The last chance to pass the ball: investigating the role of temporal expectation and motor resonance in processing temporal errors in motor actions

Rhythmic temporal prediction enhances neural representations of movement intention for brain-computer interface

Objective.Detecting movement intention is a typical use of brain-computer interfaces (BCI). However, as an endogenous electroencephalography (EEG) feature, the neural representation of movement is insufficient for improving motor-based BCI. This study aimed to develop a new movement augmentation BCI encoding paradigm by incorporating the cognitive function of rhythmic temporal prediction, and test the feasibility of this new paradigm in optimizing detections of movement intention.Methods.A visual-motion synchronization task was designed with two movement intentions (left vs. right) and three rhythmic temporal prediction conditions (1000 ms vs. 1500 ms vs. no temporal prediction). Behavioural and EEG data of 24 healthy participants were recorded. Event-related potentials (ERPs), event-related spectral perturbation induced by left- and right-finger movements, the common spatial pattern (CSP) and support vector machine, Riemann tangent space algorithm and logistic regression were used and compared across the three temporal prediction conditions, aiming to test the impact of temporal prediction on movement detection.Results.Behavioural results showed significantly smaller deviation time for 1000 ms and 1500 ms conditions. ERP analyses revealed 1000 ms and 1500 ms conditions led to rhythmic oscillations with a time lag in contralateral and ipsilateral areas of movement. Compared with no temporal prediction, 1000 ms condition exhibited greater beta event-related desynchronization (ERD) lateralization in motor area (P< 0.001) and larger beta ERD in frontal area (P< 0.001). 1000 ms condition achieved an averaged left-right decoding accuracy of 89.71% using CSP and 97.30% using Riemann tangent space, both significantly higher than no temporal prediction. Moreover, movement and temporal information can be decoded simultaneously, achieving 88.51% four-classification accuracy.Significance.The results not only confirm the effectiveness of rhythmic temporal prediction in enhancing detection ability of motor-based BCI, but also highlight the dual encodings of movement and temporal information within a single BCI paradigm, which is promising to expand the range of intentions that can be decoded by the BCI.

An active inference model of hierarchical action understanding, learning and imitation

We advance a novel active inference model of the cognitive processing that underlies the acquisition of a hierarchical action repertoire and its use for observation, understanding and imitation. We illustrate the model in four simulations of a tennis learner who observes a teacher performing tennis shots, forms hierarchical representations of the observed actions, and imitates them. Our simulations show that the agent's oculomotor activity implements an active information sampling strategy that permits inferring the kinematic aspects of the observed movement, which lie at the lowest level of the action hierarchy. In turn, this low-level kinematic inference supports higher-level inferences about deeper aspects of the observed actions: proximal goals and intentions. Finally, the inferred action representations can steer imitative responses, but interfere with the execution of different actions. Our simulations show that hierarchical active inference provides a unified account of action observation, understanding, learning and imitation and helps explain the neurobiological underpinnings of visuomotor cognition, including the multiple routes for action understanding in the dorsal and ventral streams and mirror mechanisms.

Sensorimotor expertise influences perceptual weight judgments during observation of a sport-specific gesture

This study aimed to investigate the role of sensorimotor expertise in evaluating relative weight of a lifted object during the observation of a sport-specific gesture, namely the deadlift. Fifty-six participants, assigned to three groups according to their experience in weight lifting, powerlifters, CrossFit® practitioners and naïve participants (controls), performed a perceptual weight judgments task. Participants observed videos showing a powerlifter executing a deadlift at the 80%, 90% and 100% of 1 repetition maximum (1RM) and answered a question about the weight of the lifted object. Participants' response accuracy and variability were evaluated. Findings showed that powerlifters were more accurate than controls. No differences appeared between powerlifter and CrossFit® practitioners, and between CrossFit® practitioners and controls. Response variability was similar in the three groups. These findings suggest that a fine sensorimotor expertise specific for the observed gesture is crucial to detect the weight of the object displayed in the observed movement, since it might allow detecting small changes in the observed movement kinematics, which we speculate are at the basis of the object weight recognition.

Error observation as a window on performance monitoring in social contexts? A systematic review

Living in a social world requires social monitoring, i.e., the ability to keep track of others' actions and mistakes. Here, we demonstrate the good reliability of the behavioral and neurophysiological indexes ascribed to social monitoring. We also show that no consensus exists on the cognitive bases of this phenomenology and discuss three alternative hypotheses: (i) the direct matching hypothesis, postulating that observed errors are processed through automatic simulation; (ii) the attentional hypothesis, considering errors as unexpected events that take resources away from task processing; and (iii) the goal representation hypothesis, which weighs social error monitoring depending on how relevant the other's task is to the observer's goals. To date, evidence on the role played by factors that could help to disentangle these hypotheses (e.g., the human vs. non-human nature of the actor, the error rate, and the reward context) is insufficient, although the goal representation hypothesis seems to receive more support. Theory-driven experimental designs are needed to enlighten this debate and clarify the role of error monitoring during interactive exchanges.

Motor Cortical Excitability Changes in Preparation to Concentric and Eccentric Movements

Specific neural mechanisms operate at corticospinal levels during eccentric and concentric contractions. Here, we investigated the difference in corticospinal excitability (CSE) when preparing these two types of contraction. In this study we enrolled 16 healthy participants. They were asked to perform an instructed-delay reaction time (RT) task involving a concentric or an eccentric contraction of the right first dorsal interosseus muscle, as a response to a proprioceptive cue (Go signal) presented 1 s after a warning signal. We tested CSE at different time points ranging from 300 ms before up to 40 ms after a Go signal. CSE increased 300-150 ms before the Go signal for both contractions. Interestingly, significant changes in CSE in the time interval around the Go signal (from -150 ms to +40 ms) were only revealed in eccentric contraction. We observed a significant decrease in excitability immediately before the Go cue (Pre_50) and a significant increase 40 ms after it (Post_40) with respect to the MEPs recorded at Pre_150. Finally, CSE in eccentric contraction was lower before the Go cue (Pre_50) and greater after it (Post_40) compared to the concentric contraction. A similar result was also found in NoMov paradigm, used to disentangle the effects induced by movement preparation from those induced by the movement preparation linked to the proprioceptive cue. We could conclude that different neural mechanisms observed during concentric and eccentric contractions are mirrored with a different time-specific modulation of CSE in the preparatory phase to the movement.

What modulates the Mirror Neuron System during action observation?: Multiple factors involving the action, the actor, the observer, the relationship between actor and observer, and the context

Seeing an agent perform an action typically triggers a motor simulation of that action in the observer's Mirror Neuron System (MNS). Over the past few years, it has become increasingly clear that during action observation the patterns and strengths of responses in the MNS are modulated by multiple factors. The first aim of this paper is therefore to provide the most comprehensive survey to date of these factors. To that end, 22 distinct factors are described, broken down into the following sets: six involving the action; two involving the actor; nine involving the observer; four involving the relationship between actor and observer; and one involving the context. The second aim is to consider the implications of these findings for four prominent theoretical models of the MNS: the Direct Matching Model; the Predictive Coding Model; the Value-Driven Model; and the Associative Model. These assessments suggest that although each model is supported by a wide range of findings, each one is also challenged by other findings and relatively unaffected by still others. Hence, there is now a pressing need for a richer, more inclusive model that is better able to account for all of the modulatory factors that have been identified so far.