Consumer-Grade Brain Stimulation Devices in Sports: A Challenge for Traditional Sport Psychology?

Abstract

The implementation of noninvasive brain stimulation (NIBS) techniques to improve sports performance is getting more and more popular. There are, however, practical and ethical concerns about the benefits of using NIBS in sports psychology. Two studies on the efficacy of two specific NIBS devices—AVWF method and OGIRO Modulation—were conducted and revealed no obvious benefits for cognitive and mental skills and psychophysiological activity in pupils and sport students. Recommendations derived from the empirical effectiveness of NIBS for the ethical application in routine training protocols are discussed. Finally, we suggest guidelines for sports psychologists who are faced with modern technological devices.

INTRODUCTION

The application of neuroscientific methods to improve physical performance in elite sports is increasingly of interest for coaches and athletes. Thus, the integration of such methods into the traditional work with athletes is a challenge for sport psychologists. Currently, there are numerous brain stimulation techniques available that may improve elite sports performance (Reardon, 2016). Several positive effects are promised by commercial providers, including enhanced mental abilities, superior stress coping skills, improved cognitive performance, and a more balanced autonomic nervous system (Conrady, 2013; Demmelbauer & Schmid, 2013b). In general, neuromodulation of the human brain can be achieved noninvasively by delivering magnetic, electric (Brunoni & Vanderhasselt, 2014), and auditory and visual bursts of pulses (Tang, Riegel, McCurry, & Vitiello, 2016) to predefined cortical regions. So far, there is little empirical evidence for the efficacy of brain-stimulation techniques on enhancement of sports-specific performance (Angius, Hopker, & Mauger, 2017).

Based on basic scientific knowledge (Hoogendam, Ramakers, & Di Lazzaro, 2010; Porges, 2007), companies recognized the potential of brain stimulation techniques in sports, and developed purchasable specific equipment to improve brain functions. Conclusions regarding the efficacy of noninvasive brain-stimulation (NIBS) techniques have been mainly derived from experimental studies with clinical samples. For instance, transcranial direct current stimulation and transcranial magnetic stimulation have been found to ameliorate mood states, aphasia symptoms, working memory functions, self-regulation disorders, and motor behavior (Berlim, Neufeld, & Van den Eynde, 2013; Berlim, Van den Eynde, & Daskalakis, 2013; Brunoni & Vanderhasselt, 2014; Málly, 2013; Schulz, Gerloff, & Hummel, 2013). These findings have stimulated research in healthy samples, suggesting that NIBS can also modulate typical behavior and performance (Angius et al., 2017). Facilitation effects evinced for various motor functions (including motor precision, motor learning, motor strength, acceleration, and endurance, as well as execution of daily motor task) and attentional skills (including sustained attention, focused attention, selective attention, attentional switch, and inhibition), as well as impulsive behavior, risk taking, working memory performance, planning, and deceptive capacities (for a recent review, see Levasseur-Moreau, Brunelin, & Fecteau, 2013). However, there is ongoing debate about the transferability of such enhancing effects into real-life situations. Specifically, there are concerns in terms of meaningfulness and safety of using such procedures beyond clinical conditions (Dresler et al., 2013; Kadosh, 2013; Levasseur-Moreau, Brunelin, & Fecteau, 2013; Pascual-Leone, Horvath, & Robertson, 2012). Dresler et al. (2013), for instance, warned against the premature use of NIBS techniques in healthy volunteers, especially in developmental samples, based on “hype or speculation” (p. 9). Besides ethical concerns surrounding the use of neuroenhancement methods in healthy participants (Farah, 2005; Farah et al., 2004; Schermer, 2008), there is an urgent need for research targeting cognitive side effects of NIBS (Hamilton, Messing, & Chatterjee, 2011), and long-term application of NIBS as pointed out by Helen Mayberg in an article by Fox (2011). Furthermore, issues that need to be clarified concern the optimization of stimulation parameters, the localization of stimulation, and participant's variability of neurophysiological and behavioral responses following NIBS (Clark & Parasuraman, 2014; Pascual-Leone et al., 2012; Ridding & Ziemann, 2010). Thus, current topics in the field of neuroenhancement research are dealing with the development of reliable, precise, and stable manipulations of the brain (Heinrichs, 2012).

With respect to elite sports, research using NIBS in experimentally controlled designs is still in its infancy. Much of the knowledge regarding the implementation and benefits of NIBS is limited to self-observations of athletes along with anecdotal reports of coaches and manufacturers of such techniques. Based on our daily work with athletes, coaches, and sports confederations, we feel that there exists a great deal of uncertainty about the benefits and risks of NIBS techniques for sports performance. It is thus of great importance that researchers and sports bodies call for well-controlled NIBS studies considering the specific needs and demands of athletes in elite sports disciplines. Although the scientific evidence base of NIBS in sports is still lacking (Banissy & Muggleton, 2013; Davis, 2013; Kadosh, 2013), neuroenhancement methods for improving sports performance have been available on the market for a fairly long time. Keeping in mind that there are several outstanding issues, such as how improvement of small-scale movements in the lab may translate to more complex movements in diverse sports settings (Banissy & Muggleton, 2013), it seems rather implausible that consistent effects of NIBS in sports occur, if any. Even if one assumes that all the broader open questions are solved, appropriate training protocols for specific kinds of sports, the integration of NIBS in the training process (Davis, 2013), and the timing of the NIBS (Stagg et al., 2011) have to be clarified before any application in sports can be recommended. Recently, our research group has been frequently asked to deliver expertise on the effects of brain-stimulating devices for elite athletes. Requests came from potential users of NIBS devices but also from NIBS manufacturers interested in scientific/empirical evaluation of their brain-stimulating devices. Providing evidence-based information to athletes and coaches, as well as to clubs and sports associations, is therefore a major challenge for the fields of sport psychology and sport physiology.

In this context, it is to be welcomed that companies actively pursue the evaluation of their products. According to Agazzi (1987), scientific work is performed by an open and adaptive scientific system with the global aim to produce objective knowledge that is afterward disseminated to society. The scientific system receives input from the environment in the form of request, support, and rejection and reacts in a creative manner to optimize the entire social system. Based on this system-theoretical background of the responsibility of science, we addressed the efficacy of two NIBS devices available on the market, which promise performance improvements in athletes.

