The functional relationship between yawning and vigilance

Behavioural Brain Research 179 (2007) 159–166

Research report

The functional relationship between yawning and vigilance Adrian G. Guggisberg ∗ , Johannes Mathis, Uli S. Herrmann, Christian W. Hess Center of Sleep Medicine, Department of Neurology, Inselspital, University of Berne, CH-3010 Bern, Switzerland Received 19 November 2006; received in revised form 24 January 2007; accepted 30 January 2007 Available online 3 February 2007

Abstract Background: Although yawning is a ubiquitous and phylogenetically old phenomenon, its origin and purpose remain unclear. The study aimed at testing the widely held hypothesis that yawning is triggered by drowsiness and brings about a reversal or suspension of the process of falling asleep. Methods: Subjects complaining of excessive sleepiness were spontaneously yawning while trying to stay awake in a quiet and darkened room. Changes in their electroencephalogram (EEG) and heart rate variability (HRV) associated with yawning were compared to changes associated with isolated voluntary body movements. Special care was taken to remove eye blink- and movement-artefacts from the recorded signals. Results: Yawns were preceded and followed by a significantly greater delta activity in EEG than movements (p ≤ 0.008). After yawning, alpha rhythms were attenuated, decelerated, and shifted towards central brain regions (p ≤ 0.01), whereas after movements, they were attenuated and accelerated (p < 0.02). A significant transient increase of HRV occurred after the onset of yawning and movements, which was followed by a significant slow decrease peaking 17 s after onset (p < 0.0001). No difference in HRV changes was found between yawns and movements. Conclusions: Yawning occurred during periods with increased drowsiness and sleep pressure, but was not followed by a measurable increase of the arousal level of the brain. It was neither triggered nor followed by a specific autonomic activation. Our results therefore confirm that yawns occur due to sleepiness, but do not provide evidence for an arousing effect of yawning. © 2007 Elsevier B.V. All rights reserved. Keywords: Yawning; Vigilance; Arousal; Communication; Behaviour; Maintenance of wakefulness test

1. Introduction Yawning is a stereotyped sequence of respiratory and motor phenomena, which is observed in a wide variety of animal species, from fetal stages to old age [3,32]. Although there is little doubt that such a conspicuous and phylogenetically old behaviour of ubiquitous occurrence must have a biological origin and purpose, its prerequisites and its function have remained unclear [3,27,32]. From the various hypotheses on the physiology of yawning, two concepts have remained in literature from the past to present days. The communication hypothesis states that yawning is a form of unconscious communication to synchronize the behaviour of a group [8,12,33]. Specifically, yawning was proposed to communicate drowsiness [8,12,33], psychological stress [12], and boredom [27].

∗

Corresponding author. Tel.: +41 31 632 30 54; fax: +41 31 632 94 48. E-mail address: [email protected] (A.G. Guggisberg).

0166-4328/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.bbr.2007.01.027

The arousal hypothesis suggests that yawning has an arousing effect thereby keeping off impending sleep [1,3,8,21,32]. Initially it was thought that this arousing effect depended on changes in brain perfusion with blood and oxygen. Albrecht von Haller assumed in 1749, that “Yawning is preceded by a slow-down in pulmonary blood flow,” which leads to insufficient oxygen (O2 ) in the blood, and therefore in the brain (cited in [27]). In 1881, Russell hypothesized that yawning may cause a “stimulation of the brain through increased activity of the circulation” (cited in [3]). These notions reappeared later in the concept of “critical consciousness” by Montagu [21], who suggested that a reduced state of consciousness due to a rise in carbon dioxide (CO2 ) in the brain is normalized by yawning. Askenasy [1] postulated that yawning is a “complex arousal defence reflex (. . .), whose aim is to reverse brain hypoxia”. However, theories ascribing an important role to blood gases in the physiology of yawning had to be rejected after the experiments of Provine et al. [25], who showed that healthy subjects did not yawn more frequently when breathing gas mixtures with high levels of CO2 or low levels of oxygen (O2 ). However, the

