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Enhancing Juggling Proficiency Through Slow-Tempo Virtual Reality Training
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In this paper, we follow up on research dealing with motion learning in Virtual Reality (VR). We investigate the impact of VR motion learning on motion performance, motivation for motion learning and willingness to continue with the motion learning. In our research, we used three ball juggling as a subject of learning. We performed a user study with 30 participants. A VR application was used in our study which allows setting up lower gravity and thus slowing down the motion for learning purposes. The results were statistically evaluated and we comment on the positive influence of virtual reality on motivation and possibilities of using VR in the motion learning process.
The development of more effective rehabilitative interventions requires a better understanding of how humans learn and transfer motor skills in real-world contexts. Presently, clinicians design interventions to promote skill learning by relying on evidence from experimental paradigms involving simple tasks, such as reaching for a target. While these tasks facilitate stringent hypothesis testing in laboratory settings, the results may not shed light on performance of more complex real-world skills. In this perspective, we argue that virtual environments (VEs) are flexible, novel platforms to evaluate learning and transfer of complex skills without sacrificing experimental control. Specifically, VEs use models of real-life tasks that afford controlled experimental manipulations to measure and guide behavior with a precision that exceeds the capabilities of physical environments. This paper reviews recent insights from VE paradigms on motor learning into two pressing challenges in rehabilitation research: 1) Which training strategies in VEs promote complex skill learning? and 2) How can transfer of learning from virtual to real environments be enhanced? Defining complex skills by having nested redundancies, we outline findings on the role of movement variability in complex skill acquisition and discuss how VEs can provide novel forms of guidance to enhance learning. We review the evidence for skill transfer from virtual to real environments in typically developing and neurologically-impaired populations with a view to understanding how differences in sensory-motor information may influence learning strategies. We provide actionable suggestions for practicing clinicians and outline broad areas where more research is required. Finally, we conclude that VEs present distinctive experimental platforms to understand complex skill learning that should enable transfer from therapeutic practice to the real world.
Dealing with fear of falling is a challenge in sport climbing. Virtual reality (VR) research suggests that using physical and reality-based interaction increases the presence in VR. In this paper, we present a study that investigates the influence of physical props on presence, stress and anxiety in a VR climbing environment involving whole body movement. To help climbers overcoming fear of falling, we compared three different conditions: Climbing in reality at 10 m height, physical climbing in VR (with props attached to the climbing wall) and virtual climbing in VR using game controllers. From subjective reports and biosignals, our results show that climbing with props in VR increases the anxiety and sense of realism in VR for sport climbing. This suggests that VR in combination with physical props are an effective simulation setup to induce the sense of height.
Does the structure of an adult human brain alter in response to environmental demands? Here we use whole-brain magnetic-resonance imaging to visualize learning-induced plasticity in the brains of volunteers who have learned to juggle. We find that these individuals show a transient and selective structural change in brain areas that are associated with the processing and storage of complex visual motion. This discovery of a stimulus-dependent alteration in the brain's macroscopic structure contradicts the traditionally held view that cortical plasticity is associated with functional rather than anatomical changes.
Detailed knowledge about online brain processing during the execution of complex motor tasks with a high motion range still remains elusive. The aim of the present study was to investigate the hemodynamic responses within sensorimotor networks as well as in visual motion area during the execution of a complex visuomotor task such as juggling. More specifically, we were interested in how far the hemodynamic response as measured with functional near infrared spectroscopy (fNIRS) adapts as a function of task complexity and the level of the juggling expertise. We asked expert jugglers to perform different juggling tasks with different levels of complexity such as a 2-ball juggling, 3- and 5-ball juggling cascades. We here demonstrate that expert jugglers show an altered neurovascular response with increasing task complexity, since a 5-ball juggling cascade showed enhanced hemodynamic responses for oxygenated hemoglobin as compared to less complex tasks such as a 3- or 2-ball juggling pattern. Moreover, correlations between the hemodynamic response and the level of the juggling expertise during the 5-ball juggling cascade, acquired by cinematographic video analysis, revealed only a non-significant trend in primary motor cortex, indicating that a higher level of expertise might be associated with lower hemodynamic responses.
Surpassing the initial ‘wow’ effect of a complex juggling trick and producing long-lasting engaging performances are the main goals of any juggling act. Conveying to the audience the skill and the effort required for a performance is often difficult. In this paper, we use a wearable EEG headset to investigate how juggling skills can be inferred from a juggler’s brain. We observed characteristic brain activity and synchronization while juggling in both an expert and an intermediate juggler. We also found that processing of visuomotor skills and memory retention can be distinguished during motor imagery and simulated juggling conditions. For the first time, we were able to monitor a juggler’s brain in action. We have shown that using EEG while juggling could both improve our understanding of neuronal mechanisms governing visuomotor control and, importantly, represent a potential to enrich artistic performance and increase audience engagement.
