Movement-related desynchronization of alpha rhythms is lower in athletes than non-athletes: A high-resolution EEG study

Clinical Neurophysiology 121 (2010) 482–491

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Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph

Movement-related desynchronization of alpha rhythms is lower in athletes than non-athletes: A high-resolution EEG study Claudio Del Percio a, Francesco Infarinato b, Marco Iacoboni a, Nicola Marzano c, Andrea Soricelli c,d, Pierluigi Aschieri e,f, Fabrizio Eusebi a,g, Claudio Babiloni h,i,* a

Dipartimento di Fisiologia e Farmacologia, Università ‘‘Sapienza”, Roma, Italy IRCCS San Raffaele Pisana Roma, Italy IRCCS SDN Istituto di Ricerca Diagnostica e Nucleare, Napoli, Italy d Università degli Studi di Napoli Parthenope, Napoli, Italy e Federazione Italiana Judo Lotta Karate ed Arti Marziali (FIJLKAM), Roma, Italy f Facoltà di Scienze Motorie, Università de L’Aquila, L’Aquila, Italy g IRCCS Neuromed, Via Atinense 18, I86077 Pozzilli (Isernia), Italy h Department of Biomedical Sciences, University of Foggia, Foggia, Italy i Casa di Cura San Raffaele Cassino (FR), Italy b c

a r t i c l e

i n f o

Article history: Accepted 4 December 2009 Available online 22 January 2010 Keywords: EEG Alpha event-related desynchronization (ERD) Hand movement Elite karate athletes

a b s t r a c t Objective: The ‘‘neural efficiency” hypothesis posits that neural activity is reduced in experts. Here we tested the hypothesis that compared with non-athletes, elite athletes are characterized by a reduced cortical activation during simple voluntary movement and that this is reflected by the modulation of dominant alpha rhythms (8–12 Hz). Methods: EEG data (56 channels; EB-Neuro) were continuously recorded in the following right-handed subjects: 10 elite karate athletes and 12 non-athletes. During the EEG recordings, they performed brisk voluntary wrist extensions of the right or left hand (right movement and left movement). The EEG cortical sources were estimated by standardized low-resolution brain electromagnetic tomography (sLORETA) freeware. With reference to a baseline period, the power decrease of alpha rhythms during the motor preparation and execution indexed the cortical activation (event-related desynchronization, ERD). Results: During both preparation and execution of the right movements, the low- (about 8–10 Hz) and high-frequency alpha ERD (about 10–12 Hz) was lower in amplitude in primary motor area, in lateral and medial premotor areas in the elite karate athletes than in the non-athletes. For the left movement, only the high-frequency alpha ERD during the motor execution was lower in the elite karate athletes than in the non-athletes. Conclusions: These results confirmed that compared with non-athletes, elite athletes are characterized by a reduced cortical activation during simple voluntary movement. Significance: Cortical alpha rhythms are implicated in the ‘‘neural efficiency” of athletes’ motor systems. Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

1. Introduction The ‘‘neural efficiency” hypothesis originates from psychometric tradition (Vernon, 1993), and is considered as a stable, trait-like construct that varies between individuals (Haier et al., 1988, 2004; Rypma et al., 2006). It postulates a more efficient cortical function in individuals with the best score on tests probing cognitive functions. From an operational point of view, it is expected that com-

* Corresponding author. Address: Department of Biomedical Sciences, University of Foggia, Viale Pinto 7, Foggia I-71100, Italy. Tel.: +39 0881 713276; fax: +39 0881 711716. E-mail address: [email protected] (C. Babiloni).

pared with non-experts, experts showed cortical responses lower in amplitude during tasks related to their expertise. The ‘‘neural efficiency” hypothesis has been repeatedly tested by neuroimaging studies using positron emission tomography (PET), single photon emission computed tomography (SPECT), and functional magnetic resonance imaging (fMRI) showing that subjects with the best score on tests probing intelligent quotient, word fluency, spatial skills, and working memory showed weakest fronto-parietal activation during cognitive tasks (Haier et al., 1988, 1992, 2004; Charlot et al., 1992; Parks et al., 1988; Rypma and D’Esposito, 1999; Rypma et al., 2002, 2005; Ruff et al., 2003). Only few neuroimaging studies have challenged these results (Newman et al., 2003; Gray et al., 2003).

1388-2457/$36.00 Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2009.12.004