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concept of an arousing function of yawning remained in variants: Baenninger [3] suggested “that an important function of yawning is to modify levels of cortical arousal, especially in situations where there is little external stimulation,” and Walusinski and Deputte [32] postulated that the function of yawning in humans as in animals is a “stimulation of vigilance”. The present study aimed at empirically evaluating the functional relationship between yawning and vigilance by measuring electrophysiological markers of vigilance in temporal association with yawning. Both hypotheses have in common that they assume an important causal relationship between spontaneous yawning and vigilance, and both hypotheses predicted that we would find signs of sleepiness before yawns. We therefore specifically assessed theta and delta power in EEG segments before yawns as markers of drowsiness. The hypothesis of an arousing effect of yawning additionally suggested that significant activating effects would be observable in the EEG or HRV after yawning. We therefore analyzed alpha power and the mean alpha frequency [5,6] in EEG segments after yawning as markers of the arousal level, as well as HRV changes as markers of an autonomic activation. In order to rule out confounding effects of concomitant movements during yawning, we additionally compared the data obtained before and after yawning to EEG and HRV measurements before and after isolated voluntary body movements without yawning. 2. Methods 2.1. Patients and setting Maintenance of wakefulness tests (MWT) of 16 patients (4 females, mean age 37.4 years, age range 18–62 years) having yawned at least 4 times during the test were selected among all patients who underwent vigilance tests to elucidate the origin of excessive daytime sleepiness or non-restorative sleep. Patients had been informed that their data may be used for scientific purposes and had given their written informed consent. They were, however, unaware of their yawning being of any particular significance. The procedures were approved by the local ethics committee and conformed to the standards set by the Declaration of Helsinki. The MWT is a widely used and standardized diagnostic tool to assess the ability to stay awake in patients who suffer from excessive daytime sleepiness or non-restorative sleep [13,20]. During this test, the subjects must try to stay awake while sitting alone in a quiet and darkened room, a situation which frequently leads to spontaneous yawning. MWTs consisted of four sessions recorded at 9:00 a.m., 11:00 a.m., 3:00 p.m., and 5:00 p.m. The sessions were terminated after three consecutive epochs of sleep stage 1, after a single epoch of any other sleep stage or after 40 min. The final diagnosis of the selected patients was sleep apnoea syndrome in five cases, idiopathic hypersomnia in two cases, chronic fatigue syndrome in two cases, primary insomnia in one case, disturbed sleep due to chronic depressive disorders in two cases, narcolepsy in two cases, and chronic sleep insufficiency in two case. In addition, MWT recordings of one healthy subject obtained after one night of complete sleep deprivation were included. None of the patients had brain lesions, metabolic disorders or hormonal disorders, which could have affected the physiological mechanisms underlying yawning, and none of the patients took dopaminergic medication.

Cz) mastoid, and two electrooculogram (EOG) leads were sampled at 100 Hz. Impedances were kept below 5 k. Only data from electrodes F8, Cz, and O2 were analyzed in detail, since a previous exploration of the data had shown that the remaining electrodes did not add further information. Electromyograms (EMG) of the submental, nuchal, and forearm muscles as well as the electrocardiogram (ECG) were recorded and digitized with a sampling rate of 200 Hz. Respiration was assessed by recording nasal and oral airflows with thermistors, nasal pressure with a cannula, thoracic and abdominal respiratory movements with strain gauges, and oxygen saturation with a finger oxymeter. In addition, synchronous video recordings of the head and upper trunk of subjects were obtained and digitally stored.

