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. 2009 Oct 5;587(Pt 23):5783–5794. doi: 10.1113/jphysiol.2009.176164

Increased cerebral activity suppresses baroreflex control of heart rate in freely moving mice

Shizue Masuki 1, Hiroshi Nose 1
PMCID: PMC2805385  PMID: 19805749

Abstract

We assessed whether increased cerebral activity suppressed baroreflex control of heart rate (HR) and, if so, whether this occurred prior to the onset of locomotion in daily activity of mice. We measured mean arterial pressure (MAP, arterial catheter), cerebral blood flow in the motor cortex (CBF, laser-Doppler flowmetry), and electroencephalogram in free-moving mice (n= 8) during 12 daytime hours. The contribution of baroreflex control of HR to MAP regulation was determined during a total resting period for ∼8 h from the cross-correlation function (R(t)) between spontaneous changes in HR (ΔHR) and MAP (ΔMAP) every 4 s and the sensitivity was determined from ΔHR/ΔMAP where R(t) was significant (P < 0.05). The power density ratio of θ to δ wave band in electroencephalogram (θ/δ), determined every 4 s as an index of cerebral activity, was positively correlated with CBF during 73 ± 3% of the total resting period (P < 0.05) and with R(t) during 59 ± 2% (P < 0.05). When each measurement during the resting period was divided into seven bins according to the level of θ/δ, CBF was 91 ± 2% in the lowest bin and 118 ± 3% in the highest bin (P < 0.001), R(t) was −0.69 ± 0.06 and −0.27 ± 0.04 (P < 0.001) and ΔHR/ΔMAP (beats min−1 mmHg−1) was −12.4 ± 0.9 and −7.5 ± 0.9 (P < 0.001), respectively, with significant correlations with θ/δ (all P < 0.002). Moreover, mice started to move in ∼30 sec after the sequential increases of θ/δ and R(t), mice started to move at 5 times higher probability than after a given time, followed by a rapid increase in MAP by ∼10 mmHg. These results suggest that increased cerebral activity suppresses baroreflex control of HR and this might be related to the start of voluntary locomotion with a rapid increase in MAP.

Introduction

A rapid increase in arterial blood pressure at the onset of exercise has been thought to be advantageous for blood flow to the contracting muscles to fill their oxygen demand without delay (Sheriff et al. 1987). Since arterial blood pressure at rest is controlled at a lower level than during exercise by the baroreflex control system, and since the pressure increases rapidly at the onset of exercise, it has been disputed how the system knows when to increase pressure before the start of exercise, and how the system increases pressure to a higher level to meet the subsequent intensity of exercise (Rowell et al. 1996; Secher, 2007).

Experimentally, the baroreflex sensitivity of heart rate (HR) was reportedly suppressed in cats when they were confronted with aggressive individuals (Schlör et al. 1984) or in rats with different species (Knuepfer et al. 1991). Moreover, the baroreflex sensitivity of HR in cats was suppressed when they pushed the lever of a feeder system to get food (Matsukawa et al. 2006), and more importantly for the present study, the suppression occurred prior to their pushing the lever (Komine et al. 2003). These results suggest that the activated cerebral cortex, such as by external stimuli and/or voluntary physiological desires, suppresses the baroreflex control of HR. However, the findings might be limited to the conditions designed for the experiments and it is therefore uncertain whether they occur at high frequency in their daily life.

On the other hand, it was suggested that the cerebral cortex is voluntarily activated even in the absence of external stimuli (Fox & Raichle, 2007) and indeed, cerebral activity in animals as well as humans spontaneously fluctuated in their daily life (Biswal et al. 1995; Kenet et al. 2003), which would be partially associated with the voluntary development of physiological desires (Denton et al. 1999). If so, suppression of the baroreflex control of HR, synchronized with activated cerebral activity, would occur more frequently than ever thought in daily life (Schlör et al. 1984; Komine et al. 2003), and moreover, it would be accompanied by the onset of voluntary locomotion with an increase in arterial blood pressure.

To examine these hypotheses, in the present study, we continuously measured cerebral activity and baroreflex control of HR in freely moving mice in their daily life. Here, we found that the baroreflex control of HR was suppressed during almost the whole of the period during which the cerebral cortex was activated, the suppression was in proportion to cerebral activity, and moreover, after these sequential responses, mice started to move at 5 times higher probability than after a given time. Thus, this is the first study to report such tight linkages between cerebral activity, baroreflex control of HR, and voluntary locomotion in mice in their daily life.

