Graczyk M, Pąchalska M, Ziółkowski A, Mańko G, Łukaszewska B, Kochanowicz K, Mirski A, Kropotov ID. Neurofeedback training for peak performance. Ann Agric Environ Med. 2014; 21(4): 871–875. doi: 10.5604/12321966.1129950

Abstract

Aim. One of the applications of the Neurofeedback methodology is peak performance in sport. The protocols of the neurofeedback are usually based on an assessment of the spectral parameters of spontaneous EEG in resting state conditions. The aim of the paper was to study whether the intensive neurofeedback training of a well-functioning Olympic athlete who has lost his performance confidence after injury in sport, could change the brain functioning reflected in changes in spontaneous EEG and event related potentials (ERPs).
Case study. The case is presented of an Olympic athlete who has lost his performance confidence after injury in sport. He wanted to resume his activities by means of neurofeedback training. His QEEG/ERP parameters were assessed before and after 4 intensive sessions of neurotherapy. Dramatic and statistically significant changes that could not be explained by error measurement were observed in the patient.
Conclusion. Neurofeedback training in the subject under study increased the amplitude of the monitoring component of ERPs generated in the anterior cingulate cortex, accompanied by an increase in beta activity over the medial prefrontal cortex. Taking these changes together, it can be concluded that that even a few sessions of neurofeedback in a high performance brain can significantly activate the prefrontal cortical areas associated with increasing confidence in sport performance.

Full text

Annals of Agr icultural and Env ironmental M edicine 2014, Vol 21, No 4, 871–875
www.aaem.pl
CASE REPORT
Neurofeedback training for peak performance
Marek Graczyk1, Maria Pąchalska2, Artur Ziółkowski1, Grzegorz Mańko3, Beata Łukaszewska4,
Kazimierz Kochanowicz1, Andrzej Mirski2, Iurii D. Kropotov5,6
1 Gdansk University of Physical Education & Sport, Poland
2 Chair of Neuropsychology, Andrzej Frycz Modrzewski Krakow University, Krakow, Poland
3 Institute of Physiotherapy, Faculty of Allied Health Sciences, College of Medicine, Jagiellonian University, Krakow, Poland
4 Institute of Psychology, University of Gdansk, Gdansk, Poland
5 Laboratory of the Institute of the Human Brain of Russian Academy of Sciences, St. Petersburg, Russia
6 Norwegian University of Science and Technology, Trondheim, Norway
Graczyk M, Pąchalska M, Ziółkowski A, Mańko G, Łukaszewska B, Kochanowicz K, Mirski A , Kropotov ID. Neurofeedback training for peak
performance. Ann Agric Environ Med. 2014; 21(4): 871–875. doi: 10.5604/12321966.1129950
Abstract
Aim. One of the applications of the Neurofeedback methodology is peak performance in sport.The protocols of the
neurofeedback are usually based on an assessment of the sp ectral parameters of spontaneous EEG in resting state conditions.
The aim of the paper was to study whether the intensive neurofeedback training of a well-functioning Olympic athlete
who has lost his performance condence after injury in sport, could change the brain functioning reected in changes in
spontaneous EEG and event related potentials (ERPs).
Case study.The case is presented of an Olympic athlete who has lost his performance condence after injury in sport. He
wanted to resume his activities by means of neurofeedback training. His QEEG/ERP parameters were assessed before and
after 4 intensive sessions of neurotherapy. Dramatic and statistically signicant changes that could not be explained by
error measurement were observed in the patient.
Conclusion.Neurofeedback training in the subject under study increased the amplitude of the monitoring component of
ERPs generated in the anterior cingulate cortex, accompanied by an increase in bet a activity over the medial prefrontal cortex.
Taking these changes together, it can be concluded that that even a few sessions of neurofeedback in a high performance
brain can signicantly activate the prefrontal cortical areas associated with increasing condence in sport performance.
