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Citation: Malik, J.; Stemplewski, R.;
Maciaszek, J. The Effect of Juggling
as Dual-Task Activity on Human
Neuroplasticity: A Systematic
Review. Int. J. Environ. Res. Public
Health 2022,19, 7102. https://
doi.org/10.3390/ijerph19127102
Academic Editor: Paul B. Tchounwou
Received: 9 May 2022
Accepted: 8 June 2022
Published: 9 June 2022
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International Journal of
Environmental Research
and Public Health
Systematic Review
The Effect of Juggling as Dual-Task Activity on Human
Neuroplasticity: A Systematic Review
Jakub Malik 1, * , Rafał Stemplewski 2and Janusz Maciaszek 1
1Department of Physical Activity and Health Promotion Science, Poznan University of Physical Education,
Królowej Jadwigi 27/39, 61-871 Poznan, Poland; jmaciaszek@awf.poznan.pl
2Department of Digital Technologies in Physical Activity, Poznan University of Physical Education,
Królowej Jadwigi 27/39, 61-871 Poznan, Poland; stemplewski@awf.poznan.pl
*Correspondence: malik@awf.poznan.pl; Tel.: +48-739-975-701
Abstract:
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.
Keywords: bimanual task; human brain; neural plasticity
1. Introduction
Research interest in dual-task training continues. It is defined as the ability to perform
two or more cognitive and motor activities simultaneously. The ability to divide the
attention at the same time between two or more tasks is an important aspect of functional
movement during daily activities [
1
]. During these activities, people not only stabilize their
body posture at all times but also simultaneously undertake the continuous performance
of other cognitive activities or motor tasks. A dual-task training protocol usually consists
of a primary motor task (e.g., walking or balancing) and a secondary task that requires
attention (e.g., a motor or cognitive task) [
2
]. It may cause great concern in situations of
fatigue after exercise where postural control is decreased, especially in seniors with a lower
level of habitual physical activity [3].
Daily activities do not require deliberating on the complexity of the movements the
body performs. The usage of both hands to manipulate an object or to perform a specific
task is common. However, most people have a dominant hand that is more efficient at
making precise movements, development of which begins in childhood and continues
almost throughout the entire life. Many of the tools that are used in everyday life are
designed for right-handed people. Thus, the non-dominant side of the body is often
neglected [4,5].
Juggling, as a sensorimotor task requiring complex visuomotor control and interac-
tion between both limbs, may enhance the bilateral transfer learning effect that has been
observed for the upper and lower limbs from non-dominant limb training [
6
–
8
]. This
Int. J. Environ. Res. Public Health 2022,19, 7102. https://doi.org/10.3390/ijerph19127102 https://www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2022,19, 7102 2 of 13
effect shows that the efficiency of one side of the body can be increased by developing
the other side of the body [
9
]. Moreover, classical juggling, as an activity involving si-
multaneously throwing and catching balls in a specific motor pattern with both hands
and paying attention to the trajectory of each ball without hesitation, can be considered
a dual-task motor activity. It has been shown that individuals who juggle professionally
achieve lower swing amplitude during stabilometric measurements when simultaneously
performing a three-ball cascade. More experienced jugglers not only perform the task more
accurately but also become more automatic. As a result, the cognitive resources of attention
of professional jugglers are not as exploited by juggling as in the case of beginner jugglers,
whose swing amplitude during juggling is higher [10].
The currently available
in vivo
imaging techniques of human brain structures have
revealed selective activity-dependent changes in the adult brain structure [
11
]. This obser-
vation is strongly supported by the current evidence, confirming that physical exercise has
beneficial effects on neuroplasticity and can also improve human cognition [
11
–
14
]. More
importantly, learning new motor skills brings about changes in regional brain morphology.
For example, one study found an increase in the volume of the parahippocampal region, as
well as the GM in the left precentral cortex after an 18-month dance intervention in older
adults [
15
]. Next, Kattenstroth et al. [
16
] showed that moderate sessions of physical activity
that are not sufficient to affect cardiorespiratory fitness but are sufficiently cognitively
challenging can have beneficial effects on cognition, posture, balance, and sensorimotor
performance. According to these findings, it might be concluded that participation in an
activity that requires continuous cognitive and motor learning provides greater neuro-
plasticity benefits than repetitive physical exercise [
15
]. Furthermore, it is claimed that
learning bilateral motor tasks may result in greater engagement of the cerebral hemispheres,
depending on the stage of learning [17].
Learning to juggle as a new movement task can be an interesting form of bilateral
activity which, due to its complexity, may have a positive influence on neuroplasticity in
people of all ages. What is important, in order to practice juggling, there is no need for
specific and expensive equipment or spacious surroundings. The very act of juggling seems
to be a safe activity for people of all at every stage of life [18].
Therefore, the purpose of this review was to determine how classical juggling, as a
dual-task activity, affects neuroplasticity in the human brain.