It has to be mentioned that all brain stimulation methods imply a mechanistic conception of the world (Heinrichs, 2012). In an extreme version of this view, the human behavior is seen to be affected by external stimuli while neglecting internal (cognitive) processes. However, the active confrontation of the athlete with thoughts, attitudes, and mental skills appears to be necessary to influence well-established sport psychological constructs such as attention and visualization ability (Weinberg & Comar, 1994). In numerous sport psychological studies, it has been demonstrated that psychological skills training affects sport performance in a moderate positive way (Brown & Fletcher, 2017). In contrast, research on NIBS in sports still fails to provide empirical evidence on its efficacy. This raises the question of whether NIBS manipulations targeting neural functions have any effect on cognitive skills and psychophysiological activity of athletes. In two studies, we introduce a scientific approach toward addressing this issue, providing empirical evidence on NIBS with the intention to inform users and manufacturers. In particular, two commercially available NIBS devices are evaluated concerning their claim to enhance sports performance.

In the first experiment, the impact of weak magnetic fields was evaluated. According to the manufacturers of the tested device (Mentaltech OG, Sipbachzell, Austria), the application of weak magnetic fields changes the timing of a highly synchronized synaptic activity. As a result, a synchronized neuron pool is divided into separated miniclusters. To achieve a splitting of the neuron cluster in miniclusters, the transcranial magnetic stimulation has to be repeated numerous times. The magnetic impulse sequence has been developed by the company, and no detailed information is provided about the intensity and frequency of the magnetic pulses. By using a complex algorithm, the frequency that is especially tuned to neuronal activity is selected (Demmelbauer, 2010). Deeper knowledge on the operating principle and the development of the algorithm was not provided by the manufacturers. It has to be noted critically that the intensity of the weak magnetic fields is many times less than that of what is typically used for transcranial magnetic stimulation (TMS). Another important difference to typically applied TMS (Luber & Lisanby, 2014) is the administration of magnetic pulses by a small loop that is worn around the head like a headband. Hence, a spatially precise stimulation of a specific brain area is not possible. Based on these considerations, it is very unlikely that the magnetic stimulation through OGIRO® Modulation will influence brain activity in specific regions.

In the second experiment, the impact of sound modulated music was examined. The audio-visual perception (AVWF®) method targets the stimulation of the middle ear muscle by delivering frequency modulated music. Bursts of electrical pulses are then transferred to the vagus nerve, which affects the cerebrum and the autonomic nervous system. The stimulation of the vagus nerve is assumed to have a positive effect on the balance of the nervous system activation, which is disturbed under stress (Conrady & Hollnagel, 2008). By the application of slow, sound-modulated music, the ventral portion of the vagus nerve is thought to be excited. According to the polyvagal theory, this portion is responsible for social communication, self-soothing, and calming, as well as inhibition (Porges, 2001). The manufacturer of the AVWF method argues that the activation of the ventral portion of the vagus nerve leads to a state of homeostasis accompanied by a high sense of security. The well-balanced autonomic nervous system, assumed to promote a feeling of safety, is then expected to result in improvements of cognitive and motor performance (Conrady & Hollnagel, 2008).

The aforementioned assumptions related to the efficacy of the AVWF method are based on a broader phylogenetic/physiological theoretical framework (Porges, 2007). This framework, however, was not developed to predict sports-specific effects. The question arises of how a higher feeling of safety might result in better sport-specific performance. In a prior study, the influence of the AVWF method on brain activity was systematically and empirically evaluated in athletes, using functional hemodynamic brain imaging (Kronbichler, 2014). Results revealed that in comparison to nonmodulated music, sound-modulated music evoked relatively diminished blood flow in the motor and the premotor cortex and relatively higher blood flow in regions of the auditory cortex, as well as auditory thalamic regions. These differences in activation were interpreted as evidence for the efficacy of the AVWF method (Conrady, 2014). However, it has to be noted that no empirical evidence currently supports that AVWF method stimulates the vagus nerve in the promised way, which is suggested to be accompanied by a higher sense of safety. Assuming that this effect on feelings of safety might occur, however, it is not explained why this should lead to better sports performance or any improvements in sports-specific cognitive and motor abilities, respectively. Hence, it is concluded that the theoretical rationale of the AVWF method is grounded on unproved propositions. Thus, it is not expected that this method might lead to positive effects.

To address this substantial deficit of empirical evidence, in particular with respect to the specific situation and needs of athletes, two independent experiments were conducted to explore the efficacy of OGIRO Modulation and AVWF method in athletes. One goal of these efforts was to advance evidence-based recommendations for coaches and athletes, as well as for clubs and sports associations. Furthermore, the present findings are discussed with an emphasis on ethical aspects to raise awareness in researchers and sports bodies for a critical and responsible handling of NIBS in sports.

EXPERIMENT 1

The aim of the first study was to evaluate the effect of continuous magnetic stimulation on psychophysiological stress recovery, emotional stability, mental skills, and cognitive performance. According to the manufacturers, improvements in the aforementioned domains should go along with enhancements of sports performance (Demmelbauer & Schmid, 2013b). During a treatment, weak magnetic fields are emitted to a predefined cortical region via a tele loop, which is attached around the participant's head. As a result of this stimulation, neuronal activity in the targeted brain region should be positively influenced. In the present study, we assessed the impact of weak magnetic fields on these domains by using a neuropsychological test battery along with questionnaire data, in a group of athletes, compared to a placebo intervention group.

Method

Study Design

A double-blinded 2 (group) × 2 (time) intervention design with repeated measures was conducted. Prior to and after 10 sessions of magnetic stimulation or sham stimulation, a comprehensive test battery was administered.

Participants

One week prior to the pretests, 36 male sports students were recruited and underwent a derma-response analysis (DRA® mental-analysis). The purpose of this analysis was to screen participants for abnormalities in skin resistance (Demmelbauer & Schmid, 2013a). Based on the DRA mental-analysis, six participants were excluded from the study.

The remaining 30 participants were randomly assigned to a magnetic stimulation training group (n = 15; M_age = 23.83 years, SD = 2.55) and a sham group (SG; n = 15; M_age = 24.08 years, SD = 3.90). The participants engaged in different sports (such as soccer, tennis, track and field, and alpine skiing) with weekly training hours varying from 3 to 20 hr per week (M = 10.04; SD = 7.23 training hours per week). Seven participants only completed eight training sessions out of 10 and were excluded from further analyses. Prior to the study, each participant gave informed consent. The study protocol was approved by the Ethics Committee of the local university.

Procedures

Within 2 weeks, pretests, 10 training sessions, and posttests were carried out. Pre- and posttests consisted of three cognitive tests and two questionnaires. During the pretest laboratory visit, each participant received information about the correct fixation of the tele loop, as well as the handling of the OGIRO Modulation device to be able to use the device autonomously. Subsequently, participants performed one training session of 45 min per day over 10 days at home. During this period, participants were allowed to do other activities such as reading or watching television. The intensity and duration of the magnetic stimulation was configured by Mentaltech OG. No detailed information about the programming of the stimulation protocol was available from the manufacturer. The number of completed training sessions was automatically recorded by the device.