Key worda
neurofeedback, cognitive control, anxiety, ERPs
INTRODUCTION
One of the applications of the neurofeedback methodology
is peak performance in sport. Neurofeedback (EEG
biofeedback) holds potential for retrai ning brainwave activit y
to enhance optimal performance in ath letes in various sports
[1]. Neurofeedback has been shown to have the potential for
quieting the mind to improve performance in archery, for
example. It can also be used to improve concentration and
focus, cognitive function and emotional control following
concussions and mild head injuries, and it has untapped
potential to increase physical balance in gymnastics, ice
skating, skiing, and other areas of performance [2, 3, 4, 5].
Clinical examples are provided on the use of neurofeedback
to improve physical balance, while controlled research is
called for [2, 3].e protocols of the neurofeedback are
usually based on an assessment of the spectral parameters
of spontaneous EEG in resting state conditions. e case
is presented of a sportsman who had lost performance
condence and wanted to resume his activities by means of
neurofeedback training [6].
OBJECTIVE
e aim of the paper was to study whether the intensive
neurofeedback training of a well functioning sportsmen who
has lost his performance condence aer injury in sport,
could change the brain functioning reected in changes in
the spontaneous EEG and event related potentials (ERPs).
CASE STUDY
e case study is presented of an Olympic athlete, 25 years of
age, a member of the Polish javelin team at the 2012 Olympic
Games in London. e patient had achieved a personal best
of 84.99m, which would have been sucient for a gold medal
at the London Olympics. Following obtaining this personal
best, he was subjected to strong psychological pressure
from the media and sporting circles resulting from medal
expectations, something that was to cause signicant stress
for the Polish and international sportsman.
During the period of direct preparation for the Olympics,
he suered an injury to the ankle joint and damage to the
Achilles tendon. However, despite severe pain, the spor tsman
continued his preparations for the Olympics, using only
permitted a naesthetics, as wel l as taking pa rt in physiotherapy
treatment. A standard treatment programme for this type
of case was applied, with the aim of immobilization tapping
was also used. e sportsman attended the Olympics where,
unfortu nately, he achie ved only 22nd place, which he explained
both on the basis of the injury as well as the pressure exerted
on him from his immediate sporting circles, which resulted
Address for correspondence: Grzegorz Manko, Department of Ergonomics and
Exerti on Physiology, Institute of Phy siotherapy, Faculty of Allie d Health Sciences,
College of Medicine, Jagiellonian University, Krakow, Poland
E-mail: manko@zjoterapia.pl
Received: 28 J anuary 2014; Accepted: 12 April 2014
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Annals of Agr icultural and Enviro nmental Medicine 2014, Vol 21, No 4
Marek Grac zyk, Maria Pącha lska, Artur Ziółko wski, Grzegorz M ańko, Beata Łukaszewsk a, Kazimierz Kocha nowicz et al. Neurofeedback training for peak performance
in a reduction in his condence and belief in being able to
nally achieve victory.
Following his return to Poland, the chronic pain at the
end of August 2012 intensied, a pain that appeared not
only during intensive exertion, but increasingly so during
warm-ups, walking, and even when at rest. He underwent
arthroscopy and was cl inically diag nosed as havi ng ‘posterior
ank le impingement syndrome’. is syndrome, also k nown as
os trigonum syndrome and posterior tibiotalar compression
syndrome, is a clinical disorder characterized by acute or
chronic posterior ankle pain triggered by forced plantar
exion, which causes chronic repetitive microtrauma [7].
e results of standard psychological and neuro-
psychological tests conrmed lost of cognitive control, as
well as the appea rance of emotional disturbances. He decided
to resume his act ivities by means of neurofeedback training.