2. Methods
2.1. Search Strategies
The review was conducted according to PRISMA (Preferred Reporting Items for Sys-
tematic Reviews and Meta-analysis) guidelines and followed the recommendations of the
international PRESS (Peer Review of Electronic Search Strategies) guidelines. The 27-item
PRISMA 2020 checklist was used in the development of the systematic review. The system-
atic review protocol was registered with PROSPERO (International Prospective Register of
Systematic Reviews) under the number CRD42021272053. Sources were searched for elec-
tronically in four literature databases (PubMed, Web of Science, EBSCOhost, and Scopus).
The last search for sources was performed in December 2021. The search was based on the
following index terms: ((‘juggl* [all fields]) AND (‘neuro*’ [all fields] OR ‘plasticity’ [all
fields] OR ‘brain’ [all fields])), where ‘*’ indicates any other ending of the assigned word.
The search was also supplemented with an Internet search (Google Scholar), as well as
forward and backward citation tracking from systematic reviews and the included studies.
2.2. Inclusion and Exclusion Criteria
Original articles written in English were included in the article search, without re-
striction as to the date of publication. All studies conducted on older adults, adults or
children, men or women, healthy or not, physically active or not, and who were subjected
to a juggling intervention with neuroplasticity effects were included. Exclusion criteria
Int. J. Environ. Res. Public Health 2022,19, 7102 3 of 13
included studies conducted on animals, and studies conducted with non-classical juggling
(leg juggling, contact juggling, and partner juggling were excluded).
2.3. Data Extraction
One researcher was responsible for data extraction and evaluation. The data extraction
was checked independently by two other authors. In the first step, a list of all studies was
extracted; in the next step, all duplicates were removed; in the third step, a selection of the
titles and abstracts that were identified as potentially eligible studies was made; in the final
step, the full texts of the articles were evaluated for eligibility. Each selected publication
was subjected to critical analysis.
2.4. Quality Assessment of the Experiments
The risk of bias was independently assessed by two researchers using the latest version
of the Cochrane Collaboration Risk-of-Bias tool (RoB 2.0 data) [
19
] for randomised trials.
The tool includes algorithms that give a proposed risk-of-bias score for each domain at
three levels: low, some concern, and high. All studies were assessed in five domains: bias
due to the randomisation process, bias due to deviations from the intended intervention,
bias due to missing outcome data, bias in outcome measurements, and bias in selection of
the reported outcome. The main area with the highest risk of bias was the randomisation
process. Six of the included studies had a high risk of error in this domain, one had some
risk, and five had a low risk. As a result, six studies were rated as having a high risk of
error, four as having an unclear risk of error, and one as being low-risk. The details are
shown in Figures 1and 2.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 3 of 14
children, men or women, healthy or not, physically active or not, and who were subjected
to a juggling intervention with neuroplasticity effects were included. Exclusion criteria
included studies conducted on animals, and studies conducted with non-classical juggl-
ing (leg juggling, contact juggling, and partner juggling were excluded).
2.3. Data Extraction
One researcher was responsible for data extraction and evaluation. The data extrac-
tion was checked independently by two other authors. In the first step, a list of all studies
was extracted; in the next step, all duplicates were removed; in the third step, a selection
of the titles and abstracts that were identified as potentially eligible studies was made; in
the final step, the full texts of the articles were evaluated for eligibility. Each selected pub-
lication was subjected to critical analysis.
2.4. Quality Assessment of the Experiments
The risk of bias was independently assessed by two researchers using the latest ver-
sion of the Cochrane Collaboration Risk-of-Bias tool (RoB 2.0 data) [19] for randomised
trials. The tool includes algorithms that give a proposed risk-of-bias score for each domain
at three levels: low, some concern, and high. All studies were assessed in five domains:
bias due to the randomisation process, bias due to deviations from the intended interven-
tion, bias due to missing outcome data, bias in outcome measurements, and bias in selec-
tion of the reported outcome. The main area with the highest risk of bias was the random-
isation process. Six of the included studies had a high risk of error in this domain, one had
some risk, and five had a low risk. As a result, six studies were rated as having a high risk
of error, four as having an unclear risk of error, and one as being low-risk. The details are
shown in Figures 1 and 2.
Figure 1. Risk of bias of all included studies [20–30].
Figure 1. Risk of bias of all included studies [20–30].
Int. J. Environ. Res. Public Health 2022,19, 7102 4 of 13
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 4 of 14
Figure 2. Risk of bias summary: reviewing authors’ judgements about each risk of bias item for each
included study.
3. Results
3.1. Main Search
In the electronic search, 2368 potential studies in the databases were identified (Pub-
Med: n = 54, EBSCOhost: n = 148, Web of Science: n = 82; Scopus: n = 2084). One additional
article was identified from other sources (Google Scholar). After removing 387 duplicates,
1982 records were evaluated by checking the titles and abstracts against the inclusion cri-
teria, and 1853 studies that clearly did not address juggling and neuroplasticity were ex-
cluded. In total, 129 articles were subjected to full-text review. Of these studies, 118 were
unrelated to the topic. Some did not include a classical juggling intervention (n = 37); oth-
ers did not include results on neuroplasticity (n = 16), were non-human studies (n = 4),
were not available (n = 3), or were reviews (n = 1). The remaining excluded articles were
found to be unrelated to the topic according to any of the above requirements (n = 57).