Methods

Animals

Adult male C57BL/6J mice aged 11–19 weeks (n= 8, body weight = 28 ± 2 g (s.d.)) were used for the study. They were housed at 25°C with food and water ad libitum under light conditions from 07.00 h to 19.00 h. The procedures used were in accordance with the guiding principles for the care and use of animals in the field of physiological sciences published by the Physiological Society of Japan (2003) with prior approval of the Animal Ethics Committee of Shinshu University School of Medicine.

Preparations

After anaesthetization with pentobarbital sodium (50 mg (kg body weight)−1, i.p.), three stainless-steel screws (OD 1 mm) of electroencephalogram (EEG) electrodes were placed on the skull surface according to stereotaxic coordinates (Paxinos & Franklin, 2001); AP −1 and L +1, AP −3 and L −1 mm from bregma, and AP +1 and L +1 mm from lambda (Fig. 1). Similarly, a stainless-steel pipe (OD 0.80, ID 0.57, L 8.0 mm) was inserted through the skull so that the tip was positioned on the cortex surface (AP +1.5, L −1, and V +1 mm from bregma), which was used to hold a laser-Doppler flow probe for cerebral blood flow (CBF) measurement. The screws and the stainless-steel pipe were fixed to the skull with dental cement.

Figure 1.

Figure 1

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Schematic illustration of the implantation of electroencephalogram (EEG) electrodes and a stainless-steel pipe for cerebral blood flow (CBF) measurement

A polyethylene catheter to measure mean arterial blood pressure (MAP) and HR was inserted into the left femoral artery so that the tip was positioned 5 mm below the left renal artery (Masuki et al. 2003a). The catheter was secured to the surrounding leg muscles. The catheter and EEG electrodes were tunnelled subcutaneously and then exteriorized between the scapulae. The exteriorized catheter was connected to a cannula swivel (model TCS2-21; Tsumura, Tokyo, Japan), and the mouse was placed in a cage with a free-moving system (model TFM-170; Tsumura). The arterial catheter was flushed every day with 100 i.u. heparin in 0.2 ml saline. The surgery was performed at least a week before the measurement (Masuki et al. 2005).

Measurements

To investigate the relationship between trend changes in cerebral activity and baroreflex control of HR in freely moving mice, we measured EEG through a band-pass filter of 0.5–30 Hz (Bioelectric Amplifier, model MEG-1200; Nihon Kohden, Tokyo).

Also, we measured CBF by laser-Doppler flowmetry (model FLO-C1 BV; Omegawave, Tokyo). The flow probe consisted of two glass fibres: one to insert the laser light and the other to detect the reflection. The tips of the fibres were glued together to be 0.5 mm in diameter and inserted through the probe holder to a depth of 1.5 mm from the skull surface so that the tips were positioned close to the motor cortex.

MAP was measured through a catheter connected to a pressure transducer (model TP-400T; Nihon Kohden). HR was counted from the arterial pressure pulse with a tachometer (model AT-601G; Nihon Kohden). Activity was monitored with locomotion sensors equipped on the rectangular frame of 25.5 × 18.5 cm in inner size (model LCM-10M; Melquest, Toyama, Japan) in which a mouse plastic cage of 20.8 × 15.5 cm in outer size was placed. The sensors were composed of three pairs of an infrared beam lamp and a confronting receiver on the longer frames and two more pairs on the shorter frames with ∼6.3 cm between each lamp or receiver. Mice were connected to the measuring instruments at least 12 h before the measurements. Measurements in each mouse were then performed in a free-moving state for the next 12 h during the daytime, but were not performed at night because mice moved continuously without resting during that period, which made it difficult to analyse the transient changes of measurements from the resting to locomotion state.

Data acquisition

EEG, CBF, HR, MAP and activity were digitized and stored in a computer (OptiPlex GX260; Dell, Kawasaki, Japan) at 128 Hz. HR and MAP were re-sampled at 10 Hz through a low-pass filter with an edge frequency of 1.5 Hz to remove pulsatile arterial pressure signals to determine baroreflex control of HR (see below).

