Figure 5 - uploaded by Giuseppina Schiavone
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Log of power spectral density for intermediate juggler, averaged across trials, for different electrode locations, task conditions, and frequency bands in the first experimental protocol.
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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 fro...
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... statistical analysis was performed in R. The sta- tistical analysis performed for this work should be con- sidered as indicative not assertive given that only two subjects participated in the study. Figure 4 shows the modulation in power across task con- dition and frequency. The three-way within-subject repeated-measure ANOVA showed significant main effects of frequency (F(4,4) = 33.58, p = .002), condition (F(4,4) = 6.572, p = .047), and channel (F(3,3) = 12.76, p = .032), as well as an interaction between frequency and condition (F(16,16) = 4.84, p = .0015). We proceeded by investigating Tukey's test two-factor ANOVAs, with factor task condition (Rest/Imagery/ Juggle/ImageryHands/NoBalls) and frequency (theta/ alpha/beta/low gamma/high gamma), for each subject, and considered results of the comparison between Juggle condition and other conditions, Rest and Imagery conditions, and ImageryHands and NoBalls conditions. Qualitative assessment on effects at each electrode sites is also reported ( Figure 5 depicts observation at the electrodes level for the intermediate ...
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... Eleven studies involving 400 participants were included in the study (200 men; 170 women; 30 not specified). Of these 11 studies, eight included participants who had no prior juggling experience [20,21,23,24,26,27,29,30]. Four articles included participants who had experience in juggling [21,22,25,28]. The characteristics and evaluations of the study group are shown in Table 1. ...
... The studies were published between 2004 and 2017. Seven of them were conducted in Germany [20,[22][23][24][25]29,30], two in the United Kingdom [26,27], one in the Netherlands [28], and one in Italy [21]. Seven of the included studies implemented a long-term intervention [20,23,24,26,27,29,30]. ...
... Seven of the included studies implemented a long-term intervention [20,23,24,26,27,29,30]. Three articles described a short intervention that could be implemented within 1 day [20,28,30]. In one study, the evaluation was conducted without an intervention with a specific cohort [25]. ...
This systematic review formulated a research question based on the PICO method in accordance with the Guidelines for Systematic Reviews and Meta-Analyses (PRISMA), "What is the effect of juggling as dual-task activity on neuroplasticity in the human brain?" In total, 1982 studies were analysed, 11 of which met the inclusion criteria and were included in the review. These studies included 400 participants who had no prior juggling experience or were expert jugglers. The research methodology in seven studies was based on a long-term intervention with juggling. Three studies were based on brain imaging during the act of juggling, and one study was based on comparing differences between experienced jugglers and non-jugglers without the intervention. In all of these selected studies, positive structural changes in the human brain were found, including changes mainly in the gray matter (GM) volume in the visual motion complex area (hMT/V5) and the white matter (WM) volume in fractional anisotropy (FA). Based on this evidence, it can be concluded that the bimanual juggling task, as a dual-task activity, may effectively integrate brain areas to improve neuroplasticity. The small number of well-designed studies and the high risk of bias call for further research using a juggling intervention to identify conclusive evidence.
... As the individual becomes more skilled, mental load decreases, even though precision increases. This effect can be observed when comparing EEG signals of beginners and experts Schiavone et al. (2015). It would seem the practitioner moves from more predictive based control to reaction. ...
We present here a model-free method for learning actions that lead to an all-source-all-destination shortest path solution. We motivate our approach in the context of biological learning for reactive control. Our method involves an agent exploring an unknown world with the objective of learning how to get from any starting state to any goal state in shortest time without having to run a path planning algorithm for each new goal selection. Using concepts of Lyapunov functions and Bellman's principle of optimality, our agent learns universal state-goal distances and best actions that solve this problem.
... Advances in neuroimaging, which permit the acquisition of brain data in ecological settings during active movement (Thompson et al., 2008), have allowed opportunities to study these processes at the neurophysiological level. As a consequence, juggling has been used to investigate skill acquisition, motor learning, and expert performance by examining movement related cortical potentials and functional and structural brain connectivity (Gerber et al., 2014;Schiavone et al., 2015;Berchicci et al., 2017). ...
... We identified unique patterns of inter-brain connectivity as well as several differences between the intra-brain functional networks of the two jugglers as task demands increased, suggesting that skill-level (e.g., expert vs. novice) may influence hyperbrain dynamics. Previous evidence supports differences in functional brain connectivity between expert and non-expert jugglers during individual juggling tasks (Schiavone et al., 2015), and some hyperscanning studies have examined hyperbrain connectivity between two experts (e.g., Sänger et al., 2012;Toppi et al., 2016). However, to date the effects of skill-level on hyperbrain dynamics during interpersonal tasks have not been systematically explored. ...