Ultimately, only 11 studies were included in the final analysis. The study selection process
is shown in Figure 3.
Figure 2.
Risk of bias summary: reviewing authors’ judgements about each risk of bias item for each
included study.
3. Results
3.1. Main Search
In the electronic search, 2368 potential studies in the databases were identified (PubMed:
n= 54, EBSCOhost: n= 148, Web of Science: n= 82; Scopus: n= 2084). One additional
article was identified from other sources (Google Scholar). After removing 387 duplicates,
1982 records were evaluated by checking the titles and abstracts against the inclusion
criteria, and 1853 studies that clearly did not address juggling and neuroplasticity were
excluded. In total, 129 articles were subjected to full-text review. Of these studies, 118 were
unrelated to the topic. Some did not include a classical juggling intervention (n= 37); others
did not include results on neuroplasticity (n= 16), were non-human studies (n= 4), were
not available (n= 3), or were reviews (n= 1). The remaining excluded articles were found
to be unrelated to the topic according to any of the above requirements (n= 57). Ultimately,
only 11 studies were included in the final analysis. The study selection process is shown in
Figure 3.
Int. J. Environ. Res. Public Health 2022, 19, x FOR PEER REVIEW 5 of 14
Figure 3. Study selection process.
3.2. Study Characteristics
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 [20,22–25,29,30], two in the United Kingdom [26,27],
one in the Netherlands [28], and one in Italy [21]. Seven of the included studies imple-
mented a long-term intervention [20,23,24,26,27,29,30]. Three articles described a short in-
tervention 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]. Changes in neuroplas-
ticity were evaluated by use of magnetic resonance imaging (MRI), electroencephalog-
raphy (EEG), voxel-based morphometry (VBM), or functional near-infrared spectroscopy
(fNIR). Others also used surface electromyography (sEMG), kinematic data, and other as-
sessments that are not directly described as neurological variables. Six of the included
studies were randomised controlled trials (RCTs) [21,23,26,27,29,30]. Table 2 provides a
summary of the study design, procedure, intervention period and frequency, measure-
ment time points, and outcomes. The measurements in each article did not follow the
same protocol. For example, EEG studies used a sampling rate of 250 Hz [21] or 256 Hz
[28]; also, the MRI data were mainly performed with a 3T MRI system [20,23,26,27,29]
using the MPRAGE sequence (TR = 20.40 ms; TE = 4.7 ms; flip angle = 8°; voxel size = 1 ×
1 × 1 mm3 [26,27]; or TR = 11.08 ms; TE = 4.0 ms; flip angle = 15°; voxel size = 0.97 × 0.97 ×
1.09 mm [25]) or the 3D-FLASH sequence (TR = 15.00 ms; TE = 4.9 ms; flip angle = 25°; 1
Figure 3. Study selection process.
Int. J. Environ. Res. Public Health 2022,19, 7102 5 of 13
3.2. Study Characteristics
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
–
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
]. Three articles described a short interven-
tion 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
]. Changes in neuroplasticity
were evaluated by use of magnetic resonance imaging (MRI), electroencephalography
(EEG), voxel-based morphometry (VBM), or functional near-infrared spectroscopy (fNIR).
Others also used surface electromyography (sEMG), kinematic data, and other assessments
that are not directly described as neurological variables. Six of the included studies were
randomised controlled trials (RCTs) [
21
,
23
,
26
,
27
,
29
,
30
]. Table 2provides a summary of the
study design, procedure, intervention period and frequency, measurement time points,
and outcomes. The measurements in each article did not follow the same protocol. For
example, EEG studies used a sampling rate of 250 Hz [
21
] or 256 Hz [
28
]; also, the MRI
data were mainly performed with a 3T MRI system [
20
,
23
,
26
,
27
,
29
] using the MPRAGE
sequence (TR = 20.40 ms; TE = 4.7 ms; flip angle = 8
◦
; voxel size = 1
×
1
×
1 mm
3
[
26
,
27
];
or TR = 11.08 ms; TE = 4.0 ms; flip angle = 15
◦
; voxel size = 0.97
×
0.97
×
1.09 mm [
25
]) or
the 3D-FLASH sequence (TR = 15.00 ms; TE = 4.9 ms; flip angle = 25
◦
; 1 mm slices [
20
,
24
]).
VMB studies also focused on different brain regions, which did not allow for a reliable
comparison among the obtained results.
Table 1. Summary of participants and assessments.
Study Country
Participants
Summary of the
Intervention
Procedure
Assessment
nGroups Description Male Female
Age
(Mean ±
SD)
Inclusion and
Exclusion Criteria
Boyke et al.
2008 [20]Germany 93
Intervention
n= 25;
control
n= 25; *
Healthy
adults 39 54 60.0
Healthy, without
dementia,
Parkinson’s disease,
diabetes,
hypertension. None
of them
could juggle.