The SG wore the tele loop during the training sessions without receiving magnetic stimulation. Neither the participants nor the experimenter were aware of the status of the training device (i.e., whether or not it emitted magnetic waves). The group assignment codes were kept safe by staff members of the company during the experiment and were delivered to the experimenters upon completion of data collection.

Measures

A comprehensive test battery including objective cognitive performance tests, questionnaires, and assessments of psychophysiological recovery was administered to test for the promised effects of OGIRO Modulation on cognitive performance, well-being, mental skills, and psychophysiological stress recovery.

Using the Vienna Test System (Schuhfried, Austria), the Cognitrone (version S1), which is a general attention test (Wagner & Karner, 2012), and a complex reaction time task under time pressure, the so-called Determination Test (DT; version S1), were selected for assessing general attention ability, stress tolerance, and reaction time (Neuwirth & Benesch, 2012). Furthermore, a version of the Test for the Assessment of Selective Attention under Time Pressure in Sports (TESAZIS; Krenn, Hergovich, & Würth, 2012) was administered. The selective attention test comprises 94 sports videos presented for 1,940 ms by using the software DirectRT (Empirisoft, New York, NY). Immediately after the presentation, participants were asked to indicate the number of athletes in the video by pressing the corresponding key on the computer keyboard as quickly as possible.

During the TESAZIS and a relaxation phase of 3 min that immediately followed, psychophysiological parameters were recorded with a NeXus-10 device and the corresponding software Biotrace+ (Mind Media, Herten, the Netherlands). The sample rate was set to 2048 Hz for the electrocardiogram and to 32 Hz for skin conductance level (SCL), and skin temperature (T). The electrodes of the electrocardiogram were attached in accordance to lead II chest placement (Mind Media, 2004). Skin conductance electrodes were put on the medial phalanx of the forefinger and ring finger of the nondominant hand, the sensor for T was fixed at the fourth finger of the nondominant hand, and a respiration sensor was attached at the level of the umbilical mound. The mean value of heart rate (HR), the root mean square of successive differences (RMSSD) in heartbeats, SCL, and T were calculated for the last 30 s of the stress phase, as well as the first and the last 30 s of the final relaxation phase. No feedback was provided to participants.

Changes in mental competencies, attitudes, and well-being were measured by using the Questionnaire for the Assessment of Mental Skills and Attitudes in Sports (German: Fragebogen zur Erfassung mentaler Kompetenzen und Einstellungen im Sport [FEMKES]; Amesberger, in preparation) and a mental well-being questionnaire (German: Befindlichkeitsskala [BFS]; Abele-Brehm & Brehm, 1986). The FEMKES is a broad screening tool that measures the dimensions of mental skills, motivation, locus of control, and well-being on a Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree). In total, 29 subscales are included, such as self-regulation, concentration, and achievement motivation (all subscales are listed in Table 4), each consisting of three to five items. The BFS consists of 40 bipolar items (yes/no), representing the scales Activity, Anger, Elation, Excitement, Contemplation, Depression, Calmness, and Fatigue.

Statistics

Statistical analyses were conducted using the Statistical Package for Social Sciences (SPSS; version 20.0 for Microsoft Windows; SPSS Inc., Chicago, IL). For the analyses of changes in psychophysiological activity, 2 × 2 × 3 analyses of variance (ANOVAs) were used with group (magnetic stimulation, control) as the between-subjects factor and time (pre, post) as well as condition (stress, start of recovery, end of recovery) as within-subjects factors. To explore the extent of magnetic stimulation intervention effects, a set of 2 × 2 mixed-factors ANOVAs were calculated for all variables on cognitive performance and mental competencies. Group (magnetic stimulation, control) constituted the between-subjects factor and time (pre, post) the within-subjects factor. Effects were deemed significant when p < .05.

Results

Psychophysiological data of pre- and posttest for stress, and recovery phases are reported in Table 1. Results of the ANOVAs revealed significant effects of condition for SCL, F(1, 40) = 10.02, p < .01, _pη² = .33, 1−β = .96, and HR, F(1, 42) = 5.72, p < .01, _pη² = .21, 1−β = .81. Post hoc analyses yielded that SCL and HR of the last period of the recovery phase were significantly lower than scores during stress and at the beginning of the recovery phase. Significantly lower RMSSD scores were obtained at posttest compared to pretest, F(1, 34) = 6.31, p = .02, _pη² = .27, 1−β = .66. Regarding T, a significant interaction effect of Time × Condition was found, F(1, 42) = 7.51, p = .01, _pη² = .26, 1−β = .78. No other significant main effects and interactions were observed.

Table 1 Descriptive Statistics (Mean ± Standard Deviation) of Psychophysiological Activity in the Stress and Recovery Phases for IG and SG

			Stress phase		Start of recovery phase		End of recovery phase
Measure	n IG/n SG		IG	SG	IG	SG	IG	SG
SCL (µS)	10/12	Pretest	6.38 ± 4.66	3.84 ± 3.80	6.58 ± 5.01	3.82 ± 3.40	5.96 ± 4.56	3.45 ± 3.57
		Posttest	4.89 ± 3.79	2.77 ± 1.15	4.93 ± 3.73	2.85 ± 1.25	4.62 ± 3.64	2.56 ± 1.13
T (°C)	11/12	Pretest	28.45 ± 4.96	29.13 ± 4.92	28.48 ± 4.95	29.25 ± 4.30	28.81 ± 5.06	30.00 ± 4.21
		Posttest	31.13 ± 4.39	28.89 ± 4.72	31.08 ± 4.46	28.72 ± 4.63	30.88 ± 4.53	28.89 ± 4.76
HR (beats/min)	11/12	Pretest	63.09 ± 6.27	63.24 ± 8.64	63.81 ± 8.96	64.67 ± 9.98	61.88 ± 6.96	60.60 ± 9.74
		Posttest	64.75 ± 7.23	66.58 ± 12.34	63.61 ± 7.63	68.55 ± 12.92	62.45 ± 6.19	65.84 ± 9.26
RMSSD	11/8^a	Pretest	90.49 ± 57.82	106.70 ± 76.28	95.82 ± 53.84	94.53 ± 69.54	85.05 ± 53.94	92.54 ± 63.76
		Posttest	66.73 ± 28.65	69.86 ± 61.92	83.47 ± 39.81	86.37 ± 51.48	61.68 ± 26.75	94.17 ± 64.04

Note. IG = intervention group; SG = sham group; SCL = skin conductance level; T = skin temperature; HR = heart rate; RMSSD = root mean square of successive differences.

