corresponding increases in handover durations in partner-handovers compared to solo-handovers. Likewise, receivers in partner-handovers employed lower mean grip force rates to take the object, which speaks for feedback reliance of both partners in the load transfer process of partner-handovers. Increased vertical object displacement in this phase might represent timing deficits due to the prediction uncertainties in partner-handovers. The data also provided first evidence that left-handed people serving as receivers in partner-handovers exhibit an altered take-over strategy compared to right-handed receivers.

Measuring metacognition of direct and indirect parameters of voluntary movement.

We can make exquisitely precise movements without the apparent need for conscious monitoring. But can we monitor the low-level movement parameters when prompted? And what are the mechanisms that allow us to monitor our movements? To answer these questions, we designed a semivirtual ball throwing task. On each trial, participants first threw a virtual ball by moving their arm (with or without visual feedback, or replayed from a previous trial) and then made a two-alternative forced choice on the resulting ball trajectory. They then rated their confidence in their decision. We measured metacognitive efficiency using meta-d'/d' and compared it between different informational domains of the first-order task (motor, visuomotor or visual information alone), as well as between two different versions of the task based on different parameters of the movement: proximal (position of the arm) or distal (resulting trajectory of the ball thrown). We found that participants were able to monitor their performance based on distal motor information as well as when proximal information was available. Their metacognitive efficiency was also equally high in conditions with different sources of information available. The analysis of correlations across participants revealed an unexpected result: While metacognitive efficiency correlated between informational domains (which would indicate domain-generality of metacognition), it did not correlate across the different parameters of movement. We discuss possible sources of this discrepancy and argue that specific first-order task demands may play a crucial role in our metacognitive ability and should be considered when making inferences about domain-generality based on correlations. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Accuracy of Motor Error Predictions for Different Sensory Signals.

Detecting and evaluating errors in action execution is essential for learning. Through complex interactions of the inverse and the forward model, the human motor system can predict and subsequently adjust ongoing or subsequent actions. Inputs to such a prediction are efferent and afferent signals from various sources. The aim of the current study was to examine the impact of visual as well as a combination of efferent and proprioceptive input signals to error prediction in a complex motor task. Predicting motor errors has been shown to be correlated with a neural signal known as the error-related negativity (Ne/ERN). Here, we tested how the Ne/ERN amplitude was modulated by the availability of different sensory signals in a semi-virtual throwing task where the action outcome (hit or miss of the target) was temporally delayed relative to movement execution allowing participants to form predictions about the outcome prior to the availability of knowledge of results. 19 participants practiced the task and electroencephalogram was recorded in two test conditions. In the Visual condition, participants received only visual input by passively observing the throwing movement. In the EffProp condition, participants actively executed the task while visual information about the real and the virtual effector was occluded. Hence, only efferent and proprioceptive signals were available. Results show a significant modulation of the Ne/ERN in the Visual condition while no effect could be observed in the EffProp condition. In addition, amplitudes of the feedback-related negativity in response to the actual outcome feedback were found to be inversely related to the Ne/ERN amplitudes. Our findings indicate that error prediction is modulated by the availability of input signals to the forward model. The observed amplitudes were found to be attenuated in comparison to previous studies, in which all efferent and sensory inputs were present. Furthermore, we assume that visual signals are weighted higher than proprioceptive signals, at least in goal-oriented tasks with visual targets.

Timing accuracy in self-timed movements related to neural indicators of movement initiation.

Timely movement initiation is crucial in quick reactions or when a series of movements has to be strung together in a timed fashion to create a coordinated sequence. Stochastic neural variability can lead to misinitiation errors as reaction time studies suggest. Higher reaction times occur when preparatory neural activity reaches an initiation threshold later relative to shorter reaction times. Whether this also applies to self-timed movements is harder to scrutinize because they lack an external event that could serve as a reference for timing accuracy estimations. By example of a self-timed goal-oriented throwing task, we used a method that synchronizes the throwing movements by their kinematic profiles to assess relative timing differences in throwing release. We determined neural preparatory processes of the release using the movement-related electrophysiological Bereitschaftspotential (BP). By analyzing differences in shape and timing of the BP in delayed and non-delayed throws, two variables could be extracted that are related to timing differences on the kinematic level. First, temporal deviations in BP curves partly meet the kinematic deviations. Second, delayed releases were preceded by a short flattening of the BP curves prior to release. Thus, temporal and shape deviations in the neural movement initiation are assumed to delay self-timed movements.