Modulation of Motor Area Activity by the Outcome for a Player during Observation of a Baseball Game

Background: Observing competitive games such as sports is a pervasive entertainment among humans. The inclination to watch others play may be based on our social-cognitive ability to understand the internal states of others. The mirror neuron system, which is activated when a subject observes the actions of others, as well as when they perform the same action themselves, seems to play a crucial role in this process. Our previous study showed that activity of the mirror neuron system was modulated by the outcome of the subject’s favored player during observation of a simple competitive game (rock-paper-scissors). However, whether the mirror neuron system responds similarly in a more complex and naturalistic sports game has not yet been fully investigated. Methodology/Principal Findings: In the present study, we measured the activity of motor areas when the subjects, who were amateur baseball field players (non-pitchers), watched short movie clips of scenes in professional baseball games. The subjects were instructed to support either a batter or a pitcher when observing the movie clip. The results showed that activity in the motor area exhibited a strong interaction between the subject’s supported side (batter or pitcher) and the outcome (a hit or an out). When the subject supported the batter, motor area activity was significantly higher when the batter made an out than when he made a hit. However, such modulation was not apparent when the subject supported the pitcher

Changes in visual and sensory-motor resting-state functional connectivity support motor learning by observing.

Motor learning occurs not only through direct first-hand experience but also through observation (Mattar AA, Gribble PL. Neuron 46: 153-160, 2005). When observing the actions of others, we activate many of the same brain regions involved in performing those actions ourselves (Malfait N, Valyear KF, Culham JC, Anton JL, Brown LE, Gribble PL. J Cogn Neurosci 22: 1493-1503, 2010). Links between neural systems for vision and action have been reported in neurophysiological (Strafella AP, Paus T. Neuroreport 11: 2289-2292, 2000; Watkins KE, Strafella AP, Paus T. Neuropsychologia 41: 989-994, 2003), brain imaging (Buccino G, Binkofski F, Fink GR, Fadiga L, Fogassi L, Gallese V, Seitz RJ, Zilles K, Rizzolatti G, Freund HJ. Eur J Neurosci 13: 400-404, 2001; Iacoboni M, Woods RP, Brass M, Bekkering H, Mazziotta JC, Rizzolatti G. Science 286: 2526-2528, 1999), and eye tracking (Flanagan JR, Johansson RS. Nature 424: 769-771, 2003) studies. Here we used a force field learning paradigm coupled with resting-state fMRI to investigate the brain areas involved in motor learning by observing. We examined changes in resting-state functional connectivity (FC) after an observational learning task and found a network consisting of V5/MT, cerebellum, and primary motor and somatosensory cortices in which changes in FC were correlated with the amount of motor learning achieved through observation, as assessed behaviorally after resting-state fMRI scans. The observed FC changes in this network are not due to visual attention to motion or observation of movement errors but rather are specifically linked to motor learning. These results support the idea that brain networks linking action observation and motor control also facilitate motor learning

Survey of the Itanium architecture from a programmer's perspective

Journal ArticleThe Itanium family of processors represents Intel;s foray into the world of Explicitly Parallel Instruction Computing and 64-bit system design. This survey contains an introduction to the Itanium architecture and instruction set, as well as some of the available implementations. Taking a programmer's perspective, we have attempted to distill the relevant information from a variety of sources, including the Intel Itanium architecture documentation

Sensory Plasticity in Human Motor Learning.

There is accumulating evidence from behavioral, neurophysiological, and neuroimaging studies that the acquisition of motor skills involves both perceptual and motor learning. Perceptual learning alters movements, motor learning, and motor networks of the brain. Motor learning changes perceptual function and the sensory circuits of the brain. Here, we review studies of both human limb movement and speech that indicate that plasticity in sensory and motor systems is reciprocally linked. Taken together, this points to an approach to motor learning in which perceptual learning and sensory plasticity have a fundamental role