Three-month
period of juggling
training and, after
that, a
three-month
period without
juggling.
MRI, VBM
Berchicci
et al. 2017
[21]Italy 28
Expert
jugglers (E)
n= 14; non-
jugglers
(N) n= 14;
Healthy
young
adults
23 5
E:
32.0 ±5.9
N:
30.0 ±5.2
E: able to juggle five
or more balls with
10 years of
experience.
N: No prior
experience in
juggling.
With normal or
corrected-to-normal
vision; without
musculoskeletal
injury; no reported
history of
psychiatric or
neurological disease.
Two conditions:
N: 1-ball fountain,
2-ball shower
E: 2-ball shower,
3-ball shower
20 runs with
15 cycles of
throws (150 trials
for each task).
Kinematic
data, EEG,
sEMG
Carius et al.
2016 [22]Germany 15 No groups
Healthy
expert
jugglers
15 0 26.3 ±5.2
Without
neurological and
psychological
diseases.
Assessment of
expert skills: 5-ball
cascade for at least
20 s in eight
consecutive trials.
6 trials in different
conditions (2 balls
in left hand,
2 balls in right
hand, 3 balls
bimanually,
5 balls bimanually,
control for 1 Hz,
control for 2 Hz)
were performed 8
times for 20 s with
a 60 s period
of rest.
fNIRS,
quantita-
tive rating
of juggling
expertise
Int. J. Environ. Res. Public Health 2022,19, 7102 6 of 13
Table 1. Cont.
Study Country
Participants
Summary of the
Intervention
Procedure
Assessment
nGroups Description Male Female
Age
(Mean ±
SD)
Inclusion and
Exclusion Criteria
Draganski
et al. 2004
[23]
Germany 24
Jugglers
n= 12;
Non-
jugglers
n= 12;
Young
adults 3 21 22.0 ±1.6 No prior experience
in juggling.
Three-month
period of juggling
and, after that, a
three months
period without
juggling.
VBM
Driemeyer
et al. 2008
[24]
Germany 20 No groups
Healthy
young
adults
9 11 26.5
No prior experience
in juggling, none
suffered from
any diseases.
6 weeks of
a juggling
intervention and,
after that, a
6-week period
without juggling.
MRI
Gerber
et al. 2014
[25]Germany 32
5-ball-
jugglers
(5BJ) n= 16;
controls (C)
n= 16;
Healthy
young
adults
28 4
5BJ:
26.9
C:
27.2
Healthy without any
psychiatric or
neurological
diseases.
None MRI, VBM
Sampaio-
Baptista
et al. 2014
[26]
United
Kingdom 44
High
intensity
(HI) n= 22;
low
intensity
(LI) n= 18;
Young
adults 22 22
HI:
23.9 ±3.6
LI:
23.8 ±3.3
Right-handed with
no prior experience
in juggling.
HI: 30 min of
training per day
for 29 days.
LI: 15 min of
training per day
for 29 days.
After that,
4 weeks
without juggling.
Behavior,
MRI, DTI
Sampaio-
Baptista
et al. 2015
[27]
United
Kingdom 64
High
intensity
(HI) n= 22;
low
intensity
(LI) n= 18;
Controls
n= 20;
Young
adults 33 31 23.8 ±3.5
Right-handed with
no prior experience
in juggling
5 days a week of
juggling for
6 weeks. After
that, a 4-week
period without
juggling.
HI: 30 min of
training per day.
LI: 15 min of
training per day.
Behavior,
MRI
Schiavone
et al. 2015
[28]Netherlands 2
Intermediate
jugglers (I)
and expert
jugglers (E)
Intermediate
and expert-
level
jugglers
2 0 40 (I) and
22 (E)
I: able to juggle three
balls comfortably for
more than 60 s.
E: able to juggle five
or more balls.
First protocol for I
and E:
Five conditions
(“rest”, “imagery”,
“juggle”, “imagery
hands”, “no
balls”)
Second protocol
for E:
Three conditions
(3 balls, 5 balls, 7
balls) repeated
three times.
EEG
Scholz et al.
2009 [29]Germany 48
Intervention
n= 24;
controls
n= 24;
Healthy
adults 26 22 25.02 ±
3.34
Healthy with no
prior experience in
juggling.
Six-week training
period; four-week
period without
juggling
VBM, MRI
Schultz
et al. 2012
[30]Germany 30
Intervention
n= 15;
controls
n= 15;
Healthy
adults NI NI 24.3 ±3.8
Healthy with no
prior experience in
juggling.
Two months of
juggling until
participants were
able to juggle a
cascade for a
minimum of 45 s
MRI
MRI: magnetic resonance imagining, fMRI: functional magnetic resonance imagining; fNIRS: functional near-
infrared spectroscopy; DTI: diffusion tensor imagining; VBM: voxel-based morphometry; EEG: electroencephalog-
raphy; sEMG: surface electromyography; NI: no information; *: others were excluded.
