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Abstract

The current study tests possible transfer effects from NT 3D MOT training among elite athletes from dynamic sports on executive brain functions, such as alerting, orienting, executive control, inhibition, shifting and updating. Sixty athletes from different sports, such as martial arts (boxing and wrestling), handball, soccer, orienteering, biathlon, alpine skiing, and Paralympic sports (sled hockey, badminton and table tennis), participated in a cross-over experiment-control group design over a period of 10 weeks. The results in the current study show specific training effects on training measures used by the NT 3D MOT tool, but no significant transfer effects on the executive functioning tests. The results are discussed based on the importance of training specificity and the mental state at the moment of NT 3D MOTtraining.
SPORT PSYCHOLOGY | RESEARCH ARTICLE
The effects of perceptual-cognitive training with
Neurotracker on executive brain functions among
elite athletes
Frode Moen
1
*, Maria Hrozanova
2
and Tore Stiles
3
Abstract: The current study tests possible transfer effects from NT 3D MOT training
among elite athletes from dynamic sports on executive brain functions, such as
alerting, orienting, executive control, inhibition, shifting and updating. Sixty athletes
from different sports, such as martial arts (boxing and wrestling), handball, soccer,
orienteering, biathlon, alpine skiing, and Paralympic sports (sled hockey, badminton
and table tennis), participated in a cross-over experiment-control group design over
a period of 10 weeks. The results in the current study show specific training effects
on training measures used by the NT 3D MOT tool, but no significant transfer effects
on the executive functioning tests. The results are discussed based on the impor-
tance of training specificity and the mental state at the moment of NT 3D MOT
training.
ABOUT THE AUTHORS
The first author is a mental trainer for elite ath-
letes and coaches at the Norwegian Olympic
Sports Center in the Mid-Norway region, where
he also is the manager. He is also an associate
professor at the Department of Lifelong Learning
and Education at the Norwegian University of
Science and Technology where his research
focuses on coaching in business, coaching in
sport, communication, performance psychology,
athlete burnout, attention, motivation, educa-
tion and relationship issues.
Maria Hrozanova is a PhD candidate at the
Centre for Elite Sports Research at the
Norwegian University of Science and
Technology, NTNU, Department of
Neuromedicine and Movement Science, Faculty
of Medicine and Health Science. Maria is investi-
gating the influence of cognitive, emotional and
physical loads on sleep patterns / recovery in
elite athletes. Maria's main interests include
sleep medicine, cognitive neuroscience and psy-
chology.
Tore Charles Stiles is a professor in clinical
psychology at NTNU and University of Oslo, UiO.
Tore is also the funder of a clinical institute,
Coperio, that focuses on cognitive psychology.
Tore's main interests include cognitive psychol-
ogy, insomnia, chronic fatigue, anxiety, execu-
tive functioning and sport psychology.
PUBLIC INTEREST STATEMENT
There is a growing marked for brain training tools,
such as the Neurotracker. The main goal for such
tools is to improve cognitive capacities, such as
for example attention. Thus, a systematic training
program with brain training tools should affect
executive tests measuring executive functions of
the brain. The current study could not find any
such effects on executive brain tests.
Moen et al., Cogent Psychology (2018), 5: 1544105
https://doi.org/10.1080/23311908.2018.1544105
© 2018 The Author(s). This open access article is distributed under a Creative Commons
Attribution (CC-BY) 4.0 license.
Received: 15 August 2018
Accepted: 30 October 2018
First Published: 08 November 2018
*Corresponding author: Frode Moen,
Department of Education and
Lifelong Learning, Norwegian
University of Science and Technology
(NTNU), Trondheim, Norway
E-mail: frode.moen@ntnu.no
Reviewing editor:
Antonios K. Travlos, Sports
Organization and Management,
University of Peloponnese, Greece
Additional information is available at
the end of the article
Page 1 of 13
Subjects: Elite Sports; Elite Sport Development; Cognitive Science
Keywords: elite sport; perceptual-cognitive training; attention; executive functioning
Attentional resources are claimed to be of high importance for elite athletes in dynamic sports,
such as e.g. basketball, soccer, handball and ice hockey, because of the rapidly and constantly
changing external environment (arena) during execution of their sports (Bernier, Thienot, Codron,
& Fournier, 2009; Kaufman, Glass, & Arnkoff, 2009; Kee & Wang, 2008; Moen & Firing, 2015; Moen,
Hrozanova, & Pensgaard, 2018). In typical dynamic team sports (e.g. basketball), athletes need to
pay attention to the rapidly changing movements of teammates and opponents, and quickly
perceive the most important information, interpret that information, decide needed actions and
execute these actions to detect optimal choices for their movements and where to pass the ball
(Appelbaum & Erickson, 2016; Mangine et al., 2014). In dynamic individual sports (e.g. orienteer-
ing), it is crucial to pay attention to a rapidly changing terrain and the map while running in high
speed, and execute the necessary actions to choose the fastest path from one point on the map to
the next. These attentional resources in dynamic sports constitute the perceptual-cognitive skills
that athletes depend on to perform at their best.
Given the importance of perceptual-cognitive skills, especially in dynamic sports, it is not
surprising that training programs aimed at improving such skills have a relatively long history in
elite sports (Martin, 1984; Revien & Gabour, 1981; Seiderman & Schneider, 1983; Stine, Arterburn, &
Stern, 1982). Recently, as several studies in the field of sport psychology claim that attentional
resources are crucial for performance in elite sports (Mann, Williams, Ward, & Janelle, 2007),
research has shown that programs training the perceptual-cognitive skills have the potential to
improve athletic performance (Appelbaum & Erickson, 2016). Athletic experts were found to be
both faster and more accurate in their decision-making than lesser skilled athletes (Mann et al.,
2007). Therefore, the underlying functions in the brain that regulate athletesabilities to quickly
perceive and extract the most important information in the environment, interpret that informa-
tion to decide what actions are needed, and then execute those actions to handle the situation
optimally, are key to high level performances in dynamic sports (Mangine et al., 2014). Thus,
perceptual-cognitive tools should have the potential to affect the executive functions (EF) of the
brain. However, in general, the possible effects from perceptual-cognitive tools are claimed to lack
empirical support (Owen et al., 2010). The aim of the current study is therefore to investigate if
a perceptual-cognitive tool has the potential to affect the underlying functions in the brain that
regulate the perceptual-cognitive process.