Peak performance training with neurofeedback. e
Olympic athlete took part in 4peak performance training
sessions with neurofeedbackat the beginning of September
2012. HRV biofeedback training was conducted for a period
of 10 minute, as well as EEG feedback (neurofeedback)
for 20 minutes on a bipolar montage with electrodes at
points C3 – C4 on the 8 canal PROCOM Inniti BIOMED
Neurotechnology apparatus. e training sessions were
conducted by the psychologist Robert Kozłowski at the
National Research-Implementation Centre for Sport
Psychology at the Universityof Physical Education and Sport
in Gdańsk, Poland. e training protocol was developed
on the basis of results obtained by means of the QEEG/
ERPs method. Electrodes were placed in accordance with the
international system for the localisation of electrodes 10–20.
e patient was prepared for tests in a standard manner,
keeping the impedance of the electrodes below 5 kilo Ohm.
e frequency 9–13Hz was amplied during training.
e patient was placed in a NEEDO company chair with a
footrest ensuring a comfortable body position with par ticular
attention being placed on the foot under treatment. e head
was placed on the headrest, while t he arms were comfortable
placed on the armrests of the chair. e monitor displaying
the stimuli was located out of sight on a separate small
table. e implementation of such a model of intensive Peak
performance training with neurofeedback was the result
of the sportsman’s request for rapid help for the dicult
psychological situation in which he found himself following
unsatisfactory results in the competition, as well as being
conditioned by the absence of a strategic goal-directed
programme within the process of neuromodulation, and a
repeated reintegration of cognitive control for competitors at
the very hig hest sporting levels. During the course of the tests
and training sessions, the patient took medication [framin
5000, ciprinol 500, rantudil forte, cyclo3Fort], which did
not have an eect on the monitoring abilities of the frontal
lobes [5, 8, 9, 10].
Permission to conduct the experiment was obtained
from both the Olympic athlete himself and the Bioethics
Commission.
MATERIALS AND METHOD
e following methods were used to ascertain the Olympic
athlete’s state of health:
1.
Analysis of the patient’s relevant documentation
(illness case history, test results, including the results of
arthroscopy)
2. A clinical interview, during which emphasis was placed
particularly on psychic experiences in connection with
MEDIA pressure and patient expectations, as well as the
means of coping with the limitations resulting from the
threat of illness connected with dysfunction of the ankle
joint.
3.
QEEG/ERPs directed for evaluation of performance in
GO/NOGO task.
Neuropsychological testing. Neuropsychological testing at
baseline (Exam 1) showed mild multiple decits (Tab. 1). At
follow-up, aer conclusion of the neurotherapy programme
(Exam 2), the Olympic athlete showed improvements
in neuropsychological functioning. His cognitive and
executive functions increased signicantly and reached
norm. is general pattern was repeated in nearly all the
neuropsychological parameters (Tab. 1).
Table 1. Neuropsychological testing of the Olympic athelets
Measure Exam. 1 Exam. 2
Attention
WMS-III Spatial Span 12 (75th%ile) 100th percentile
Visuospatial Ability
WAIS-III Block Design 3 (1st%ile) 100th percentile
Verbal memory
CVLT Short Delay Free Recall 2/9 (<1st%ile) 100th percentile
CVLT Long Free Recall 2/9 (<1st%ile) 100th percentile
CVLT Long Delay Cue Recall 2/9 (<1st%ile) 100th percentile
Executive Functions
TMT– Number Sequencing 54s. (10th%ile) 100th percentile
TMT– Number Letter Sequencing 150s. (<1st%ile) 100th percentile
Stroop
Colour 41s. (16th%ile) 100th percentile
Word 42s. (63rd%ile) 100th percentile
Interferences 128s. (<1th%ile) 100th percentile
WCST
Categories 2 (>16th%ile) 100th percentile
Perseverative Errors 19 (37th percentile) 100th percentile
Conceptual Level Responses 48 (45th%ile) 100th percentile
Fail to Maintain Sets 4 (2–5th%ile) 100th percentile
Neurophysiological testing – EEG recording. e
electroencephalogram (EEG) was recorded with the Mitsar
21-channel EEG system, manufactured by Mits ar, Ltd. (http://
www.mitsarmedical. com), with a 19-channel electrode cap
with tin electrodes that included Fz, Cz, Pz, Fp1/2, F3/4,
F7/8, T3/4, T5/6, C3/4, P3/4, O1/2. e cap (Electro-cap) was
placed on the scalp according to the standard 10–20 system.