C.D. Percio et al. / Clinical Neurophysiology 121 (2010) 482–491

It is well known that a main neurophysiological mechanism regulating the excitability of cortical neural networks is the modulation of dominant oscillations of brain electromagnetic activity at about 8–12 Hz, the so called alpha rhythms (Steriade and Llinas, 1988; Brunia, 1999; Pfurtscheller and Lopes da Silva, 1999). Keeping in mind this theoretical framework, it has been tested the hypothesis that ‘‘neural efficiency” is, at least in part, the reflection of event-related power decrease/increase of resting electroencephalographic (EEG) alpha rhythms at 8–12 Hz, the so called alpha event-related desynchronization/synchronization (ERD/ERS; Pfurtscheller & Lopes da Silva, 1999). In this vein, a less pronounced alpha ERD has been shown in people with high intelligent quotient (IQ) during several cognitive tasks (Neubauer et al., 1995, 1999; Neubauer and Fink, 2003; Grabner et al., 2004) and in subjects highly trained for specific skills (‘‘experts”) during the execution of retrieval short-term memory tasks (Grabner et al., 2006). In the last years, several lines of evidence have extended the ‘‘neural efficiency” hypothesis to cortical motor and visual systems in elite athletes engaged in sensorimotor tasks. It has been shown that compared with non-athletes, elite karate and fencing athletes (experts) are characterized by less alpha ERD during upright standing, as a reflection of spatially focused cortical activation associated to the regulation of dominant alpha rhythms (Del Percio et al., 2009a). The athletes have also shown peculiar modulation of alpha rhythms in tasks during the preparation of pistol or rifle shots (Haufler et al., 2000; Janelle et al., 2000; Loze et al., 2001; Del Percio et al., 2009b) and in a task of social cognition (i.e. observation of rhythmic gymnastic videos; Babiloni et al., 2009). Furthermore, less cortical activation as revealed by event-related cortical potentials has been found in elite kendo and gymnastic athletes (Kita et al., 2001) as well as elite rifle and gun shooters (Fattapposta et al., 1996; Di Russo et al., 2005) during simple self-paced right finger movements. The same was true for elite fencing and karate athletes during right finger movements triggered by visual stimuli depicting sport situations (Del Percio et al., 2008). To contribute to the vivid debate on the ‘‘neural efficiency” in elite athletes, the present study tested the hypothesis that compared with non-athletes, elite karate athletes are characterized by a reduced cortical activation during the preparation and the execution of simple voluntary wrist extensions and that this is reflected by the modulation of dominant alpha rhythms, the so called alpha ERD. To test ‘‘neural efficiency” hypothesis in elite karate athletes, we used a simple self-paced wrist extension as motor task, since this kind of movement belongs to a motor category that is crucial for several karate attack/defense acts, which are based on a fast hand displacement. Noteworthy, simple self-paced wrist extensions could be performed by elite karate athletes and non-athletes with similar features in terms of movement duration and amplitude, thus allowing a reliable inter-group comparison of the related cortical responses.

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computed to evaluate the presence or absence of statistically significant differences between the two groups for age (p < 0.05). Furthermore, Fisher exact test was computed to evaluate the presence or absence of statistically significant differences between the two groups for gender (p < 0.05). No statistically significant inter-group difference was found (age: p > 0.15; gender: p > 0.6). However, the age and gender values were used as covariates in the subsequent statistical analysis to exclude that small differences in age and gender could influence the final statistical results. All subjects gave their informed consent according to the Declaration of Helsinki. They were free to withdraw from the study at any time. The procedure was approved by the local Institutional Ethics Committee (I Medical School, University of Rome ‘‘Sapienza”). 2.2. Experimental procedure A sketch of the experimental design is shown in Fig. 1 (top). The subjects comfortably sat in an armchair and performed two motor tasks, which were brisk voluntary wrist extensions of the right or left hand (right movement, left movement). They were instructed to perform the motor tasks as quickly as possible and were asked to avoid blinking and eye movements during few seconds preceding and following hand movements. The inter-movement interval was of 6– 10 s. For each right and left movement, three periods of interest were considered: a baseline as the period from 3 to 2 s with respect to the zerotime (i.e. zerotime = onset of the motor response), Pre-Mov as the period from 2 s to the zerotime, and Mov as the period from the zerotime to +1 s. For illustrative purpose, Fig. 1 (bottom) shows the movement-related EEG alpha (about 10 Hz) rhythms. A training session included the execution of about 10 right and left movements to establish an approximately stable level of motor performance, as shown by duration and peak amplitude of the concomitant electromyographic (EMG) response of the operant hand. About 100 EEG single trials were recorded for each condition (right movement, left movement). The order of the recording blocks (right movement, left movement) was pseudo-randomized across subjects. 2.3. EEG recordings

2. Methods

The EEG data were continuously recorded (bandpass: 0.01– 100 Hz, sampling rate: 512 Hz; EB-Neuro Be-plusÓ, Firenze, Italy) from 56 scalp electrodes (cap) positioned over the whole scalp according to a 10–10 system. The electrical reference was located between the AFz and Fz electrodes, and the ground electrode was located between the Pz and Oz electrodes. The electrode impedance was kept below 5 kOhm. In parallel, the recording of bipolar electrooculographic data (EOG; bandpass: 0.1–100 Hz; sampling rate: 512 Hz) monitored blinking and eye movements. Finally, the EMG activity (bandpass: 0.1–100 Hz; sampling rate: 512 Hz) of bilateral extensor digitorum muscles was recorded to monitor movements required by the task as well as involuntary mirror movements or other unspecific muscle activations.