1. Executive functions of the brain
In the rapidly changing environments of dynamic sports, it is the EF linked to the prefrontal cortex
in the brain that make the athletes capable of regulating the dynamics of perception, cognition
and action (Miyake & Friedman, 2012), while collecting the environmental information needed for
performance. Furthermore, EF make the collected information available for athletesperception
and enable the identification of actions that are most suitable in the situation (Welford, 1968).
Athletesattentional resources are therefore crucial in this perceptual-cognitive process that
makes them capable of responding effectively to a situation.
According to Miyake and Friedman (2012), there are three important EFs related to this atten-
tional regulation: updating, shifting and inhibition. Updating is the ability to constantly monitor the
environment for essential information and to rapidly add or delete contents in working memory.
Shifting is the ability to switch between different tasks or mental sets and use attention with
flexibility. Inhibition is the ability to deliberately override dominant or prepotent responses to
certain stimuli. The EFs are correlated, but they also show diversity with one another, and are all
related to the attentional processes in the brain (Miyake & Friedman, 2012; Moran, 2012). Thus, the
attentional processes involve the ability to focus on the task at hand while ignoring any irrelevant
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distractions, the ability to shift focus when it is needed and the ability to change ones mind
according to suitable actions in the dynamic sporting environment (Moran, 2012).
1.1. Attentional resources
Perception and decision-making (cognition and action) are closely related processes where atten-
tional resources are central. Accordingly, working memory is closely connected to attentional
processes, wherein attention serves as a monitor and decides what content is placed in working
memory (Fougnie, 2008; Moen, Firing, & Wells, 2016). Thus, working memory requires the monitor-
ing that is executed by attention as part of completing goal-directed actions in the setting of
interfering processes and distractions (Conway, Cowan, & Bunting, 2001; Moen et al., 2016).
Attentional processes are therefore complex cognitive systems, containing three independent,
but related network stages: orienting to sensory events, detecting signals for focal (conscious)
processing, and maintaining information in a vigilant alert state (Moen et al., 2016; Posner &
Petersen, 1990). The goal-directed actions are then executed as the result of a comparison of
information stored in working memory and relevant experience that is stored in long-term mem-
ory. In this case, experience is the amount of training on skills and actions that are necessary to
perform in sport-specific situations. Thus, attentional resources and experience operate close
together to influence performance in dynamic sports.
1.2. Research on perceptual-cognitive training programs
Research has shown that perceptual-cognitive training has the potential to influence sport-specific
tasks (Crist, Li, & Gilbert, 2001; Mangine et al., 2014; Moen et al., 2018; Romeas, Guldner, & Faubert,
2016) and that elite athletes have significantly better attentional resources than non-elite, less
skilled athletes (Ericcson, 2003; Mann et al., 2007). Elite athletes also gain better improvements
and have a higher learning rate from perceptual-cognitive training than less skilled athletes
(Faubert, 2013; Romeas & Faubert, 2015; Zhang, Yan, & Yangang, 2009). However, the underlying
idea of perceptual-cognitive training programs is that these programs are supposed to improve the
mechanisms that regulate the dynamics of human perception, cognition and action (Miyake &
Friedman, 2012). Therefore, these programs should improve the EFs related to attentional pro-
cesses. To the authorsknowledge, there is only one study showing that perceptual-cognitive
training has an effect on cognitive functions, such as attention, visual information processing
speed and working memory, in a group of University students (Parsons et al., 2016). To our
knowledge, no studies have investigated how perceptual-cognitive training tools are related to
the general underlying mechanisms that regulate the dynamics in elite athletesperception,
cognition and action, such as the EFs (Miyake & Friedman, 2012). The perceptional-cognitive tool
that is used in the current study is the Neurotracker (NT) 3-dimensional (3D) multiple object
tracking (MOT) device (Parsons et al., 2016). The NT 3D MOT is a tool for non-contextual perceptual-
cognitive training and is used among elite athletes in dynamic sports (Faubert, 2013).
1.3. The current study
The aim of this study is therefore to investigate if the NT 3D MOT training program improves the
basal executive functions in the brain.
Hypothesis 1: Perceptual-cognitive training with NT 3D MOT will improve athletesexecutive
functioning.
2. Method
2.1. Participants
Sixty elite athletes from dynamic sports were randomly selected based on the group of sport they
belonged to and invited to participate in the study. The dynamic sports included martial arts (boxing
and wrestling), handball, soccer, orienteering, biathlon, alpine skiing and Paralympic sports (sled
hockey, badminton and table tennis). Participants were randomly selected from a cohort of athletes
who were previously involved in projects with the Norwegian Olympic center in mid-Norway, currently
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competing at elite level in the abovementioned dynamic sports. Data from the current study is a part
of a bigger data set that is used in different theoretical approaches (Moen et al., 2018).
2.2. Materials
2.2.1. Executive functions tests
A web portal that required a two-factor identification key was used to administer a questionnaire
measuring demographic data, such as age, gender and type of sport, and the EF tests. The four EF
tests investigated in this study were the attention network test (ANT), the anti-saccade task (AST),
the color shape task and the letter memory task (LMT).