Analyses

Data for analyses

We analysed the data limited to the resting period in the present study because baroreflex control of HR during locomotion was reportedly affected by signals from exercising skeletal muscle and higher brain centres (Komine et al. 2003; Matsukawa et al. 2006; McIlveen et al. 2001; Sala-Mercado et al. 2007), which would make it difficult to assess the relationship between cerebral activity and baroreflex control of HR. Indeed, in the present study, although θ/δ of EEG, CBF and R(t) (see below for details of θ/δ and R(t)) were closely linked during rest and just before locomotion, this linkage disappeared after the onset of locomotion, suggesting that mechanisms other than cerebral activity also affected the baroreflex control of HR during locomotion. The criterion to judge the resting period was zero counts of activity for 30 s. As a result, ∼470 min of 720 min was the resting period on average and the data during this period were used for the following analyses.

Baroreflex control of HR

More details of the analyses were reported previously (Masuki et al. 2003a,b, 2005). Briefly, the slope of ΔHR/ΔMAP was determined from HR response to the spontaneous change in MAP every 4 s using the cross-correlation function (R(t)). As shown in Fig. 2, R(t) above (red) and below (blue) the lines of P= 0.05 indicate significantly positive and negative correlations, respectively, which were used to determine positive (red) and negative (blue) ΔHR/ΔMAP. The formulae used for analyses are as follows:

graphic file with name tjp0587-5783-m1.jpg

where R(t) is the cross-correlation coefficient between x (= MAP) and y (= HR) at the given time of t after correction for the delay time (Δt= 0.6 s) of HR response to MAP change. The Inline graphic and Inline graphic were averaged values of MAP and HR, respectively, from time Inline graphic to Inline graphic (τ= 4 s). The slope of ΔHR/ΔMAP was used as an index of baroreflex sensitivity of HR after R(t) was confirmed significant.

Figure 2. Typical example of measurements in a free-moving mouse.

Figure 2

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Top to bottom: activity counts, ratio of θ to δ wave band in EEG (θ/δ), CBF, cross-correlation function (R(t)) between ΔMAP and ΔHR, ΔHR/ΔMAP, HR and MAP in the mouse for 90 min. *R(t) was transformed to ZR(t). θ/δ and ZR(t) determined every 4 s were averaged for a period from t− 40 to t+ 40 s (21 values) while moving t by an increment of 4 s. These values were used to determine the correlation period with θ/δ (Table 1) and the probability of locomotion (Fig. 4B). The part with a filled bar is shown on a larger scale in Fig. 4A.

Relationships between θ/δ, CBF, and R(t)

EEG power density was calculated every 4 s in two frequency bands: δ (0.75–4.0 Hz) and θ (6.0–9.0 Hz), to determine the ratio of θ to δ wave band (θ/δ). CBF values were averaged every 4 s, expressed as percentage of the total resting values (Dirnagl et al. 1989). To assess the relationship between R(t) and these variables quantitatively, we transformed R(t) to ZR(t) as follows (Fisher, 1915):

graphic file with name tjp0587-5783-mu5.jpg

Since an increase in CBF following an increase in θ/δ occurred at 4–8 min per cycle, their cross-correlation function was determined every 4 min after correction for the delay time by which the highest value was marked in each mouse as performed in the R(t) for the present and our previous studies (Masuki et al. 2003a,b, 2005). Similarly, a cross-correlation function between θ/δ and ZR(t) was determined. The results are shown in the Table 1.

Table 1.

Correlation period of θ/δ with CBF and ZR(t)

Mouse no. Resting period (min) Positive correlation period at rest (%)
θ/δvs. CBF θ/δvs. ZR(t)
1 428 69 60
2 484 59 53
3 457 80 62
4 454 73 65
5 403 74 54
6 428 74 58
7 500 63 54
8 583 90 65
Mean ±s.e.m. 467 ± 20 73 ± 3 59 ± 2
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Values are the means ±s.e.m. θ/δ, power density ratio of θ to δ wave band in electroencephalogram; CBF, cerebral blood flow; R(t), cross-correlation function between changes in heart rate and mean arterial pressure; ZR(t), transformed R(t). Positive correlation period is presented as a percentage of the total resting period. Total measuring period in each mouse was 720 min.

Circulatory responses to graded levels of θ/δ

To analyse CBF, ZR(t), ΔHR/ΔMAP, HR and MAP responses to the graded level of θ/δ, they were divided into subgroups belonging to seven bins of θ/δ with 0.25 increment from 0 to >1.5 after correction for the delay time of their responses to an increase in θ/δ. Mean values of CBF, ZR(t), ΔHR/ΔMAP, HR and MAP in each bin were determined in each mouse and the results are presented as the means and s.e.m. for eight mice in Fig. 3A and B.