2.1. Subjects and ethical approval

2.4. Preliminary data analysis

Ten (6 women) elite karate athletes and twelve (7 women) nonathletes were recruited. All subjects were right-handed as revealed by Edinburgh inventory (Oldfield, 1971). The elite karate athletes were part of Italian national karate team. They had been practicing karate for more than 12 years at least five times a week. They also regularly compete in national and international tournaments. The non-athletes did not play karate or sports similar to karate (i.e. kung fu, etc.) at competitive or amateur level. The mean subjects’ age was 22.3 years in the elite karate athletes (±1.3 standard error, SE; range: 18–30 years) and 25.5 years in the non-athletes (±1.9 SE; ranging from 20 to 35 years). T-testing for independent populations was

The onset of the rectified EMG response was used as a recording zerotime. Recorded EEG data were segmented in single trials of 8 s, each spanning 4 to +4 s with reference to the zerotime. The EEG epochs with ocular, muscular, and other types of artifact were preliminarily identified by a computerized automatic procedure (Moretti et al., 2003). The EEG epochs contaminated by ocular artifacts were then corrected by an autoregressive method (Moretti et al., 2003). Finally, two expert electroencephalographists (C.D.P. and N.M.) manually confirmed this automatic selection and correction, with special attention to residual contaminations of the EEG epochs due to eye movements, blinking, and mirror movements. Therefore,

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Fig. 1. (top) Sketch of the experimental design. The subjects performed two motor tasks, which were brisk voluntary wrist extensions of the right or left hand (right movement, left movement). The inter-movement interval was 6–10 s. For each right and left movement, three periods of interest were considered: a baseline as the period from 3 to 2 s with respect to the zerotime (i.e. zerotime = onset of the motor response), Pre-Mov as the period from 2 s to the zerotime, and Mov as the period from the zerotime to +1 s. (bottom): Sketch of the movement-related EEG alpha (about 10 Hz) rhythms along the periods considered for the data analysis.

only the EEG epochs totally free from artifact residuals were accepted for the subsequent analyses. These EEG epochs were referred to common average reference for further analyses. For the right movement, the mean number of the artifact-free EEG single trials was 80 (±3 SE) for the elite karate athletes and 80 (±5 SE) for the non-athletes. For the left movement, the mean number of the artifact-free EEG single trials was 78 (±5 SE) for the elite karate athletes and 79 (±4 SE) for the non-athletes. Of note, two ANOVAs (one for the right movement and one for the left movement) using the factor Group (elite karate athletes, non-athletes) served to compare the amount of artifact-free EEG single trials between the two groups. No statistically significant difference was found (p > 0.9). 2.5. Frequency analysis of alpha rhythms Power spectrum analysis of the artifact-free EEG data was based on FFT approach using Welch technique and Hanning windowing function (1 Hz frequency resolution). For the determination of the alpha sub-bands, individual alpha frequency (IAF) peak was identified according to literature guidelines (Klimesch, 1996, 1999; Klimesch et al., 1998). First, the mean of the EEG spectrum across all 56 electrodes was evaluated. Second, the IAF was defined as the frequency within the 6–13 Hz range of the EEG spectrum mean showing the maximum power. With reference to the IAF, the alpha sub-bands of interest were as follows: low-frequency alpha band as IAF-2 Hz to IAF, and high-frequency alpha band as IAF to IAF + 2 Hz (Babiloni et al., 2005a,b). The mean IAF value was 10.6 Hz (±0.5 SE) for the elite karate athletes and 10 Hz (±0.3 SE) for the non-athletes. There was no significant inter-groups difference in the IAF peak as evaluated by an ANOVA (p > 0.2). However, the IAF peak was used as a covariate (together with age and gender) for further statistics on EEG data to control for slight effects of IAF on the EEG comparisons. 2.6. Cortical source analysis of the EEG rhythms by sLORETA The artifact-free EEG data were given as an input to the original standardized low-resolution brain electromagnetic tomography

(sLORETA) software for the EEG source analysis (Pascual-Marqui, 2002; http://www.unizh.ch/keyinst/NewLORETA/LORETA01.htm). sLORETA is a functional imaging technique belonging to a family of standardized linear inverse solution procedures, modeling 3-D distributions of the cortical source patterns generating scalp EEG data (Pascual-Marqui, 2002). With respect to the dipole modeling of EEG cortical sources, no a priori decision of the dipole position is required by the investigators in sLORETA estimation. In a previous paper, it has been shown that sLORETA is quite efficient when compared to linear inverse algorithms like minimum norm solution, weighted minimum norm solution or weighted resolution optimization (Pascual-Marqui, 2002). Furthermore, sLORETA has been successfully used in recent EEG and MEG studies (Babiloni et al., 2009; Wagner et al., 2004; Sekihara et al., 2005; Greenblatt et al., 2005; Du et al., 2007). sLORETA computes 3-D linear solutions (sLORETA solutions) for the EEG inverse problem standardized with respect to instrumental and biological noise as mathematically defined in the original paper by Pascual-Marqui (2002). sLORETA solutions are computed within a three-shell spherical head model including scalp, skull, and brain compartments. The brain compartment is restricted to the cortical gray matter/hippocampus of a head model co-registered to the Talairach probability brain atlas, which has been digitized at the Brain Imaging Center of the Montreal Neurological Institute (Talairach and Tournoux, 1988). This compartment includes 6239 voxels (5 mm resolution), each voxel containing an equivalent current dipole. The head model for the inverse solution uses the electric potential lead field computed with a boundary element method (BEM) applied to the MNI152 template (Fuchs et al., 2002). The electrode coordinates were based on the average location of the 10–5 system placement system (Jurcak et al., 2005). As a methodological remark, the use of sLORETA cannot resolve fine functional topographical details in motor and premotor areas, when compared to PET or fMRI. Nevertheless, we preferred the use of the present high-resolution EEG technique, since it allowed testing the working hypothesis that compared with non-athletes, elite athletes are characterized by a reduced cortical activation as