2.2.1.1. Attention network test. The ANT is an experimental measure of the three attention net-
works: alerting, orienting and executive control (Fan, McCandliss, Sommer, Raz, & Posner, 2002).
The alerting network is concerned with an individuals ability to achieve and maintain a state of
increased sensitivity to incoming information, the orienting network manages the ability to select
and focus on the to-be-attended stimulus, and the executive control network manages the ability
to control our own behavior to achieve intended goals and resolve conflict among alternative
responses. There are three types of target stimuli (neutral, congruent and incongruent) and four
types of cues (no, center, double, spatial) (Fan et al., 2002).
The ANT involves a cued reaction time task and a flanker task. During the cued reaction time
conditions, one of four cue types was provided: no cue, a center cue, a double cue, or a spatial cue
to alert the participant to the possible location of an array of arrows (the flanker condition) that
would subsequently appear on the screen. Next, an array of stimuli was presented consisting of
a central stimulus (an arrow pointing either left or right) and flankers that were either congruent
(two flanking arrows on either side of the central arrow all pointing in the same direction as the
central arrow), incongruent (a set of flanking arrows which pointed in the opposite direction of the
central arrow), or neutral (two horizontal lines on either side of the central arrow). Compared to
the congruent flankers, the incongruent flankers introduce conflict likely to result in longer RTs (i.e.,
slower information processing speed) and the potential for reduced response accuracy.
2.2.1.2. Anti-saccade task. The AST is an inhibition task, investigating the voluntary and flexible
cognitive control (Miyake & Friedman, 2012). In the AST, participants are required to make
a decision based on the direction of an arrow, appearing either right or left from the fixation
mark. On the right from the fixation mark, the arrow can either point to right or left, and similarly,
on the left from the fixation mark, the arrow can point to either right or left. Two types of stimuli
are presented in the task: congruent and incongruent. The congruent stimuli involve the arrow
pointing in the same direction as to where it is placed (i.e. arrow on the right from fixation mark
that points to the right), while the incongruent stimuli involve the arrow pointing in the opposite
direction as to where it is placed (i.e. arrow on the right from fixation mark that points to the left).
Incongruent trials have a longer latency than pro-saccades and subjects are more likely to make
errors on anti-saccade trials (Friedman et al., 2008; Jamadar, Fielding, & Egan, 2013; Roberts,
Hager, & Heron, 1994).
2.2.1.3. Color-shape-task. The color-shape-task (CST) is an experimental measure of shifting
(Miyake & Friedman, 2012). During this test, a letter (either C or S) appear above a colored shape
(outline of either a circle or triangle). The letter is a cue telling the participant what response to
make. When the letter was C, it indicated for the participant to respond with whether the color of
the shape was red or blue. When the letter was S, it indicated for the participant to respond with
whether the shape was a triangle or a circle. Given that both colors and shapes are presented
simultaneously, task switching requires participants to move visuospatial attention away from one
set of features in order to selectively attend to the alternative feature set. Half of the trials were
switch (different), the other half were no-switch (same) (Miyake, Emerson, Padilla, & Ahn, 2004).
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2.2.1.4. Letter memory task. The LMT is an experimental task of updating (Miyake & Friedman,
2012). Participants view series of letters (5, 7, 9 letters long), one at a time in the middle of the
computer screen. Whenever a new letter appears on the screen, the participants have to rehearse
out loud the last three letters in the series. After the last letter disappears, they have to enter the
last three letters by selecting the correct letters on the keyboard. There were 12 trials in total
(Friedman et al., 2008; Morris & Jones, 1990).
In the current study, ANT executive functioning will be used to measure alerting, orienting and
executive control, while the CST will be used to measure shifting, the LMT will be used to measure
updating, and the AST will be used to measure inhibition (Posner & Rothbart, 2007).
2.3. The Neurotracker 3D multiple object tracking tool
An online version of NT 3D MOT was used, and athletes were instructed to sit upright on a stool in
front of their computer with a pair of 3D glasses for each trial. The NT 3D MOT device uses a 3D
transparent cube containing eight identical yellow balls that are presented on the screen. In the
first stage of each trial, two of these balls were randomly illuminated for 2 s while marked with
a red color, before returning to the baseline yellow color again. Athletes were instructed to track
the two balls while all the eight balls were moving simultaneously and randomly in all areas of the
cube for 8 s. The movement speed was adjusted according to the current level. After 8 s, the balls
were frozen in their individual space and assigned a number from 1 to 8 by the computer. Athletes
were instructed to identify the two balls they were originally asked to track by clicking on them in
the cube with their mouse or keyboard. The movement speed of the balls depended on the score
the athletes received on their previous session. If the athletes correctly selected both two balls, the
speed was increased, if not, the speed was reduced. All athletes started their sessions with
tracking two balls and increased up to maximum tracking of four balls.
Relevant variables were detected as baseline scores in the beginning of the training and at the
end of the 5th week of training. The 3 first sessions were used to compute the geometric mean
defined as the initial baseline. The number of balls they were tracking was defined as number of
targets. The variable improvement rate was calculated to measure if and how much the athletes
had improved from when they started using NT 3D MOT. The following formula was used to
calculate the improvement rate: (Baseline at 2 Targetsinitial baseline)/initial baseline. Learning
rate was defined by the athletesscore had they been tracking at two targets.
2.4. Procedure
Prior to the beginning of the study, an approval was granted by the Norwegian Social Science Data
Services (NSD), which is the research ethic board for social sciences in Norway. The current study
utilized a cross-over design involving two groups, with participants randomized based on the group
of sport they belonged to and the timing of the competition season of the respective sports. The
aim was to avoid clashes between the duration of the study and the competition season. Group 1
included wrestling, handball, biathlon, and alpine skiing. Group 2 included soccer, Paralympic
sports, boxing and orienteering. Athletes belonging to these respective sports were randomly
invited to participate. Prior to the beginning of the study, all invited athletes, their coaches and
coaching staff received oral and written information about purpose, procedure, and requirements
of the study.