Figure 3. CBF, ZR(t), HR and MAP (A) and ΔHR/ΔMAP (B) in graded levels of θ/δ in free-moving mice.

Figure 3

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Means and s.e.m. bars are presented for 8 mice. Data in the resting period for ∼8 h in each mouse were used for analyses. ΔHR/ΔMAP was determined when R(t) between ΔHR and ΔMAP was significant regardless of negative or positive. Significant differences from values at 0–0.25 of θ/δ, *P < 0.05, **P < 0.01 and ***P < 0.001.

Probability of locomotion

To estimate the probability that mice would start locomotion after the sequential increases of θ/δ and ZR(t), we determined the time at which ZR(t) decreased closest to but above the threshold of 2 s.d. determined during the total period after a transient increase above the threshold (Fig. 4A). If locomotion, with more than zero counts for 30 s, occurred within 30 s after that time, we judged that it was associated with the increase of θ/δ and ZR(t). The probability was determined as (the number of the increase of θ/δ and ZR(t) accompanied by the locomotion/the total number of the increase of θ/δ and ZR(t)) × 100%, during the total resting period. To confirm whether the locomotion specifically linked with the increase of θ/δ and ZR(t), we compared the probability with that within 30 s after a given time every 4 s during the total resting period. In this analysis, locomotion separated by less than a 30 s resting period was regarded as consecutive locomotion.

Figure 4. Cerebral activity, ZR(t) and voluntary locomotion.

Figure 4

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A, typical example of activity counts, moving average of θ/δ, CBF and moving average of ZR(t) on an expanded time scale from the part indicated by the filled bar in Fig. 2 (19.5–38.5 min). B, the probability of locomotion after a given time and after the increase in θ/δ and ZR(t). Means and s.e.m. bars are presented for 8 mice. ***Significant difference from the value after a given time, P < 0.001.

Circulatory responses before and after the onset of locomotion

When we analysed the transient changes in θ/δ, CBF, and ZR(t) at the onset of exercise (Fig. 5), we extended the analyses to the data for 240 s after the start of locomotion, which occurred after significant increases in θ/δ, CBF and ZR(t). We derived some from the data used for the analyses of circulatory responses to graded levels of θ/δ according to three criteria: (1) both θ/δ and ZR(t) increased to greater than a threshold of 2 s.d. during the total resting period; (2) the increases were followed by locomotion within 30 s; and (3) the locomotion lasted longer than 60 s. The major patterns of body movement observed during the measurements were grooming, walking, eating and drinking. Since at least three movements met the criteria for inclusion in every mouse, the variables for the three movements were randomly chosen from each mouse, averaged every 4 s in the range of ±240 s from the start of locomotion, adopted as representative values for each mouse, and then presented as the means and s.e.m. values for eight mice. When some ΔHR/ΔMAP values were lacking immediately before and after the onset of locomotion due to no significant R(t) during the period, they were interpolated from the next values, and the means and s.e.m. for eight mice were similarly calculated to the other variables stated above (Fig. 5B upper). Moreover, to confirm the reliability of the ΔHR/ΔMAP determination, we calculated the means and s.e.m. of ΔHR/ΔMAP for 24 trials (3 trials × 8 mice) without interpolating the lacking values (Fig. 5B middle). In this case, the number of slopes calculated is presented below the figure.

Figure 5. θ/δ, CBF, ZR(t), HR and MAP (A), and ΔHR/ΔMAP and activity counts (B) before and after the onset of voluntary locomotion.

Figure 5

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Means and s.e.m. bars are presented for 8 mice. Analyses were performed on data that met 3 criteria: (1) both θ/δ and ZR(t) increased to > threshold of 2 s.d. during the total resting period; (2) the increases were followed by locomotion within 30 s; and (3) locomotion lasted longer than 60 s. *Because some ΔHR/ΔMAP was lacking when R(t) was not significant, they were interpolated from the next values and means and s.e.m. for 8 mice were calculated as in other variables. **Means and s.e.m. of ΔHR/ΔMAP were calculated for 24 trials (3 trials × 8 mice) without interpolating the missing values. In this case, the number of slopes calculated is presented below the figure.