2.3. Event definition and creation of data segments Yawns consisted of the typical sequence of respiratory (long inspiration, brief acme, and rapid expiration), and motor (opening of the jaw, closure of the eyes, contraction of facial muscles, sometimes stretching of trunk, neck, and arms) behaviours. The phenomenology of yawns in individual patients was not the primary interest of this study and was therefore not analyzed in detail. Voluntary body movements consisted of variable movements of the arms or the neck such as scratching, changes of position, and stretching (without yawns). They were included as a control condition to account for the possibly confounding unspecific effect on vigilance of movements accompanying yawns. Although these movements were different from movements associated with yawning with regard to their generation (voluntary versus partly involuntary) and with regard to the involved muscle groups, they were still expected to be a valid contrast to elucidate the specific circumstances and consequences of yawning. Data segments with yawns or voluntary body movements were detected visually in the video recordings, and exported to the software MATLAB (The MathWorks, Inc.). The onsets of yawns and of movements were determined visually in the smoothed rectified EMG of the submental muscle and of the forearm and nuchal muscles, respectively. Respiratory flow measurements proved to be less reliable markers of the yawning onset. The endings of yawns and body movements were defined as the time-points of return to baseline values of the corresponding EMG activity and of disappearance of muscle artefacts in the EEG. Yawns and movements accompanied by a tonic muscle activity not allowing the determination of onsets and endings were excluded from further analysis. Artefact-free EEG segments were obtained by using three consecutive procedures. First, the EEG time-frames corresponding to the actual yawn or movement were removed, since they were often heavily contaminated by EMG activity. Instead, the following EEG segments were created: Baseline segments lasting from 15 to 12 s before onset of EMG activity, pre-yawning and pre-movement segments corresponding to a time period from 10 to 0 s before the onset of the corresponding EMG activity, and post-yawning and post-movement EEG segments, occurring from 0 to 10 s after the ending-points of the corresponding EMG activity. Second, EEG components corresponding to eye movements, ECG activity or single electrode-artefacts were removed from the signal by means of an independent component analysis (ICA) of all seven EEG leads and both EOG leads. ICA was performed separately for each subject with all pre- and post-event EEG segments, using the “runica”-function of the toolbox EEGLAB [11] for MATLAB (http://www.sccn.ucsd.edu/eeglab/). Third, the remaining segments were visually inspected and rejected if not artefact-free. Artefact-free HRV segments. Since the ECG and the HRV were found to be largely unaffected by movement artefacts during yawns or movements, contiguous HRV-segments lasting from 15 s before to 40 s after the corresponding onset were created. Segments with arrhythmic beats or movement artefacts were rejected. One female subject had abundant ventricular extrasystoles in the recorded segments and was therefore excluded from analysis of HRV.

2.4. Analysis of EEG 2.2. Recordings Seven EEG leads (F8, F7, C4, Cz, C3, O2, and O1 according to the international 10–20 system), each referenced to the contralateral (left in case of

2.4.1. Long-term power spectra Long-term EEG changes were analyzed by calculating the averaged power spectral differences between two out of four different EEG segments: (1)

A.G. Guggisberg et al. / Behavioural Brain Research 179 (2007) 159–166 pre-yawning, (2) post-yawning, (3) pre-movement, and (4) post-movement. Power spectral estimates of each trial were obtained by dividing the segments of 10 s duration into 7 epochs of 2.5 s duration with 50% overlap, which were zeropadded to 256 sampling points, Hanning-windowed, Fourier-transformed, and averaged (Welch’s modified periodograms). The resulting power spectra with a frequency resolution of 0.39 Hz were averaged over trials, and log-transformed. Power spectral differences between two conditions were obtained by subtraction, and averaged across subjects. In addition, shifts in the peak and weighted mean alpha frequencies were computed for each subject and averaged, since they yield valuable information about the arousal level [5,6]. The alpha peak frequency was defined as the frequency bin with the greatest spectral estimate in the alpha range; the weighted mean alpha frequency was the mean of all alpha frequency bins, which were weighted with their normalized power spectral estimate. 2.4.2. Short-term time–frequency decomposition For analysis of short-term or transient EEG changes, overlapping EEG epochs were Hanning-windowed and Fourier-transformed, sliding the epoch’s time window of 2 s in 0.5 s steps (short-time Fourier transform). The resulting power spectra of each time step were averaged over trials and log-transformed. Power changes at each time–frequency point were obtained by subtracting the mean baseline log-power spectrum from each spectral estimate [11,34]. Grand averages of power changes were obtained by averaging over subjects.

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2.6.4. Significance cut-off All p-values were required to be smaller than 0.05 after corrections to be considered significant.

3. Results 3.1. Long-term EEG power spectra An average of 7.7 (range 3–21) artefact-free EEG segments of yawning and 8.8 (range 4–14) artefact-free EEG segments of movements could be obtained from each subject, yielding a total of 123 yawns and 140 movements. 3.1.1. Yawning versus isolated movements The long-term EEG power spectra – corresponding to a stationary time window of 10 s duration – before and after yawns and movements are plotted in Fig. 1. The differences between

2.5. Analysis of HRV Heart rate was calculated from the inverse R–R intervals in the ECG, which were down-sampled and interpolated to a sampling frequency of 1 Hz. HRV was obtained by calculating the difference between the actual heart rate and the heart rate of the previous second. The grand average of HRV during yawning and during movements was obtained by averaging across trials and subjects.