Throughout the study, both groups underwent three testing sessions: pre-test, post-test 1 and
post-test 2, in which they completed the EF tests. In addition, both groups completed the demo-
graphic information questionnaire at pre-test. An invitation to participate at each testing session
was sent by email to each participant. At each testing point, athletes were given one week to
complete the materials. Furthermore, all athletes trained with the NT 3D MOT. The NT 3D MOT
license was sent to athletes immediately prior to the beginning of their training period, to ensure
that athletes were completely unfamiliar with the tool to avoid possible training effects confounds
(Faubert, 2013). Each athlete received instructions to perform at least 4 sessions per week, over
a period of five consecutive weeks. The procedure is illustrated in Figure 1.
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2.5. Data analysis procedures
Missing data were identified for six athletes, who had not completed the experiment in its full
entirety. For these subjects, the SPSS function replace missing with series mean was used to
replace missing values. Thus, data was analyzed for all 60 athletes. Then, NT data was examined
with the use of descriptive statistics, such as statistical means, standard deviations, maximum and
minimum values.
To test the hypothesis that perceptual-cognitive training with the NT 3D MOT improves EFs in elite
athletes, data analysis procedure with the following variables were conducted: alerting, orienting
and executive control (assessed with ANT) (Petersen & Posner, 2012), updating (assessed with LMT),
shifting (assessed with CST) and inhibition (assessed with AST). Firstly, descriptive statistics including
statistical means and standard deviations measuring the investigated EF variables were carried out
for Group 1 and Group 2 respectively, at each testing time-point. Additionally, paired samples t-tests
were applied to test for improvements between pre-test and post-test 1, and between post-test 1
and post-test 2, in each of the two groups respectively. To investigate whether Group 1, after
receiving NT training, has significantly improved the EFs compared to athletes in Group 2, a series
of seven separate hierarchical regression analyses were conducted. The EFs variables at post-test1
(ANT- alerting, orienting, executive, AST-inhibition incongruence and congruence, CST-shifting, and
LMT-updating) were included as dependent variables. In the first step, age, sex and pre-scores of the
EF variables were entered simultaneously as covariates to rule out their potential confounding
effects. In the second step, the group variable was entered as a dichotomized variable.
Figure 1. The implemented
cross-over design with the pro-
cedure for the two respective
groups (Group 1 in red arrows,
Group 2 in blue arrows).
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To investigate whether Group 2, after receiving NT training between post-test 1 and post-test 2,
has significantly improved the EF variables compared to athletes in Group 1, new series of seven
hierarchical regression analyses were conducted. The analyses were set up in the same way as for
Group 1, with the following exceptions: dependent variables scores were used from post-test2, and
EFs scores from post-test1 were entered. All statistical analyses were carried out with IBM SPSS
version 25. Statistical significance was established at alpha level <0.05.
3. Results
From the 60 participants, 48.3% were male and51.7%werefemale.Thesamplehadamean
age of 21.7 years (ranging from 17 to 35 years). Group 1 included 31 participants, 21 were
from individual sports (alpine skiing 11, boxing 2, biathlon 8) and 10 from team sports
(handball 8, football 1, ice hockey 1), and 16 were males and 15 were females. Group 2
included 29 participants, 16 were from individual sports (Orienteering 13, boxing 1, table
tennis 1, badminton 1) and 13 from team sports (football 9, sledge hockey 4), and 13 were
males and 16 were females.
3.1. NT training in Group 1 and Group 2
Descriptive statistics of participantsNT training, from groups 1 and 2, respectively, are shown
in Table 1. Based on the NT improvement rate and learning rate variables, these results show
that both groups experienced NT-specific improvements as a result of NT training (Faubert,
2013).
Table 1. Descriptive statistics assessing the NT variables n=60
Group 1 Group 2
Variables Mean Std Max Min Mean Std Max Min
Age 22 3.5 35 17 22 4.19 35 17
NT number of sessions 26.5 13.3 76 9 27.54 10.48 61 14
NT baseline 3.04 0.60 4.40 1.91 3.50 0.91 5.06 1.68
NT improvement* 45.45 50.64 213 24.5 42.79 30.15 98.63 8.70
NT learning rate 3.23 0.53 4.21 2.25 3.25 0.75 4.67 1.75
NT targets 3.8 0.41 4 3 3.83 0.48 4 2
* Values in percent.
Table 2. Mean, standard deviation and p-values for Group 1 at pre-test, post-test 1 and post-
test 2 (n= 31)
Pre-test Post-test 1 Post-test 2
Variable Mean Std Mean Std pMean Std p
ANT-alerting 3.95 45 6.94 33 .16 11 23 .54
ANT-orienting 12.44 30 3.37 19 .08 6.42 23 .55
ANT-executive 117 90 79 36 .02 74 41 .38
AST-inhibition* 652 191 640 184 .79 604 144 .30
AST-inhibition** 635 197 609 134 .49 594 101 .56
CST-shifting 693 827 496 271 .18 486 482 .91
LMT-updating 64 24 72 17 .02 84 13 .000
* Congruence, ** incongruence.
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Table 3. Mean, standard deviation and pvalues for Group 2 at pre-test, post-test 1 and post-
test 2 (n= 29)
Pre-test Post-test 1 Post-test 2
Variable Mean Std Mean Std pMean Std p
ANT-alerting 19 64 11 37 .64 10 26 .93
ANT-orienting 17 35 14 23 .61 14 18 .99
ANT-executive 102 73 83 59 .08 72 18 .26
AST-inhibition* 937 1419 601 109 .19 579 84 .19
AST-inhibition** 637 198 602 136 .27 556 75 .02
CST-shifting 580 449 472 244 .18 474 207 .97
LMT-updating 76 17 80 16 .11 88 11 .02
*Congruence, ** incongruence.