Statistics

Values are expressed as the means ±s.e.m. for eight mice unless otherwise indicated. The difference in delay time between CBF and ZR(t) and in the probability of locomotion between after the increase in θ/δ and ZR(t) and after a given time were tested by one-way ANOVA for repeated measures. Specific trend analysis was performed with one-way ANOVA for repeated measures. Subsequent post hoc tests to determine significant differences in the various pairwise comparisons were performed using Fisher's least significant difference test. All P values < 0.05 were considered significant.

Results

Figure 2 shows a typical example of activity counts, θ/δ, CBF, R(t), ΔHR/ΔMAP, HR and MAP every 4 s in a free-moving mouse for 90 min during the daytime. R(t) increased as θ/δ and CBF increased while it decreased as they decreased. Accordingly, we determined the periods during which θ/δ was significantly correlated with CBF and ZR(t), and summarized the results in Table 1.

As in Table 1, the resting period was 65% of the total measuring period of 720 min, and the period during which θ/δ was significantly correlated with CBF and ZR(t) was 73% and 59% of the resting period, respectively. The delay time for CBF to start to increase after an increase in θ/δ was 6 ± 2 s, significantly shorter than 19 ± 4 s for ZR(t) (P= 0.003).

Figure 3A shows CBF, ZR(t), HR and MAP in each bin of θ/δ with a 0.25 increment from 0 to >1.5. The number of data in each bin was 236 ± 87, 2280 ± 386, 2349 ± 145, 1185 ± 158, 516 ± 91, 227 ± 51 and 214 ± 81, respectively. CBF and ZR(t) increased as θ/δ increased (both P < 0.001); CBF and ZR(t) at the highest θ/δ were 118 ± 3% and −0.27 ± 0.04, significantly higher than 91 ± 2% and −0.69 ± 0.06 at the lowest θ/δ, respectively (both P < 0.001). In contrast, HR and MAP remained unchanged in any bins of θ/δ (P= 0.07–0.48).

Figure 3B shows ΔHR/ΔMAP in each bin of θ/δ with a 0.25 increment from 0 to >1.5. The number of data for each bin was 195 ± 73, 1793 ± 329, 1782 ± 131, 869 ± 132, 360 ± 74, 152 ± 40 and 135 ± 54, respectively. Similar to CBF and ZR(t) responses, the slope of ΔHR/ΔMAP increased as θ/δ increased (P < 0.001); ΔHR/ΔMAP at the highest θ/δ was −7.5 ± 0.9, significantly higher than −12.4 ± 0.9 at the lowest θ/δ (P < 0.001), indicating that baroreflex sensitivity of HR decreased as cerebral activity increased.

Figure 4A shows typical example of activity counts, θ/δ, CBF and ZR(t) on an expanded time scale from 19.5 to 38.5 min of Fig. 2. An increase in θ/δ was followed by an increase in CBF and ZR(t), and then the mouse started to move. Moreover, the frequency that both θ/δ and ZR(t) increased beyond the threshold of 2 s.d. was 14 ± 3 times for eight mice during the total resting period, which was followed by voluntary locomotion within 30 s at the probability of 69 ± 9%, 5 times higher than 14 ± 2% after a given time as shown in Fig. 4B (P < 0.001).

Figure 5A shows θ/δ, CBF, ZR(t), HR, MAP and activity counts before and after the onset of voluntary locomotion. When values from −240 to −200 s from the onset of locomotion were regarded as ‘baseline’, θ/δ and CBF started to increase at ∼−120 s (P < 0.01), and peaked at −52 s and −48 s, respectively, significantly higher than the baseline from −120 to 0 s for θ/δ (P < 0.001) and from −120 to 12 s for CBF (P < 0.01). Similarly, ZR(t) started to increase with θ/δ and CBF but the time to peak was −20 s, significantly delayed by ∼30 s compared with θ/δ and CBF. ZR(t) was significantly higher than the baseline from −120 to 40 s (P < 0.01). In contrast, HR and MAP did not start to increase until −4 s (P= 0.002) and 20 s (P < 0.001), respectively. After the start of voluntary locomotion, θ/δ and CBF rapidly returned to the baseline in a few seconds while ZR(t) gradually returned by ∼40 s, whereas the increases in HR and MAP were sustained after the onset of locomotion (P < 0.01).