^a Four participants had to be excluded from RMSSD analysis due to a bad ECG quality during the stress phase that was still sufficient for determining HR.

Table 2 shows the psychophysiological and cognitive performance data before and after the treatment (OGIRO Modulation) in the intervention group (IG) and SG.

Table 2 Descriptive Statistics (Mean ± Standard Deviation) of Cognitive Performance Data for IG and SG

			Pretest		Posttest
Test	Measure	nIG/n SG	IG	SG	IG	SG
TESAZIS	No. of correct resp. (94 videos)	11/11	63 ± 13.36	54.91 ± 16.46	69.27 ± 8.83	63.73 ± 14.44
	Reaction time (ms)	11/11	3073 ± 165	2981 ± 481	2932 ± 135	2928 ± 214
COG	No. of correct resp. (80 items)	11/12	60.91 ± 7.98	57.42 ± 8.43	66.09 ± 6.47	67.08 ± 5.04
	No. of incorrect resp.	11/12	13.27 ± 4.84	12.58 ± 3.61	11.36 ± 4.72	12.67 ± 5.66
	Mdn reaction time of correct resp. (ms)	11/12	1118 ± 66	1108 ± 103	1091 ± 44	1103 ± 58
	Mdn reaction time of incorrect resp. (ms)	11/12	1214 ± 115	1211 ± 138	1188 ± 177	1194 ± 157
DT	No. of correct reactions	11/12	318.36 ± 31.96	308.33 ± 36.89	338.82 ± 16.84	339.92 ± 15.28
	No. of delayed reactions	11/12	24.45 ± 20.47	23.83 ± 21.44	8.18 ± 7.61	8.75 ± 10.19
	No. of incorrect reactions	11/12	16.00 ± 7.64	20.75 ± 18.13	13.64 ± 7.47	16.58 ± 11.20
	No. of omitted reactions	11/12	9.82 ± 11.75	16.58 ± 18.71	4.82 ± 8.34	3.25 ± 4.39
	Mdn reaction time (ms)	11/12	682 ± 51	687 ± 52	637 ± 45	622 ± 40

Note. IG = intervention group; SG = sham group; TESAZIS = test for the assessment of selective attention under time pressure in sports; COG = Cognitrone; resp. = responses; DT = Determination Test;

Results of the ANOVAs performed on psychophysiological recovery and cognitive performance variables are summarized in Table 3. Neither significant interaction of factors time and group nor significant differences between groups were obtained for the psychophysiological and cognitive performance data. Significant effects of time were found for T indicating less change at posttest. The number of correct responses in TESAZIS, Cognitrone, and DT showed a significant increase from pre- to posttest. In addition, DT scores of delayed and omitted reactions as well as median reaction time demonstrated significant decreases (see Table 3).

Table 3 Results of Time × Group Mixed-Factors Analyses of Variance for Cognitive Performance Data as a Function of OGIRO Modulation

		Time × Group					Time					Group
Test	Measure	df	F	p	η^2	1−β	df	F	p	η^2	1−β	df	F	p	η^2	1−β
TESAZIS	No. of correct responses	1, 20	0.72	.41	.04	.13	1, 20	25.16	< .001^***	.56	.99	1, 20	1.50	.24	.07	.21
	Reaction time	1, 20	0.57	.46	.03	.57	1, 20	2.70	.12	.12	.35	1, 20	0.21	.65	.01	.07
COG	No. of correct responses	1, 21	2.39	.14	.10	.31	1, 21	26.20	< .001^***	.56	.99	1, 21	0.23	.63	.01	.08
	No. of incorrect responses	1, 21	1.41	.25	.06	.21	1, 21	1.18	.29	.05	.18	1, 21	0.03	.87	.01	.05
	Mdn reaction time of correct resp.	1, 21	1.15	.30	.05	.18	1, 21	0.50	.49	.02	.10	1, 21	0.06	.82	.01	.06
	Mdn reaction time of incorrect resp.	1, 21	0.02	.90	.01	.05	1, 21	0.52	.48	.02	.11	1, 21	< .001	.98	.01	.05
DT	No. of correct reactions	1, 21	1.73	.20	.08	.24	1, 21	37.86	< .001^***	.64	1	1, 21	0.18	.67	.01	.07
	No. of delayed reactions	1, 21	0.05	.83	< .01	.06	1, 21	31.85	< .001^***	.60	1	1, 21	0.01	.99	.01	.05
	No. of incorrect reactions	1, 21	0.30	.59	.01	.08	1, 21	3.94	.06	.16	.47	1, 21	0.65	.43	.03	.12
	No. of omitted reactions	1, 21	3.27	.09	.14	.41	1, 21	15.82	< .01^**	.43	.97	1, 21	0.34	.57	.02	.09
	Mdn reaction time	1, 21	4.14	.06	.17	.49	1, 21	118.81	< .001^***	.85	1	1, 21	0.08	.78	.01	.06

Note. TESAZIS = test for the assessment of selective attention under time pressure in sports; COG = Cognitrone; DT = Determination Test.

^** p <.01.

^*** p < .001.

The descriptive statistics for mental competencies, attitudes, and well-being are presented in Table 4. No significant main effects of time and significant interaction effects between time and group were observed for the scales of the FEMKES. Participants of the IG, however, scored significantly higher on the “external locus of control” scale, compared to participants of the SG, across pre- and posttesting, F(1, 20) = 6.65, p = .02, _pη² = .24, 1−β = .66. None of the remaining scales of the FEMKES was systematically influenced by the factor group. In terms of mental well-being (BFS), the SG showed overall higher scores on the “depression” scale than the IG across both measurement times, F(1, 21) = 4.49, p < .05, _pη² = .18, 1−β = .53. No other main or interaction effects approached statistical significance.