Table 4. Summary of linear regression analysis for variables predicting the dependent vari-
ables specified as the executive test variables (n= 60)
Dependent
variable
Predictors BtpR
2
ANT-alerting 2 Age .16 1.21 .232
Gender .07 .459 .648
ANT-alerting 1 .07 .51 .613
Group .08 .60 .554 .03
ANT-orienting 2 Age .32 2.60 .012
Gender .05 .44 .658
ANT-orienting 1 .32 2.61 .012
Group .20 1.69 .096 17
ANT-executive 2 Age .04 .31 .760
Gender .03 .25 .805
ANT-executive 1 .46 3.81 .000
Group .10 .79 .436 16
AST-inhibition* 2 Age .06 .44 .665
Gender .04 .29 .773
AST-inhibition* 1 .27 1.86 .068
Group .17 1.35 .182 .05
AST-inhibition**
2
Age .19 1.534 .131
Gender .04 .28 .779
AST-inhibition**
1
.38 3.08 .003
Group .04 .31 .761 13
CST-shifting 2 Age .12 .89 .377
Gender .01 .11 .911
CST-shifting 1 .34 2.58 .012
Group .02 .19 .853 .05
LMT-updating 2 Age .00 .03 .975
Gender .06 .52 .607
LMT-updating 1 .56 4.76 .000
Group .08 .68 .502 32
*Congruence, ** incongruence.
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3.2. Effects of NT training on executive functions
Means, standard deviations and paired samples t-tests for the outcome variables at pre-test,
post-test 1 and post-test 2 are given in Table 2for Group 1 and Table 3for Group 2. The paired
samples t-tests compared values between pre-test vs. post-test 1 and post-test 1 vs. post-test 2.
Overall, there has been a slight improvement on all tested variables in both groups, especially
from pre-test to post-test 1. Analysis revealed a significant improvement in executive control
function from pre-test to post-test 1 and a significant improvement in updating at both tested
time points in Group 1, and a significant improvement in inhibition and updating from post-test 1
to post-test 2 in Group 2.
3.3. Effects of group differences in NT training on executive functions at post-test1
The hierarchical regression analyses did not reveal any significant effects of group on the EF
measures, neither in Group 1 nor in Group 2. Consistently, the only variables that predicted the
respective EF measures were the respective EF measures at pre-test. The results of step 2 of the
regression analyses are summarized in Table 4.
3.4. Effects of group differences in NT training on executive functions at post-test2
In addition, results of the hierarchical regression analyses using EF scores at post-test 2 as
dependent variables gave similar results, with no significant effect of group. For the sake of
keeping this article concise, results of hierarchical analyses for Group 2 are not reported in full.
4. Discussion
The purpose of the present study was to examine possible effects from a 5-week experiment with
a control group design with the NT 3D MOT tool on executive brain function tests, such as ANT-
alerting, orienting and executive control, AST-inhibition congruence, AST-inhibition incongruence,
CST-shifting and LMT-updating. After the 5-week intervention period the two groups changed
positions in a cross-over design for another 5-week intervention period. Sixty elite athletes from
different dynamic sports participated in the experiment. The analysis in the current study shows
that there were significant improvements among the participants in both groups on the NT 3D MOT
tool used in this study. The training effect on the perceptual-cognitive tool was comparable to
other studies (Faubert, 2013). However, the results in the current study show that the specific
benefits from NT training did not transfer to other more specific executive functioning regulating
attentional processes. No significant effects from the NT 3D MOT tool were found on the EF tests
used in the current study.
Possible explanations of the results in the current study are grounded on the importance of
training specificity and the mental state at the moment of NT training.
4.1. The importance of training specificity
First of all, research claims that individual differences in EF are almost entirely genetic in origin
(Friedman et al., 2008). However, the development of the brain is also claimed to be epigenetic
(Edelman, 1992), which involves the idea that genes alone cannot explain the development of the
brain, and that specific experiences from training on specific skills are needed to fully develop the
potential of the brain. Edelmansneural group selectiontheory claims that it is the specific
neural brain development that ultimately causes learning and development of that particular skill
(Edelman, 1987,1992; Moen et al., 2018; Sigmundsson, Trana, Polman, & Haga, 2017). Thus, to
learn a skill implies the necessity to specific experience repeated executions of that skill, so that
the specific neurons in the brain that are needed for that particular skill are activated (Edelman,
2006). In this process groups of activated neurons will establish networks that connect the
different areas of the brain that are needed to execute that specific skills (Edelman, 1993). The
neural group selectionalso involves the idea that neurons, group of neurons and networks that
are not used in this process are not activated, and will therefore eventually disappear (Freberg,
2006). Such an explanation also find support in the theoretical framework behind neural plasticity
(Hebb, 1949), which also claims that neurons or group of neurons that are active at the same time
Moen et al., Cogent Psychology (2018), 5: 1544105
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Page 9 of 13
will strengthen their connections and fire simultaneously (Taya, Sun, Babiloni, Thakor, &
Bezerianos, 2015). Thus, perceptual-cognitive training programs that are repeated will strengthen
areas in the brain that work together to execute that particular brain-training actions, and build
stronger associations between them. Interestingly, several studies confirm this and document
effects on neural activity in the brain when using brain training (Jolles & Crone, 2012; Klingberg,
2010).
The general idea behind cognitive-perceptual training, such as the NT 3D MOT tool, is that when
neurons and groups of neurons build stronger associations into networks in the brain, these
networks can transfer to other tasks that need these same neurons and networks. It is therefore
reason to believe that the NT tool used in the current study has not affected the neurons, groups of
neurons and networks of groups of networks that are needed for completing the executive
functioning tests used in the current study.