Figure 5B shows ΔHR/ΔMAP and activity counts before and after the onset of voluntary locomotion. Similar to the ZR(t) response, ΔHR/ΔMAP values averaged in two different ways both started to increase ∼120 s before the onset of locomotion, peaked at ∼ −20 s, and had gradually returned to the baseline by ∼40 s. Significant differences from the baseline were found from −120 to 40 s (P < 0.05) in Fig. 5B upper and middle.

Discussion

To our knowledge, this is the first study to clarify tight linkages between cerebral activity, baroreflex control of HR and arterial blood pressure at the onset of voluntary locomotion in mice in their daily life. The major findings are that (1) ZR(t), an index of baroreflex control of HR, varied while synchronizing with cerebral activity, which occurred in ∼60% of the total resting period in the daytime, (2) the baroreflex control of HR was suppressed in proportion to voluntary activation of the cerebral cortex, and (3) mice started to move within ∼30 s after activation at 5 times higher probability than after a given time. These results suggest that activation of the cerebral cortex reduced the contribution of the baroreflex control of HR to arterial pressure regulation and this might be related to the onset of voluntary locomotion.

Baroreflex control of HR

In the present study, we used HR response to spontaneous change in MAP (ΔHR/ΔMAP) as an index of the contribution of peripheral baroreflex control to arterial blood pressure regulation. In our previous study (Masuki et al. 2003a), we determined R(t) in the same way as in the present study before and after carotid sinus denervation in freely moving mice, and found that after denervation, the incidence of significantly negative R(t) during a given period decreased while that of significantly positive R(t) increased, resulting in less negative ZR(t) on average during a given period. Similarly, we found that after denervation, ΔHR/ΔMAP, where R(t) was significantly negative, became less negative while ΔHR/ΔMAP, where R(t) was significantly positive, remained positive, resulting in less negative ΔHR/ΔMAP on average during a given period. Based on these results, we thought that more negative ZR(t) and ΔHR/ΔMAP on average during a given period indicated the greater contribution of peripheral baroreflex control to arterial blood pressure regulation while less negative ZR(t) and ΔHR/ΔMAP indicated the greater contribution of other mechanisms, namely central pressor responses (Berteotti et al. 2007; Aslan et al. 2007).

Cerebral activity

In this study, we used the power density ratio of θ to δ wave band (θ/δ) in EEG as an index of cerebral activity. Musizza et al. (2007) compared EEG waves between awake and anaesthetized rats, and suggested that θ wave activity increased while δ wave activity decreased as anaesthesia by ketamine–xylazine became shallower. Moreover, Tobler et al. (1997) compared EEG waves between awake and sleeping mice, and suggested that θ wave activity increased during the waking period while δ wave activity increased during the sleeping period of non-rapid eye movement. On the other hand, cerebral activity has been suggested to be higher in the awake state than in anaesthesia or non-rapid eye movement sleep (Nofzinger, 2006; Shulman et al. 2009). Therefore, in the present study, we used θ/δ as an index of cerebral activity.

We also used CBF as an index of cerebral activity. It is well known that tissue blood flow in the brain is tightly coupled with regional neuronal activity (Raichle, 1987) in anaesthetized rats (Golanov et al. 1994) and also in freely moving rats (Nishijima & Soya, 2006). However, since tissue blood flow measured by needle-type laser-Doppler flowmetry reflected that in a hemisphere area of 0.5 mm radius from the tip of the probe (Kashima et al. 1996), CBF might indicate neural activity of a more local region of the brain, close to the motor cortex in the present study, than EEG.

Despite the different techniques to measure cerebral activity, we found that CBF varied with θ/δ during more than 70% of the total resting period with significant correlation (Table 1 and Fig. 3A). Moreover, we confirmed that the change in CBF always occurred after the change in θ/δ, consistent with the results in a previous study on rats (Golanov et al. 1994). These results suggest that major changes in cerebral activity in the present study occurred close to the motor cortex and, more importantly, that the change in θ/δ was reliable enough to estimate cerebral activity.