Table 4 Descriptive Statistics (Mean ± Standard Deviation) for Questionnaire Data Before and After OGIRO Modulation

		Pretest		Posttest
Test	Measure	IG^a	SG^b	IG	SG
FEMKES	Self-regulation	3.84 ± 0.41	3.80 ± 0.61	3.88 ± 0.54	3.63 ±1.28
scale from 1–5	Relaxation	2.96 ± 0.89	3.60 ± 0.88	3.08 ± 0.94	3.85 ± 0.71
	A-o planning	3.97 ± 0.53	4.11 ± 0.57	3.97 ± 0.60	4.08 ± 0.65
	A-o after poor performance	3.00 ± 0.79	2.97 ± 0.76	3.02 ± 0.89	3.23 ± 0.78
	Concentration	3.90 ± 0.44	3.85 ± 0.76	3.82 ± 0.43	3.90 ± 0.76
	Outcome goal	3.57 ± 0.67	3.44 ± 0.83	3.67 ± 0.94	3.67 ± 0.89
	Process goal	3.53 ± 0.59	3.81 ± 0.70	3.93 ± 0.62	3.83 ± 0.72
	Performance goal	3.33 ± 0.63	3.25 ± 0.99	3.63 ± 0.74	2.97 ± 0.74
	Imagination	3.78 ± 0.58	3.70 ± 0.82	3.92 ± 0.65	4.05 ± 0.77
	Mental preparation	3.22 ± 0.88	3.08 ± 0.77	3.42 ± 1.10	3.12 ± 0.99
	Hope of success prior to competition	4.00 ± 0.52	4.28 ± 0.51	4.03 ± 0.60	4.14 ± 0.80
	Fear of failure prior to competition	2.13 ± 1.02	2.14 ± 1.07	1.97 ± 0.79	2.06 ± 0.95
	Hope of success during competition	3.67 ± 0.72	3.53 ± 1.37	3.83 ± 0.77	3.86 ± 1.36
	Fear of failure during competition	2.40 ± 0.86	1.92 ± 0.80	2.27 ± 0.90	1.81 ± 0.80
	Achievement motivation	4.10 ± 0.54	4.13 ± 0.66	4.26 ± 0.47	4.05 ± 0.71
	Ego-orientation	3.80 ± 0.98	2.78 ± 1.05	3.73 ± 1.20	3.22 ± 1.15
	Task-orientation	4.53 ± 0.42	4.56 ± 0.41	4.30 ± 0.48	4.56 ± 0.36
	Social approval	4.07 ± 0.58	3.22 ± 1.17	3.87 ± 1.03	3.17 ± 1.18
	External locus of control	2.90 ± 0.88	2.31 ± 0.58	2.97 ± 0.96	2.00 ± 0.75
	Internal locus of control	4.33 ± 0.50	4.27 ± 0.58	4.41 ± 0.43	4.53 ± 0.44
	Fatalistic locus of control	2.33 ± 0.85	1.94 ± 0.65	2.36 ± 0.60	1.72 ± 0.71
BFS bipolar scale yes/no	Activity	.60 ± .37	.42 ± .40	.56 ± .37	.37 ± .39
	Anger	.84 ± .37	.95 ± .17	.82 ± .40	.97 ± .12
	Elation	.51 ± .40	.35 ± .36	.38 ± .30	.20 ± .31
	Excitement	.75 ± .31	.87 ± .20	.84 ± .29	.82 ± .29
	Contemplation	.67 ± .24	.72 ± .25	.60 ± .36	.70 ± .20
	Depression	.73 ± .41	.97 ± .08	.76 ± .40	.95 ± .12
	Calmness	.38 ± .33	.27 ± .31	.33 ± .37	.23 ± .28
	Fatigue	.69 ± .38	.77 ± .34	.67 ± .37	.75 ± .32

Note. IG = intervention group; SG = sham group; FEMKES = Fragebogen zur Erfassung mentaler Kompetenzen und Einstellungen im Sport (Questionnaire for the Assessment of Mental Skills and Attitudes in Sports); A-o = Action-organization; BFS = Befindlichkeitsskala.

^a n = 10.

^b n = 12.

Discussion

The purpose of Study 1 was to evaluate effects of the OGIRO Modulation on psychophysiological stress recovery, well-being, mental skills, and cognitive performance in athletes. None of the ANOVAs revealed a significant Time × Group interaction, Thus, the present findings do not indicate that magnetic stimulation effected by OGIRO Modulation facilitate psychophysiological stress recovery, mental well-being, and cognitive performance as proposed by Demmelbauer and Schmid (2013b). On the contrary, our findings are in line with several methodological concerns regarding the application of NIBS in real-world settings. For instance, the magnetic field strength was lower than usually applied in TMS practice and research (Rossi, Hallett, Rossini, & Pascual-Leone, 2009). Moreover, effects of magnetic stimulation are supposed to increase when specific cortical regions are stimulated precisely (Luber & Lisanby, 2014). OGIRO Modulation, however, applies the magnetic field by a tele loop that distributes the magnetic waves very imprecisely to the scalp. Finally, it is worth considering whether a single method can be appropriate to improve a variety of physiological and behavioral aspects, such as regeneration, emotional stability, mental skills, and cognitive performance as proposed by OGIRO Modulation. In prior experimental studies, facilitating TMS effects have been converged to occur in tasks tapping into specific cognitive skills, such as sustained attention, selective attention, or focused attention (Levasseur-Moreau et al., 2013). To our knowledge, there is no empirically tested NIBS method, which is appropriate to enhance various abilities equally well. We conclude that the magnetic stimulation technique as applied in our study does not provide any advantage to athletes. At the present time, we thus cannot recommend the application of OGIRO Modulation in athletes.

EXPERIMENT 2

The goal of the second study was to test the impact of a specific audiovisual perception enhancement technique on cognitive performance and psychophysiological balance. According to the manufacturers, AVWF improves depth sensitivity, prosocial behavior, regeneration, and coping with stress, and it leads to a reduction of tension, superior concentration, and optimized balance of the autonomic nervous system. Moreover, these facilitating effects should be transferred to sports situations in order to augment sports performance of elite athletes (Conrady, 2013). The present experiment set out to explore possible effects of the AVWF method on cognitive performance and autonomic balance in high school students who have an emphasis on sports in their curriculum.

Method

Study Design

A pseudoexperimental single blind study was conducted using a 3 (group) × 3 (time) design with repeated measures. The IGs and control group (CG) were tested immediately before and after a 14-day intervention period, and a third time 4 months after the posttests.

Participants

A group of 57 high school students (22 female) with an emphasis on sports in their curriculum volunteered in the second study. The students attended Grades 9 to 11 and participated in 6 to 8 hr of sports per week. Due to organizational reasons, students were not randomly assigned to the IGs and CG. Participants of the IGs wore the AVWF device but were not aware of whether they were to listen to modulated or typical music. Before and after the AVWF intervention, participants were administered a psychophysiological and cognitive test battery. The CG was also tested repeatedly but with no music intervention in between. The participant characteristics are shown in Table 5. The sample size was reduced with continuation of the study due to absence from intervention or testing (n = 5), technical problems (n = 3 in TESAZIS), or time constraints concerning schedule (n = 11 in d2 Attention and Stress Test). Regarding psychophysiological data, six students were excluded due to artifacts. The study was approved by the Ethics Committee of the department by the local educational board. The parents gave informed consent about the participation of their children.

