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Figures
- Fig. 1.
Use of photoplethysmography (PPG) allows for continuous non-invasive recording of the heart and pyloric muscles. (A) Drawing of the PPG sensor system, indicating the light source and photosensor of the device. (B) Drawing of the PPG sensor positioning for detection of heart and pylorus movements when placed on the carapace of an animal. Infrared light from the sensors is emitted and travels through the animal's carapace before being reflected from the muscle directly below the PPG sensor. Crab image modified from http://stg.rutgers.edu/Resources.html. Stomach image modified from Maynard and Dando (1974).
- Fig. 2.
Variability of heart and pyloric rhythm frequency under baseline conditions. (A) Heart rhythm recordings from three animals at different times under baseline conditions (left) with their spectrograms (right). Roman numerals mark where 30 s raw traces were obtained in the longer baseline frequency data (spectrograms). (B) Pyloric recordings from two animals under baseline conditions (left) with their spectrograms (right).
- Fig. 3.
Frequency distributions of the heart and pyloric rhythms. (A) The sum of all of the normalized frequency distributions of the heart rhythms from 49 animals under baseline conditions. (B) The sum of the normalized frequency distributions of the pyloric rhythms from 29 animals under baseline conditions. (C) Plot of the baseline heart rhythm frequency versus pyloric rhythm frequency for those animals for which both rhythms were recorded. The red line is the linear regression of the data (R=0.61 and R2=0.37).
- Fig. 4.
The heart rhythm exhibits inhibitory bouts that influence the pyloric rhythm. (A) Top panel: a 24 h recording of the heart rhythm with inhibitory bouts throughout the recording session. Middle panel: states identified from the heart rhythm trace using a hidden Markov model. State 1 corresponds to an active state and state 0 corresponds to an inhibitory bout. Bottom panel: simultaneously recorded pyloric rhythm. Expanded traces during a single inhibitory bout (red box) are shown on the right. (B) Distribution of durations (in s) of active and inhibitory states of the heart rhythm shown in A, identified using the hidden Markov model, using baseline data. (C) Cumulative distribution of the durations (in s) of active and inhibitory states of the heart activity from 20 animals that showed inhibitory bouts with a mean duration of 30 s. Active state durations displayed a bimodal distribution. (D) Top panel, spectrogram of the heart rhythm shown in A. The heart rhythm frequency between the inhibitory bouts was relatively constant at 1.5 Hz. Bottom panel, spectrogram of the pyloric rhythm shown in A. The pyloric rhythm decreased in frequency during the heart inhibitory bouts followed by an increase in frequency at the end of the bouts. An enlarged portion of the spectrogram (red box) is shown on the right. (E) Additional examples of the frequency changes of the pyloric rhythm during and following the heart inhibitory bouts from four different animals. Top panels, spectrograms of heart activity. Bottom panels, spectrograms of pyloric activity. These data feature an interaction between the cardiac and the pyloric activity on the time scale of minutes.
- Fig. 5.
Pyloric and heart recordings often show coherence at the frequency of the heart rhythm. (A) An example of high coherence between heart and pyloric PPG recordings. Left, top panel: time–frequency coherence of the heart and pyloric recordings at baseline. Left, middle and bottom panels: spectrograms of the heart and pyloric recordings at baseline. Right, top panel: 15 s segments of heart rhythm (blue) and pyloric recordings (green), simultaneously recorded under baseline conditions. Right, middle panel: heart–pyloric cross-correlation (gray) and autocorrelation functions of heart (blue) and pyloric (green) recordings. Right, bottom panel: the distribution of phase differences between the heart and pyloric recordings calculated in 2 min windows, moved in 10 s steps (left) and the distribution of magnitudes of peak coherence calculated in 2 min windows, moved in 10 s steps (right). (B) Example of the absence of coherence between the heart and pyloric rhythms. Left, top panel: time–frequency coherence of heart and pyloric rhythms at baseline. Left, middle and bottom panels: spectrograms of heart and pyloric rhythms at baseline. Right, top panel: heart rhythm (blue) with simultaneously recorded pyloric rhythm (green) recorded at baseline for 30 s segments of the full data range for which spectra and coherence were calculated. Right, bottom panel: heart–pyloric cross-correlation (gray) and autocorrelation functions of heart (blue) and pyloric (green) rhythms. (C) Coherence statistics for all animals with simultaneous recordings of heart and pyloric PPG recordings (n=40). Left: percentage of time pyloric and heart recordings were significantly coherent at baseline versus the amplitude of the recorded heart signal. Right: percentage of time pyloric and heart recordings were significantly coherent at baseline versus heart rhythm frequency. (D) Scatter plot showing median magnitudes of peak coherence versus median phase difference between heart and pyloric recordings.
- Fig. 6.
The pyloric rhythm is more sensitive to increases in temperature than is the heart rhythm. (A) Raw traces of heart (top) and pyloric (bottom) muscle activity at baseline (11°C), and during increasing (25°C), critical (28°C) and decreasing portions (25°C) of the temperature ramp. (B) Top panel: change in frequency of heart rhythms of three animals in response to almost identical temperature ramps shown in the bottom panel. Middle panel: change in frequency of simultaneously recorded pyloric rhythm in response to the temperature ramp. The pyloric rhythm is less robust to temperature increases than the heart rhythm and crashes at a much lower temperature. The crash is evident from a significant decrease in frequency and amplitude of the pyloric rhythm. (C) Frequencies of the heart and pyloric rhythms during portions of increasing temperature ramps plotted as a function of temperature on a logarithmic scale. Each color corresponds to an individual animal. A line was fitted to data points for each animal's heart frequencies to estimate the Q10. (D) Critical temperature of the heart rhythm is significantly higher than that of the pyloric rhythm (mean heart critical temperature 25.0±1.6°C, mean pyloric critical temperature 19.1±2.8°C, one-way ANOVA, ***P=0.0005, F1,19=21.07). (E) Q10 values of heart and pyloric frequencies are not significantly different (mean Q10 of heart frequency 2.007±0.854, pyloric frequency 2.040±0.467, one-way ANOVA, P=0.9155, F1,19=0.01).
- Fig. 7.
Coherent heart and pyloric recordings remain coherent during the temperature ramp without change in phase relationship. (A) An individual example of coherence between the heart and pyloric recordings and spectrograms of the recordings at baseline and during the temperature ramp. Bottom panel shows tank temperature. (B) Examples of coherence at baseline during temperature increases and temperature decreases. Horizontal black lines indicate the theoretical significance level. The times at which example coherences were taken are shown by the vertical red bars in A. Recordings are coherent throughout the whole experiment at the frequency of the heart rhythm. (C) Phase difference of the rhythms in A at baseline, and during rising and decaying phases of the temperature ramps. (D) Peak coherence between heart and pyloric recordings from all temperature experiments (n=9) at baseline and during the rising phase of the temperature ramp. Coherence during the temperature ramp was calculated up to the critical temperature of the pyloric rhythm. There were no statistically significant differences between mean peak coherence at baseline and during the temperature ramp as determined by one-way ANOVA (P=0.806, F1,32=0.06). (E) Phase difference between heart and pyloric recordings for all temperature experiments (n=9). There were no statistically significant differences between mean phase differences at baseline and during the temperature ramp as determined by one-way ANOVA (P=0.759, F1,32=0.1). (F) Percentage of time heart and pyloric recordings were coherent. There were no statistically significant differences between mean percentage of time the recordings were coherent at baseline and during the temperature ramp as determined by one-way ANOVA (P=0.354, F1,16=0.91). In all nine temperature experiments, recordings showed coherence more than 95% of the time.
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