D Cong Khac
email: congkhacdung@yahoo.de

M Sharikadze

G Staude

H Deubel

W Wolf

Dung-Khac Cong

Spontaneous blinks 1 Running head: SPONTANEOUS BLINKS ARE ENTRAINED BY TAPPING Spontaneous eye blinks are entrained by finger tapping

Keywords: Spontaneous Endogenous Blinks, Unimanual and Bimanual Finger Tapping, PsycINFO classification: 2300 Human Experimental Psychology; 2330 Motor Processes

We studied the mutual cross-talk between spontaneous eye blinks and continuous, self-paced unimanual and bimanual tapping. Both types of motor activities were analyzed with regard to their time-structure in synchronization-continuation tapping tasks which involved different task instructions, namely "standard" finger tapping (Experiment 1), "strong" tapping (Experiment 2) requiring more forceful finger movements, and "impulse-like" tapping (Experiment 3) where upward-downward finger movements had to be very fast. In a further control condition (Experiment 4), tapping was omitted altogether. The results revealed a prominent entrainment of spontaneous blink behavior by the manual tapping, with bimanual tapping being more effective than unimanual tapping, and with the "strong" and "impulse-like" tapping showing the largest effects on blink timing. Conversely, we found no significant effects of the tapping on the timing of the eye blinks across all experiments. The findings suggest a functional overlap of the motor control structures responsible for voluntary, rhythmic finger movements and eye blinking behavior.

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Spontaneous blinks 3

Spontaneous eye blinks are entrained by finger tapping

Introduction

Humans are well equipped with different adaptive mechanisms, which have evolved to guarantee successful and optimal behavior in changing habitat conditions. Eyeblink behavior is an example of such optimized behavior. Blinking is so effortless that usually individuals do not pay attention to it: blink execution does not require much cognitive effort. However, blinking behavior is not as simple. There are different types of eyeblinks which serve to distinct functions: (i) spontaneous or involuntary blinking serves the physiological needs of the ocular system; it avoids eye-drying as it spreads tears on the surface of the cornea and conjunctiva (e.g., [START_REF] Mcewen | Secretion of tears and blinking[END_REF][START_REF] Stern | The endogenous eyeblink[END_REF]. (ii) Voluntary blinking [START_REF] Gittins | Electrical stimulation as a therapeutic option to improve eyelid function in chronic facial nerve disorders[END_REF]) is self-initiated or due to the request of an experimenter in response to an external stimulus; it has been studied in relation to visual functions [START_REF] Volkmann | Measurement of visual suppression during opening, closing and blinking of the eyes[END_REF]. (iii) Reflexive blinks (e.g., [START_REF] Esteban | A neurophysiological approach to brainstem reflexes. Blink reflex[END_REF][START_REF] Pellegrini | The trigeminally evoked blink reflex. I. Neuronal circuits[END_REF] are involved in the startle reflex [START_REF] Filion | The psychological significance of human startle eyeblink modification: A review[END_REF] and play indirect defensive as well as protective roles. The latter occur in response to various stimuli which mirror potentially dangerous situations for the eyes; they result from different types of eyeblink reflexes such as air-puff-, acoustic-click-, or dazzling-light-induced reflex blinking. The present study focuses on the spontaneous blinks registered in parallel to finger tapping movements in different experimental conditions. The conditions for the eyes were kept constant to avoid any threat stimuli, which could elicit a reflexive eyeblink.

The physiological basis of blinking is simple: two antagonistic muscles, the levator palpebrae superioris and orbicularis oculi, participate in eyelid movements during blinking [START_REF] Evinger | Eyelid movements. Mechanisms and normal data[END_REF][START_REF] Esteban | Eyelid movements in health and disease. The supranuclear impairment of the palpebral motility[END_REF]; turning off the otherwise tonically active levator palpebrae superioris together with bursts of activity of the orbicularis oculi causes a rapid lowering of the upper eyelid. The opposite process elevates the eyelid back to the upper position [START_REF] Evinger | A brain stem reflex in the blink of an eye[END_REF]. Recently, it has been established that there is a distributed brain network active during blinking: the primary motor cortex, the supplementary motor area, the cingulate motor cortex, the dorsolateral prefrontal cortex, the posterior parietal cortex, the visual cortex, the central thalamus, and the cerebellum participate in spontaneous as well as in voluntary and reflexive blinking [START_REF] Tsubota | Functional MRI of brain activation by eye blinking[END_REF].

The functional role of spontaneous blinking is mainly to guarantee protection against corneal drying [START_REF] Evinger | Dry eye, blinking, and blepharospasm[END_REF] which is avoided by an appropriate tear film distribution over its surface [START_REF] Evinger | A brain stem reflex in the blink of an eye[END_REF][START_REF] Vanderwerf | Blink recovery in patients with Bell's palsy: A neurophysiological and behavioral longitudinal study[END_REF]. While reduced blinking leads to tear film thinning, longer prevention of blinks can eventually result in the tear film breaking up [START_REF] Holly | Formation and rupture of the tear film[END_REF]. Due to altered blink rates observed in "dry eye" cases (e.g., in the video display terminal syndrome [START_REF] Tsubota | Quantitative videographic analysis of blinking in normal subjects and patients with dry eye[END_REF])), a blepharospasm, i.e., an abnormal, involuntary blinking or spasm of the eyelids [START_REF] Hallett | Blepharospasm: Recent advances[END_REF], is quite frequent today as the visual information intake from printed materials and electronic displays, e.g., computer, television, mobile devices increases rapidly. Reports of spontaneous blink rates differ, ranging from 12/min [START_REF] King | Muscular tension and the human blink rate[END_REF] up to 24/min [START_REF] Collins | Blinking and corneal sensitivity[END_REF]. Individuals with a spontaneous blink rate greater than 20 blinks/min constitute a "frequent eyeblink activity" group [START_REF] Doughty | Further analysis of the human spontaneous eye blink rate by a cluster analysis-based approach to categorize individuals with 'normal' versus 'frequent' eye blink activity[END_REF]. All these reported rates are much higher than required to keep the cornea moist [START_REF] Evinger | A brain stem reflex in the blink of an eye[END_REF], which indicates the involvement of the blink mechanism in various processes different from motor control.

In general, a task requiring visual vigilance and attention reduces the blink rate [START_REF] Bauer | Auditory discrimination and the eyeblink[END_REF], whereas intensified sympathetic stimulation increases it. Therefore, the importance of studying the blink rate is widely acknowledged not only from theoretical but also from practical and clinical points of view. Blinking behavior was found to be influenced by various external factors [START_REF] Ponder | On the act of blinking[END_REF]: blink rate (and blink amplitude) dramatically changes with the psychological and perceptual factors such as attention, stress, fatigue, emotional, or other cognitive states. Therefore, spontaneous blinks can be good markers of completion of cognitive tasks such as a solution of arithmetic problems (e.g., [START_REF] Evinger | A brain stem reflex in the blink of an eye[END_REF]. It was also found that blinking often accompanies other tasks with some regularity, for instance, at "physical gaps", "punctuation-marks" during reading, or at the onset of redirecting the gaze when sequentially looking at multiple objects [START_REF] Hall | The origin and purposes of blinking[END_REF]. Eyeblinks can also be related to selective attention, and they can also serve as an indicator to disclose deception [START_REF] Fukuda | Eye blinks: New indices for the detection of deception[END_REF].

These factors mostly reflect cognitive (cortical) aspects, i.e., the central stage of blink control. Analysis of blink rate and interblink-interval distributions revealed different types of blink patterns (Zaman & Doughty, 1997;[START_REF] Doughty | Consideration of three types of spontaneous eyeblink activity in normal humans: During reading and video display terminal use, in primary gaze and while in conversation[END_REF]. [START_REF] Doughty | Consideration of three types of spontaneous eyeblink activity in normal humans: During reading and video display terminal use, in primary gaze and while in conversation[END_REF] promoted the idea that blinks are controlled by a central pacemaker, which resides in the basal ganglia. Freudenthaler, Heuf, Kadner, and Schlote (2003) provided further support to this view.

Observing the various blink patterns during video display terminal usage, they presumed that at least the frequency of homogenous blink patterns can be based on the endogenous pacemaker.

However, heterogeneous patterns could also originate from a central pacemaker if it is assumed that blink behavior is modulated by both internal and external factors. Further evidence for the idea of central or endogenous control is derived from the dopamine hypothesis of blink control which assumes that blink rate is a neurobiological measure of dopaminergic activity [START_REF] Dreisbach | Dopamine and cognitive control: The influence of spontaneous eyeblink rate and dopamine gene polymorphisms on perseveration and distractibility[END_REF][START_REF] Taylor | Spontaneous blink rates correlate with dopamine levels in the caudate nucleus of MPTP-treated monkeys[END_REF]cf., van der Post, de Waal, de Kam, Cohen, & van Gerven, 2004).

The supposed linkage between dopaminergic activity and spontaneous blinks is in agreement with clinical studies of psychiatric and neurological patients suffering from the consequences of an altered dopaminergic activity such as in Parkinson disease, schizophrenia, depression, etc. (MacLean, et al. 1985;[START_REF] Bodfish | Blink rate as an index of dopamine function in adults with mental retardation and repetitive behavior disorders[END_REF].