Table 5 Assigned Groups and Participants Characteristics

Group	Grade	Age (M ± SD)	M	F	Total
Music group	9	15.41 ± .51	9	11	20
AVWF group	10	16.16 ± .90	10	15	25
Control group	11	16.90 ± .32	3	9	12

Procedures

The IGs and CG were tested immediately before and after a 14-day intervention period, and a third time 4 months after the posttests. The intervention consisted of 10 music sessions, each lasting 50 min, and took place within the regular curriculum in a free period. While listening to the music, participants were allowed to complete homework, to read, or talk to one another. The selection and manipulation of music followed the procedure of the AVWF manufacturers. No detailed information on the manipulation of the music is provided by the manufacturers. Participants of the IGs listened to the same pieces of music (e.g., first session: music from Grieg; second session: music from Mozart; 10th session: music from Haydn).

Measures

The d2 Attention and Stress Test (Brickenkamp, 2002), the DT (version S1; Neuwirth & Benesch, 2012), and the TESAZIS (see Experiment 1) were used at pretest, posttest, and follow-up assessments.

The electrocardiogram and respiration rate were recorded for 3 min prior to the cognitive testing in order to assess the basal psychophysiological state, as propagated by the manufacturers. The attachment of electrodes and the sample rate followed the same protocol as described in Experiment 1. Data were visually corrected for artifacts and then segmented into 150-s epochs. Epochs were exported to the software Kubios HRV version 2.0 (Tarvainen, Niskanen, Lipponen, Ranta-Aho, & Karjalainen, 2014) to analyze the HRV parameters. The R-R intervals were interpolated at a rate of 4 Hz. The artifact correction option was adjusted at a medium correction level. In the time domain, the RMSSD was chosen, which reflects parasympathetic activity. An autoregressive model was used to calculate the HF component (0.15–0.4 Hz) in normalized units (HFnu). HFnu represents the percentage of the power in the HF band related to power of the low frequency and the HF band (0.04–0.4 Hz). This parameter reflects parasympathetic activity (Malik et al., 1996).

Statistics

Statistical analyses were conducted using SPSS, version 20.0 for Windows. For each dependent variable, a 3 × 3 mixed-factors ANOVA was calculated with group (AVWF, Music, Control) as the between-subjects factor and time (pre, post, follow-up) as the within-subjects factor to assess potential intervention-induced effects. Greenhouse-Geisser corrected values are reported.

Results

Test scores obtained at pretest, posttest, and follow-up assessments as a function of participant group are listed in Table 6. The number of participants that are included in the calculation differs across tests (see Participants) and is described in Table 6 for each test.

Table 6 Descriptive Statistics (Mean ± Standard Deviation) for Psychophysiological and Cognitive Data as a Function of Participant Group and Assessment Time

			Pre-test			Post-test			Follow up
Test	Measure	n1/n2/n3	Music group	AVWF® group	Control group	Music group	AVWF® group	Control group	Music group	AVWF® group	Control group
Psycho-physio- logical values	RMSSD	17/19/10	51.49 ± 30.44	60.97 ± 23.27	45.14 ± 17.43	47.39 ± 15.50	64.07 ± 28.96	41.03 ± 15.88	48.81 ± 19.09	65.13 ± 40.41	49.07 ± 21.23
	HF (%)	17/19/10	26.26 ± 16.42	28.15 ± 11.90	24.15 ± 8.49	20.42 ± 12.07	28.00 ± 15.24	23.70 ± 7.68	24.71 ± 13.90	31.37 ± 15.73	25.35 ± 12.30
	LF/HF	17/19/10	2.45 ± 2.74	1.94 ± 1.76	2.49 ± 1.18	2.51 ± 1.76	2.02 ± 1.80	1.83 ± .89	2.61 ± 1.89	1.56 ± 1.42	1.89 ± .96
	respiration rate	17/19/10	16.51 ± 3.88	16.89 ± 3.80	16.71 ± 3.26	17.87 ± 4.54	18.28 ± 3.89	17.35 ± 1.40	17.41 ± 4.22	18.07 ± 3.10	16.18 ± 2.59
TESAZIS (30 videos)	number of correct responses	15/22/12	14.27 ± 4.88	15.73 ± 4.12	14.50 ± 4.23	14.93 ± 4.91	17.36 ± 4.98	16.25 ± 3.91	16.53 ± 3.74	17.45 ± 4.06	18.33 ± 4.03
	reaction time (ms)	15/22/12	3096 ± 284	3133 ± 139	3107 ± 202	2996 ± 332	3069 ± 148	3045 ± 176	2998 ± 299	3045 ± 170	3058 ± 229
DT	number of correct reactions	18/22/12	243.67 ± 30.06	239.14 ± 23.65	245.33 ± 23.57	264.41 ± 34.16	269.91 ± 29.86	260.92 ± 21.28	268.28 ± 32.95	266.14 ± 36.71	263.42 ± 24.67
	number of delayed reactions	18/22/12	66.72 ± 14.96	59.23 ± 14.82	60.00 ± 16.13	73.67 ± 18.64	71.55 ± 17.42	63.08 ± 13.77	75.28 ± 18.98	69.27 ± 21.84	65.08 ± 18.76
	number of incorrect reactions	18/22/12	25.17 ± 16.42	20.91 ± 9.56	20.83 ± 12.14	29.06 ± 13.91	26.41 ± 15.15	29.25 ± 8.19	30.78 ± 13.86	27.36 ± 15.88	25.00 ± 10.26
	number of omitted reactions	18/22/12	17.39 ± 6.39	22.45 ± 6.52	24.08 ± 9.41	17.56 ± 6.72	19.64 ± 6.90	24.25 ± 8.35	18.61 ± 8.81	20.36 ± 13.55	23.33 ± 11.89
	median reaction time (ms)	18/22/12	769 ± 70	744 ± 50	727 ± 54	704 ± 55	681 ± 42	668 ± 47	694 ± 49	676 ± 52	677 ± 47
d2 Attention and stress test	total number	15/17/6	428.13 ± 85.78	433.29 ± 84.00	433.17 ± 60.58	498.87 ± 68.03	481.76 ± 85.61	511.83 ± 67.12	536.27 ± 63.68	510.76 ± 89.32	547.67 ± 65.29
	errors (%)	15/17/6	7.68 ± 4.72	8.61 ± 5.46	7.16 ± 9.67	4.26 ± 2.51	5.31 ± 3.61	2.98 ± 4.29	4.06 ± 3.39	4.90 ± 3.62	2.62 ± 3.21
	reactions minus errors (GZ -F)	15/17/6	395.47 ± 71.74	392.94 ± 58.85	401.33 ± 67.93	478.06 ± 62.13	454.47 ± 70.60	496.17 ± 66.37	514.93 ± 61.14	484.18 ± 76.79	517.67 ± 72.02
	concentration score (KL)	15/17/6	148.80 ± 30.28	142.88 ± 20.17	149.00 ± 46.82	192.20 ± 31.90	177.71 ± 29.87	203.33 ± 36.73	210.47 ± 35.42	193.94 ± 36.04	219.17 ± 39.43