... In the current study, we limited our functional connectivity analysis to the alpha frequency band because it has been shown to be an important marker of human social coordinated behavior (Tognoli et al., 2007) and because our previous research identified differences in hyperbrain functional connectivity between expert and non-expert jugglers at alpha band frequencies (Filho et al., 2017). Nevertheless, additional differences in functional connectivity are likely to occur at other frequency bands (Schiavone et al., 2015). Examining functional connectivity in other bands and directly comparing functional networks across bands could yield further insights into differences between individual and interactive juggling. ...
Hyperscanning studies, wherein brain activity is recorded from multiple participants simultaneously, offer an opportunity to investigate interpersonal dynamics during interactive tasks at the neurophysiological level. In this study, we employed a dyadic juggling paradigm and electroencephalography (EEG) hyperscanning to evaluate functional connectivity between EEG sources within and between jugglers’ brains during individual and interactive juggling. We applied graph theoretical measures to identify significant differences in functional connectivity between the individual and interactive juggling conditions. Connectivity was measured in multiple juggler pairs with various skill levels where dyads were either skill-level matched or skill-level unmatched. We observed that global efficiency was reduced during paired juggling for less skilled jugglers and increased for more skilled jugglers. When jugglers were skill-level matched, additional reductions were found in the mean clustering coefficient and small-world topology during interactive juggling. A significant difference in hemispheric brain lateralization was detected between skill-level matched and skill-level unmatched jugglers during interactive juggling: matched jugglers had an increased right hemisphere lateralization while unmatched jugglers had an increased left hemisphere lateralization. These results reveal multiple differences in functional brain networks during individual and interactive juggling and suggest that similarities and disparities in individual skills can impact inter-brain dynamics in the performance and learning of motor tasks.
... These conditions are defined during the preparation stage according to known characteristics of the query tool and the practice. The research with jugglers by Schiavone et al. [19] suggest a way to differentiate between expert and non-expert jugglers according to the spectral power in certain frequency bands. In this case, a practitioner-researcher might be notified when the spectral power profile changed from non-expert to expert. ...
... The last project we review involves research on a particular artistic practice rather than research through artistic practice. The aim of the authors was to monitor the brain activity of a juggler while performing, with the long term goal of creating real-time visualizations of that activity [19]. Two subjects, one intermediate and one expert juggler, participated in the study. ...
Practice as research (PaR) is concerned with practice both as a method for inquiry and as evidence of the research process, producing embodied knowledge. It has been proposed that it is the foundational strategy in performative research, a kind of research apart from quantitative and qualitative research, characterized by being expressed using forms of symbolic data different from quantities or words in discursive texts. In this context, practice requires constant reflection upon itself to yield insights that can be used in a never-ending loop of creation. As practice is performed by the body and produces embodied knowledge, tools that allow querying the body during the artistic process may provide information that supports this creation/reflection loop. Previous artistic BCI applications have shown that they are suited to work as introspection tools (affective states, correlation between performed actions and area activations), as the source of raw material to be used in the creative process (raw signal, patterns of activation, band power), and as controllers for artistic instruments. We believe that previous research has laid the groundwork for the use of BCIs as tools in PaR. In this paper, we propose a framework for this and review three examples of previous artistic work using BCIs that illustrate different aspects of said framework.
... Two recent studies analyzed EEG frequency bands from a couple of individuals performing a dyadic juggling task [16,17], and observed that task difficulty and jugglers' personal skills may influence the features of the "hyperbrain" network. Another recent study by Schiavone and colleagues [18] explored the electrical brain activity in expert and intermediate jugglers. Their results showed a significant difference in the brain activity between the two levels of experience in the EEG frequency bands. ...
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.
... Presentations described providing ALS patients with painting tools for home use [115], an initiative to organize a design competition, and a neuro-catwalk fashion show displaying designs of attractive and artistically satisfying BCI headsets. Research was presented on what goes on in the brain of a juggler and whether that information can be visualized or sonified to make a performance even more attractive [116]. What goes on in the brains of readers of fiction? ...
The Sixth International Brain–Computer Interface (BCI) Meeting was held 30 May–3 June 2016 at the Asilomar Conference Grounds, Pacific Grove, California, USA. The conference included 28 workshops covering topics in BCI and brain–machine interface research. Topics included BCI for specific populations or applications, advancing BCI research through use of specific signals or technological advances, and translational and commercial issues to bring both implanted and non-invasive BCIs to market. BCI research is growing and expanding in the breadth of its applications, the depth of knowledge it can produce, and the practical benefit it can provide both for those with physical impairments and the general public. Here we provide summaries of each workshop, illustrating the breadth and depth of BCI research and highlighting important issues and calls for action to support future research and development.
... Two recent studies analyzed EEG frequency bands from a couple of individuals performing a dyadic juggling task [16,17], and observed that task difficulty and jugglers' personal skills may influence the features of the "hyperbrain" network. Another recent study by Schiavone and colleagues [18] explored the electrical brain activity in expert and intermediate jugglers. Their results showed a significant difference in the brain activity between the two levels of experience in the EEG frequency bands. ...