Electrodes were referenced to linked earlobes (o-line) and
the input signals sampled at a rate of 250 Hz (bandpass
0.5–30Hz). e ground electrode was placed on the forehead.
Impedance was kept below 5 kΩ. e participant sat upright
in a comfortable chair, looking at a computer screen (17
inch screen), 1.5 meter in front of him. All recordings were
performer by the author of this article. ERP waveforms were
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Marek Grac zyk, Maria Pącha lska, Artur Ziółko wski, Grzegorz M ańko, Beata Łukaszewsk a, Kazimierz Kocha nowicz et al. Neurofeedback training for peak performance
averaged and computed o-line and trials with omission and
commission errors were automatically excluded.
Behav ioural ta sk. e task consisted of 400 tria ls sequentially
presented to the subject every 3 seconds. ree categories of
visual stimuli were used:
1) 20 dierent images of animals – referred to later as A;
2) 20 dierent images of plants – P;
3)
20 dierent images of people of dierent professions
(presented together with an articial ‘novel’ sound)
referred to as H.
e trials consisted of presentations of pairs of stimuli
with inter-stimulus intervals of 1 s. Duration of stimuli
presentation was 100 ms. Four categories of trials were used:
A-A, A-P, P-P, and P-H (Fig. 1). In the trails with A-A and
P-P pairs, the rst and the second stimuli were identical
(physically the same). e trials were grouped into 4 sessions
with 100 trials in each. In each session, a unique set of 5
A stimuli, 5 P and 5 H stimuli was selected. Each session
consisted of a pseudo-random presentation of 100 pairs of
stimuli, with equal probability for each category and each
tr ial c ategory.
e task was to press a button with the right hand for all
A-A pairs as fast as possible, and to withhold from pressing
in response to other pairs. e par ticipant performed 10 trials
without recording to see if they understood the instruction.
He rested for a few minutes aer completing 100 trials.
Stimuli occupied about 3.8° of the visual eld around the
centre of the screen. Visual stimuli (were selected to have)
had similar 2D sizes and luminosities.
Artifact correction procedures. Eye blink artifacts were
corrected by zeroing the activation curves of individual
independent components corresponding to eye blinks. ese
components were obtained by application of Independent
Component Analysis (ICA) to the raw EEG fragments as
described in [9,10]. Epochs with excessive amplitude of
ltered EEG and/or excessive faster and/or slower frequency
activity were automatically marked and excluded from
further analysis. e exclusion thresholds were set as follows:
1) 100 μV for non-ltered EEG;
2) 50 μV for slow waves in 0–1Hz band;
3) 35 μV for fast waves ltered in the band 20–35Hz.
In addition, the recordings were visually inspected and
excluded remaining artifacts.
EEG spectra. EEG spectra were computed for Eyes Open,
Eyes Closed, and the GO/NOGO task conditions separately.
e artifact free fragments of EEG were divided into 4 sec
episodes with 50% overlap. e Hanning time window was
used [2]. EEG spectra were computed for each episode and
averaged. Mean value and standard deviations for each
0.25Hz bin were computed. For comparison of EEG spectra
pre- and post-intervention, the t-test was used.
Decomposition of collection of ERPs into independent
components. To obtain valid independent components, the
number of training points is essential (Onton and Makeig
2006). In this study, ERP’s from 215 healthy subjects recorded
under the HBIdb project were used [11].