Note. n1 = sample size of the music group; n2 = sample size of the AVWF group; n3 = sample size of the control group; RMSSD = root mean square of successive differences; HF = high frequency band (0.15–0.4 Hz); LF = low frequency band (0.04–0.15 Hz); TESAZIS = test for the assessment of selective attention under time pressure in sports; DT = Determination Test

Table 7 summarizes the ANOVA results for each dependent variable. None of the psychophysiological and cognitive variables revealed a significant Time × Group interaction. For 10 of 15 variables, a significant time effect was obtained in nearly all objective performance variables indicating faster processing time and higher number of correct responses in TESAZIS, DT, and d2 Attention and Stress Test over time. Groups did not differ significantly across all measures examined.

Table 7 Results of Time × Group Mixed-Factors Analyses of Variance for Psychophysiological and Cognitive Data as a Function of AVWF Modulation

		Time × Group					Time					Group
Test	Measure	df	F	p	η^2	1−β	df	F	p	η^2	1−β	df	F	p	η^2	1−β
Psycho	RMSSD	4, 86	0.34	.82	.02	.12	2, 86	0.37	.65	.01	.10	2, 43	3.19	.05	.13	.58
physiological	HF (%)	4, 86	0.39	.80	.02	.13	2, 86	0.88	.41	.02	.19	2, 43	1.50	.24	.07	.30
parameters	LF/HF	4, 86	0.49	.73	.02	.16	2, 86	0.41	.65	.01	.74	2, 43	1.18	.32	.05	.24
	Respiration rate	4, 86	1.07	.38	.05	.31	2, 86	5.74	< .01^**	.12	.86	2, 43	0.30	.74	.01	.09
TESAZIS	No. of correct responses	4, 92	1.05	.39	.04	.30	2, 92	11.82	< .001^***	.20	.99	2, 46	0.79	.46	.03	.18
	Reaction time	4, 92	0.46	.77	.02	.15	2, 92	11.24	< .001^***	.20	.99	2, 46	0.29	.75	.01	.09
DT	No. of correct reactions	4, 98	1.10	.35	.04	.28	2, 98	34.27	< .001^***	.41	1	2, 49	0.03	.97	< .01	.05
	No. of delayed reactions	4, 98	0.70	.58	.03	.21	2, 98	7.21	< .01^**	.13	.90	2, 49	1.43	.25	.06	.29
	No. of incorrect reactions	4, 98	0.59	.64	.02	.17	2, 98	7.78	< .01^**	.14	.91	2, 49	0.50	.61	.02	.13
	No. of omitted reactions	4, 98	0.56	.64	.02	.16	2, 98	0.23	.73	.01	.08	2, 49	2.40	.10	.09	.46
	Mdn reaction time	4, 98	1.57	.20	.06	.41	2, 98	163.23	< .001^***	.77	1	2, 49	1.69	.20	.06	.34
d2 Attention	Total number	4, 70	1.44	.23	.08	.41	2, 70	82.89	< .001^***	.70	1	2, 35	0.24	.79	.01	.08
and Stress Test	Errors	4, 70	0.08	.96	.01	.06	2, 70	0.08	.96	.01	.06	2, 35	0.67	.52	.04	.15
	Sum of reactions minus errors	4, 70	1.68	.17	.09	.47	2, 70	137.00	< .001^***	.80	1	2, 35	0.57	.57	.03	.14
	Concentration score	4, 70	1.43	.24	.08	.37	2, 70	140.12	< .001^***	.80	1	2, 35	1.14	.33	.06	.23

Note. RMSSD = root mean square of successive differences; HF = ; LF = ; TESAZIS = Test for the Assessment of Selective Attention under Time Pressure in Sports; DT = Determination Test.

^** p < .01.

^*** p < .001.

Discussion

In this study, we assessed possible changes in cognitive performance and autonomic balance following AVWF application in adolescent athletes. In line with Study 1, we did not find any facilitating effects of brain stimulation, compared to participants of the IG without brain stimulation and the CG. Assumptions regarding the efficacy of the AVWF are based on a broader phylogenetic theoretical framework, which targets the prediction of psychophysiological processes. Within this framework, Porges (2007) described three autonomic subsystems that are linked to social communication, mobilization, and immobilization. The AVWF method utilizes sound modulated music, which is thought to regulate the vagus nerve, and behaviorally related social behavior, to change the activation pattern of higher brain regions. Thus, the athletes’ autonomic nervous system should be more balanced, which promotes feelings of safety. In the current study, AVWF did not induce changes of vagus nerve activity in a resting condition. Even if sound-modulated music induces augmented vagus activity, and concurrently a state of high security in competitive situations, it remains unclear whether mental and cognitive aspects of athletes are influenced at all, and if so, how this may lead to higher sports performance. Conrady's (2013) conclusions regarding the efficacy of AVWF on the basis of polyvagal theory in sports are rather speculative and are not supported by empirical evidence so far. Our study showed that AVWF has no enhancing effects on mental well-being, cognitive performance, and stress recovery in a group of high school students who have an emphasis on sports in their curriculum. Although no obvious side effects or other disadvantages have been reported by the participants or teachers/coaches, we cannot recommend the implementation of AVWF in sports at this point in time.

GENERAL DISCUSSION

By conducting two studies on the efficacy of NIBS in sports, we responded to requests of coaches, athletes, and sports officials, as well as NIBS manufacturers, to provide an empirical evaluation of possible enhancing effects of currently advertised brain stimulation methods, namely, OGIRO Modulation and AVWF. We tried to meet the requirements on scientific research by taking up inputs from the environment and reacting as a scientist in a creative manner in order to provide knowledge to society as proposed by Agazzi (1987). The willingness to explore promising NIBS methods offered by companies is a prerequisite to give scientifically sound recommendations regarding their efficacy in sports. So far, there is no scientific evidence that the two NIBS methods examined here provide any performance advantage in sports. Only two different NIBS methods, however, were tested in the present research. Therefore, the possibility exists that other NIBS methods may be effective in improving sports performance. It is expressly pointed out that the study results cannot be generalized to other commercially available NIBS methods.