Beside these central factors involved in blink control, an essential role of peripheral factors has also been acknowledged, e.g., a damage of an ocular surface [START_REF] Tsubota | Quantitative videographic analysis of blinking in normal subjects and patients with dry eye[END_REF], an ocular anaesthesia [START_REF] Naase | An assessment of the pattern of spontaneous eyeblink activity under the influence of topical ocular anaesthesia[END_REF], a presentation of sensory stimuli to eye surface [START_REF] Nakamori | Blinking is controlled primarily by ocular surface conditions[END_REF], and effects due to pharmacological substances [START_REF] Dudinski | Acceptability of thickened eye drops to human subjects[END_REF]. Thus, a controversy about the dominance of central vs. peripheral factors of blink control has evolved. However, a combined hypothesis has also emerged; it emphasizes primacy of the central control being potentially modulated by the peripheral factors [START_REF] Naase | An assessment of the pattern of spontaneous eyeblink activity under the influence of topical ocular anaesthesia[END_REF]. Following this line of thought, one can assume that if exogenous blink-generating stimuli are eliminated (e.g., as a result of anaesthesia or in constant environmental conditions), then the central control should define the blink behavior. Furthermore, if the central blink generator with a stationary pace rate is in operation, then the generator will determine the intervals between blinks, though the intervals will still show some random fluctuations [START_REF] Ponder | On the act of blinking[END_REF][START_REF] Naase | An assessment of the pattern of spontaneous eyeblink activity under the influence of topical ocular anaesthesia[END_REF].

This study primarily addresses the central pacing mechanism of spontaneous blink generation. Its operation in the autonomous pacing mode was shown to be limited by psychological factors as discussed before. However, it is not yet clear from current literature

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Spontaneous blinks 7 whether repetitive motor actions have different modulatory effects on blinking. To be more specific, one can ask: how does the repetition of a simple voluntary motor action (which is based on an internal clock) influence spontaneous blinking? Addressing this question, our study investigated spontaneous blinking behavior during voluntary repetitive finger tapping, a motor task which has been widely used in a number of investigations to examine issues of motor and perceptual timing as well as other effects such as task concurrency and laterality of neuropsychological functions.

The finger tapping task as designed by [START_REF] Stevens | On the time-sense[END_REF] includes two subsequent phases (Fig. 1A). In the synchronization phase, participants tap in synchrony with an external pacer. In the following continuation phase, they tap maintaining the target rate without the external pacing using their own internal pacer (Further details of this paradigm are described in the Section "Procedure"). Various control mechanisms of tapping were proposed from a motor timing perspective, such as a single central pacemaker which successively provides relevant intervals and triggers motor commands each time an interval has elapsed [START_REF] Wing | Voluntary timing and brain function: An information processing approach[END_REF].

There is consistent evidence from recent studies that, due to the open loop situation, selfpaced tapping in the continuation phase is highly sensitive to interferences with other ongoing processes. Notably, the temporal accuracy of periodic tapping with the dominant hand has been found to suffer from the concurrent execution of another (discrete) motor task with the nondominant hand (Yoshino, Takagi, Nomura, Sato, & Tonoike, 2002;[START_REF] Wachter | Coordination of a discrete response with periodic finger tapping: Additional experimental aspects for a subtle mechanism[END_REF]). The opposite effect, i.e., an influence of tapping on a concurrent motor task, is also documented in our earlier studies [START_REF] Wachter | Coordination of a discrete response with periodic finger tapping: Additional experimental aspects for a subtle mechanism[END_REF]. These findings are of particular interest for the present investigation which studied the interaction between continuous

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Spontaneous blinks 8 and spontaneous motor tasks, since they suggest that eye blinking may affect manual tapping as well.

Thus, analyzing blinking behavior during the execution of a tapping task should provide further indications about whether blinking and finger tapping share some central control mechanism. If this is not the case, spontaneous blinking should be independent of concurrently active repetitive motor processes, indicating that the implementations of multiple concurrent central commands for blinks and finger movements are not constrained by a common bottleneck.

To address these issues, four experiments, each with different tapping demands were conducted in which blink patterns and tapping behavior were monitored. Compared to normal "standard" tapping (Exp. 1), "strong tapping" (Exp. 2) required more pronounced force generation leading to a greater finger movement amplitude, whereas "impulse-like tapping" (Exp. 3) stressed a very fast execution of movements. In the fourth (reference) experiment, tapping was omitted. We anticipated that more arduous conditions could lead to a stronger interaction between the tasks.

Methods

Participants

Seven (two female, five male) right-handed healthy participants (P1-P7) took part in this investigation. They had neither signs nor a history of neurological disorders or motor diseases. They all volunteered to participate in the study and gave their informed consent according to the International Ethical Guidelines for Biomedical Research (2002).

Experimental setup

Participants were seated with elbows comfortably semi-flexed, their forearms and palms rested on a table (ulnar side down), which allowed the effortless bimanual tapping with the index fingers. Moving the fingertip up and down with the upper position being the resting position they performed tapping. Two force transducers were embedded in the tabletop for recording the finger taps (ground contact of the index finger tips of both hands). Two high-resolution laser distance sensors (LAM50-10, WAYCON, Germany) fixed about 10 cm above the table surface registered the actual vertical position of fingers. A single-channel high-gain differential input electrooculogram amplifier module (EOG100B, Biopac Inc., USA) was used together with two Ag-AgCl electrodes placed above and below the right eye referenced to linked mastoids (as used e.g., by Skotte, Noygaard, Jorgensen, Christensen, & Sjogaard, 2007) for tracking the eyeblinks.

An ADC (PCI-6025E, National Instruments Inc., USA) digitized all signals at a sampling rate of 1 kHz, and data were stored on a computer. The experiment was controlled by DIAdem (National Instruments Inc., USA) software. Sample traces are shown in Fig. 2.

Fig. 2 about here

Procedure

An experimental session consisted of 25 trial blocks. As shown in Fig. 1A, each trial started with a synchronization phase, where a sequence of five acoustic pacing signals (duration 50 ms, 500 Hz tone, sound level 79 dB, silence noise level was 40 dB) with an interstimulus interval (ISI) of 550 ms was presented to participants to synchronize their periodic finger tapping. Participants were instructed to proceed with tapping in a self-paced mode at the same rate after pace ceased in the subsequent so-called continuation phase. However, different from the original Stevens's (1886) concept, the continuation phase of each trial was additionally divided into 12 (bi-partite) segments: the first part of each segment (with duration randomly selected between 6 s and 8 s) involved pure self-paced tapping, whereas in the second resynchronization part, an additional triad of pacing signals helped to stabilize the tap rate in self-pacing. The onset of the first pace within the triad was synchronized with the actual tap, whereas the next two paces occurred with an ISI of 550 ms as in the synchronization phase.

Short pauses of 8 s (which could be extended by the participants by pressing a footswitch) were interspersed between the 25 trials. The first trial of the experimental session served for some tapping practice and was omitted from the data evaluation. Total time during which of blinks were collected and assessed was about 25 minutes for each condition; this is far beyond the minimum standard recording period of five minutes which was proved to be sufficient for spontaneous blinking analysis (Zaman & Doughty, 1997). Diurnal variations of blink rate [START_REF] Barbato | Diurnal variation in spontaneous eye-blink rate[END_REF] were minimized as the four experiments of each individual were conducted at the same daytime, mostly in the morning and later afternoon hours.

4 Tapping experiments and conditions

Each experiment was split into two parts. The first 13 trials were dedicated to unimanual tapping with the index finger of the dominant hand only, followed by 12 trials of bimanual tapping with both index fingers simultaneously. Two participants performed in reverse order but no order effect was found. In the unimanual condition, the non-dominant (inactive) index finger rested on the force sensor surface. All seven participants took part in all four experimental conditions.

Experiment 1: standard tapping. The participants could tap as they felt comfortable, without any specific instruction about finger movement and contact force.

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Spontaneous blinks 11

Experiment 2: strong tapping. The participants received instructions to tap stronger, i.e., with a force more pronounced than in the case of standard tapping but not exaggerated (to avoid fatigue).

Experiment 3: impulse-like tapping. The finger tap had to be as short lasting as possible.

A specific instruction was given: the upward and downward movements of the finger tip had to be as fast as possible and the duration of ground contact had to be as short as possible. No tap force restrictions were applied.

Experiment 4 (reference): no tapping at all. To obtain patterns of the interblink interval distribution at rest, the participants were exposed to the same experimental setup but without performing a manual task.

Sample records of taps as performed in these different experiments are shown in Fig. 3; they clearly demonstrate the different movement profiles for each condition.

Data analysis

Data evaluation was based on custom-made scripts for MATLAB (MathWorks, Inc.).

The main task was the detection of all motor events in the raw data as shown in Fig. 2. Onsets of taps were automatically determined in the force as well as in the position signals [START_REF] Hofer | Sequential segmentations of time series containing gradual changes in mean: Fitting multiple ramp-step templates[END_REF]; subsequently, an experimenter visually evaluated detection accuracy and, if necessary, interactively corrected event detections.

The following events were specifically defined when a blink was detected:

The finger tap occurring before the blink onset represents the reference tap (reference event) and defines the time origin (i.e., t = 0) within this segment (see Figs. 1B and4).