2.6. Statistical analyses 2.6.1. Long-term power spectra To test the statistical significance of long-term power differences, 6 frequency bands were defined by averaging over adjacent frequency bins: delta (0.7–3.1 Hz), theta (3.5–7.4 Hz), slow alpha (7.8–9.8 Hz), fast alpha (10.2–11.7 Hz), slow beta (12.1–14.8 Hz), and fast beta (15.2–20.3 Hz). For each frequency band, the mean spectral differences between segments and events of all subjects were tested against 0 using a two-tailed t-test for one sample. In addition, the double contrast of power changes in the yawning condition compared to power changes in the movement condition was also tested for significance using two-tailed paired t-tests. 2.6.2. Short-term time–frequency decomposition The methods used for statistical analysis of short-term spectral EEG changes are described in detail elsewhere [14,34]. In short, the statistical significance of power changes at each time–frequency point was tested for each subject using 200,000 bootstrap permutations with pseudo-t statistics, which compared baseline with active time-points [14]. Correction for multiple testing was achieved by using a false discovery rate of 5% [14,15]. Overall significance across subjects was assessed by performing binomial statistics with p-values of each subject [22]. Furthermore, mean power changes in the time–frequency plane were compared between yawns and movements with paired t-tests at each time–frequency point. A false discovery rate of 5% was used to adjust for the family-wise error [14,15]. 2.6.3. HRV A time × event (yawn or movement) analysis of variance (ANOVA) was used to test mean HRV changes for significance. Individual time-points were further compared against baseline time-points using a Tukey–Kramer HSD procedure. Comparison of HRV between yawns and movements at individual time-points was performed with paired t-tests, using a false discovery rate of 5% to adjust for the family-wise error [14,15].

Fig. 1. The grand averages of long-term power spectral estimates – corresponding to a time window of 10 s duration before and after yawning as well as before and after isolated movements – are shown for the three studied electrodes.

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Fig. 2. The grand average of long-term power spectral differences ±95% confidence interval is indicated for all comparisons between the pre-yawning, post-yawning, pre-movement, and post-movement EEG segments. Note the difference in delta power between the yawning and the movement conditions (filled arrows) as well as the changes in alpha power after the events compared to before the events (unfilled arrows).

yawning and movements are shown in Fig. 2 (left and right panel) and Table 1. Power in the delta frequency range at electrode Cz was found to be significantly greater before and after yawning than before and after isolated movements (t(15) ≥ 3.1, p ≤ 0.008). In addition, the pre- and post-yawning conditions were also associated with greater slow beta power over occipital brain regions than the pre- and post-movement conditions (t(15) ≥ 2.2, p ≤ 0.045, Table 1 and Fig. 2).

3.1.2. After versus before yawning The differences between the post-yawning and the preyawning segments are shown in Fig. 2 (upper panel) and Table 2: After yawning, power in the fast alpha frequencies was significantly reduced in the occipital (t(15) = −5.3, p = 0.0001) and frontal brain regions (t(15) = −4.1, p = 0.001), whereas slow alpha power was significantly increased in the central brain region (t(15) = 2.4, p = 0.028). In addition, peak and mean alpha

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Table 1 Long-term EEG power spectral differences and alpha frequency changes after yawning and movements compared to before yawning and movements Before yawns–before movements