Int. J. Environ. Res. Public Health 2022,19, 7102 7 of 13
Table 2. Summary of study design, period, time points of measurement and outcomes.
Study Study
Design Period and/or Frequency Time Points of
Measurement Main Outcomes
Boyke et al.
2008 [20]FUS 3 months of training Scan 1—baseline,
Scan 2—3 months,
Scan 3—6 months
Compared with the first time point (Scan 1), there was an increase in
hMT/V5 on the right side during skill performance (Scan 2). This
pattern reversed at the third time point (Scan 3). GM volume in the
left frontal cortex, cingulate cortex, left hippocampus, and precentral
cingulate cortex on the right increased during exercise. After the
exercises were discontinued, the change subsided. Transient increases
in the GM in hMT/V5, in the hippocampus on the right side, and
bilaterally in the nucleus accumbens occurred only in the exercise
group. In Scan 3, the effect was reversed.
Berchicci et al.
2017 [21]RCT
1 session
2 conditions
10 s rest between
conditions
During the intervention
The results showed large MRCP, starting before the action of juggling
and lasting for the whole duration of the act. The tasks’ difficulty was
related to large pN during preparation and execution of the juggling
task in both groups. In the more experienced group, the results
showed smaller prefrontal and larger frontal activity, mainly during
juggling. Juggling practice may induce prefrontal neural plasticity,
perhaps because juggling requires important level of coordination,
focused attention, and balance during execution.
Carius et al.
2016 [22]CSS
1 session
6 trials
8×20 s
60 s rest between trials
During the intervention
Execution of a complex task such as juggling is related to
neurovascular changes in MT/V5 and also to changes in
sensorimotor areas (M1, S1, PMC). The complexity of the task seems
to modulate the abovementioned brain regions. The 5-ball cascade
showed enhanced hemodynamic responses for oxy-Hb when
compared with less complex tasks.
Draganski et al.
2004 [23]RCT 3 months of training Scan 1—baseline,
Scan 2—3 months,
Scan 3—6 months
Compared with the first time point (Scan 1), the second time point
(Scan 2) showed a bilateral increase in GM volume in the hMT/V5
and in the left posterior medial sulcus. This change decreased at the
third time point (Scan 3). These changes occurred only in the
training group.
Driemeyer et al.
2008 [24]FUS 6 weeks of training
Scan 1—Baseline,
Scan 2—7 days,
Scan 3—14 days,
Scan 4—35 days,
Scan 5—2 months
after training,
Scan 6—4 months
after training
Compared with the first time point (Scan 1), subsequent time points
at which skills were examined (Scans 2–4) showed a bilateral increase
in hMT/V5 area, as well as a change in the GM in the frontal lobes,
temporal lobes, and the cortex of the cingulate gyrus. This pattern
reversed during subsequent time points (Scans 4 and 5).
Gerber et al.
2014 [25]V-BMS - Once/no intervention
Jugglers displayed regional GM density in the occipital and parietal
lobes including the secondary visual cortex, the hMT+/V5 area
bilaterally and the intraparietal sulcus bilaterally. In jugglers, the
results showed a correlation between performance and GM density in
the right hMT+/V5 area.
Sampaio-
Baptista et al.
2014 [26]
RCT
29 days of training every
day (low intensity:
15 min; high intensity:
30 min)
Scan 1—baseline,
Scan 2—after training,
Scan 3—4 weeks
after training
Regions of the brain which had been identified as those where an
increase in volume had been observed after juggling training [26]
were correlated with the subsequent learning rate in a complex
visuo-motor task. In these regions, a significant increase in GM
volume after learning was observed in these groups of participants.
The results showed that performance outcomes can have an
important role in modulating positive structural changes in GM
volume over certain time points.
Sampaio-
Baptista et al.
2015 [27]
RCT
6 weeks of training,
5 sessions per week (low
intensity: 15 min; high
intensity: 30 min)
Scan 1—baseline,
Scan 2—after training,
Scan 3—4 weeks
after training
In the low intensity group, the results showed increases in motor
network connectivity and decreases in GABA. Scan 3 showed that the
increased motor RSN strength was still present. This may suggest
that changes in functional connectivity do not require ongoing
practice to be maintained. In the high intensity training group, the
results showed decreases in connectivity within the motor RSN, and
no significant change in GABA. It was shown that lower intensity of
practice might rely mostly on previously established functional
connections. An increase in the strength of functional connectivity
was observed. A higher intensity of practice might cause the
formation of new connections and an increase in of circuit efficiency.
The phenomenon of decreased functional connectivity was observed.
Schiavone et al.
2015 [28]CR 1 session, 2 conditions During the intervention
Higher power of oscillation across the scalp during juggling was
observed in the case of expert jugglers. A higher alpha coherence
during execution may be associated with hemispheric
synchronization in the control and coordination of bimanual tasks.
The dominance of the right hemisphere in this case possibly reflects a
stronger visuomotor adaptation and a more efficient bimanual motor
routine due to extensive practice. Intermediate jugglers were
characterized by higher power in the theta and high gamma
frequency bands and higher interhemispheric gamma coherence.