The onset time t b of the blink event relative to the reference tap was normalized by the ISI and expressed as phase Φ = t b / ISI. The phase Φ describes the instant of the blink within the actual cycle of the periodic tapping, with Φ = 0 (as well as Φ = 1 due to periodicity) indicating simultaneous (in-phase) execution of a blink and a tap, and Φ = 0.5 indicating that a blink occurred in the middle of a periodic tapping cycle. Based on reference taps and blink phases, phase resetting curves and phase histograms were computed for each tapping experiment in order to assess possible mutual interactions between spontaneous blinking and tapping.

Phase resetting curves

In order to investigate the mutual effects of spontaneous blinking and periodic tapping, we used the phase resetting curve method (Fig. 4) introduced by Yoshino et al. (2002); basically, the resetting curve depicts the timing of the periodic taps around the blinks as a function of the blink phase Φ within the periodic tapping process. For each blink, the last preceding periodic tap was designated as the reference tap (labelled as R in Fig. 4); for timing analysis, the intertap intervals (ITIs) were assessed: two intervals preceding the reference tap (unaffected due to causality) together with three intervals following the reference tap (maybe affected by the blink), contained in a tap group of six taps for each blink. Each tap is indicated by a symbol. The vertical distance between the symbols (star, circle, and triangle) represents the ITI as shown in Fig. 4A. Together all of these tap groups build the phase resetting curve: (i) vertically, they are aligned such that the reference tap is located at t = 0 of the ordinate (showing the ITIs), and (ii) horizontally, they are placed at their phase value Φ which results from t b being the time interval between the reference tap and the blink. The time of the blink occurrences is indicated by the inclined dashed Spontaneous blinks 13 line. -What is expressed by the phase resetting curve? (i) If the blink occurrence is independent of the periodic tapping, the tap groups are uniformly distributed over phase Φ, and (ii) if the periodic tapping process is not affected by the blinks, taps (represented by dots) form equidistant horizontal dot lines only, as shown in Fig. 4B. Any systematic deviation from this undisturbed tapping after the reference tap, however, would indicate a mutual influence of the blinks and the periodic tapping process. For illustration, Fig. 4C depicts the case where the blink event completely restarts the periodic tap cycle, thus the distance between the inclined dashed line and the dot line above it is equal to the ITI (i.e., discrete action affects the periodic action). In contrast, the dots in Fig. 4D are restricted to small phase values Φ, indicating that the blink execution becomes synchronized with the periodic tapping (i.e., periodic action affects the discrete action).

Distribution of blink phases

If the interblink intervals are described by a stochastic process [START_REF] Hoshino | One-dimensional stochastic models for spontaneous and burst blink[END_REF][START_REF] Greene | Gaussian and Poisson blink statistics: A preliminary study[END_REF] and if both processes, tapping and blinking are progressing independently of each other, the observed phases Φ describing their temporal relationship should show a uniform distribution of their values within [0, 1[. However, if there is some systematic interaction between the blink and tapping process, the histogram of the observed blink phases Φ should be shaped. Thus, any deviation of the phase histogram from the expected uniform distribution would indicate an influence of the tapping process on the blink behavior.

Since both the phase resetting curve and the phase histogram are constructed with the phase values Φ = t b / ISI (i.e., based upon ISI), ideally, they require the participants to perfectly reproduce the pacing frequency, i.e., equalize ITI with ISI. For real data, however, the measured ITI is scattered around the ISI value. Therefore, the measured quantities will slightly differ from their ideal theoretical expectations, even when the blink and tapping processes are completely independent. For instance, a blink occurring at the end of an actual ITI (which is longer than the targeted ISI) may result in a phase value Φ > 1, which is not compatible with the strictly cyclic interpretation allowing phase values 0 ≤ Φ < 1 only. In order to assess the effects of scattered ITI on the phase histogram and phase resetting curve, for each participant, the blink series of the reference experiment was combined with the tapping series of the corresponding session of Experiment 1. Then, we evaluated each phase as described above for this new (artificial) signal combination. This new set combines two definitely uncorrelated signals since they were recorded in different experiments but it still comprises the effects of scattered ITI. Thus, a phase resetting curve and phase histogram of this dataset serves as a reference for independent processes in real measurements.

Results

Mean contact forces (in N) and mean contact durations (in ms) generated by the participants in all three tapping experiments are summarized in Table 1. Consistently for all participants and for both unimanual and bimanual tapping experiments, the mean contact forces were largest in Experiment 2 ("strong" tapping) whereas mean contact durations were shortest in Experiment 3 ("impulse-like" tapping). This indicates that all participants were capable of adequately performing the required tasks. The longest contact durations obtained in Experiment 2 show that, in general, longer contact durations accompanied the required larger peak force. 5A). Both diagrams are consistent with the theoretical expectation for independent processes showing a horizontal dot pattern in the phase resetting curve (Fig. 5A) and an approximately uniform distribution in the phase histogram (Fig. 5B), respectively. reference data (Fig. 5A), the six dot-lines are basically horizontal, in particular, the upper three dot-lines of the phase resetting curves stay horizontal. This is a first important finding indicating that the tapping process is not significantly disturbed by the preceding spontaneous blinking.

A second central finding of this study results from the distribution of the dot symbols over phase. Fig. 6 demonstrates that the dots in most cases are not uniformly distributed over phase as in the reference experiment in Fig. 5A, but show a higher density at small phase values. As explicated previously, presence of preferred phases indicates that the periodic taps entrained the onsets of the eyeblinks. The phase resetting curves of the unimanual tapping experiments revealed a similar horizontal orientation of dot-lines but with less pronounced concentration of density at preferred phases. Differences between unimanual and bimanual conditions are elaborated in more detail below.

Fig. 6 about here

The tendency of the participants to execute blinks at preferred phases of tapping is even more obvious in the histograms of the blink phases shown in Fig. 7. Although with different degrees of modulation, all histograms of the bimanual tapping experiments show peaky distributions, which clearly differ from the approximate uniform distributions of the corresponding uncorrelated reference data. The peaks in the distributions obtained from participants P1-P7 (Fig. 7) are located at different phase values indicating some individual internal delays (typical for each participant). Also, the strength of interference varied between individuals: P1, P4, and P5 showed a very strong effect of tapping upon spontaneous blinking in all experiments, whereas P7 had a less pronounced shaping of phase distributions for standard (uninstructed) tapping, possibly due to the participant's very light surface contact forces.

Table 1 and Fig. 7 about here Generally, the prominent phase preference was more pronounced in the bimanual tapping experiments than in the unimanual tapping experiments. Fig. 8 demonstrates this difference between unimanual (Fig. 8A) and bimanual (Fig. 8B) tapping for participant P1; this behavior was also typical for the other participants P2-P7.

Fig. 8 about here

For a quantitative analysis, the variable phase was tested for deviations from the uniform distribution by performing 2I-tests [START_REF] Sachs | Applied statistics[END_REF] separately for each experiment and each individual. The test asserts the null hypothesis that the distribution of the data is uniform; the decision is taken at the significance level p < 0.05. In order to prohibit false positive decisions due to scattered ITI, the test was confined to phase values 0 ≤ Φ < 0.8. Table 2 presents The test expectedly proved the uniform distribution for the reference data (blinking only), consistently showing small 2I values below the significance limit. In contrast, for 38 out of 42 phase distributions obtained in the experiments with tapping the results of the 2I-test indicated significant deviations from the uniform distribution. While the four distributions for which the null hypothesis was not rejected were all obtained in the standard (uninstructed) tapping situation (Experiment 1), both the strong tapping (Experiment 2) and impulse-like tapping (Experiment 3) data exhibited the non-uniform distributions in all participants. Moreover, with the exception of participant P7, who generally showed a less pronounced shaping of phase distributions in uninstructed tapping (cf., Fig. 7), 2I values were consistently larger in bimanual tapping as compared to unimanual tapping experiments. Thus, the concurrent tapping leads to a stronger entrainment of spontaneous blinking in case of the tapping task (i) being intensified by instruction, or (ii) being performed bimanually.

Table 2 about here Finally, it should be noted that the modification of Steven's (1886) original tapping paradigm by introducing the re-synchronizing pace triads did not affect the basic finding that the tapping entrains blinking -this was checked in additional pilot experiments without resynchronization. The additional pacing signals reduced the ITI variation to some degree, but it could not preclude the commonly observed tendency to accelerate during self-paced tapping.

Such drifts in the continuation phase would hamper the clarity of results since phase is dependent on ITIs. Further, the mean values of the three ITIs before, including and after the blink (see Fig. 1B) were 522.37 ms (SD ± 34.00), 525.59 ms (SD ± 34.50) and 521.36 ms (SD ± 35.50), respectively; thus it is a clear indication that the blink events (occurring after the reference event) did not influence the global timing of the tapping.