Power difference (dB) Delta m p

After yawns–after movements

F8

Cz

O2

F8

Cz

O2

−0.12 (±3.1) 0.88

+0.93 (±1.2) 0.008

+0.16 (±1.9) 0.74

−0.52 (±3.4) 0.55

+1.04 (±1.3) 0.007

+0.34 (±1.9) 0.47

Theta

m p

−0.54 (±3.5) 0.54

+0.34 (±1.6) 0.41

+0.37 (±2.2) 0.51

−0.63 (±2.9) 0.40

+0.40 (±1.5) 0.32

+0.44 (±2.0) 0.39

Slow alpha

m p

+0.28 (±5.8) 0.84

+0.97 (±4.1) 0.36

+0.04 (±3.5) 0.96

+0.96 (±6.1) 0.54

+2.44 (±4.2) 0.34

+1.53 (±4.1) 0.15

Fast alpha

m p

+0.73 (±4.6) 0.53

+1.40 (±3.7) 0.15

+1.16 (±3.7) 0.23

+0.34 (±4.9) 0.78

+1.81 (±3.5) 0.06

+1.32 (±4.1) 0.21

Slow beta

m p

+0.35 (±3.4) 0.69

+1.03 (±2.2) 0.08

+1.63 (±2.4) 0.017

+0.45 (±3.5) 0.61

+1.20 (±2.3) 0.06

+1.46 (±2.7) 0.045

Fast beta

m p

+0.04 (±3.7) 0.96

−0.17 (±2.2) 0.76

+0.91 (±2.2) 0.11

+0.01 (±3.8) 0.99

+0.22 (±2.4) 0.73

+0.49 (±2.2) 0.38

Mean values ± standard deviation (m) and their statistical significance (p, t-tests) are tabulated for the three studied EEG electrodes. Positive values indicate greater power in the yawning condition, negative values greater power in the movement condition. Note that yawns were preceded and followed by a significantly greater delta activity over the vertex than movements.

frequencies were shifted to lower frequencies in occipital and central regions after yawning (Table 2; t(15) ≤ −2.9, p ≤ 0.01). Thus, a significant slowing of alpha rhythms and a shift towards central regions occurred after yawning. Beta frequencies also

showed significant changes after yawning: fast beta activity increased over central brain regions (t(15) = 5.3, p = 0.0001), whereas slow beta rhythms decreased over occipital regions (t(15) = −4.4, p = 0.0005).

Table 2 Long-term EEG power spectral differences before and after yawning compared to before and after movements After yawns–before yawns

After movements–before movements

F8

Cz

O2

F8

Cz

O2

m p

−0.09 (±0.5) 0.46

+0.04 (±0.3) 0.60

−0.03 (±0.3) 0.72

+0.30 (±0.6) 0.052

−0.07 (±0.5) 0.58

−0.21 (±0.7) 0.25

Theta

m p

−0.16 (±0.6) 0.29

−0.04 (±0.4) 0.73

−0.21 (±0.5) 0.06

−0.07 (±0.4) 0.47

+0.09 (±0.4) 0.41

−0.28 (±0.7) 0.14

Slow alpha

m p

−0.38 (±0.9) 0.10

+0.43 (±0.7) 0.028

−0.25 (±1.3) 0.46

−1.06 (±0.8) 0.0001

−1.05 (±0.8) 0.0001

−1.74 (±1.2) 0.00004

Fast alpha

m p

−0.66 (±0.7) 0.001

−0.14 (±0.7) 0.71

−0.92 (±0.7) 0.0001

−0.28 (±1.3) 0.40

−0.48 (±0.9) 0.049

−1.08 (±2.1) 0.06

Slow beta

m p

+0.10 (±0.5) 0.42

+0.09 (±0.2) 0.13

−0.60 (±0.5) 0.0005

−0.01 (±0.5) 0.97

−0.07 (±0.7) 0.65

−0.43 (±0.5) 0.007

Fast beta

m p

+0.09 (±0.5) 0.47

+0.38 (±0.3) 0.0001

−0.23 (±0.5) 0.06

+0.12 (±0.6) 0.44

−0.01 (±0.6) 0.98

+0.18 (±0.5) 0.16

m p

−0.05 (±0.5) 0.71

−0.32 (±0.3) 0.001

−0.39 (±0.3) 0.00001

+0.37 (±1.0) 0.17

+0.17 (±0.8) 0.42

−0.12 (±0.8) 0.53

m p

−0.02 (±0.1) 0.30

−0.05 (±0.1) 0.09

−0.07 (±0.1) 0.010

+0.02 (±0.2) 0.56

+0.10 (±0.1) 0.013

+0.02 (±0.2) 0.66

Power change (dB) Delta

Frequency shift (Hz) Alpha peak Alpha mean

Abbreviations as in Table 1. Positive values indicate a power increase after the event, negative values a decrease. Note that yawning was associated with a slowing and attenuation of alpha rhythms whereas movements were followed by an acceleration and attenuation of alpha rhythms.