Multiple Motor Learning Strategies in Visuomotor Rotation

When exposed to a continuous directional discrepancy between movements of a visible hand cursor and the actual hand (visuomotor rotation), subjects adapt their reaching movements so that the cursor is brought to the target. Abrupt removal of the discrepancy after training induces reaching error in the direction opposite to the original discrepancy, which is called an aftereffect. Previous studies have shown that training with gradually increasing visuomotor rotation results in a larger aftereffect than with a suddenly increasing one. Although the aftereffect difference implies a difference in the learning process, it is still unclear whether the learned visuomotor transformations are qualitatively different between the training conditions.We examined the qualitative changes in the visuomotor transformation after the learning of the sudden and gradual visuomotor rotations. The learning of the sudden rotation led to a significant increase of the reaction time for arm movement initiation and then the reaching error decreased, indicating that the learning is associated with an increase of computational load in motor preparation (planning). In contrast, the learning of the gradual rotation did not change the reaction time but resulted in an increase of the gain of feedback control, suggesting that the online adjustment of the reaching contributes to the learning of the gradual rotation. When the online cursor feedback was eliminated during the learning of the gradual rotation, the reaction time increased, indicating that additional computations are involved in the learning of the gradual rotation.The results suggest that the change in the motor planning and online feedback adjustment of the movement are involved in the learning of the visuomotor rotation. The contributions of those computations to the learning are flexibly modulated according to the visual environment. Such multiple learning strategies would be required for reaching adaptation within a short training period

Spinal stretch reflexes support efficient hand control

© 2019, The Author(s), under exclusive licence to Springer Nature America, Inc. Motor behaviour is most efficiently controlled by correcting only disturbances that influence task success. It is currently thought that such control is computed within a transcortical feedback pathway. Here we show that, for postural hand control, even the fastest spinal feedback pathway can produce efficient corrective responses, forcing a re-evaluation of how the nervous system derives the control laws that support motor behavior

Accuracy, Stability, and Corrective Behavior in a Visuomotor Tracking Task: A Preliminary Study

Visuomotor tracking tasks have been used to elucidate the underlying mechanisms that allow for the coordination of a movement to an environmental event. The main purpose of the present study was to examine the relationship between accuracy and stability of tracking performance and the amount of corrective movements that emerge for various coordination patterns in a unimanual visuomotor tracking task. Participants (N = 6) produced rhythmic elbow flexion–extension motions and were required to track an external sinusoidal signal at five different relative phases, 0°, 45°, 90°, 135°, and 180°. Differential accuracy and stability were found among the five tracking patterns with the 0° relative phase pattern being the most accurate and stable pattern. Corrective movements were correlated with changes in accuracy only for the 0° relative phase pattern, with more corrections emerging for less accurate performance. The amount of corrective movements decreased as the stability of tracking performance increased for the 0°, 45°, and 135° patterns. For the 90° and 180° tracking patterns, the amount of corrective movements was not correlated with pattern accuracy or pattern stability. The results demonstrate that corrective behaviors are an important motor process in maintaining the stability of stable perception-action coordination patterns, while offering little benefit for unstable perception-action patterns

Learning from Mistakes: Improving Initial Fingertip Force Scaling by Observing Lifting Errors

• When lifting objects that are lighter or heaver than we expect them to be, individuals typically misapply forces in a way that reflects their prior expectations of heaviness. • Because we lift in this predictive way, large and small cubes elicit these characteristic errors even when they are adjusted to have equal mass. Lifters will apply too much force to a large cube and substantially less force to a small cube – errors that are rapidly corrected with repeated lifts (Flanagan & Beltzner, 2000). • When watching others lift objects, an observer’s motor system automatically reacts in a way that reflects the object’s weight (Alaerts et al., 2010). It is, however, unclear how the motor system reacts to observing lifting errors. • To examine how observing an action improves motor learning in the context of fingertip force scaling, participants watched a video of an object lifting task before lifting equally-weighted large and small cubes themselves. • To determine what style of kinematic information is more valuable to observe, participants watched either error filled, first-time lifts or error free, expert lifts before lifting these equally-weighted small and large cubes themselves.

On the Similarity of Functional Connectivity between Neurons Estimated across Timescales

A central objective in neuroscience is to understand how neurons interact. Such functional interactions have been estimated using signals recorded with different techniques and, consequently, different temporal resolutions. For example, spike data often have sub-millisecond resolution while some imaging techniques may have a resolution of many seconds. Here we use multi-electrode spike recordings to ask how similar functional connectivity inferred from slower timescale signals is to the one inferred from fast timescale signals. We find that functional connectivity is relatively robust to low-pass filtering—dropping by about 10% when low pass filtering at 10 hz and about 50% when low pass filtering down to about 1 Hz—and that estimates are robust to high levels of additive noise. Moreover, there is a weak correlation for physiological filters such as hemodynamic or Ca2+ impulse responses and filters based on local field potentials. We address the origin of these correlations using simulation techniques and find evidence that the similarity between functional connectivity estimated across timescales is due to processes that do not depend on fast pair-wise interactions alone. Rather, it appears that connectivity on multiple timescales or common-input related to stimuli or movement drives the observed correlations. Despite this qualification, our results suggest that techniques with intermediate temporal resolution may yield good estimates of the functional connections between individual neurons