However, the results also indicate a specific training effect on the executive functioning tests,
whereas both the experiment group and the control group improved their scores on the executive
tests used in the current study (especially from test 1 to test 2). However, only ANT-executive and
LMT-updating improved significantly and only in Group 1. The results in the current study therefore
indicate that the brain networks that are engaged in the NT training tasks do not overlap with the
brain networks related to the EF test tasks. The question is if the NT 3D MOT used in the current
study is specific enough compared to the test used to measure executive functioning? The results
in the current study indicate that it is not.
4.2. The mental state at the moment of training
Another possible explanation of the results in the current study can be that the mental state at
the moment of training with the NT tool was not optimal. Research shows that if the task is too
demanding or difficult it can be difficult to concentrate at the task, which can result in exhaustion
from such workloads (Taya et al., 2015). Interestingly, the training difficulty level (NT targets) is
found to explain effects from NT training on subjective performance (Moen et al., 2018). Future
studies should include measurements of mental states during training with perceptual-cognitive
tools, such as the NT 3D MOT.
5. Conclusion and limitations
The current study shows that training with the NT 3D MOT used in the current study results in
specific benefits on skills used when training with this specific tool. However, the results in the
current study show no significant general improvements on different aspects of executive func-
tioning (ANT-alerting, orienting and executive, AST-inhibition, CST-shifting, LMT-updating). Thus,
the specific benefits do not transfer to other brain tasks.
A possible limitation in the current study might be that the participants were not familiarized with
the executive tests. However, other studies also used the first tests scores to analyze possible effects
from brain training (Owen et al., 2010). Future studies should however consider using the mean from
several executive tests to set the baseline score on the first test. Future studies also should consider
using electroencephalography (EEG) to provide biomarkers that document brain networks when
performing brain training and executive tests, to compare transferability. In the current study, only
the CORE program was used, while there are a wide variety of different training protocols that can be
utilized depending on what type of training one wants to emphasize. A variable that measures
motivation and concentration should be included in future research to control for possible transfer
effects from perceptual-cognitive tools. Experiments with a control group design and a larger number
of participants are also called for in future research. Also, studies with a larger intervention period are
called for in future studies, to control for possible effects related to time, since neural adaption in the
brain takes time to develop.
Moen et al., Cogent Psychology (2018), 5: 1544105
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Page 10 of 13
Funding
The authors received no direct funding for this research.
Competing Interest
The authors declare no competing interest.
Author details
Frode Moen
1
E-mail: frode.moen@ntnu.no
ORCID ID: http://orcid.org/0000-0002-6290-5070
Maria Hrozanova
2
E-mail: maria.hrozanova@gmail.com
ORCID ID: http://orcid.org/0000-0002-1309-489X
Tore Stiles
3
E-mail: tore.stiles@coperio.no
1
Centre for Elite Sports Research, Department of
Education and Lifelong Learning, Faculty of Social and
Educational Sciences, Norwegian University of Science
and Technology, Trondheim, Norway.
2
Centre for Elite Sports Research, Department of
Neuromedicine and Movement Science, Faculty of
Medicine and Health Science, Norwegian University of
Science and Technology, Trondheim, Norway.
3
Department of Psychology, Faculty of Social and
Educational Sciences, Norwegian University of Science
and Technology, Trondheim, Norway.
Citation information
Cite this article as: The effects of perceptual-cognitive
training with Neurotracker on executive brain functions
among elite athletes, Frode Moen, Maria Hrozanova &
Tore Stiles, Cogent Psychology (2018), 5: 1544105.
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... In contrast, there is little evidence for improvements in near-transfer or far-transfer tasks (for reviews, see Harris et al., 2018;Zentgraf et al., 2017). For example, in two different studies, training interventions applied over the course of several weeks using domain-general tasks to train the visual processing functions of elite athletes only led to task-specific improvements in the trained task, but not to improvements in other visual tasks or in tasks measuring executive functions (Moen et al., 2018;Scharfen & Memmert, 2021). Findings on perceptual-cognitive trainings in athlete populations are largely consistent with findings in other areas, where perceptual-cognitive training effects that extend beyond the trained task are not frequently observed in non-athlete populations (for reviews, see Green & Bavelier, 2008;Simons et al., 2016). ...
... Here, only task-specific effects of the training were found. Participants of the 360-MOT training group improved significantly in the trained task, as was also the case in past MOT studies (Fleddermann et al., 2019;Harenberg et al., 2021;Moen et al., 2018;Scharfen & Memmert, 2021). However, no positive effects of 360-MOT training on performance in the visuospatial attention task (near transfer) or soccer-specific performance (far transfer) were found. ...
... On the one hand, these results contradict the findings of Romeas et al. (2016), who found an improvement of passing decisions in a small-sided soccer game through 3D-MOT training. On the other hand, they confirm recent studies that found no transfer effects of MOT training on perceptual-cognitive performance (Harris, Wilson, Smith, et al., 2020;Moen et al., 2018;Scharfen & Memmert, 2021) or on performance in team sports (Fleddermann et al., 2019;Harenberg et al., 2021). Thus, the results of the current study contribute to the growing literature that questions the effectiveness of brief, isolated, context-unspecific perceptual-cognitive training interventions (Simons et al., 2016). ...