Discussion

In this study, we monitored blinking behavior in experiments with and without concurrent tapping. Distinct rhythmic finger tapping tasks such as "standard tapping", "strong tapping" and "impulse-like tapping" were applied. The obtained results revealed that self-paced finger tapping at a predefined rate affects spontaneous blinking, whereas the tapping behavior was largely unaffected by the eyeblinks. This supports the hypothesis that the blinking behavior reflects not only psychological and perceptual factors (such as attention, stress, fatigue, etc.), but also concurrently active simple motor processes. The assumption of a Poisson distribution of the interblink intervals theoretically predicts uniform distributions in phase histograms as shown in Fig. 8 (column 1). The 2I-test, however, rejected the null hypothesis of uniform distribution over phase for the overwhelming majority of tapping data, strongly indicating that blinking in these conditions cannot be considered as being purely spontaneous but rather dependent on the tapping process.

Brain areas related to finger tapping

Many tapping studies provided evidence for the involvement of multiple brain areas. The results of a meta-analysis of 38 articles (Witt, Laird, & Mayerand, 2008) revealed that primary sensorimotor cortices, supplementary motor area, premotor cortex, inferior parietal cortices, basal ganglia, and anterior cerebellum take part in finger tapping tasks. Moreover, during unpaced continuous tapping neuronal activation increased bilaterally in supplementary motor areas and in the basal ganglia in comparison to (paced) synchronization tapping [START_REF] Lewis | Brain activity correlates differentially with increasing temporal complexity of rhythms during initialisation, synchronisation, and continuation phases of paced finger tapping[END_REF]. The supplementary motor area participates in many endogenously generated movements and is a prominent candidate for the implementation of an internal clock [START_REF] Halsband | The role of premotor cortex and the supplementary motor area in the temporal control of movement in man[END_REF]. Thus, it is likely that the supplementary motor area participates in auditory-paced finger tapping [START_REF] Rao | Distributed neural systems underlying the timing of movements[END_REF][START_REF] Jenkins | Selfinitiated versus externally triggered movements II. The effect of movement predictability on regional cerebral blood flow[END_REF].

Brain areas related to blinking

The central control of blinks is based on cortex, extrapyramidal motor tracts and rostral brainstem circuits (reviewed in [START_REF] Van Eimeren | Right lateralized motor cortex activation during volitional blinking[END_REF]. More specifically, blinking activated the supplementary motor area and the right motor cortex along with premotor cortex, basal, ganglia, cerebellum, insula, and midbrain areas. It is important to note that, in comparison to externally induced blinks, increased activation of rostral supplementary motor area and dorsolateral prefrontal cortex was found for endogenous blinks, similarly to hand motor actions [START_REF] Jenkins | Selfinitiated versus externally triggered movements II. The effect of movement predictability on regional cerebral blood flow[END_REF].

Anatomical studies evidenced substantial involvement of cingulate motor areas in upper facial movement: via the efferents of the dorsal and intermediate facial subnuclei, the cingulate area controls the orbicularis oculi and frontalis [START_REF] Morecraft | Cortical innervation of the facial nucleus in the non-human primate: A new interpretation of the effects of stroke and related subtotal brain trauma on the muscles of facial expression[END_REF]. In primates, the supplementary motor area also sends projections to the medial facial subnuclei which control auricular muscles [START_REF] Morecraft | Cortical innervation of the facial nucleus in the non-human primate: A new interpretation of the effects of stroke and related subtotal brain trauma on the muscles of facial expression[END_REF]. Further, increased activity was reported between the supplementary and cingulated motor areas in spontaneous blinking study of humans [START_REF] Yoon | Neural correlates of eye blinking; improved by simultaneous fMRI and EOG measurement[END_REF]. Anterior cingulate cortex participates in complex motor behavior [START_REF] Paus | Primate anterior cingulate cortex: Where motor control, drive and cognition interface[END_REF] and plays some role in bimanual movement coordination [START_REF] Swinnen | Two hands, one brain: Cognitive neuroscience of bimanual skill[END_REF]. Cingulate activity was also found in volitional suppression of blinking [START_REF] Chung | Event related fMRI studies of voluntary and inhibited eye blinking using a time marker of EOG[END_REF]. In summary, there is compelling neuroscientific evidence that the blinking and bimanual tapping tasks may activate overlapping medial frontal structures [START_REF] Hanakawa | The representation of blinking movement in cingulate motor areas: A functional magnetic resonance imaging study[END_REF].

3 Blinking and other motor tasks

So far, the relationship between blinking behavior and other centrally controlled motor monotonous actions (e.g., like gait and respiration) has not been systematically investigated [START_REF] Wilson | Evoked potential, cardiac, blink, and respiration measures of pilot workload in air-to-ground missions[END_REF]. Only speech was considered as an influencing motor action in this regard, and an increased blink rate was observed during verbal tasks (e.g., von

Cramon [START_REF] Von Cramon | Blink frequency and speed motor activity[END_REF]. This is in line with the results of the present study showing a 30 percent average increase of blink rate during tapping as compared to the reference experiment (i.e., without performing a cyclic motor task). Speech combines cognitive and motor functions; however, it is more likely that interference between speech and blinking is due to motor circuits while, in primary motor cortex, eyelid representation neighbours the ones of the tongue, larynx and face [START_REF] De Jong | Eyeblink frequency, rehearsal activity, and sympathetic arousal[END_REF]. Thus, the spreading of neural activity ("motor overflow") in these adjacent structures [START_REF] Van Eimeren | Right lateralized motor cortex activation during volitional blinking[END_REF][START_REF] Hanakawa | Finger and face representations in the ipsilateral precentral motor areas in humans[END_REF] can be partially responsible for the increased blink rate during verbalization. The present study did not involve verbalization but participation of a subvocal activity (i.e., rehearsal) cannot be excluded; participants could use a rehearsal strategy to optimise their tapping performance. The subvocal activity (i.e., rehearsal) itself could increase a spontaneous blinking rate [START_REF] Von Cramon | Blink frequency and speed motor activity[END_REF][START_REF] De Jong | Eyeblink frequency, rehearsal activity, and sympathetic arousal[END_REF] as verbalization related muscles are also active during rehearsal [START_REF] Mcguigan | Psychological measurements of covert behaviour[END_REF]. However, more recent studies do not support the "motor overflow" based explanation of the interaction (e.g., [START_REF] Morecraft | Cortical innervation of the facial nucleus in the non-human primate: A new interpretation of the effects of stroke and related subtotal brain trauma on the muscles of facial expression[END_REF], acknowledging that the speech and eyelid motor systems share the secondary areas and not the primary motor circuits.

Tapping and blinking

On the other hand, it is conceivable that the representation of time for speech generation might be derived from an endogenous timing process (or a pacemaker) linked to some type of counting device [START_REF] Ivry | Temporal control and coordination: The multiple timer model[END_REF]. In line with this assumption, counting out loud from 1 to 100 significantly increased blinking, whereas reciting the alphabet had no significant effects on blinking [START_REF] Von Cramon | Blink frequency and speed motor activity[END_REF]. This demonstrates that time-structured simple motor tasks like in our study can be coupled or decoupled from blinking, depending on the task requirements. One can speculate that brain regions engaged in endogenous timing are shared between tapping and blinking tasks; one possible well-suited candidate can be a supplementary motor area [START_REF] Rao | Distributed neural systems underlying the timing of movements[END_REF][START_REF] Jenkins | Selfinitiated versus externally triggered movements II. The effect of movement predictability on regional cerebral blood flow[END_REF].

Concurrent speech and finger tapping studies have documented verbal-manual interactions implying common timing processes [START_REF] Klapp | Temporal compatibility in dual-motor tasks II: Simultaneous articulation and hand movements[END_REF][START_REF] Franz | Evidence of common timing processes in the control of manual, orofacial, and speech movements[END_REF]. Based on the [START_REF] Wing | Response delays in the timing of discrete motor responses[END_REF] model, these earlier studies provided support that the central timing mechanisms are shared across effectors, especially, across such effectors as limb and oral motor systems [START_REF] Franz | Evidence of common timing processes in the control of manual, orofacial, and speech movements[END_REF]). More recent findings also favoured the notion of a central effector-independent network involved in internal motor timing [START_REF] Bengtsson | Effector-independent voluntary timing: Behavioural and neuroimaging evidence[END_REF][START_REF] Studenka | The influence of dominant versus non-dominant hand on event and emergent motor timing[END_REF], suggesting brain regions such as the supplementary motor area and the superior temporal and inferior frontal cortices as important structures for movement-independent voluntary timing [START_REF] Bengtsson | Effector-independent voluntary timing: Behavioural and neuroimaging evidence[END_REF][START_REF] Ullen | Independent neural control of rhythmic sequences -behavioural and fMRI evidence[END_REF]. Furthermore, an increased activation was found in the supplementary and cingulate motor cortices, along with sensorimotor areas, putamen and globus pallidus, for internally paced bimanual tapping (Debaere, Wenderoth, Sumaert, Van Hecke, & Swinnen, 2003;[START_REF] Ullen | Neural networks for the coordination of the hands in time[END_REF]. Patient studies [START_REF] Ivry | Subcortical locus of temporal coupling in the bimanual movements of a callosotomy patient[END_REF][START_REF] Kennerley | Callosotomy patients exhibit temporal uncoupling during continuous bimanual movements[END_REF] have demonstrated the importance of subcortical structures for in-phase activation of homologous muscles during bimanual tapping.