Scholz et al.
2009 [29]RCT 6 weeks Scan 1—baseline,
Scan 2—6 weeks,
Scan 3—10 weeks
A significant increase in FA was observed in the WM under the right
posterior interparietal sulcus when comparing the first time point
(Scan 1) with the second (Scan 2). This change occurred in the training
group. After juggling, a significant increase in GM density was
observed in the medial occipital and parietal lobe in cortical regions
overlying the WM area.
Int. J. Environ. Res. Public Health 2022,19, 7102 8 of 13
Table 2. Cont.
Study Study
Design Period and/or Frequency Time Points of
Measurement Main Outcomes
Schultz et al.
2012 [30]RCT
2 months
Progress was reported
daily by volunteers
Scan 1—baseline,
Scan 2—at the end of
intervention period,
Scan 3—2 month
after end
In juggle group of 225 voxels was obtained within the corpus
callosum that showed increased FA between scan 1 and scan 2. This
results were obtained just in juggle group. Also a mean of GM density
increased in both hemispheres (medial occipital and parietal lobes)
from scan 1 to scan 2. This effect was specific for experimental group.
Decrease of WM and GM volume was not observed after period
without intervention.
FA: fractional anisotropy; GM: gray matter; WM: white matter; GABA: gamma-aminobutyric acid; RSN: resting-
state network; PMC: pontine micturition center; M1: primary motor cortex; S1: primary somatosensory cortex;
MRCP: movement-related cortical potential; pN: prefrontal negativity; V5: visual cortex area; hMT or MT: middle
temporal area; RCT: randomised controlled trial; CR: case report; FUS: follow-up study; CSS: cross sectional study;
VB-MS: voxel-based morphometry study.
4. Discussion
4.1. Summary of the Main Results
The results of this systematic review showed that juggling training appears to be a
good form of activity to induce brain plasticity. All of the selected studies showed positive
structural changes or differences fostered by juggling. Some of them showed that jugglers
have more developed brain structures compared with non-jugglers. These differences were
mainly seen in the GM density of the hMT/V5 area [
25
]. Moreover, other studies proved
that this form of activity may develop the abovementioned brain areas and WM density
in the human brain [
29
,
30
]. Furthermore, brain activity during the task was different in
participants who had more experience with juggling, and these differences were observed
in groups with various training intensities or task difficulty levels. As shown in one of the
publications, the juggling task can be practiced safely at home without any presence of a
trainer or other participants [
26
]. This may be a very positive aspect of this form of activity,
especially in unfavorable conditions when group meetings are limited for some reason (for
example, a pandemic situation). However, due to the inability to conduct a meta-analysis
and the small sample sizes of the selected studies, conclusions about the effect of juggling
on neuroplasticity should be approached with caution. In future studies on this topic, care
should be taken to ensure an adequate sample size that provides a power of at least 0.8 to
provide conclusive results regarding the effect of this physical activity on the human brain.
4.2. Impact of Juggling on the Brain
There are only sparse studies reporting the effects of classical juggling on neuroplas-
ticity. The low number of studies on juggling can be explained by the inconsiderable
popularity of this activity. This form of movement is commonly associated with art, which
can affect the perception of juggling as a difficult skill to achieve. This misconception
means that the potential of this undemanding form of activity remains untapped. Devel-
opmental research on motor skills proved that juggling can be successfully learned by
children and elderly people. In this study, the performance of older people (>60 years),
children (
10–14 years
), and older adults (30–59 years) was comparable. Only adolescents
and younger adults (15–29 years) performed better than older adults. Thus, the potential
for learning a novel motor task such as juggling is still high, even in older adults [
18
].
Moreover, during the thorough literature search, one study with an efficient juggling inter-
vention in a group of children with spina bifida was found [
31
]. These promising results
allow for the implementation of juggling activity regardless of the age and health ailments
of a participant.
In the studies selected for this review, the intervention (if used) focused specifically on
juggling. Boyke et al. [
20
] undertook a study of learning juggling in older adults (mean age:
60 years). The results showed that older adults retain the ability to alter their brain structure
in response to motor learning needs. This study extends the knowledge of the structural
changes occurring in the human brain that were observed by
Draganski et al. [23]
, who
applied a three-month juggling intervention to young adults (mean age: 22 years). Despite
Int. J. Environ. Res. Public Health 2022,19, 7102 9 of 13
having the same duration of the intervention and the same instructions, the results showed
a poorer final outcome of learning to juggle in the older adult group. This was also
confirmed in the study of Voelcker-Rehage and Willimczik [
18
]. However, this difference
did not translate to nervous system plasticity, as it was comparable in both studies and
occurred in the same areas, resulting in a significant increase in GM in the hippocampus and
nucleus accumbens and hMT/V5 in individuals practicing juggling for three months [
20
,
23
].