Article
Introduction Soccer is a complex game in which athletes perform in a dynamic 360°-environment. The results of numerous studies highlight the importance of perceptual-cognitive functions for soccer performance. Moreover, in recent years, the idea of improving sports performance through systematic perceptual-cognitive training has been increasingly investigated. Contradictory results and limitations in previous research call for further investigation. The current study aims to investigate both the relationship between perceptual-cognitive performance in a dynamic 360°-environment and soccer performance as well as the effects of perceptual-cognitive training in such an environment on soccer performance. Methods 42 youth soccer players aged 11–13 years were tested at a first time of measurement (T1) on their perceptual-cognitive functions using a 360°-multiple object tracking task (360-MOT) and a visuospatial attention task. Soccer performance was assessed using an isolated, validated 360°-passing task and a small-sided game. Subsequently, participants were randomly divided into a perceptual-cognitive training group, an active control group, or a passive control group. Participants in the training group received 360-MOT training twice per week during a 5-week intervention phase, while participants in the active control group received a pseudo video training. Perceptual-cognitive and soccer-specific performance was assessed after the intervention phase at a second time of measurement (T2). Results At T1, there was a significant positive relationship between 360-MOT performance and both the accuracy score in the 360°-passing task and the defensive performance score in the small-sided game. Regarding the perceptual-cognitive training intervention, the analysis at T2 revealed significant task-specific training effects but no transfer effects on perceptual-cognitive or soccer-specific performance. Conclusions The results highlight the relevance of perceptual-cognitive performance in a 360°-environment for soccer-specific performance but question the effects of short isolated perceptual-cognitive training interventions on soccer-specific performance.
... Study 3 Moen et al. (2018) found, for elite athletes in several sports, that Neurotracker training did not improve executive function. Four executive function tests were used: an attention network test, anti-saccade task, color shape task and letter memory task. ...
... In some studies the objects bounce off the walls and also change direction when they are close to other objects (Legault et al., 2013;Legault & Faubert, 2012;Romeas et al., 2016). In another study, objects only bounce off the walls but not off other objects (Harris et al., 2020a) and in other studies, it is not mentioned how objects interact (Assed et al., 2016;Moen et al., 2018;Vartanian et al., 2016). This is an important issue as previous MOT research has shown that object distances and interactions affect attentional (Iordanescu et al., 2009;Shim et al., 2008) and perceptual strategies (Vater et al., 2017b;Zelinsky & Todor, 2010) as well as tracking performance (Holcombe et al., 2014;Vater et al., 2017b). ...
... This is an important issue as previous MOT research has shown that object distances and interactions affect attentional (Iordanescu et al., 2009;Shim et al., 2008) and perceptual strategies (Vater et al., 2017b;Zelinsky & Todor, 2010) as well as tracking performance (Holcombe et al., 2014;Vater et al., 2017b). Related to this issue, objects randomly changed direction at times in some Neurotracker studies (Moen et al., 2018;Tullo, Faubert, & Bertone, 2018a, b) but remained on straight paths in others (Musteata et al., 2019;Romeas et al., 2016). Objects with random motion trajectories can be more difficult to track and require a greater amount of sustained attention, although this may be less true when there are more objects to track, because participants then seem to have less knowledge of object velocity (Horowitz & Cohen, 2010;Howe & Holcombe, 2012;Luu & Howe, 2015). ...
Article
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In this systematic review, we evaluate the scientific evidence behind "Neurotracker," one of the most popular perceptual-cognitive training tools in sports. The tool, which is also used in rehabilitation and aging research to examine cognitive abilities, uses a 3D multiple object-tracking (MOT) task. In this review, we examine Neurotracker from both a sport science and a basic science perspective. We first summarize the sport science debate regarding the value of general cognitive skill training, based on tools such as Neurotracker, versus sport-specific skill training. We then consider the several hundred MOT publications in cognitive and vision science from the last 30 years that have investigated cognitive functions and object tracking processes. This literature suggests that the abilities underlying object tracking are not those advertised by the Neurotracker manufacturers. With a systematic literature search, we scrutinize the evidence for whether general cognitive skills can be tested and trained with Neurotracker and whether these trained skills transfer to other domains. The literature has major limitations, for example a total absence of preregistered studies, which makes the evidence for improvements for working memory and sustained attention very weak. For other skills as well, the effects are mixed. Only three studies investigated far transfer to ecologically valid tasks, two of which did not find any effect. We provide recommendations for future Neurotracker research to improve the evidence base and for making better use of sport and basic science findings.
... Perceptual-cognitive training is designed to improve an athlete's performance during the search, identification, processing, and integration of information with the knowledge and ability to perform appropriate actions (1) These skills are essential to improve sporting performance, and several methods have been implemented to ensure perfection, including visual simulation, video projection, and the use of Neurotrackers (2). Besides, these approaches are widely used by coaches, sports experts, and athletes to enhance skills (3) and are potentially practiced in diverse sports, including the dynamic team forms (e.g., football, basketball, ice skating, baseball, softball, and field hockey) and individual sports (e.g., running, tennis) (2,4). ...
... Perceptual-cognitive training is designed to improve an athlete's performance during the search, identification, processing, and integration of information with the knowledge and ability to perform appropriate actions (1) These skills are essential to improve sporting performance, and several methods have been implemented to ensure perfection, including visual simulation, video projection, and the use of Neurotrackers (2). Besides, these approaches are widely used by coaches, sports experts, and athletes to enhance skills (3) and are potentially practiced in diverse sports, including the dynamic team forms (e.g., football, basketball, ice skating, baseball, softball, and field hockey) and individual sports (e.g., running, tennis) (2,4). Moreover, perceptualcognitive training is also applied to improve athlete concentration for the actual game (5). ...
... Furthermore, players and teams always show unique traits while playing with different opponents at different times (2,38). This study is highly relevant in the conditions of this study subject, and different opponents, as well as game quality, were determined to influence athlete play performance. ...
... The following perceptual-cognitive skills were tested: Visual attentional control was assessed by a Multiple object tracking task (MOT), administered as a one "Core" session on the Neurotracker system [17]. Participant stood in front of a screen with 3D glasses on. ...
... Interpretation of the results must take into account possible advantages that one group had over another. Neurotracker and Dynavision tests were developed specifically for the evaluation and cognitive training of athletes [17,18]. Neurotracker presents objects in 3D, while Dynavision demands wide hand movements, favoring those who swing with strength; both tests involve a wide field of view. ...