Relationship between cerebral activity and baroreflex control of HR

Several studies have investigated the relationship between cerebral activity and baroreflex control of HR. Schlör et al. (1984) suggested that baroreflex sensitivity of HR in a cat was reduced when confronted with another aggressive cat and similar findings were suggested in rats (Knuepfer et al. 1991). Moreover, Dworkin & Dworkin (2004) measured the baroreflex sensitivity of HR and EEG in pharmacologically immobilized rats and suggested that the sensitivity decreased with reduced δ wave activity of EEG, an indicator of an arousal state. Although these results suggest that the activated cerebral cortex judged from the arousal state suppresses baroreflex sensitivity of HR, it remained unknown how the trend changes in the sensitivity with the activated cerebral cortex. Moreover, the findings in immobilized animals might be different from those in free-moving ones. In the present study, we first found in freely moving mice that the trend changes in ΔHR/ΔMAP, ZR(t) and cerebral activity were tightly linked (Table 1, Fig. 2) and that the baroreflex sensitivity of HR and its contribution to arterial pressure regulation decreased as cerebral activity increased while they increased as cerebral activity decreased (Fig. 3).

In the classic studies by Smith et al. (1960a,b); on how the central nervous system produces an interaction between cardiovascular and motor systems, they proposed a pathway from the hypothalamic nuclei to the cardiovascular centre in conscious dogs. Later, anaesthetized animal studies suggested that baroreflex-mediated bradycardia was suppressed by stimulation of the cerebral motor cortex (Achari & Downman, 1978) and also that rostral ventrolateral medulla neurons were activated by stimulation of the motor cortex and they were involved in the suppression of the baroreflex-mediated bradycardia (Len & Chan, 1999; Nosaka et al. 2000; Viltart et al. 2003). Together, these results are likely to support our idea that the suppression of baroreflex control of HR at the onset of voluntary locomotion was caused by an activated motor cortex. However, in the present study, since we did not measure CBF in other areas of the brain, it is uncertain whether these signals originated only from the motor cortex.

Rapid restoration of cerebral activity and baroreflex control of HR after the start of locomotion

As in Fig. 5, the significant increase in θ/δ and CBF before locomotion was rapidly restored, different from the case of regional CBF in a previous study on rats running on a treadmill (Nishijima & Soya, 2006). This discrepancy might be caused by different types of exercise: voluntary and forced exercise. Sadato et al. (1996) suggested that a larger area of the cortex was activated by a complex task than by a simple task. Moreover, Kleim et al. (1996) suggested in rats that activation of the motor cortex gradually decreased with training progress for acrobatic movement. Since the locomotion by mice in the present study was habitual and simple daily life movement (e.g., eating, drinking and grooming), activation of the cerebrum might be limited in area and duration. Indeed, Denton et al. (1999) suggested in humans that although activity in the cingulate, measured by positron emission tomography, was enhanced during the development of thirst, the activity rapidly declined when they irrigated the mouth with water to alleviate dryness at maximum thirst. In the present study, if the sequential increase in θ/δ and CBF before locomotion reflected neuronal activity for cognition/intention to perform daily activity, it is plausible that the activation of neurons declined immediately after locomotion started.

Similar to cerebral activity, we found that baroreflex control of HR was also restored shortly after the start of locomotion (Fig. 5). Komine et al. (2003) suggested that in conscious cats, baroreflex-mediated bradycardia by aortic nerve stimulation was most suppressed 1 s before the onset of voluntary static exercise while the suppression was largely restored by ∼10 s after the start of static exercise. Thus, the baroreflex control of HR was closely linked with activation of the higher central nervous system.

Cerebral activity and baroreflex control of HR before the start of locomotion

In this study, we found that within 30 s after increased cerebral activity and decreased baroreflex control of HR, voluntary locomotion started at high probability (Fig. 4). Green et al. (2007) suggested that anticipation of exercise increased local field potentials in the periaqueductal grey area in humans. Also, imagined exercise has been suggested to increase regional CBF in several parts of the cerebral cortex (Thornton et al. 2001; Williamson et al. 2002; Michelon et al. 2006). Moreover, Ebert (1986) examined the effects of anticipating the start of exercise with no actual muscular work on baroreflex control of HR in humans and suggested that baroreflex-mediated bradycardia was suppressed by the anticipation. Thus, when some parts of the brain are activated only by anticipating and/or imaging locomotion, suppression of baroreflex control of HR occurs. In the present study, considering the high probability of the start of locomotion after increased cerebral activity, mice might anticipate or imagine the procedure of locomotion before they actually started. However, 30 s before locomotion might be too early for mice.