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3.1.3. After versus before isolated movements When comparing long-term EEG power spectra before and after isolated movements (Fig. 2 lower panel, Table 2), a significant decrease in alpha power could be observed. In contrast to yawning, the decrease after movements concerned mostly slow alpha rhythms (t(15) ≤ −5.3, p ≤ 0.0001), whereas fast alpha activity was less altered (t(15) ≥ −2.1, p ≥ 0.049). In addition, a weak but significant increase in the mean alpha frequency could be observed over central regions (t(15) = 2.8, p = 0.013). Thus, isolated movements reduced alpha rhythms and, unlike yawns, accelerated them. 3.1.4. Double contrast Power decrease in the slow alpha band was significantly smaller after yawns than after movements at all three electrodes (t(15) ≥ 2.9, p ≤ 0.011). 3.2. Short-term EEG power changes The EEG time–frequency decomposition – corresponding to moving time-windows of 2 s length – showed some power fluctuations over time mainly in the alpha and theta frequency range, but no significant power spectral changes compared to the baseline period of 15–12 s before event onset (p > 0.05, data not shown). Furthermore, the short-term power spectra in the time–frequency plane did not differ significantly between the yawning and movement condition (p > 0.05). 3.3. HRV An average of 14.1 (range 3–29) artefact-free HRV segments of yawning and 13.7 (range 4–33) artefact-free HRV segments of movements could be obtained from each subject, yielding a total of 212 yawns and 205 movements. HRV changed significantly during yawning and movements (F(55, 1568) = 3.6, p < 0.00001, see Fig. 3). A significant increase occurring 1–4 s after onset of yawning or movements was followed by a significant decrease 17 s after onset (p < 0.05). HRV changes did not differ significantly between yawns and movements, neither globally (F(1, 1568) = 0.38, p = 0.54), nor between individual time points (p > 0.05).

Fig. 3. Grand averages of the HRV before, during, and after yawns as compared to before, during, and after movements are shown. A significant increase 1–4 s after the onset of the event was followed by a significant decrease 17 s after onset (p < 0.05). None of the time points showed a significant difference between the events (p > 0.05).

4. Discussion This study evaluated the functional relationship between yawning and vigilance by measuring indicators of the cortical arousal level and of autonomic activity before and after yawning, as compared to isolated movements. Our findings demonstrate, that yawning indeed occurs during progressive drowsiness, which is compatible with the notion that yawning is triggered by states of low vigilance. In contrast, we were unable to observe a specific arousing effect of yawning on the brain or the autonomic nervous system. The arousal hypothesis of yawning is therefore not supported by our data. 4.1. The prerequisites of yawning When analyzing long-term EEG power spectra, we found that central midline delta power density was significantly greater before and after yawns than before and after movements (Table 2 and Figs. 1 and 2). Delta power is known to increase with the duration of wakefulness and to decrease during sleep, and is therefore interpreted as an indicator of a sleep promoting process [7]. In addition, delta band activity increases in anterior and central brain areas during the transition from wakefulness to sleep and shows a maximum over the fronto-central midline during drowsiness [9,10,31]. Thus, sleep pressure and drowsiness proved significantly greater when subjects yawned than when they moved only. This finding provides strong evidence for the notion that yawns are triggered by drowsiness, which is also in agreement with previous behavioural studies showing that yawning occurs most frequently before and after sleep [18,24]. In contrast, several studies have observed an arousal rather than drowsiness before chemically or electrically induced yawns of anesthetized animals. For instance, microinjection of histamine [29], l-glutamate, or nitric oxide releasing compounds [26] into the paraventricular nucleus of the hypothalamus, or electrical stimulation of the same structure [26], evoked an arousal response in the EEG or electrocorticogram, which was followed by yawning after about 11 s. Yawning also occurred during induction of anaesthesia in humans, where it was found to be associated with an arousal shift as indicated by an increased bispectral EEG index, although this shift may have been confounded by EMG artefacts [19]. The time range of 15 s before yawning analyzed in our study was adjusted so that an arousal of this type would have been detected. The fact that spontaneous yawns were independent of a previous arousal in our study shows that arousal is not a prerequisite of spontaneous yawning during wakefulness or drowsiness. However, preceding arousals may be necessary for yawns to occur in the non-physiological state of anaesthesia. It is noteworthy that no significant short-term EEG changes were observed before or after yawning, which speaks against any fast “reflex”-like [1] cortical processes generating yawns. Furthermore, there was no evidence for a significant autonomic activity before onset of yawning, which might have triggered the yawning process. Besides central midline delta power, occipital slow beta activity was also significantly greater in the yawning condition than