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Table 1 Summary of the statistical results relative to the electromyographic (EMG) responses and alpha ERD/ERS. Statistical comparisons were performed by ANOVA. Mauchley’s test evaluated the sphericity assumption when necessary. Correction of the degrees of freedom was made with the Greenhouse–Geisser procedure. Duncan’s test was used for post hoc comparisons (p < 0.05). Design

Factors (covariates)

Statistically significant results

EMG data: to test the control hypothesis that the duration and the peak amplitude of the EMG response of the operant hand were similar in the elite karate athletes and non-athletes EEG data: to test the working hypothesis that the amplitude of high- and low-frequency alpha ERD was lower (higher) in the elite athletes than in the non-athletes, in line with the idea of ‘‘neural efficiency”

Factors: Group (elite karate athletes, non-athletes) Covariates: age and gender

Left movement: none Right movement: none

Factors: Group (elite karate athletes, non-athletes), Movement (right, left), Band (low-frequency alpha, highfrequency alpha), Time (Pre-Mov, Mov), Hemisphere (right, left), Region of interest (BA 6d, BA 6m, BA 4) Covariates: age, gender and IAF

Statistically significant interaction among the factors Group, Movement, Band and Time (F(1, 20) = 4.68; p < 0.04)

revealed by the modulation of alpha rhythms during voluntary hand movements. The frequencies of alpha rhythms cannot be resolved by PET and fMRI. 2.7. Event-related desynchronization/synchronization (ERD/ERS) The sLORETA solutions were used to index the magnitude of the brain rhythmicity. Specifically, they served to compute the event-related desynchronization/synchronization (ERD/ERS) of the low- and high-frequency alpha sub-bands. The alpha ERD/ ERS was defined as the percentage decrement/increment of instant power density at the event period compared with a baseline. The formula was the following:

  event  baseline  100 : baseline

ð1Þ

Two event periods were considered: Pre-Mov as the period from 2 s to the zerotime (i.e. zerotime = onset of the motor response), and Mov as the period from zerotime to +1 s. The baseline period was defined as the period from 3 to 2 s.

athletes. To this aim, we performed 4 ANOVAs (amplitude and latency peak  the two hands). The ANOVAs had the duration (ms) and the peak amplitude (lV) of the EMG response of the operant hand as a dependent variable and the factor Group (elite karate athletes, non-athletes). Subjects’ age and gender were used as covariates. The second statistical session (EEG data) tested the working hypothesis that alpha ERD was lower in amplitude in the elite karate athletes compared with the non-athletes, in line with the idea of ‘‘neural efficiency”. To this aim, we performed an ANOVA having the alpha ERD/ERS as a dependent variable. The factors were Group (elite karate athletes, non-athletes), Side of movement (right, left), Band (low-frequency alpha, high-frequency alpha), Time (Pre-Mov, Mov), Hemisphere (right, left), and Region of interest (BA 6d, BA 6m, BA4). Subjects’ age, gender, and IAF were used as covariates. The hypothesis would be confirmed by the following two statistical results: (i) a statistical ANOVA effect including the factor Group (p < 0.05); (ii) a post hoc test indicating statistically significant differences of the alpha ERD with the pattern elite karate athletes < non-athletes (Duncan test, p < 0.05). Table 1 summarizes the above statistical results.

2.8. Alpha ERD/ERS at Brodmann areas 3. Results Since the sLORETA procedure intrinsically provides ‘‘low-resolution” EEG source solutions, we decided to evaluate these solutions at the rough level of Brodmann areas (BAs). At this level, the sLORETA solutions for a certain BA were defined as the mean of the sLORETA solutions across all the voxels of that BA. The following BAs were considered: BA 4, BA 6 dorsal (6d), and BA 6 mesial (6m). Indeed, it is supposed that frontal motor cortex is divided into a primary motor area (BA 4) and a premotor area (BA 6; Fulton, 1935; Geyer, 2004; Chouinard and Paus, 2006). Both areas play a pivotal role in cortical motor control (Geyer, 2004). The BA 4 influences kinematic and dynamic parameters of movements, whereas the lateral-dorsal (BA 6d) and mesial (BA 6m including supplementary motor area ‘‘proper”) aspects of the BA 6 use external (e.g., sensory) or internal cues to trigger and guide movements, respectively (Penfield and Welch, 1951; Picard and Strick, 1996, 2001; Geyer, 2004; Chouinard and Paus, 2006). 2.9. Statistical analysis Statistical comparisons were mainly performed by ANOVA. With the ANOVA, Mauchley’s test evaluated the sphericity assumption when necessary. Correction of the degrees of freedom was made with the Greenhouse–Geisser procedure, and Duncan’s test was used for post hoc comparisons (p < 0.05). Specifically, the following two statistical sessions were performed. The first statistical session (EMG data) tested the control hypothesis that the duration and the peak amplitude of the EMG response of the operant hand were similar in the elite karate athletes and non-