Chapter
Video game competitions known as “esports” are rapidly gaining popularity around the world. Esports is legally recognized as a sport in several countries. It was a demonstration event at the 2018 Asian Games and was discussed as a potential addition to the Olympic program at the 2018 Esports Forum, organized by the International Olympic Committee. Even so, the status of esports remains a highly disputed topic in academia. In this paper, we argue that to be promoted as a full-fledged sport esports has to be associated with talents and health benefits similar to traditional sports. Existing studies indicate that traditional team sports and amateur gaming are both related to cognitive advantages. To evaluate the extent of this similarity at the professional level, we assessed perceptual-cognitive abilities of (semi-)professional esports players (N = 31) and professional soccer and basketball players (N = 43). Esports players and athletes performed equally well in complex tests measuring attentional control, short-term and working spatial memory span, attention distribution, reaction time, and hand-eye coordination. Esports players outperformed athletes in the speed of visual search. This data supports the idea that esports and traditional team sports demand a similar level of perceptual-cognitive ability from professionals and might provide similar cognitive benefits.
... NeuroTracker [5] is a cognitive training program designed to improve mental performance in various contexts, such as sport [33] or old age [9]. It provides a single 3D visual exercise, where users see a number of yellow balls moving around their screen and are asked to track the highlighted balls. ...
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Computer-assisted cognitive training can help patients affected by several illnesses alleviate their cognitive deficits or healthy people improve their mental performance. In most computer-based systems, training sessions consist of graded exercises, which should ideally be able to gradually improve the trainee’s cognitive functions. Indeed, adapting the difficulty of the exercises to how individuals perform in their execution is crucial to improve the effectiveness of cognitive training activities. In this article, we propose the use of reinforcement learning (RL) to learn how to automatically adapt the difficulty of computerized exercises for cognitive training. In our approach, trainees’ performance in performed exercises is used as a reward to learn a policy that changes over time the values of the parameters that determine exercise difficulty. We illustrate a method to be initially used to learn difficulty-variation policies tailored for specific categories of trainees, and then to refine these policies for single individuals. We present the results of two user studies that provide evidence for the effectiveness of our method: a first study, in which a student category policy obtained via RL was found to have better effects on the cognitive function than a standard baseline training that adopts a mechanism to vary the difficulty proposed by neuropsychologists, and a second study, demonstrating that adding an RL-based individual customization further improves the training process.
... For that reason, it indicates that the NeuroTracker training has a better effect than the conventional training on the archery athlete shooting performance. These findings are relevant to several studies conducted by experts that NeuroTracker exercise is a tool that has an influence on brain function that regulates perceptual processes of cognition [10]. Several studies conducted by psychologists explain that cognitive ability is an important source for achieving the athlete success [11]. ...
Article
Full-text available
Nowadays, there are a number of non-conventional training methods utilizing science and technology that can improve athlete performances, one of them is NeuroTracker technology. In Indonesia, this technology is still limited. Meanwhile, in developed countries, this method is developing rapidly and implemented for gaining sport achievements, including in archery. In archery, athletes must focus on performing techniques consistently, be fast, and be precise in making decisions when aiming and releasing arrows. In this condition, athletes often experience disturbances and doubts in aiming and releasing arrows so that the shooting performance is often not optimal. To overcome this problem, NeuroTracker technology can be provided in the training process to improve the archery athlete shooting ability. The method of this research used the experimental method with pretest-posttest control group design. The population of this study consisted of 40 archery athletes of one of the campus sports clubs. Samples were selected using non-random sampling to obtain 20 athletes. The samples were divided into two groups, including the experimental group and control group. The experimental group received NeuroTracker trainings, while the control group received the conventional trainings. The instrument used to measure the archery shooting ability was the 30m shooting test. The results showed that NeuroTracker training and conventional training had a significant effect on the archery athlete shooting performance. Furthermore, NeuroTracker training had a greater effect than conventional training on the archery athlete shooting performance.
... One study (Romeas et al., 2016) for example found improvement in in-game parameters and therefore proved a transfer effect, in this case, for decision-making and passing accuracy in basketball. Other findings show an increase in MOT ability, but found no transferable effects (Moen et al., 2018) or documented improved basic mental skills such as sustained attention or processing speed, but also found no transfer to specific sport related parameters such as jumping performance (Fleddermann et al., 2019). Despite the ambiguous results, it might in summary be of great benefit for both esport players and traditional sportsmen to improve their MOT ability with varying training methods and profit from possible basic ability improvements and transfer effects. ...
Article
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Chapter
Training to optimize visual performance abilities is a logical supplement to other training programs that athletes perform in order to improve sports performance in competition. An overview of how to develop and successfully implement sports vision training is presented. A detailed description of common sports vision training approaches is provided with research evidence to support efficacy, when available. Updates on commercially available instrumentation to train various visual performance abilities is presented.
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Book
Burgeoning advancements in brain science are opening up new perspectives on how we acquire knowledge. Indeed, it is now possible to explore consciousness--the very center of human concern--by scientific means. In this illuminating book, Dr. Gerald M. Edelman offers a new theory of knowledge based on striking scientific findings about how the brain works. And he addresses the related compelling question: Does the latest research imply that all knowledge can be reduced to scientific description? Edelman's brain-based approach to knowledge has rich implications for our understanding of creativity, of the normal and abnormal functioning of the brain, and of the connections among the different ways we have of knowing. While the gulf between science and the humanities and their respective views of the world has seemed enormous in the past, the author shows that their differences can be dissolved by considering their origins in brain functions. He foresees a day when brain-based devices will be conscious, and he reflects on this and other fascinating ideas about how we come to know the world and oursel.