Learning novel motor skills alters local inhibitory circuits within primary motor cortex (M1) (Floyer-Lea et al., 2006) and changes long-range functional connectivity (Albert et al., 2009). Whether such effects occur with long-term training is less well established. In addition, the relationship between learning-related changes in functional connectivity and local inhibition, and their modulation by practice, has not previously been tested.
Here, we used resting-state functional magnetic resonance imaging (rs-fMRI) to assess functional connectivity and MR spectroscopy to quantify GABA in primary motor cortex (M1) before and after a 6 week regime of juggling practice. Participants practiced for either 30 min (high intensity group) or 15 min (low intensity group) per day. We hypothesized that different training regimes would be reflected in distinct changes in brain connectivity and local inhibition, and that correlations would be found between learning-induced changes in GABA and functional connectivity.
Performance improved significantly with practice in both groups and we found no evidence for differences in performance outcomes between the low intensity and high intensity groups. Despite the absence of behavioral differences, we found distinct patterns of brain change in the two groups: the low intensity group showed increases in functional connectivity in the motor network and decreases in GABA, whereas the high intensity group showed decreases in functional connectivity and no significant change in GABA. Changes in functional connectivity correlated with performance outcome. Learning-related changes in functional connectivity correlated with changes in GABA.
The results suggest that different training regimes are associated with distinct patterns of brain change, even when performance outcomes are comparable between practice schedules. Our results further indicate that learning-related changes in resting-state network strength in part reflect GABAergic plastic processes.
Novice and expert jugglers employ different visuomotor strategies: whereas novices look at the balls around their zeniths, experts tend to fixate their gaze at a central location within the pattern (so-called gaze-through). A gaze-through strategy may reflect visuomotor parsimony, i.e., the use of simpler visuomotor (oculomotor and/or attentional) strategies as afforded by superior tossing accuracy and error corrections. In addition, the more stable gaze during a gaze-through strategy may result in more accurate movement planning by providing a stable base for gaze-centered neural coding of ball motion and movement plans or for shifts in attention. To determine whether a stable gaze might indeed have such beneficial effects on juggling, we examined juggling variability during 3-ball cascade juggling with and without constrained gaze fixation (at various depths) in expert performers (n = 5). Novice jugglers were included (n = 5) for comparison, even though our predictions pertained specifically to expert juggling. We indeed observed that experts, but not novices, juggled significantly less variable when fixating, compared to unconstrained viewing. Thus, while visuomotor parsimony might still contribute to the emergence of a gaze-through strategy, this study highlights an additional role for improved movement planning. This role may be engendered by gaze-centered coding and/or attentional control mechanisms in the brain.
Electronic supplementary material
The online version of this article (doi:10.1007/s00221-011-2967-6) contains supplementary material, which is available to authorized users.
Improving performance in sports can be difficult because many biomechanical, physiological, and psychological factors come into play during competition. A better understanding of the perception-action loop employed by athletes is necessary. This requires isolating contributing factors to determine their role in player performance. Because of its inherent limitations, video playback doesn't permit such in-depth analysis. Interactive, immersive virtual reality (VR) can overcome these limitations and foster a better understanding of sports performance from a behavioral-neuroscience perspective. Two case studies using VR technology and a sophisticated animation engine demonstrate how to use information from visual displays to inform a player's future course of action.
Although experience-dependent structural changes have been found in adult gray matter, there is little evidence for such changes in white matter. Using diffusion imaging, we detected a localized increase in fractional anisotropy, a measure of microstructure, in white matter underlying the intraparietal sulcus following training of a complex visuo-motor skill. This provides, to the best of our knowledge, the first evidence for training-related changes in white-matter structure in the healthy human adult brain.
We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
It has been suggested that learning is associated with a transient and highly selective increase in brain gray matter in healthy young volunteers. It is not clear whether and to what extent the aging brain is still able to exhibit such structural plasticity. We built on our original study, now focusing on healthy senior citizens. We observed that elderly persons were able to learn three-ball cascade juggling, but with less proficiency compared with 20-year-old adolescents. Similar to the young group, gray-matter changes in the older brain related to skill acquisition were observed in area hMT/V5 (middle temporal area of the visual cortex). In addition, elderly volunteers who learned to juggle showed transient increases in gray matter in the hippocampus on the left side and in the nucleus accumbens bilaterally.