3.1. EMG data For the right movement, the mean of the duration of the EMG response was of 316 ms (±27 SE) in the elite karate athletes and 278 ms (±28 SE) in the non-athletes. For the left movement, the mean of duration of the EMG response was of 276 ms (±24 SE) in the elite karate athletes and 287 ms (±27 SE) in the non-athletes. For both movements, the ANOVAs showed no statistically significant result (right movement: p > 0.15; left movement: p > 0.9). For the left movement, the mean of the peak amplitude of the EMG response was of 23 lV (±3 SE) in the elite karate athletes and 20 lV (±4 SE) in non-athletes. For the left movement, the mean of duration of the EMG response was of 20 lV (±3 SE) in the elite karate athletes and 17 lV (±3 SE) in the non-athletes. For both movements, the ANOVAs showed no statistically significant result (right movement: p > 0.7; left movement: p > 0.3). Globally, the present results showed that the EMG parameters were substantially similar in the two groups and could not explain possible differences of alpha rhythms between the elite karate athletes and the non-athletes. 3.2. Cortical alpha ERD/ERS For illustrative purpose, Fig. 2 show the grand average of sLORETA solutions modeling distributed EEG sources of the low- (about 8–10 Hz) and high-frequency (about 10–12 Hz) alpha ERD/ERS in the non-athletes and elite karate athletes for the right and left

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marked frontal and central alpha ERD. Compared to the non-athletes, the elite karate athletes showed a lower central low- and high-frequency alpha ERD for the right movement during the Pre-Mov and Mov periods, as a possible index of spatially selective cortical activation (neural efficiency). Furthermore, the elite karate athletes showed a slight reduction of high-frequency alpha ERD amplitude during the Mov period of the left movement. The ANOVA of alpha ERD/ERS showed a statistically significant interaction (F(1, 20) = 4.68; p < 0.04) among the factors Group (elite karate athletes, non-athletes), Side of the movement (right, left), Band (low-frequency alpha, high-frequency alpha), and Time (Pre-Mov, Mov; see Fig. 3). Duncan post hoc testing indicated that for the right movement, low- and high-frequency alpha ERD in BA 4, BA 6d, and BA 6m was lower in amplitude in the elite karate athletes than in the non-athletes, during the Pre-Mov (p < 0.0005) and Mov (p < 0.005) periods. For the left movement, high-frequency alpha ERD in BA 4, BA 6d and BA 6m was lower in amplitude in the elite karate athletes than in the non-athletes, during the Mov period (p < 0.005). On the whole, these results gave statistical support to the working hypothesis that the amplitude of the alpha ERD was lower in the elite karate athletes than in the non-athletes, as an index of spatially selective cortical activation (‘‘neural efficiency”).

3.3. Control analyses

Fig. 2. Grand average of sLORETA solutions (z-coordinate of the slices = 45) modeling the distributed EEG sources of the low- and high-frequency alpha event-related desynchronization/synchronization (ERD/ERS) in the elite karate athletes and the non-athletes for the right and left movement. The alpha ERD/ERS is mapped at the following two periods of interest: Pre-Mov from 2 to zerotime (i.e. zerotime = onset of the motor response) and Mov from zerotime to +1 s. Color scale: maximum ERD and ERS are coded in red and blue, respectively. The maximal (%) value of the ERD/ERS is reported beneath the maps. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

movement. The alpha ERD/ERS is mapped at the following two periods: Pre-Mov and Mov. For both movements and both alpha sub-bands, the maps of the non-athletes were characterized by a

One might argue that the above between-groups differences of the alpha ERD amplitude can be ascribed to different levels of subjects’ attention, motivation, interest, and habituation. If this is true, subjects of a certain group would be characterized by a different global source power of the baseline alpha rhythms, especially at low frequencies (Klimesch, 1999). To address this issue, we compared the global source power of the alpha rhythms between the two groups of the elite karate athletes and non-athletes. The global source power was defined as the mean of the source power across all voxels of the sLORETA brain volume (dependent variable). A control ANOVA included the factors Group (elite karate athletes, non-athletes) and Band (low- and high-frequency alpha). The results showed no statistically significant effect including the factor Group (p > 0.2), thus indicating that it is improbable that subjects’

Fig. 3. Across subjects’ means of the alpha ERD/ERS amplitude illustrating a statistical ANOVA interaction among the factors Group (elite karate athletes, non-athletes), Side of movement (right, left), Band (low-frequency alpha, high-frequency alpha), and Time (Pre-Mov, Mov). Legend: the asterisks indicate the sLORETA solutions at which alpha ERD presented statistically significant differences with respect to the pattern: elite karate athletes < non-athletes (Duncan post hoc testing, ***p < 0.0005, **p < 0.005).