Our bimanual experiments, especially the instruction-guided tapping such as the strong and the impulse-like tapping, physically require a higher force and rate of movement, respectively. Thus, increased neural activity is expected in the aforementioned brain regions, along with stronger triggering of motor commands and higher attentive loads [START_REF] Johansen-Berg | Attention to movement modulates activity in sensori-motor areas, including primary motor cortex[END_REF]. Indeed, this kind of tapping showed a stronger coupling (phase synchronization caused by phase entrainment) than uninstructed unimanual tapping. In support of these results, Zijdewind, van Duinen, Zielman, and Lorist (2006) found that instructed force production also requires cognitive resources. Further, the existence of a central bottleneck, resonant properties of eyelid motor system, and a widely distributed eyelid-related brain network can create appropriate conditions for the hand motor system to entrain the onsets of concurrent spontaneous movements (blinks) with the onset of its motor events. [START_REF] Ivry | Temporal control and coordination: The multiple timer model[END_REF] suggested that motor commands for bimanual tapping coming from two hemispheres are integrated for the control of the coordinated behavior. The eyelid movements are generated and controlled centrally, but they are also influenced via certain "secondary paths" [START_REF] Ponder | On the act of blinking[END_REF]. On the other hand, the neural pathways responsible for tapping may cross talk to these "secondary paths" leading to the entrainment of blinks. A major role in these processes can also be assigned to dopaminergic regulation of motor actions (e.g., [START_REF] Dreisbach | Dopamine and cognitive control: The influence of spontaneous eyeblink rate and dopamine gene polymorphisms on perseveration and distractibility[END_REF]. Thus, blinking behavior may indicate the "strength" of the internal representations of motor commands, not only through changes of the blink rate but also through specific timing. Accordingly, the obvious entrainment effect of the strong tapping and impulse-like tapping on blink timing can be due to probably more pronounced motor commands in these cases. Also, the stronger entrainment effect observed in bimanual tapping as compared to unimanual tapping can be interpreted in the same way.

It should be noted that the present findings do not necessarily mean that the tapping task itself directly modulates the spontaneous blinking behavior; alternatively, an indirect influence via a shared central clock can be considered: Actually, it is more likely that tapping affects the common timing mechanism(s) which also defines the temporal pattern of blink generation. Therefore, any other direct impact on this common timing mechanism can change both the tapping behavior and the blink behavior. Our experiments focus on spontaneous blink behavior; therefore, other parameters were kept constant and only the tapping was manipulated by instruction. However, whether a direct exogenous manipulation of the blink behavior (e.g., startle, air puff, etc.) would influence the tapping behavior, in turn, is a different interesting hypothesis for future research.

Spontaneous blinks 32

Yoshino, K., Takagi, K., Nomura, T., Sato, S., & Tonoike, M. (2002). Responses of MEG during rhythmic finger tapping in humans to phasic stimulation and their interpretation based on neural mechanisms. Biological Cybernetics, 86, 483-496. Zaman, M. L. & Doughty, M. J. (1997). Some methodological issues in the assessment of the spontaneous eyeblink frequency in man. Ophthalmic and Physiological Optics, 17, 421-432. Zijdewind, I., van Duinen, H., Zielman, R., & Lorist, M. M. (2006). Interaction between force production and cognitive performance in humans. Clinical Neurophysiology, 117, 660-667.

Fig

  Fig. 1 about here

Fig

  Fig. 3 about here

Fig

  Fig. 4 about here

Fig. 5

 5 Fig. 5 depicts phase resetting curve and phase histogram (normalized by the total number

Fig. 5

 5 Fig. 5 about here

  2I-test values for all participants, conditions and experiments with larger values indicating larger deviations from the uniform distribution. Shaded cells mark 2I values which did not reach significance, while non-shaded cells indicate significant deviations from a uniform distribution.

Fig. 1 .

 1 Fig. 1. (A) Time course of the tapping paradigm. The basic element is a trial comprising of a

Fig. 2 .

 2 Fig. 2. Sample records of signals in Experiment 2 (strong tapping). The two upper panels show

Fig. 3 .

 3 Fig. 3. Examples of recorded contact force (first panel) and finger position signals (second

Fig. 4 .

 4 Fig. 4. Phase resetting curve construction and basic interpretation. -Construction: (A) the three

Fig. 5 .

 5 Fig. 5. Phase resetting curve (A) and phase histogram (B) (frequency on ordinate is normalized

Fig. 6 .

 6 Fig. 6. Phase resetting curves of all experimental data for the bimanual tapping. The row headers

Fig. 7 .

 7 Fig. 7. Phase histograms of eyeblinks in bimanual tapping. Ordinate scaling shows the frequency

Table 1

 1 Mean contact forces (F) in N and mean contact durations (D) in ms and respective standard deviations (SD) of the right finger tap in unimanual and bimanual tapping conditions. The pooled results of all 7 participants are presented.

			Unimanual				Bimanual
		F	SD (F)	D	SD (D)	F	SD (F)	D	SD (D)
	Exp. 1	1.33	0.47	152.43	40.22	1.10	0.55	128.71	20.55
	Exp. 2	5.16	2.20	188.57	45.84	5.13	1.62	191.43	49.27
	Exp. 3	1.06	0.30	57.71	17.81	1.02	0.46	53.43	21.33

Acknowledgments

We are grateful to our colleagues from the mathematical department, Prof. Dr. K.

Pilzweger and Dr. R. von Chossy, for their contributions to the statistical problems of the study.

We are also indebted to W. Weber and J. Dochtermann for their invaluable support in the realization of the study. The support of R. Noragon as a native speaker was very helpful, when we prepared the revision of the manuscript. We express special thanks to Prof. H. Zelaznik and the other anonymous reviewer for their input. This work was supported by the DAAD (Germany) fellowship for M. Sharikadze, by DFG grant Wo 364/7-3 to W. Wolf and G. Staude, and by DFG Excellence-Cluster "Cognition for Technical Systems", Project 181 to H. Deubel and W. Wolf as well as by the Bulgarian National Science Fund of the Ministry of Education and Science (B 1505/05 to A. Kossev and W. Wolf).

Spontaneous blinks 38

the corresponding reference experiment. Note that the scatter of the peaks of the phase histograms indicates individual internal delays.


INTER-LIMB COORDINATION IN SWIMMING: EFFECT OF SPEED AND SKILL LEVEL

Keywords: motor control, biomechanics, swimming, skill, continuous relative phase PsycINFO Classification: 2330, 3720

The aim of this study was to examine the effects of swimming speed and skill level on interlimb coordination and its intra-cyclic variability. The elbow-knee continuous relative phase (CRP) was used as the order parameter to analyze upper-lower limbs coupling during a complete breaststroke cycle. Twelve recreational and 12 competitive female swimmers swam 25 m at a slow speed and 25 m at maximal speed. Underwater and aerial side views were mixed and genlocked with an underwater frontal view. The angle, angular velocity, and phase were calculated for the knee and elbow by digitizing body marks on the side view. Three cycles were analyzed, filtered, averaged, and normalized in percentage of the total cycle duration. The competitive swimmers showed greater intra-cyclic CRP variability, indicating a combination of intermediate phase and in-phase knee-elbow coupling within a cycle. This characteristic was more marked at slow speed because more time was spent in the glide period of the stroke cycle, with the body completely extended. Conversely, because they spent less time in the glide, the recreational swimmers showed lower intra-cyclic CRP variability (which is mostly in the in-phase coordination mode), resulting in superposition of contradictory actions (propulsion of one limb during the recovery of the other limb).

Introduction

Swimming the breaststroke appears to be a complex cyclic sport task, for which the challenge is to tightly organize the inter-limb coupling in order to overcome the environmental constraints (aquatic resistance, which increases with velocity squared; for a review, see [START_REF] Toussaint | Biomechanical aspects of peak performance in human swimming[END_REF].

First, the swimmers have to manage the transition of underwater and aerial movements, showing a variety of strategies in response to the FINA rules. For example, the FINA rules require that the elbows remain underwater, while the shoulders and hands can break the surface of the water at each cycle; some elite breaststrokers therefore make an aerial recovery of the hands to minimize the aquatic resistance.

Second, the swimmers must favour a hydrodynamic body position and propulsive continuity to avoid high intra-cyclic velocity variation [START_REF] Colman | A comparison of the intra-cyclic velocity variation in breaststroke swimmers with flat and undulating styles[END_REF]. The breaststroke has the highest intra-cyclic velocity variation because the recovery times of the two pairs of limbs provoke strong forward resistances in the opposite direction of movement.

For this reason, arm and leg recoveries should not be performed in isolation: expert breaststroke coordination is characterized by synchronized recovery times to diminish this negative time [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF]Seifert & Chollet, 2005[START_REF] Takagi | Differences in stroke phases, armleg coordination and velocity fluctuation due to event, gender and performance level in breaststroke[END_REF]. Thus, the propulsion of one set of limbs should be performed while the other set is in hydrodynamic position, as when the limbs are extended to glide [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF]Seifert & Chollet, 2005). This part of the cycle shows alternating arm and leg propulsions to ensure propulsive continuity.