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in the isolated movement condition. Slow beta (i.e., spindle) activity increases in frontal, central, and parietal brain regions during the transition from sleep stage 1 to stage 2 [9,30]. The significance of the observed difference over occipital regions is, however, unclear. 4.2. The function of yawning Once it is established that yawning occurs due to drowsiness, the next question one has to consider is the function of yawning itself. We studied the effect of yawns and movements on the brain arousal level by comparing long-term EEG power spectra after yawns and movements to power spectra before yawns and movements, respectively (Table 1 and Figs. 1 and 2). First, it is important to note that the increased delta power over the vertex (electrode Cz) observed before yawning persisted to the same amount also after yawning. Thus, yawning did not reverse the increased sleep pressure and drowsiness that seemed to have triggered it. From studies assessing EEG power changes during the transition from wakefulness to sleep, it is known that alpha activity decreases and moves in an anterior direction along the midline of the scalp with increasing drowsiness [9,10,30]. In contrast, increased arousal levels are manifested by an acceleration and attenuation of alpha oscillations in EEG [5,6]. Here, we show that yawns and movements were associated with different power changes in the alpha frequency band: whereas alpha rhythms were significantly accelerated and attenuated by movements, they were decelerated, shifted towards central brain regions, and attenuated by yawning (see Fig. 2). Furthermore, slow alpha rhythms decreased significantly less after yawns than after movements. Thus, isolated movements seemed to have an arousing effect on EEG that was qualitatively similar as – but quantitatively smaller than – the effect that can be observed 30 min after oral ingestion of 250 mg caffeine [6]. In contrast, yawning was associated with signs of a decreasing arousal level. Both movements as well as yawns were also followed by rather complex changes in beta power density, the significance of which remains unclear. An influence of EMG artefacts is unlikely, since increases as well as decreases in power could be observed, and power changes were most prominent over the vertex and occipital brain regions where less motor artefacts would be expected. In addition, great precautions were taken to avoid artefacts. The effects of yawning on autonomic activity was investigated by calculating the heart rate variability before, during, and after yawning, and by comparing the results with the movement condition (Fig. 3). Both yawns and movements provoked a transient increase in HRV starting after the corresponding EMG onset, followed by a slow decrease. However, no difference between yawning and isolated movements could be found at any time-point. Thus, although an autonomic activation occurs after the onset of submental muscle activity induced by yawning, it is entirely unspecific and obviously due to the movement rather than the yawning as such. This is in fact not the first study that is unable to find evidence for an arousing effect of yawning. When analyzing