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attention, motivation, interest, and habit explain the differences of alpha ERD amplitude in the main experiment. To cross-validate the sLORETA results on the elite karate athletes and non-athletes, the analysis was directly repeated on the scalp EEG data used as an input for the sLORETA software. This was done to control for a possible effect of the source and head modeling procedures by means of sLORETA software. The same frequency bands of interest of the sLORETA were considered, namely low- and high-frequency alpha. Analogously to the sLORETA, two time periods were considered: Pre-Mov as the period from 2 s to the zerotime, and Mov as the period from zerotime to +1 s. The baseline period was defined as the period from 3 to 2 s. The alpha ERD/ERS was computed as in the main analysis. Topographic maps (256 colors) were calculated on the basis of alpha ERD/ERS at all scalp electrodes. Student’s t-test mapping was performed for low- and high-frequency alpha ERD/ERS in the elite karate athletes and non-athletes. Fig. 4 shows topographical maps of

Fig. 4. Topographical maps of the low- and high-frequency scalp alpha ERD/ERS in the non-athletes and elite karate athletes for the right and left movements. The alpha ERD/ERS is mapped at the following two periods of interest: Pre-Mov (from 2 s to the zerotime) and Mov (zerotime to +1 s). The corresponding t maps (elite karate athletes vs non-athletes) are also reported. Color scale: maximum ERD and ERS are coded in white and violet, respectively. The maximal (%) value of the ERD/ ERS percentages is reported under the maps. The maximum t value in the nonathletes compared to the elite karate athletes is coded in white. In contrast, the maximum t value in the elite karate athletes compared to the non-athletes is coded in violet. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

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the low- and high-frequency scalp alpha ERD/ERS in the non-athletes and elite karate athletes for the right and left movements. The alpha ERD/ERS is mapped at the following two periods: PreMov and Mov. The corresponding t maps (elite karate athletes vs. non-athletes) are also reported. The maps of the non-athletes were characterized by a marked frontal and central low- and high-frequency alpha ERD during the Mov period of the right and left motor acts. During the Pre-Mov period, the amplitude of alpha ERD was less pronounced. Compared with the non-athletes, the elite karate athletes showed lower amplitude of the low- and high-frequency alpha ERD during the Pre-Mov and Mov periods of the right movement. On the contrary, the elite karate athletes showed only a slight reduction of alpha ERD during the Mov period of the left movement with reference to the non-athletes. The t maps for the right movement showed that the amplitude of low- and high-frequency alpha ERD was significantly lower (p < 0.05) in the elite karate athletes than in the non-athletes. On the contrary, the t maps for the left movement showed no statistically significant difference in alpha ERD amplitude between the elite karate athletes and nonathletes. Globally, the present results are in agreement with those obtained by sLORETA. In the main experiment, we demonstrated that compared with the non-athletes, the elite athletes are characterized by a reduced cortical activation (alpha ERD) during brisk self-paced wrist extension of the hand, in line with the ‘‘neural efficiency” hypothesis. This model of voluntary movements is quite suitable for EEG experiments, since the typical movements of karate repertoire (i.e. attacks with upper or lower limbs, torsion of the trunk, etc.) would have induced irremediable artifacts during the recording of EEG signals. However, one might claim that the original experimental design did not address to the issue of specificity of the ‘‘neural efficiency” effects found during the simple voluntary hand movements, To demonstrate that the reduced brain activity of the elite athletes’, as revealed by the alpha ERD, is not a common neural mechanism for all tasks, we performed a post hoc effort. A control experiment was carried out to test the hypothesis that elite karate athletes and non-athletes did not show differences in alpha ERD during the observation of untrained motor acts, namely rhythmic gymnastics. This control task was chosen on the basis of recent evidence showing that understanding of motor acts observed in other people is related to the activation of peculiar fronto-parietal motor systems, namely the ‘‘mirror motor systems” (Gallese et al., 2004; Rizzolatti and Craighero, 2004; Vogt and Thomaschke, 2007). Therefore, the observation of the untrained motor acts was expected to engage subjects’ motor systems without the inclusion of actual head, shoulder or trunk movements of rhythmic gymnastics that would have induced artifacts into the recorded EEG signals. For this control experiment, EEG data were recorded in six elite karate athletes and in seven non-athletes of the main experiment, namely the only who accepted to come back for a new EEG recordingEEG data were recorded in six elite karate athletes and in seven non-athletes of the main experiment, namely the only who accepted to come back for a new EEG recording. The group of the elite karate athletes was formed by four women, whereas those of the control subjects by six women. The mean subjects’ age was of 22.3 years in the elite karate athletes (±1.4 SE; range: 20– 29 years) and of 19.5 years in the control subjects (±1 SE; range: 18–23 years). All subjects observed a series of 120 rhythmic gymnastic videos (Fig. 5). The videos showed elite gymnasts executing real exercises with different kinds of apparatus (rope, hoop, ball, ribbon, and clubs) during national or international competitions. Each video lasted 8 s with a random inter-stimulus interval ranging from 4.5 to 5.5 s. A central cross was always present as a target for eyes fixation. The recorded EEG, EOG, and EMG data were segmented into single trials lasting 10 s, each spanning from 2 to +8 s with reference to the zerotime, defined as the onset of the

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Fig. 5. Experimental control paradigm. The control elite karate athletes and nonathletes observed a series of 120 rhythmic gymnastic videos. The videos showed elite gymnasts executing real exercise with different kinds of apparatus (rope, hoop, ball, ribbon, and clubs) during national or international competitions. Each video lasted 8 s with a random inter-stimulus interval ranging from 4.5 to 5.5 s. A central cross was always present as a target for eyes fixation.