Alternatively, as enhanced cerebral activity due to the thirst sensation stated above (Denton et al. 1999; Parsons et al. 2000), the increase in cerebral activity might reflect elevated motivation to acquire water or food, or to groom their body. Although the precise temporal and quantitative responses of the brain are not known, the lamina terminalis and hypothalamus in rats are reportedly activated by water deprivation (Watanabe et al. 2004; Ji et al. 2005). Moreover, Hollis et al. (2008) identified functional pathways from the lamina terminalis to the cortical regions in rats so that osmotic signals are translated into awareness of thirst to cause drinking behaviours. Since similar regions were also reportedly activated by hunger (Hinton et al. 2004; Tataranni et al. 1999), and since infusion of an osmotic hormone, vasopressin, into the regions was suggested to cause grooming behaviour in mice (Lumley et al. 2001), it is plausible that enhanced motivation was responsible for increased cerebral activity before the start of locomotion in the present study.

Suppression of baroreflex control of HR and exercise-induced pressor response

In the present study, we found an increase in cerebral activity and a subsequent suppression of baroreflex control of HR ∼30 s before the onset of voluntary locomotion while, despite this, there were no significant changes in HR and arterial pressure during this period. Although the significance of the suppression of baroreflex control of HR remains unclear, we speculate that it might be a preparation process for increasing arterial pressure to a level to meet the subsequent intensity of exercise in an anticipatory manner.

Limitations

There are four main limitations that deserve additional discussion. First, as mentioned above, the probability that the increase in θ/δ and ZR(t) was followed by locomotion within 30 s was 69%, whereas the reverse probability that locomotion was preceded by the increase in θ/δ and ZR(t) within 30 s was 15 ± 1% in the total number of locomotions. Although the reverse probability was low, this might represent the fact that the percentage of locomotion initiated with motivation was lower than that without motivation. Alternatively, even in such ‘locomotion without motivation’, cerebral activity would have increased a few seconds before locomotion, but our time resolution for θ/δ and ZR(t) was more than 4 s, too long to detect their increases.

Second, we used not only negative but also positive slopes of ΔHR/ΔMAP determined every 4 s as an index of baroreflex sensitivity of HR in the present study, while only a negative slope was adopted in previous studies (Parati et al. 2000). However, since arterial pressure is controlled predominantly by negative feedback but also by central pressor responses (Fig. 2), we used this index to quantify the relative contribution of peripheral baroreflex control to arterial pressure regulation.

Third, we only determined the cardiac component of arterial baroreflexes, but did not determine the vasomotor component. Recent evidence in pharmacologically immobilized rats suggests that baroreflex sensitivity of HR decreased with arousal whereas baroreflex sensitivity of arterial pressure was independent of arousal (Dworkin & Dworkin, 2004). Additionally, Komine et al. (2003) reported dissociation of the cardiac and vasomotor components of baroreflex at the onset of static exercise. However, in the present study, we found in mice that at least the cardiac component of baroreflexes closely relates to cerebral activity in their daily life.

Fourth, we did not confirm the sleep/waking state; therefore, an increase in θ/δ and ZR(t) before locomotion (Fig. 5) might be overlapped with rapid eye movement sleep characterized by high θ wave activity in EEG (Tobler et al. 1997). However, during the sleep, MAP is known to decrease by ∼10 mmHg in C57BL/6J mice (Schaub et al. 1998; Campen et al. 2002), whereas, in the present study, MAP pre-locomotion was similar to that during the total resting period, suggesting that the effect of rapid eye movement sleep in the pre-locomotion period was minor.

In summary, the results from the present investigation suggest that cerebral activity and baroreflex control of HR were tightly linked and the increase in cerebral activity suppressed the relative contribution of the baroreflex control of HR to arterial pressure regulation. Since these responses were followed by the high probability of locomotion, they might be a preparation process for the start of voluntary locomotion with a rapid increase in MAP.

Acknowledgments

This research was supported by grants from the Ministry of Education, Culture, Sports, Science, and Technology of Japan (Grant-in-Aid for Young Scientists to SM, 18689009) and from the Japan Society for the Promotion of Science (Grant-in-Aid for Scientific Research to HN, 17209007).

Glossary

Abbreviations

CBF

cerebral blood flow;

EEG

electroencephalogram;

HR

heart rate;

MAP

mean arterial pressure;

R(t)

cross-correlation function between spontaneous changes in HR and MAP;

ZR(t)

transformed R(t);

ΔHR/ΔMAP

HR response to the spontaneous change in MAP;

θ/δ

the power density ratio of θ to δ wave band in EEG.

Author contributions

S.M. and H.N. designed and performed research; S.M. analysed data; and S.M. and H.N. wrote and revised the paper.

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