As a main result, we found that OGIRO Modulation and AVWF are not superior to placebo and nontreatment conditions. It is most likely that the observed changes from pre- to postassessments across groups are due to practice effects. Specifically, in Experiment 2, the CG showed increases on measures of TESAZIS, DT, and d2 Attention and Stress Test, which did not systematically diverge from the change scores of the two IGs. The findings of the studies at hand illustrate the present state of research outlined by Davis (2013), who suggested that more research is needed on the appropriate doses and implementation of brain stimulation in the training process outside from the laboratory in order to guarantee efficacy in elite athletes. It seems that there is a gap between empirically validated treatment outcomes and the assumptions of the NIBS manufacturers that were tested in the two studies, regarding the merit of their devices in sports. At present, the available evidence suggests that the two NIBS methods cannot yet be recommended for use in sports. However, this does not mean that NIBS will not have the potential to be a key technology in the future of sports and sports medicine, as speculated by Davis. Moreover, NIBS might not be the only way of modifying brain activity to enhance performance in sport. There is a further promising parallel line of research in sports recognizing that internal processes can be trained noninvasively through the feedback of brain activity (Mirifar, Beckmann, & Ehrlenspiel, 2017).

A limitation of our studies is that sports students and students at a school with an emphasis on sports in their curriculum were recruited instead of elite athletes. However, the developers of the two tested devices promise the same beneficial effects for nonelite athletes as well as elite athletes. Furthermore, Davis (2013) stated that elite athletes may not gain from brain doping as he described TMS or sound modulated music because they “are already performing close to the physical limits of the human body” (p. 650). He further suggested that it is likely that nonexperts and healthy participants, who have not reached their physical maximum, may benefit more from brain stimulation, compared to elite athletes. This reasoning would apply for the present set of studies. As a methodological limitation the assignment of participants to the IGs and CG in Experiment 2 was not random due to organizational reasons. As a consequence, the age between the three tested groups was slightly different, by a range of 1.5 years. Thus, it cannot be excluded that the different age in this critical and sensitive period of brain development (Steinberg, 2010) with respect to gray matter (Gogtay & Thompson, 2010), white matter (Paus, 2010), structural connectivity (Schmithorst & Yuan, 2010), and neurotransmission (Doremus-Fitzwater, Varlinskaya, & Spear, 2010) might have influenced study results. However, according to assumptions of the manufacturer, the tested method should result in improvements regardless of age. A third limitation represents the fact that no detailed information on the applied protocols was provided by the manufacturer. It is impossible to fully evaluate the proposed benefits and mechanisms underlying any benefits of NIBS devices until manufactures provide more detail about the basic science underpinning what their devices do and how they are purported to elicit changes to brain activity and behavior. A further limitation arises by reducing the test instruments to cognitive and psychophysiological measurements in our studies. In high elite sport, for instance, the significant question is not only whether a NIBS method improves cognitive skills and psychophysiological states but rather whether these alterations enhance sport performance. However, as long as a substantial impact of NIBS methods on basal cognitive and psychophysiological measures is empirically not evident, the link to sport performance becomes obsolete. Consequently, in a first step, manufacturers and researchers should focus on the development and/or modification of devices that stimulate brain activity in a reliable and valid manner. Only then can the causal chain be extended to other areas of human behavior like sport performance. The consecutive step-by-step approach, in turn, can avoid the raising of premature and unrealistic expectations of potential users on NIBS devices. However, one might argue that NIBS has substantial impact on human behavior in terms of a placebo effect rather than in terms of alterations of brain activity. This aspect was not addressed by our research but seems to be considerable for further studies in this field.

Finally, ethical considerations have to be considered when applying NIBS. Irrespective of the current knowledge on the effectiveness of NIBS in real-world settings, NIBS may represent an unfair means to gain a performance advantage (Schermer, 2008). For example, Davis (2013) denoted the use of NIBS in healthy people as neurodoping. He argued that in the future, the modulation of brain activity during training will lead to benefits comparable to those of drugs. In his opinion, each sports discipline should advance an informed decision regarding the extent to which neurodoping is considered cheating. In the field of ethics in medicine, NIBS is considered under four principles of principlism (Brukamp & Gross, 2012), in particular, autonomy, beneficence, and nonmaleficence, as well as justice. The principle of autonomy suggests that the athlete should have the ability to choose NIBS or not. Important to note, using NIBS must not represent a coercive pressure toward success (Farah et al., 2004). The principles of beneficence and nonmaleficence seek to maximize benefit and to minimize harm. Justice is related to a fair distribution of NIBS methods. Everybody should get the possibility to benefit from neuroenhancement. Thus, these four principles might be fruitful in the conceptualization of ethical standards for the application of NIBS in sports.

Providing empirical data may not directly translate into recommendations for practitioners and sport federations. We suggest that empirical results should be provided to sport psychologists and suitable sport associations. Moreover, dissemination of the results should involve discussions about theoretical and methodological issues. It should also be noted that findings of experimental studies represent a snapshot of various aspects, such as participant characteristics, sample size, and measures used. The final responsibility concerning the application of NIBS devices has to be taken by the potential user or, in case of minors, by legal guardians. When advertising NIBS devices, the manufacturers should also inform the public about the limits and benefits of their products, suggested by the findings of well-controlled studies.

To our knowledge, the present studies are the first attempts to address the efficacy of consumer-grade NIBS devices for application in sports. Our research was based in the scientific realm, and thus took an experimental approach, in which interventions are systematically compared under different experimental manipulations using sham and randomized control groups. There is still a lack of basic research in order to offer scientifically tested NIBS devices for real-world settings. Furthermore, there are still pending questions regarding the kind of stimulation, the duration and frequency of the stimulation, the location of stimulation, long-term application, sports-specific training protocols, the integration of NIBS in the training process, and many more. Addressing these questions, an individualized prescription of NIBS rather than a one-size-fits-all approach appears to be required to maximize the chances of beneficial effects on sports performance. Thus, it is recommended that one clarify these aspects at first in laboratory studies before NIBS methods are applied in field settings. However, reality tells a different story, with manufacturers who might skip this first step.

Concerning the application of NIBS, sport psychologists and coaches are additionally faced with ethical issues: What are the benefits and risks of NIBS, and how well do they have to be established before use can be recommended? Would a potential placebo effect (which was not shown in our experiments) justify the use of NIBS in elite sports? What information on NIBS is needed in order to provide well-justified recommendations to sport federations about the use of NIBS in athletes? Of importance: Is the application of NIBS a kind of doping?

In conclusion, ethical aspects of the application of NIBS in healthy persons and especially in athletes should be discussed in the future. Before the application of NIBS in sports can be recommended, well-established scientific knowledge meeting widely accepted theoretical, empirical, and ethical standards must be gained. Such an approach will ultimately enable the field to establish safe and effective NIBS methods that are considered ethically acceptable.