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vigilance states of premature human newborns before and after spontaneous yawns, significant vigilance changes (mostly from wakefulness to drowsiness) were found in the time period before but not in the period after yawning [16], which fits well with our finding of yawning occurring during progressive drowsiness, but not having an arousing effect. Autonomic changes during and after yawning as observed in our study have been previously described in a study assessing the muscle sympathetic nerve activity during yawning in a single subject, and these changes were found to be temporally related to respiration [2]. An increase in skin conductance (indicating autonomic activation) was reported during yawns that were voluntarily produced by the examined subject, but this increase could be observed to the same extent when subjects only opened their mouth or took a deep breath [17]. In addition, a significant increase in the mean heart rate was found only when subjects opened their mouth or took a deep breath, but not during the self-produced yawns [17]. Thus, although an autonomic activation was indeed observed in several studies, it was consistently found to be unspecific. In contrast, the communication hypothesis of yawning has received recent empirical support from functional imaging studies, which showed that watching other persons yawn provokes specific activations of brain areas responsible for social behaviour [28] or self-processing [23]. One of the main arguments [3,8] for the concept of an arousing effect of yawning had been the observation that motor activity was significantly increased after yawns [4,16]. In the light of our results, this finding may be explained differently: the yawning subjects try to reduce their drowsiness by making body movements that indeed proved to have an arousing effect in this study. Thus, the increased motor activity observed after yawning is not an indicator of an arousing effect of yawning, but an effective countermeasure against the underlying drowsiness. A further argument [3] for an arousing effect of yawning was based on the observation that yawning occurs frequently before going to bed, but not anymore when the subjects are actually lying in bed waiting to fall asleep, thus at a moment when drowsiness is expected to be greatest and no arousal is required [4]. However, this observation may just as well be explained by the communication hypothesis, by stating that yawning is a non-verbal signal to go to sleep when drowsiness occurs, which is obviously no longer needed when already lying in bed. One might argue that the lacking empirical support for the arousal hypothesis is due to inherent methodological problems in the assessment of vigilance and of yawning itself. Thus, it might be suggested that yawning provokes an arousal in certain brain areas that are not accessible by measurements of EEG, HRV, and skin conductance. However, vigilance changes are typically manifested diffusely over the whole brain rather than in a restricted area, and we used the EEG electrode locations that are most sensitive to them (Cz). Furthermore, we were able to detect an arousing effect of voluntary body movements, which shows that the methodology was indeed capable of detecting relevant brain activations. A further criticism might refer to the rather short time window of 10 s after yawning that was analyzed in our study, and postulate that the arousing effect of yawning occurs later. However, our data not only demonstrates a lacking

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increase of the arousal level, but even a decrease of the arousal level after yawning. Even if one assumed a reversal of this trend after 10 s, one still would have to explain the advantage of yawning over simple body movements, which proved to have a much faster arousing effect. Finally, one might object that some earlier studies assessed self-produced [17] or chemically induced yawns [19,26,29] rather than spontaneous yawns, which might have a different physiology, and this study analyzed mostly patients rather than healthy subjects, for which reason the results may not reflect the physiological mechanisms of yawning. However, none of the subjects included in our study suffered from a condition which might provoke pathological yawning (see Section 2), and the increased sleepiness present in the examined patients is hardly sufficient to fundamentally alter a phylogenetically old behaviour such as yawning. On the contrary, one can expect that, if yawning indeed had an arousing effect, its physiological function would have been maximally challenged in our setting. In conclusion, having found no empirical evidence for an arousing effect of yawning, and in the absence of convincing arguments against the validity of the available data, we advocate a rejection of the arousal hypothesis of yawning as stated above. In contrast, our findings are compatible with the communication hypothesis. Acknowledgments The authors would like to thank Heidi Mani, Center of Sleep Medicine, Inselspital Berne, for her help with data acquisition and inspection, and an anonymous reviewer for his helpful comments. References [1] Askenasy JJ. Is yawning an arousal defense reflex? J Psychol 1989;123: 609–21. [2] Askenasy JJ, Askenasy N. Inhibition of muscle sympathetic nerve activity during yawning. Clin Auton Res 1996;6:237–9. [3] Baenninger R. On yawning and its functions. Psychonom Bull Rev 1997;4:198–207. [4] Baenninger R, Binkley S, Baenninger M. Field observations of yawning and activity in humans. Physiol Behav 1996;59:421–5. [5] Barry RJ, Clarke AR, McCarthy R, Selikowitz M, Rushby JA, Ploskova E. EEG differences in children as a function of resting-state arousal level. Clin Neurophysiol 2004;115:402–8. [6] Barry RJ, Rushby JA, Wallace MJ, Clarke AR, Johnstone SJ, Zlojutro I. Caffeine effects on resting-state arousal. Clin Neurophysiol 2005;116:2693–700. [7] Borbely AA, Baumann F, Brandeis D, Strauch I, Lehmann D. Sleep deprivation: effect on sleep stages and EEG power density in man. Electroencephalogr Clin Neurophysiol 1981;51:483–95. [8] Daquin G, Micallef J, Blin O. Yawning. Sleep Med Rev 2001;5:299– 312. [9] De Gennaro L, Ferrara M, Bertini M. The boundary between wakefulness and sleep: quantitative electroencephalographic changes during the sleep onset period. Neuroscience 2001;107:1–11.

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