ICA was performed on the full ‘ERP scalp location’ x
‘Time series’ matrix P. ERPs were constructed in response
to the second (S2) stimuli in the time interval of 700 ms aer
the second (S2) stimulus presentation for GO and NOGO
cues. Assumptions that underlie the application of ICA to
individual ERPs are as follows:
1) summation of the electric currents induced by separate
generators is linear at the scalp electrodes;
2)
spatial distribution of components’ generators remains
xed across time [12, 13].
e ICA method was implemented in the analysis soware
described in [14]. e topographies of the independent
components are presented as topographic maps, while time
courses of the components (also called ‘activation time
courses’) are presented as graphics with time corresponding
to the X-axis.
Spatial lters were obtained and applied to individual
ERPs in order to estimate the corresponding components in
a single individual [15]. e ERP independent components
of the subject who participated in the presented study were
compared with t he grand average ERPs of the healt hy controls
aged 24–25 (N= 46). e ERP independent components
of the subject were also compared between pre and post-
intervention conditions.
RESULTS
Behavioural data. e behavioural data, such as omission
and commission errors, reaction time and variance of the
reaction time, are presented in Table 2. When the parameters
of the rst recording were compared with the averaged
parameters of t he healthy control group of the corresponding
age, no statistically signicant at p<0.05 deviations from
the norms were found. It should be stressed, however, that
the subject is 100 ms faster than the average norm, which is
almost twice more consistent in response than the average.
However in the second recording, the subject performed
so consistently that the variance of reaction time became
statistically (p<0.05) smaller than the average norm.
Table 2. Parameters o f the subject’s per formance in the cued GO/NOGO
task in the rst an d second recording, compare d with the averaged data
of the healthy controls group
Omission
errors
Commission
errors
Reaction
time (RT)
Variance of
RT in ms
1 recording 0 0 273 39
2 recording 0 0 276 25
Healthy controls 4.4.% 0.6% 378 83
p-value of the
dierence from the
normal average
0.58 0.54 0.22 0.21
Spectra. In the rst recording, no statistically signicant
deviations from the reference were found in EEG spectra for
Eyes Open, Eyes Closed, and GO/NOGO task conditions. In
the second recording, compared with the rst recording, a
statist ically signic ant increase in high bet a activity was found
in central-frontal locations (Fig. 1A). e decomposition of
the background EEG into independent components revealed
3 independent components associated with this beta activ ity.
e topographies and sLOR ETA images of these components
are presented in Figure 1 B, C.
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Annals of Agr icultural and Enviro nmental Medicine 2014, Vol 21, No 4
Marek Grac zyk, Maria Pącha lska, Artur Ziółko wski, Grzegorz M ańko, Beata Łukaszewsk a, Kazimierz Kocha nowicz et al. Neurofeedback training for peak performance
Figure 1. Relative EEG spectra dierences between the rst and second recordings
A. Map of spect ra dierence (2 rec – 1 rec) at 25Hz .
B.
Relative sp ectra diere nce (2 rec – 1 re). Below the cur ve p-values o f the spectra
dierence. L arge vertical bar s – p<0.001, small vertical bars – p<0. 05).
C.
Maps and sLORETA images of independent components associated with increase
in beta ac tivity.
Event-related potentials. e largest changes in ERPs
induced by the intervention were observed for the NOGO
condition. Fig. 2A depicts ERPs computed for NOGO
condition in the rst (red line) and the second (green line)
conditions. At the bot tom, topographies at t he peak amplitude
at the rst and second recordings are presented. Fig 2B depicts
the two P3 NOGO independent components into which the
P3 NOGO is decomposed. ey are: 1) early P3 NOGO
component, and 2) the late P3 NOGO components. Time
courses and topographies of the components are presented
at the bottom. As can be seen, only the P3 NOGO late
component changes aer intervention.
Figure 2. ERP changes induced by inter vention
Raw ERP data for the NOGO condition in the rst (red
line) and the second (green line) conditions. Below are
topographies computed at the peaks of the NOGO P3 waves
(indicated by an arrow). e horizontal blue line indicates
the time interval with signicant pre-post changes at p<0.01.