Last, a breaststroke cycle is composed of three arm phases and three leg phases (propulsion, recovery, and glide). Depending on the time spent in the glide, three coordination modes can be observed in the breaststroke [START_REF] Maglischo | Swimming fastest[END_REF]: (i) glide coordination in which the body stays fully extended and streamlined before the arm catch, usually used for the 200-m event;

(ii) continuous coordination in which arm propulsion takes over just as leg propulsion is completed, destined for the 100-m event; and (iii) superposition coordination in which the arms start their propulsion before the completion of leg propulsion, used in the 50-m event.

Given that a breaststroke cycle lasts about 2 s, efficient motor organization is difficult to achieve, particularly with regard to two points: (i) combining two contrasting modes of coordination within the same cycle, the alternation of the arm and leg propulsions and the synchronization of the recoveries, and (ii) managing the glide time. For this reason, the beginner's coordination is quite different from that of the expert. Two types of superposition coordination, both often arising spontaneously, are seen in the beginner [START_REF] Seifert | Inter-limb coordination and constraints in swimming: a review[END_REF]): (i) the superposition of two contradictory phases (leg propulsion during the arm recovery and arm propulsion during the leg recovery), and (ii) the superposition of two propulsions (arm and leg propulsions).

(i) The superposition of contradictory actions can be characterized as an "accordion-like" coordination and results in in-phase muscle contraction (i.e., simultaneous arm and leg flexion or arm and leg extension corresponding to an iso-contraction; [START_REF] Baldissera | Preferential coupling between voluntary movements of ipsilateral limbs[END_REF][START_REF] Baldissera | Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot[END_REF][START_REF] Swinnen | Egocentric and allocentric constraints in the expression of patterns of interlimb coordination[END_REF]. This superposition coordination is ineffective because each propulsive action is thwarted by a recovery action. The superposition of contradictory actions can also be partial, occurring at two points in the cycle: the beginning of leg recovery can overlap the end of arm propulsion, and the end of arm recovery can overlap the beginning of leg propulsion [START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF].

(ii) The complete superposition of propulsions resembles the movement of "windscreen wipers", with anti-phase muscle contraction (i.e., simultaneous arm flexion and leg extension or arm extension with leg flexion), and results in a preference for moving the limbs in the same direction (iso-direction principle) [START_REF] Baldissera | Preferential coupling between voluntary movements of ipsilateral limbs[END_REF][START_REF] Baldissera | Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot[END_REF][START_REF] Swinnen | Egocentric and allocentric constraints in the expression of patterns of interlimb coordination[END_REF].

The superposition of the propulsions of the arms and legs can be partial, with the body in an X position with arms and legs in complete extension [START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF].

All of these studies [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF][START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF]Seifert & Chollet, 2005) analyzed the arm to leg coordination in breaststroke by calculating time gaps between the key points marking the beginning and the end of arm and leg stroke times. As outlined by [START_REF] Glazier | Dynamic systems theory and the functional role of movement variability[END_REF] and Hamill, Haddad, and McDermott (2000), this discrete method was based on time data and could be completed by spatial data (like the angular positions of the limbs) to enable spatial-temporal analysis. Thus, the calculation of the continuous relative phase (CRP) would provide information on the inter-limb coordination from angle and angular velocity data to facilitate the examination of coordination dynamics through a complete cycle [START_REF] Hamill | Issues in quantifying variability from a dynamical systems perspective[END_REF][START_REF] Kelso | Dynamic patterns: The self-organization of brain and behaviour[END_REF]. Moreover, using the CRP, interlimb coordination could be captured with only one macroscopic order parameter, while [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF], [START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF], [START_REF] Seifert | A new index of flat breaststroke propulsion: comparison between elite men and elite women[END_REF] assessed the time gaps at four key points of the cycle.

The aim of this study was to analyze how swim speed and skill level affect upper-lower limbs coupling during a complete breaststroke cycle using the elbow-knee continuous relative phase (CRP). Swimmers with a higher skill level were expected to combine in-phase and intermediate phase coupling within a cycle, with this characteristic more marked at slow speeds because of a longer time spent in the glide period of the stroke cycle with the body completely extended. Conversely, because they spend less time in the glide, the lower skilled swimmers were expected to show a longer in-phase mode of inter-limb coordination (due to simultaneous flexion of the knee and elbow or simultaneous extension of these two joints).

Material and Methods

Participants

Twenty-four female swimmers were separated into two groups according to their performance level (best time on 50-m: recreational group: 52.05 ± 6.70 s; competitive group: 37.77 ± 2.90 s) and swimming skill (respective percentages of female world record for the short course on January 1, 2007: recreational group: 58.2 ± 6.5 %; competitive group: 79.6 ± 6.1 %). The 12 recreational swimmers were 16.5 ± 1.9 years old, had a body mass of 57.1 ± 7.2 kg, and were 162.5 ± 6.3 cm tall. The 12 competitive swimmers were: 15.7 ± 1.5 y, 52.4 ± 4.8 kg and 166.0 ± 7.0 cm. All the swimmers were able to perform a symmetric leg kick and partially or completely immerse their head during the arm extension, as required by the FINA rules. The two groups showed no significant differences in age, weight, and height. Six markers were placed on the anatomical landmarks of the shoulder, elbow, wrist, hip, knee, and ankle on the right side of the body.

Protocol

The protocol was fully explained to the participants and they provided written consent to participate in the study, which was approved by the university ethics committee. In the case of minors, informed written consent was obtained from the participants and their parents.

One week prior to the experimental trials, the recreational swimmers swam a preliminary breaststroke trial to establish their performance levels during a 25-m swim with an in-water start. The performance levels of the competitors were based on their best competitive times of the current season and were provided by their coaches. The trials consisted of swimming at two speeds over a set of 2 × 25-m, with 5 minutes of rest between laps: one trial at maximal speed and one trial at 80% of the maximal speed. The order in which swimmers performed their trials was randomly assigned. After each trial, all swimmers were informed of their performances. The swimmers were asked to swim within ± 5 % of their targeted time. If this was not the case, the participant had to repeat the trial. The trials were monitored by two experienced timers who assessed the stroke rate and velocity with a stopwatch and a Seiko Base 3-frequency-meter in order to validate each trial.

Video analysis and stroking parameters (velocity, stroke rate, stroke length)

Two Samsung SC107 digital camcorders were connected via an AV/DV analogical input to two custom-made underwater cameras. One camera filmed the swimmers from a frontal view, the other from a side view (distance 11 m). A third camcorder (Canon Obtura) placed on the pool deck videotaped and timed the swimmers over a distance of 12.5 m (between the 10-m and 22.5-m marks on the pool edges), which enabled us to calculate the average swimming velocity and stroke rate. Using the average velocity and the stroke rate, the stroke length could be calculated: stroke length = (velocity × stroke rate)/60. Underwater and above-water views were mixed and synchronized for data processing. A flashing light was used to synchronize the pictures. After being digitized, the images of the underwater side view (sagittal plane) were analyzed with Dartfish Prosuite 4.0 ® software (Atlanta, GA) to assess the elbow and knee angles. The acquisition rate was 66 frames.s -1 . The underwater cameras had a 500-line definition. [START_REF] Persyn | An evaluation procedure for competitive swimmers[END_REF] were the first to observe a synchronization between the 90° of flexion of the elbow and knee. Then, [START_REF] Colman | A comparison of the intra-cyclic velocity variation in breaststroke swimmers with flat and undulating styles[END_REF] used these angles to distinguish the flat and undulating styles in breaststroke. Through four laps increased in speed, [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF], [START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF], and [START_REF] Seifert | A new index of flat breaststroke propulsion: comparison between elite men and elite women[END_REF] determined the arm to leg coordination changes from the elbow and knee angles during the propulsion, glide, and recovery times. Based on these studies which suggested that the elbow and knee angles in the sagittal plane could be used to analyze arm-to-leg coordination, it was checked that the timeseries of elbow and knee angles possess a periodic quasi-sinusoidal form (Fig. 1) that is obviously not perfectly harmonic but could be modelled by the following function:

Arm to leg coordination

y = a + b sin [(2 Pi/(d + c)]
(1)

Insert Fig. 1 Thus, the continuous relative phase (CRP) between the elbow (shoulder-elbow-wrist) and knee (hip-knee-ankle) angles was analyzed from two or three cycles, taken in the central part of the pool to avoid start and turn effects; these cycles being averaged by normalizing the duration of each cycle in percentage. A cycle began from a position of maximal leg flexion (feet at the butt) and ended at the return to this position. The curves of elbow and knee angles during an entire cycle were smoothed by Fourier analysis using a Butterworth low-pass filter (cut-off frequency 6 Hz) by OriginPro 7.5714 ® software [START_REF] Baldissera | Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot[END_REF]( -2003, OriginLab , OriginLab Corporation, Northampton, MA, USA). In accordance with [START_REF] Hamill | Issues in quantifying variability from a dynamical systems perspective[END_REF], the data on angular displacements and angular velocities were normalized in the interval [-1, +1] as follows:

Angular position:

θ norm = ( ) ( ) ( ) θ θ θ + - - - (2)
where θmax is the maximum angular position within one complete cycle and θmin is the minimum angular position within one complete cycle.