Brain plasticity is especially stimulated by complex bimanual tasks, because, as for juggling, they require simultaneous control of multiple movements, high level of bimanual coordination, balance and sustained swapping attention to multiple objects interacting with both hands. Neuroimaging studies on jugglers showed changes in white and grey matter after juggling training, while the very few electroencephalographic (EEG) studies showed changes in the frequency domain. However, no study has focused on the fine temporal brain activations during a bimanual coordinative task in ecological settings. We aimed at understanding the neural correlates of juggling tasks comparing expert jugglers to non-jugglers. Both groups performed two juggling tasks with increasing difficulty (1-ball fountain and 2-ball shower in non-jugglers, 2- and 3-ball shower in expert jugglers), while the EEG was recorded. This design allowed to compare brain activities related to increasing task difficulty within the same group, and the two groups on the same task. The movement-related cortical potentials (MRCPs) for each task were segmented into epochs lasting 4.5s (-1.5/+3.0s). Results showed enhanced prefrontal recruitment with increasing task difficulty in both groups, even before movement onset. Comparing the groups on the same task, non-jugglers showed enhanced activation of prefrontal regions before and during the task execution, whereas jugglers showed enhanced activity in motor-related regions. The results provide a clear indication of practice-induced brain efficiency during the performance of complex bimanual coordinative skills.
Virtual reality environments are great tools for training as they are very cheap compared to on-site training for many tasks. While the focus has mostly been on the visual experience, we present a system that combines real world interactions with the virtual visual world to train motor skills that are applicable to the real world. Body pose tracking is combined with an Oculus Rift to create such an interactive virtual environment. As an example application, we taught users to juggle using a virtual training course. A third of the users were able to immediately transfer the newly acquired skills and juggle with real balls.
By recent development of HMD technology, it becomes possible to provide a feeling as if his own intrudes into the VE. HMD is a wearable visual equipment used by being mounted on a human head, so user can retract into VE without seeing the outside of the information by blocking the outside world information and reflecting only VE image in front of user's eye. Therefore, using HMD is possible to reproduce a roller coaster experience, freely exploration of virtual house, etc.
In this paper, a new dance training system based on the motion capture and virtual reality (VR) technologies is proposed. Our system is inspired by the traditional way to learn new movements-imitating the teacher's movements and listening to the teacher's feedback. A prototype of our proposed system is implemented, in which a student can imitate the motion demonstrated by a virtual teacher projected on the wall screen. Meanwhile, the student's motions will be captured and analyzed by the system based on which feedback is given back to them. The result of user studies showed that our system can successfully guide students to improve their skills. The subjects agreed that the system is interesting and can motivate them to learn.
The search for the neural substrates mediating the incremental acquisition of skilled motor behaviors has been the focus of a large body of animal and human studies in the past decade. Much less is known, however, with regard to the dynamic neural changes that occur in the motor system during the different phases of learning. In this paper, we review recent findings, mainly from our own work using fMRI, which suggest that: (i) the learning of sequential finger movements produces a slowly evolving reorganization within primary motor cortex (M1) over the course of weeks and (ii) this change in M1 follows more dynamic, rapid changes in the cerebellum, striatum, and other motor-related cortical areas over the course of days. We also briefly review neurophysiological and psychophysical evidence for the consolidation of motor skills, and we propose a working hypothesis of its underlying neural substrate in motor sequence learning.
The acquisition of a new motor skill is characterized first by a short-term, fast learning stage in which performance improves rapidly, and subsequently by a long-term, slower learning stage in which additional performance gains are incremental. Previous functional imaging studies have suggested that distinct brain networks mediate these two stages of learning, but direct comparisons using the same task have not been performed. Here we used a task in which subjects learn to track a continuous 8-s sequence demanding variable isometric force development between the fingers and thumb of the dominant, right hand. Learning-associated changes in brain activation were characterized using functional MRI (fMRI) during short-term learning of a novel sequence, during short-term learning after prior, brief exposure to the sequence, and over long-term (3 wk) training in the task. Short-term learning was associated with decreases in activity in the dorsolateral prefrontal, anterior cingulate, posterior parietal, primary motor, and cerebellar cortex, and with increased activation in the right cerebellar dentate nucleus, the left putamen, and left thalamus. Prefrontal, parietal, and cerebellar cortical changes were not apparent with short-term learning after prior exposure to the sequence. With long-term learning, increases in activity were found in the left primary somatosensory and motor cortex and in the right putamen. Our observations extend previous work suggesting that distinguishable networks are recruited during the different phases of motor learning. While short-term motor skill learning seems associated primarily with activation in a cortical network specific for the learned movements, long-term learning involves increased activation of a bihemispheric cortical-subcortical network in a pattern suggesting "plastic" development of new representations for both motor output and somatosensory afferent information.
What can vr systems tell sports players? reaction-based analysis of baseball batters in virtual and real worlds
- M Isogawa
- D Mikami
- T Fukuda
- N Saijo
- K Takahashi
- H Kimata