Additionally, Berghuis et al. [
32
] also showed that the motor performance of older adults
(mean age: 63.1 years) was 53% lower during learning a motor task than that of young adults
(mean age: 25.5 years). Based on this study, it appeared that motor practice improved motor
performance similarly in both groups, while brain activation was greater in the older group.
However, a difference was observed during deactivation in specific areas of the brain,
depending on age. Young adults had greater deactivation from post-test to retention in the
parietal, occipital, and temporal cortex, while older adults showed less deactivation in the
frontal cortex. The authors concluded that this is likely due to compensatory mechanisms
in older adults that activate brain areas to a greater extent during motor tasks.
Changes in GM structure were also observed byDriemeyer et al. [
24
], Scholz et al. [
29
],
andSampaio-Baptista et al. [
26
,
27
]. They noted that changes in GM volume can occur as
early as after one week of the intervention. These results also confirmed previous reports
by Draganski et al. [
23
] and Boyke et al. [
20
] showing that the GM volume changes in the
visual and parietal areas of the cerebral cortex; however, in some of studies, these changes
occurred at later time points [
26
]. However, most published studies have shown a decrease
in GM density at a time point that was evaluated at a longer time after the cessation of the
intervention [
20
,
23
,
24
]. However, in the study by Scholz et al. [
29
], these changes persisted
up to four weeks after juggling was stopped. Furthermore, these studies did not reveal a
correlation between the final learning effect or daily training amount and structural changes.
What is more important, the initial phase of learning correlated with an increase in GM,
while refinement of previously learned skills no longer showed a tendency to change the
brain structure [
24
]. This phenomenon was also seen in animal studies, where learning was
associated with synaptogenesis and glial hypertrophy, whereas increased motor activity
was associated exclusively with angiogenesis – the process of capillary formation [33,34].
Sampaio-Baptista et al. [
26
] divided participants into a high-intensity exercise group
(30 min per day) and a low-intensity group (15 min per day), and they found that the two
groups had slightly different changes in brain structure. The group that learned a new skill
at a lower intensity was characterized by a decrease in GM volume in the premotor areas
and DLPFC, which correlated with task performance, while the high-intensity exercise
group was characterized by increased GM volume, which also correlated with performance.
In addition, the same authors, in another study, demonstrated that less intensive skill ac-
quisition may rely primarily on previously formed functional connections, increasing their
strength while increasing functional connectivity, whereas more intensive practice leads to
the formation of new connections, increasing circuit performance [
27
]. In addition, it was
noted that the GM volume at the first measurement (before learning) in the occipito-parietal
areas correlated with the learning rate, and also that individuals with higher GM volume
in the areas responsible for complex whole-body and bilateral movements maintained the
acquired skills for longer [
26
]. This is because juggling engages, among other areas, the
posterior cingulate cortex responsible for efficient shifting of the attention [
35
,
36
]. Thus, not
only was an increase in GM volume observed after an intervention of learning juggling, but
the effect of this learning also depends, to some extent, on the individual’s initial GM level.
Changes in GM are also observed with other interventions. Müller et al. [
15
] observed
an increase in GM volume in the left precentral bend in a study of seniors after six months
of dance instruction. Moreover, other authors, based on observational studies, highlighted
the positive effects of long-term dance practice on brain activity, modifying the volume
of both the WM and GM in different brain regions [
37
–
39
]. This rationale should be an
incentive to practice and learn new motor skills at every stage of life. Juggling, however, is
a specific skill focused on the trajectory of the balls, which implies changes in the areas of
Int. J. Environ. Res. Public Health 2022,19, 7102 10 of 13
the brain mainly responsible for visual motor activities, while requiring the practitioner
to constantly maintain an appropriate posture. Therefore, it should mainly improve those
used regions that are additionally responsible for the spatial relations of body movements
such as reaching or grasping [
40
] and that are more active during complex two-handed
tasks than during unilateral tasks [41].
Observations related to increased WM volume were also observed after the juggling
intervention. The results of Scholz et al. [
29
] showed that there was an increase in FA in
the group that undertook juggling compared with the control group. The increase in FA
did not correlate with performance in the juggling task, and no correlation was observed
between the level of FA prior to the start of training with the skill acquisition speed of
the participants.
Three studies included in this review were based on a brief one-day intervention.
These studies included, among others, individuals who specialized in juggling tasks. In
the study bySchiavone et al. [
28
], despite the low sample size (n= 2), it was noticed
that increasing the task’s difficulty enhances the power of neuronal oscillations in all
frequency bands, thus extending synchronous brain activity, which may be due to the
higher demands of attentional focus and motor control during increasingly difficult motor
tasks, even in experienced jugglers. On the other hand, in a second study, Berchicci
et al. [
21
] observed differences occurring in the brains of experienced jugglers and non-
jugglers during the performance of a juggling task, which supported the hypotheses of
prefrontal neural plasticity during this type of task, due to the fact that they require high
levels of coordination, balance, and attention. A study by Carius et al. [
22
] on young adults
engaged in juggling showed that juggling is associated with neurovascular changes in the
sensorimotor and visual brain areas. Moreover, they confirmed that greater task complexity
modulates these brain regions more. This may be related to the fact that activities that are
more difficult are elements that engage the exerciser more cognitively than activities that
have already been automated [22]. Additional confirmation of these changes occurring in
the brain of experienced jugglers was provided by the study of Gerber et al. [
25
], where
changes were observed to occur specifically in the visual cortex region (V2, hMT+/V5,
and IPS) related to motion perception and eye–hand coordination, as well as correlations
between GM density (mainly in the hMT+/V5 area) and performance in jugglers. Thus, the
development of human brain structures could perhaps be practiced both by motor learning
of previously unknown skills and by attempting to learn new motor activities in an already
familiar form of physical activity.