Angular velocity:

ω norm = ( ) ( ) ( ) max min 2 max min max min ω + ω ω - ω -ω ω -ω (3)
where ωmax is the maximum angular velocity within one complete cycle and ωmin is the minimum angular velocity within one complete cycle. Angular velocity was obtained through differentiating displacement data.

Phase angles were calculated using the following formula:

Phase angle: φ = tan -1 (ω norm /θ norm ) (4)
Finally, the continuous relative phase (CRP) for a complete cycle was: CRP = Elbow phase angle -Knee phase angle (5)

Theoretically, two coordination modes are possible: in-phase (0°) and anti-phase (180°); however, as adopted by [START_REF] Bardy | Dynamics of human postural transitions[END_REF], [START_REF] Diedrich | Why change gaits? Dynamics of the walk-run transition[END_REF], and Seifert, Delignières, Boulesteix, and Chollet (2007), a lag of ± 30° was accepted in this study for the determination of a coordination mode. Therefore, an in-phase mode was assumed to occur for -30° < CRP < 30°, while the anti-phase mode was taken to be between -

Statistical analysis

Mean and standard deviation of angles, phases, and CRP are presented. The normality of the distribution (Ryan Joiner test) and the variance homogeneity (Bartlett test) were checked before using parametric statistics. Two Groups × two Speeds ANOVA, with swim speed as a repeated measures factor, compared (i) the stroking parameters (velocity, stroke rate, stroke length), (ii) the mean CRP, (iii) the standard deviation (SD) of CRP within a cycle, (iv) the time spent in in-phase mode, (v) the CRP at the beginning and at the end of the cycle, (vi) the maximum and minimum CRP values, and (vii) the times at which the maximum and minimum CRP occurred in the two skill levels and at the two swimming speeds.

In accordance with [START_REF] Cohen | Statistical power analysis for the behavioural sciences[END_REF], the between-factor effect size was calculated from η² as the difference between the sum of squares between groups and the total sum of squares. The effect size explained the variance, i.e., indicated the amount of association between groups that was due to skill level and swimming speed. η² = .2 is small, η² = .5 is moderate, η² > .8 is large differences [START_REF] Cohen | Statistical power analysis for the behavioural sciences[END_REF]. All tests were conducted with Minitab 15.1.0.0 ® software (Minitab Inc., Paris, France, 2006) with a conventional significance level of p < .05.

Results

Stroking parameters

The effects of skill level and swim speed on velocity, stroke rate, and stroke length are presented in Table 1.

Insert Table 1

The relative value of velocity for the slow speed was not significantly different between the recreational and competitive groups (respectively, slow speed equalled 75.7% and 82.5% of the maximal speed) and thus imposed the same task constraint on both groups.

Nature of the arm to leg coordination

The time spent in in-phase mode (-30° < CRP < 30°) was not significantly different between the two skill levels (34.8±21.1% of the cycle for the recreational swimmers and 42.0±12.8%

for the competitive swimmers). However, on the mean of the two speeds, the mean CRP of the recreational swimmers was close to in-phase mode (-24.1°), whereas the mean CRP of the competitive swimmers was in intermediate phase (-43.7°), F(1,33) = 15.75, p < .05, η² = .26, due to the greater intra-cyclic variability of CRP (SD CRP = 56.5° and ranged from -167.9±29.5° to 138.5±27.3° through a complete cycle) compared with the recreational group (SD CRP = 36.1° and ranged from -83.8±34.3° to 22.9±32.7° through a complete cycle),

F(1,33) = 30.65, p < .05, η² = .39 (Fig. 2). The small effect size concerning the differences in mean CRP and SD CRP between the two groups required further analysis. An analysis of CRP at several key points of the cycle was thus undertaken and indicated that the two groups had some common coordination features, as well as significant differences: (i) for both groups, the maximum value of CRP indicated in-phase coordination (range from 0.7±20.4° to at 5% of the cycle), whereas the CRP of the competitive swimmers increased from the start of the cycle (Fig. 2).

Concerning the speed effect, the time spent in in-phase mode (0° < CRP < 30°) significantly decreased between the slow (43.1±17.1% of the cycle duration) and maximal speeds (33.7±17.3% of the cycle duration), F(1,33) = 33.79, p < .05, η² = .13. The maximum value of CRP significantly decreased between the slow (18.1±16.4°) and maximal speeds (4.5±21.2°),

F(1,33) = 5.08, p < .05, η² = .12, particularly in the recreational group (. η² = .25). Indeed, the significant interaction between skill level effect and swimming speed effect, F(1,33) = 4.40, p < .05, and the post-hoc Tukey test indicated a decrease in the maximum value of CRP for the recreational group from the slow speed (maximum CRP = 22.9±32.7°) to the maximal speed (maximum CRP = 0.7±20.4°).

Insert Fig. 2 The coordination differences between groups and between speeds resulted from differences in the angles and angular velocities of the elbow and knee (Fig. 3), which led to differences in the phases (Fig. 4). At the start of the cycle, both groups began their leg propulsion from the maximal leg flexion (35° at 0% of the cycle) and continued up to the maximal leg extension (170° at 25% of the cycle). Conjointly, the recreational swimmers spent 20% (at maximal speed) and 25% (at slow speed) of the cycle start finishing their arm recovery from a maximal flexion to attain an extended position (elbow angle close to 170°), whereas the competitive swimmers spent only 10% of the cycle start to complete their arm recovery.

Even though the two groups of swimmers started the arm recovery at the same relative moment in the stroke cycle (on average: 80 %), the data indicated that at the end of the cycle, the arms of the recreational swimmers were still only half-extended (mean arm/forearm angle: 100°), whereas the competitive swimmers had them stretched almost completely forward (153°).

The between-group difference in the time at which the minimum CRP occurred was related to the greater time the competitive swimmers spent gliding with the arms extended forward.

Indeed, the recreational swimmers started their arm propulsion directly from the extended position (at 20% of the cycle at maximal speed and 25% at slow speed) and continued up to the maximal flexion (elbow angle close to 70° at 80% of the cycle). Conversely, the competitive swimmers glided with the arms extended forward at 165° from 10% of the cycle start up to 30% of the cycle at maximal speed and 50% at slow speed. Only after this glide time did they propel with their arms until the maximal elbow flexion (60° at 80% of the cycle).

The between-speed difference in maximum CRP concerned the recreational group and was related to their inadequate maximal arm extension, which occurred after the maximal leg extension at slow speed and before the maximal leg extension at maximal speed. Therefore, the elbow and knee phases showed a difference in time value (Fig. 4) that led to greater inphase coupling at maximal speed than at slow speed.

Insert Figs. 3 and 4

Discussion

The results indicated significant swim speed and skill level effects on the upper-lower limbs coupling during a complete breaststroke cycle.

The first hypothesis was that competitive swimmers would show a combination of in-phase and intermediate phase coordination modes. The finding of greater intra-cyclic variability in the elbow-knee coupling (SD of CRP) of these swimmers confirmed this hypothesis. The second hypothesis, of the prevalence of in-phase mode in the recreational swimmers, was partially confirmed: (i) they spent less time in in-phase mode than the competitive swimmers due to the absence of glide time and, conversely, (ii) they adopted a superposition of contradictory actions, which oscillated between in-phase and an intermediate phase coupling [START_REF] Vereijken | Freezing degrees of freedom in skill acquisition[END_REF]. Therefore, during leg propulsion, the swimmers switched from anti-phase coupling (legs maximally flexed/arms maximally extended) to in-phase (legs maximally extended/arms maximally extended). Conversely, during arm propulsion, the swimmers switched from in-phase coupling (legs maximally extended/arms maximally extended) to antiphase (legs maximally flexed/arms maximally extended). Between arm and leg propulsions, a second part of the cycle was devoted to glide time, which varied from 20 to 40% of the cycle (vs. 0% for the recreational swimmers), depending on the swim speed. During the glide, the competitive swimmers adopted a hydrodynamic position, i.e., an in-phase mode (arms and legs fully extended). According to previous studies [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF][START_REF] Leblanc | Arm-leg coordination in flat breaststroke: A comparative study between elite and non-elite swimmers[END_REF]Seifert & Chollet, 2005;[START_REF] Takagi | Differences in stroke phases, armleg coordination and velocity fluctuation due to event, gender and performance level in breaststroke[END_REF], the glide time varies from 0 to 40% with gender, speed and skill level, with high-skilled breaststrokers removing the glide and superposing the end of leg propulsion with the beginning of arm propulsion to maintain a high average speed [START_REF] Maglischo | Swimming fastest[END_REF]Seifert & Chollet, 2005). In accordance with [START_REF] Persyn | An evaluation procedure for competitive swimmers[END_REF], the competitive swimmers in our study devoted the third part of the cycle to synchronising the arm and leg recoveries using an anti-phase mode of muscle contraction (arm extension and leg flexion). This anti-phase mode of arm and leg contractions reflects an iso-direction of the arms and legs that results in simultaneous forward recoveries. Indeed, given that both arm and leg recoveries are underwater and thus cause high drag, they should be synchronized [START_REF] Chollet | Evaluation of the arm-leg coordination in flat breaststroke[END_REF][START_REF] Persyn | An evaluation procedure for competitive swimmers[END_REF].