rhythmic gymnastic video. The same EEG frequency bands of interest of the main experiment were considered, namely low- and high-frequency alpha. Three event periods were considered: T1 as the period from +1 to +3 s with respect to the zerotime, T2 as the period from +3 to +5 s, and T3 as the period from +5 to +7 s. The baseline period was defined as the period from 2 s to the zerotime. The same procedure followed for the main experiment was used for the computation of ERD/ERS of the low- and high-frequency alpha sub-bands. For illustrative purposes, Fig. 6 shows the grand average of sLORETA solutions modeling distributed EEG sources of the low- and high-frequency alpha ERD/ERS in the

Fig. 6. Grand average of sLORETA solutions modeling the distributed EEG sources of the low- and high-frequency alpha ERD/ERS in the elite karate athletes and in the non-athletes during the observation of the rhythmic gymnastic videos. The alpha ERD/ERS is mapped at the three periods of interest: T1 from +1 to +3 s with respect to the zerotime (zerotime = onset of the rhythmic gymnastic video), T2 from +3 to +5 s, and T3 from +5 to +7 s. Color scale: maximum ERD and ERS are coded in red and blue, respectively. The maximal (%) value of the ERD/ERS amplitude is reported beneath the maps.

non-athletes and in the elite karate athletes during the observation of the rhythmic gymnastic videos. The alpha ERD/ERS is mapped at the three periods of interest: T1, T2, and T3. All maps were characterized by an evident alpha ERD/ERS, more represented in parietal and occipital areas. Furthermore, the maps did not show clear differences in the amplitude of alpha ERD between the elite karate athletes and the non-athletes. Finally, we performed an ANOVA having the amplitude of the alpha ERD/ERS as a dependent variable. The ANOVA factors were Group (elite karate athletes, nonathletes), Band (low-frequency alpha, high-frequency alpha), Time (T1, T2, T3), Hemisphere (left, right), and Region of interest (BA 6d, BA 6m, BA 4). Subjects’ age, gender, and IAF were used as covariates. The ANOVA showed no statistically significant difference (p > 0.1). These results support the idea of a similar cortical activity (i.e. no ‘‘neural efficiency”) in the elite karate athletes and non-athletes during a control condition of observation of an untrained sporting motor act.

4. Discussion In line with the ‘‘neural efficiency” hypothesis in experts, we tested the hypothesis that compared with non-athletes, elite karate athletes are characterized by a reduced cortical activation as a reflection of the regulation of dominant alpha rhythms (i.e. alpha ERD) in motor systems during simple voluntary hand movements. Since the focus of the present study was on ‘‘neural efficiency” in the control of a ‘‘non-spatial” voluntary hand movement, we just considered cortical motor regions of interest within frontal motor cortex. Future studies should test the ‘‘neural efficiency” hypothesis in visuo-spatial cortical systems during visuo-spatial and visuo-motor transformations. As main results, we showed that for the right movement, the amplitude of low- (about 8–10 Hz) and high-frequency (about 10–12 Hz) alpha ERD in bilateral primary motor area (BA 4) and premotor areas (BA 6m and BA 6d) was lower in the elite karate athletes than non-athletes during the preparation and execution of the movement (Pre-Mov and Mov periods). For the left movement, the elite karate athletes were characterized only by a reduction of high-frequency alpha ERD amplitude during the execution of the movement. These results suggest that a voluntary hand movement is related to lower amplitude of bilateral frontal and central alpha ERD in the elite athletes than in the non-athletes, as a possible reflection of the implication of dominant frontal alpha rhythms in the spatially selective cortical activation of frontal motor systems (‘‘neural efficiency”). Such ‘‘neural efficiency” effect would be preponderant but not exclusively represented in the control of right (dominant) voluntary brisk hand movements. The present results lend support to the idea that frontal alpha rhythms might represent one of the physiological mechanisms at the basis of ‘‘neural efficiency” during right voluntary hand movements in athletes. These rhythms reflect the functional modes of thalamo-cortical and cortico-cortical loops that facilitate/inhibit the transmission and retrieval of sensorimotor information into the brain (Steriade and Llinas, 1988; Brunia, 1999; Pfurtscheller and Lopes da Silva, 1999). The functional meaning of low- (about 8–10 Hz) and high-frequency (about 10–12 Hz) alpha rhythms is supposed to be different. Low-frequency alpha rhythms would subserve subject’s global attentive readiness, whereas high-frequency alpha rhythms would reflect the movement-related oscillation of specific neural systems for the elaboration of sensorimotor information (Pfurtscheller and Lopes da Silva, 1999). In general, alpha ERD is a neurophysiological variable extremely sensitive to changes in the functional status of frontal and parietal-occipital areas processing sensorimotor and visuo-spatial information, in line with the high representation of alpha rhythms on these re-