It is probable that structural changes in the brain after the juggling intervention may
also improve cognitive function among participants who practice this form of activity.
This may be supported by the studies of Jansen et al. [
42
,
43
] andLehmann et al. [
31
], who
examined the effects of juggling on the outcome of mental rotations among different groups
of individuals. The results of all these studies clearly indicated a relationship between
motor training in the form of juggling and a shorter reaction time in a mental rotation
test, which is associated with improved spatial imagination or mathematical skills. In
summary, it can be concluded that learning classical juggling has the potential to develop
brain structures.
5. Authors’ Conclusions
5.1. Limitations
The low number of studies and significant differences in the methodological proceed-
ings prevented the execution of a meta-analysis that could reliably prove the effect of
juggling on neuroplasticity. In addition, some of the articles included in the systematic
review had a high risk of bias because they were not randomised controlled clinical trials
and were therefore based primarily on observations.
Int. J. Environ. Res. Public Health 2022,19, 7102 11 of 13
5.2. Implications for Practice
The effect of physical activity on neuroplasticity is an increasingly widespread topic.
Research on this subject has focused on both cyclic endurance forms of physical activity [
44
]
as well as motor learning of novel, sensory-enriched, and often motor control-intensive
activities (such as learning to dance) [
15
,
36
,
45
]. The creation of a ball exercise program
in the form of juggling, the effects of which on neuroplasticity have been demonstrated
in this systematic review, among others, could become one of the ways in which adults
can independently attempt to improve their quality of life. Nevertheless, it is important to
notice that some of the articles showed, in the follow-up measurements, that an inactivity
period tends to reduce the previously obtained positive effects to the same level as before
the intervention [
20
,
23
,
24
]. Knowledge of whether a bimanual task in the form of juggling
affects the human brain can also contribute to broadening awareness of the impact of
various forms of physical activity on neuroplasticity. The advantages of this form of activity,
which requires only the use of the upper limbs, are that there is no need for specialized
equipment and space, the possibility of safe individual work, and the availability of this
form of exercise for people with lower limb aliments. Thus, it can be easily applied in
different population groups.
5.3. Implications for Research
Future studies with the juggling intervention should meet the criteria for randomised
controlled clinical trials. Ideally, a positive control group (where the effect of the interven-
tion results in positive changes in neuroplasticity) and a negative control group (where the
effect of the intervention does not result in changes in neuroplasticity) would be used in
comparison with the classical juggling intervention. Furthermore, future research should
take into account both the participant’s prior juggling experience and learning rate during
the intervention to control for subjective task difficulty [
26
,
29
]. The results of this systematic
review showed that EEG, MRI, fNIRS, and VBM can effectively reveal changes occurring
during juggling and after a prolonged intervention with this activity. Moreover, measure-
ments just before the intervention, immediately after the intervention, and some time after
the intervention seem to be the optimal number of measurements that can demonstrate
both the differences caused by this specific activity and the ability of the observed changes
to persist [
20
,
23
,
24
,
26
,
27
,
29
,
30
]. However, it is very important to note that the brain imaging
method should be chosen on the basis of proven protocols that allow reliable comparison
of the results obtained with existing ones, and that these are accurately described so that
replication of the studies can be performed. Studies of individuals of different ages with
a standardized methodology will allow for a robust meta-analysis in the future that may
show clearer evidence regarding the effects of juggling on neuroplasticity. It may also be
important for scientific research to not only measure structural changes in the brain but
also functional changes that affect behavior.
Author Contributions:
Conceptualization, J.M. (Jakub Malik), R.S. and J.M. (Janusz Maciaszek);
methodology, J.M. (Jakub Malik), R.S. and J.M. (Janusz Maciaszek); investigation, J.M. (Jakub Malik),
R.S. and J.M. (Janusz Maciaszek); writing—original draft preparation, J.M. (Jakub Malik); writing—
review and editing, J.M. (Jakub Malik), R.S. and J.M. (Janusz Maciaszek). All authors have read and
agreed to the published version of the manuscript.
Funding: This research received no external funding.
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable.
Data Availability Statement: Not applicable.
Acknowledgments:
We would like to thank Natalia Główka for linguistic support during the prepa-
ration of the manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
Int. J. Environ. Res. Public Health 2022,19, 7102 12 of 13
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