Concerning the second hypothesis, the recreational swimmers displayed a superposition coordination that oscillated between in-phase and an intermediate phase mode, with the mean CRP in in-phase mode. This motor organization was related to the in-phase muscle contraction of the arms and legs [START_REF] Baldissera | Preferential coupling between voluntary movements of ipsilateral limbs[END_REF][START_REF] Baldissera | Differential control of in-phase and anti-phase coupling of rhythmic movements of ipsilateral hand and foot[END_REF][START_REF] Swinnen | Egocentric and allocentric constraints in the expression of patterns of interlimb coordination[END_REF].

Although this coordination mode appears to be the most stable and the easiest to perform in bimanual coordination [START_REF] Kelso | Phase transitions and critical behavior in human bimanual coordination[END_REF], hand-foot tasks [START_REF] Jeka | Spontaneous transitions and symmetry: pattern dynamics in human four-limb coordination[END_REF][START_REF] Kelso | Symmetry breaking dynamics of human multilimb coordination[END_REF] and walking-running [START_REF] Diedrich | Why change gaits? Dynamics of the walk-run transition[END_REF], this arm to leg coordination was ineffective for breaststroke swimming because it entails a freezing of the degrees of freedom (as previously observed on ski-simulator, [START_REF] Vereijken | Freezing degrees of freedom in skill acquisition[END_REF] that superposes contradictory actions: (i) an overlap of arm recovery with leg propulsion (i.e., arms and legs simultaneously extended, Fig. 3) and (ii) an overlap of arm propulsion with leg recovery (i.e., arms and legs simultaneously flexed, Fig. 3). In both cases, the propulsion of one pair of limbs is thwarted by the underwater recovery of the other pair, which causes high drag. These results confirmed those of an electromyographic study, where the arm propulsion of unskilled young breaststroke swimmers was associated with noticeable discharges of the rectus femoris muscle, which is a hip flexor (Tokuyama, Okamoto & Kumamoto, 1976). First, the superposition of the arm recovery on the leg propulsion was related to the incomplete spatial recovery of the arms: the recreational swimmers had their arms still flexed at 100° at the end of their recovery, whereas a 153° extension was observed for the competitive swimmers (the perfect extension for streamlined position is 180°). Second, the arm recovery was performed too slowly, often after letting the hands stop under the breast. This hand-stopping under the breast could not be considered as glide time because the trunk inclination and the arm flexion caused a non-hydrodynamic position that increased the drag [START_REF] Kolmogorov | Hydrodynamic characteristics of competitive swimmers of different genders and performance levels[END_REF][START_REF] Mc Elroy | Intra-cycle velocity fluctuations of highly skilled breaststroke swimmers[END_REF]. As a direct consequence, the arm recovery was delayed compared with that of the competitors.

According to [START_REF] Leblanc | Velocity variations in breaststroke swimmers of different competitive levels[END_REF], the superposition of arm propulsion with leg recovery occurs because of no glide time with the body fully extended after the arm recovery. Indeed, the lack of sensations often led beginners to squeeze the glide and catch times and to directly start arm propelling with a circular movement of the outstretched arms. This type of swimming was aimed at maintaining the head and the upper part of the trunk above the water surface rather than to go forward. The superposition of arm propulsion with leg recovery could also be related to the difficulty of keeping the trunk and lower limbs nearly parallel to the water surface during arm propulsion [START_REF] Tokuyama | Electromyographic study of swimming in infants and children[END_REF][START_REF] Yoshizawa | Electromyographic study of the breaststroke[END_REF].

Nature of the arm to leg coordination: effect of speed

Speed influenced the amount of time spent in in-phase, which decreased from 43 to 33% of a complete stroke between slow speed and maximal speed. In fact, the increase in speed mainly affected competitive swimmers for whom the glide time with the body fully extended decreased from 40 to 20% of a complete stroke between slow speed and maximal speed, whereas arm propulsion followed arm recovery in the recreational swimmers due to the lack of glide time. Intra-cycle velocity curves have usually revealed a decrease in the duration of the leg-arm transitional phase with speed increase [START_REF] Leblanc | Velocity variations in breaststroke swimmers of different competitive levels[END_REF][START_REF] Mc Elroy | Intra-cycle velocity fluctuations of highly skilled breaststroke swimmers[END_REF][START_REF] Manley | Intra-stroke velocity fluctuations in paced breaststroke swimming[END_REF][START_REF] Takagi | Differences in stroke phases, armleg coordination and velocity fluctuation due to event, gender and performance level in breaststroke[END_REF]. Therefore, [START_REF] Maglischo | Swimming fastest[END_REF] observed the switching from glide coordination at slow speed to superposition coordination (superposition of the end of leg propulsion with the beginning of arm propulsion) at maximal speed for expert swimmers. In our study, the competitive swimmers did not reach such high speeds and did not have sufficient experience to adopt superposition coordination.

The recreational swimmers showed differences in maximum CRP between speeds; notably, they displayed a partial superposition of two contradictory phases (the beginning of leg propulsion overlapping the end of arm recovery) at slow speed that disappeared at maximal speed. For elite swimmers, this strategy could be effective to maintain a high mean velocity [START_REF] Mc Elroy | Intra-cycle velocity fluctuations of highly skilled breaststroke swimmers[END_REF][START_REF] Seifert | Longitudinal evaluation of breaststroke spatial-temporal and coordinative parameters: preparing of the 100-m breaststroke bronze medallists of the Athena 2004 Olympic Games[END_REF] but appears ineffective for unskilled swimmers who move their limbs at much the same velocity during recovery and propulsion [START_REF] Leblanc | Velocity variations in breaststroke swimmers of different competitive levels[END_REF].

Conclusion

The greater intra-cyclic variability of the competitive swimmers' CRP curves indicated that they had the capability to combine different coordination modes within a single 2-second cycle: (i) intermediate phase coupling with alternating limb propulsions, (ii) in-phase of the arm and leg extensions for gliding, and (iii) anti-phase muscle contraction (legs flexed/arms extended) during the recovery, with a forward iso-direction of the arm and leg. Conversely, the recreational swimmers used ineffective superposition coordination with an in-phase muscle contraction of the arms and legs, with the propulsion of one pair of limbs thwarted by the underwater recovery of the other pair.

Figure Captions

Fig. 1. Time-series of three cycles of elbow and knee angles.

  180° < CRP < -150° and 150° < CRP < 180°. Beyond this step, a coordination mode of intermediate phase was also taken into account.The time spent in in-phase mode indicates how the swimmers synchronize the propulsion of one pair of limbs with the glide of the second pair of limbs, as well as the time spent in glide with the body fully extended. The CRP value at the beginning and end of the cycle indicates the swimmer's capability to keep the arms extended forward while the legs are starting their propulsion from knee flexion. The maximum CRP value is the greatest positive CRP value, which is distinct from the CRP value reached at the beginning and end of the cycle, and it indicates the presence or lack of the glide. The minimum CRP value is the greatest negative CRP value, which again is distinct from the CRP value reached at the beginning and end of the cycle, and it indicates how the arm recovery (elbow extension) and leg recovery (knee flexion) are synchronized.

  22.9±32.7°) while the minimum value of CRP revealed intermediate coordination (range from -83.8±34.3° to -77.3±22.6°); (ii) the CRP of the recreational swimmers remained between inphase and intermediate mode (~80°) while the CRP of the competitive swimmers varied greatly, alternating between in-phase and a pronounced intermediate phase mode (mostly close to anti-phase at the start and end of the cycle). Indeed, the ANOVA indicated a significant difference in the CRP of the recreational and competitive swimmers at the beginning of the cycle (respectively, CRP = -47.6±32.7° and -164.9±27.1°; F(1,33) = 176.44, p < .05, η² = .80) and the end (respectively, CRP = 15.2±26.5° and 132.2±26.9°; F(1,33) = 232.89, p < .05, η² = .83). The time at which the minimum CRP occurred also significantly differed, F(1,33) = 33.79, p < .05, η² = .41, at 66.1±10.6% of the cycle for the recreational swimmers and at 80.3±5.4% for the competitive swimmers. Finally, it is interesting to note that the CRP of the recreational swimmers started to decrease (at slow speed, their CRP decreased from -45.8±29.3° at the start of the cycle to -62.6±22.0° at 4% of the cycle; at maximal speed, their CRP decreased from -49.4±37.1° at the start of the cycle to -70.2±35.6°

  that did not reach the high values of intermediate phase observed in the competitive swimmers. The first hypothesis concerned the competitive swimmers. The combination of the in-phase and intermediate phase modes confirmed their skill in monitoring their coordination over a 2second cycle. The first part of the cycle in intermediate phase coordination was devoted to propelling with one pair of limbs while the other pair remained in extended position, indicating that these highly skilled performers released the degrees of freedom not useful to the task (as previously shown on ski-simulator by Vereijken, van Emmerik, Whiting &

Fig. 2 .

 2 Fig. 2. Continuous relative phase between elbow and knee through a complete cycle for the

Fig. 3 .

 3 Fig. 3. Variations of the elbow and knee angles through a complete cycle: 3A: slow speed for

Fig. 4 .

 4 Fig. 4. Variations of the elbow and knee phase angles through a complete cycle: 4A: slow

  Fig.1

Fig. 3

 3 Fig. 3

Fig. 4

 4 Fig. 4