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gions (Pfurtscheller and Lopes da Silva, 1999; Neuper and Pfurtscheller, 2001; Neuper et al., 2006). Keeping mind this theoretical premise, the present results hint that compared with the brain of non-athletes, the brain of elite athletes requires a quite selective engagement of thalamo-cortical and cortico-cortical loops spanning primary motor and premotor areas during voluntary hand movements. It can be speculated that such modulation of frontal alpha rhythms in the athletes supports only movement specific (high-frequency alpha rhythms) processes in the present experimental conditions (Pfurtscheller and Lopes da Silva, 1999). This might be the same mechanism at the basis of a well known phenomenon observable also in non-athletes, namely the progressive reduction of event-related cortical activity along learning phases. In this vein, it has been shown that training induces a decrease of activity in motor cortex from pre- to post-training phase during motor tasks (Haufler et al., 2000; Koeneke et al., 2006; Jäncke et al., 2006). Furthermore, the trained motor tasks were performed with a suppression of cognitive processes (Kerick et al., 2001). The results of the present study are globally in line with previous EEG findings showing that the amplitude of sensorimotor cortical activity was lower in elite athletes (kendoists, gymnasts, shooters, fencers, karate athletes) than in non-athletes during right finger movements (Fattapposta et al., 1996; Kita et al., 2001; Di Russo et al., 2005; Del Percio et al., 2008). Furthermore, the present findings extend previous evidence reporting that the amplitude of cortical activity, as revealed by alpha rhythms, was inversely correlated to the skillfulness, being smaller in people best-scorers in cognitive tasks such as stimulus encoding, working memory, and memory retrieval processes (Grabner et al., 2004, 2006; Neubauer et al., 1995, 1999; Neubauer and Fink, 2003). An interesting result of the present study is that in the elite karate athletes, the ‘‘neural efficiency” was more represented in the control of voluntary right (dominant) than left hand movements in terms of extension of the alpha frequencies modulated (i.e. both low- and high-frequency alpha) and of periods of the motor information processing (i.e. both motor preparation and execution). This result extends previous EEG studies showing that movement related potentials over contralateral sensorimotor areas and supplementary motor area was smaller in elite athletes (shooters, fencers and karate athletes) compared with non-athletes for the right movement but not for the left movement (Di Russo et al., 2005; Del Percio et al., 2008). Why is then long training of righthanded elite athletes able to determine the ‘‘neural efficiency” principally for the movement of the right (dominant) hand? At the present stage of research, we are not in the position to provide a conclusive explanation. The results of the present study cannot be merely explained by typical variables responsible for brain reorganization such as sensory deprivation/joint immobilization, musculoskeletal injury, chronic pain, gender, handedness, etc. (Flor et al., 1997; Liepert et al., 1995; Zanette et al., 1997; Flor, 2002, 2003). They cannot be explained by a specific training of the right (dominant) arm/hand in the karate athletes, since they daily train both right and left arms/hands with the same accuracy during the defense and attack actions. Rather, the present results might be explained by specific abilities of bilateral frontal motor systems of sculpturing the alpha oscillatory circuits associated with voluntary right (dominant) hand movements in athletes, due to genetic and/ or intensive training. This speculation extends to experts’ ‘‘neural efficiency” the idea of asymmetrically functional patterns for the dominant and non-dominant motor cortices (Wu et al., 2008), and should be tested with longitudinal studies pre- vs. post-training in athletes and non-athletes or transversal studies involving athletes at different level of training (amateurs, first agonistic level, advanced agonist level, etc.). In precedence, it has been shown that bilateral activation is more pronounced during the non-dominant than the dominant unilateral hand movement, especially in

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right-handed subjects (Kim et al., 1993; Urbano et al., 1996, 1998a,b; Singh et al., 1998; Babiloni et al., 2003). Furthermore, it has been reported a decrease of activation in the ipsilateral primary motor cortex during the movement of the dominant hand, although both the underlying mechanisms and the neurophysiological significance of this phenomenon remain unclear (Allison et al., 2000;Hamzei et al., 2002; Nirkko et al., 2001; Reddy et al., 2000). Finally, it has been documented that proximal tasks (i.e. shoulder movements) induce a bilateral activation of primary motor cortex whereas distal tasks (i.e. finger movements) are associated to a lower activation of ipsilateral primary motor cortex during the movement of the dominant limb (Nirkko et al., 2001). Remarkably, all present elite karate athletes and non-athletes were right-handed. The inclusion of left-handed and ambidextrous subjects would have allowed a better explanation of the present results. Unfortunately, we were unable to recruit a sufficient number of left-handed and ambidextrous subjects in the elite karate group, since only one subject of the Italian national karate team was left-handed and none was ambidextrous. Future studies should address this important issue. In conclusion, here we tested the hypothesis that compared with non-athletes, elite karate athletes are characterized by a reduced cortical activation as revealed by dominant alpha rhythms during brisk voluntary hand movements For the right movement, the amplitude of low- and high-frequency alpha ERD in primary motor area and premotor area was lower in the elite karate athletes than non-athletes during the preparation and execution of the movement. For the left movement, the elite karate athletes were characterized only by a reduction of high-frequency alpha ERD amplitude during the execution of the movement. These results suggest that cortical alpha rhythms are implicated in the ‘‘neural efficiency” of athletes’ motor systems.

Acknowledgements The research was granted by Sport Medicine School – University of Rome Sapienza, Tosinvest Sanità, and Federazione Italiana Judo, Lotta, Karate ed Arti Marziali (FIJLKAM). Drs. Francesco Infarinato, Nicola Marzano, and Marco Iacoboni carried out this research in the framework of Doctoral School on ‘‘Neurophysiology” at the Department of Physiology and Pharmacology, University of Rome Sapienza – Italy.

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