Independent component P3 NOGO early. Above –
activation time courses for the rst and second recordings.
e horizontal blue line indicates the time interval with
signica nt pre-post changes at p<0.01. Below – topographies
at the peaks (indicated by an arrow).
Independent component P3 NOGO late. Above –
activation time courses for the rst and second recordings.
e horizontal blue line indicates the time interval with
signicant pre-post changes at p<0.01. Below – topographies
at the peaks (indicated by an arrow).
DISCUSSION
An Olympic athlete took part in 4peak performance tra ining
sessions with neurofeedback. e training protocol was
developed on the basis of results obtained by means of the
QEEG/ERPs method.
Spectra changes aer relative beta training. e results of
the presented study show that even short-term but intensive
training sessions in the peak performing subject changed
the beta activity over the trained electrodes. is beta
activity was decomposed into 3 independent components
localized in the somato-sensory strip. Taking into account
the positive relationship between the beta EEG activity
and underlying cortical metabolic activity [16], and the
results of decomposition of the increased beta activity into
3 independent components, it can be concluded that the
neurofeedback intervention in this subject induced elevation
of metabolic activity in the areas located near the Rolandic
ssure.
Post- pre-changes of event-related potentials. Only the P3
NOGO wave was changed in the course of training. As shown
in our previous paper [15], the P3 NOGO wave is decomposed
into 2 independent components: 1) the P3 NOGO early
component with latency of 340 ms and central distribution,
and 2) the P3 NOGO late component with latency of 400
ms and more frontal distribution. In this study [17], these
components were shown to be rather stable and did not change
within the time interval of up to several months. In the other
studies in which the task setting was manipulated [14] and
the components were correlated with neuropsychological
parameters [18], these 2 components were shown to have a
quite dierent functional meaning. e numerous results of
lesion studies enabled separation into 3quite independent
domains of the prefrontal lobe functioning, such as
energization, monitoring and task setting [19, 20].
In our previous studies, the P3 NOGO early component
disappeared when the subjects had to respond to GO
and NOGO cues with dierent hands [14], and strongly
correlated in amplitude with the parameters of energization
neuropsychological domain [18]. ese results enabled
association of the P3 NOGO early component with the
subject’s ability to sustain attention, to respond as fast as
possible, and to suppress the prepared action, i.e. with
energization domain.
In contrast, t he amplitude of the P3 NOGO late components
strongly correlated with the other neuropsychological
domain – the monitoring domain [19, 20], i.e. the ability
to keep the balance between speed and accuracy in task
performance. As the results of the presented study show, the
neurofeedback training resulted in a selective increase in the
energization component of the ERPs of the Olympic athlete
under study. erefore, it is a valuable technique to change
the brain a nd life of indiv iduals [21, 22, 23, 24], and therefore
it can help to overcome or more eectively manage a variety
of conditions in sportsmen who have lost the performance
condence aer injury in sport.
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Annals of Agr icultural and Enviro nmental Medicine 2014, Vol 21, No 4
Marek Grac zyk, Maria Pącha lska, Artur Ziółko wski, Grzegorz M ańko, Beata Łukaszewsk a, Kazimierz Kocha nowicz et al. Neurofeedback training for peak performance
CONCLUSIONS
e results of the presented st udy show that pea k performance
neurofeedback training in t he highly-performing sportsman
changed both t he spontaneous EEG pattern and ERPs in the
cued visua l GO/NOGO task. e peak performance training
resulted in a n increase in high beta ac tivity recorded centrally.
Taking into account the positive relationship between beta
EEG activ ity and underlying cort ical metabolic activ ity, and
the results of decomposition of the increased beta activity
into 3 independent components, it can be concluded that the
training induced elevation of metabolic activity in the areas
located near the Rolandic ssure. It can also be concluded
that Event-Related Potentials (ERPs) in the GO/NOGO task
can be used as valuable neuromarkers to assess functional
brain changes induced by urotherapeutical programmes.
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