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Statistical coding and decoding of heartbeat intervals.

Lucena F, Barros AK, Príncipe JC, Ohnishi N - PLoS ONE (2011)

Bottom Line: Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm.We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation.Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

View Article: PubMed Central - PubMed

Affiliation: Biological Information Engineering Laboratory, Nagoya University, Nagoya, Aichi, Japan. lucena@ohnishi.nagoya-u.ac.jp

ABSTRACT
The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

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Power law analysis.(A) Power spectrum of the averaged set of decoding population code. (Black) Very-low, (red) low, and (blue) high frequency bands. (B) Binned log-log plot of the filter response (245 filters) to a Gaussian white noise. The straight line represents the power decay with slope .
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pone-0020227-g008: Power law analysis.(A) Power spectrum of the averaged set of decoding population code. (Black) Very-low, (red) low, and (blue) high frequency bands. (B) Binned log-log plot of the filter response (245 filters) to a Gaussian white noise. The straight line represents the power decay with slope .

Mentions: Despite the well-known sympathovagal balance, one of the inherent properties of heartbeat intervals is that the amplitude spectrum of beat-to-beat variations decays according to the power law [46]. If the average power spectrum of the filter bank decreases linearly with frequency (Fig. 8A), one can expect that the decoding filters modulate its input signal to have a falloff. Thus, could the decoding population itself give rise to long-range correlations close to the ones reported in physiological studies? One way to verify this is to convolve a temporal series drawn from a spectrally white random distribution with the decoding filters. After repetitions, the average response of the decoding filters (Fig. 8B) to a Gaussian white noise yields a slope that varies from to (, ). The variability at the low end of the spectrum is expected because of the limited duration of the analysis window ( samples) that precludes good estimation of the filters at the low end of the spectrum, again due to Gabor's uncertainty relation.


Statistical coding and decoding of heartbeat intervals.

Lucena F, Barros AK, Príncipe JC, Ohnishi N - PLoS ONE (2011)

Power law analysis.(A) Power spectrum of the averaged set of decoding population code. (Black) Very-low, (red) low, and (blue) high frequency bands. (B) Binned log-log plot of the filter response (245 filters) to a Gaussian white noise. The straight line represents the power decay with slope .
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3111410&req=5

pone-0020227-g008: Power law analysis.(A) Power spectrum of the averaged set of decoding population code. (Black) Very-low, (red) low, and (blue) high frequency bands. (B) Binned log-log plot of the filter response (245 filters) to a Gaussian white noise. The straight line represents the power decay with slope .
Mentions: Despite the well-known sympathovagal balance, one of the inherent properties of heartbeat intervals is that the amplitude spectrum of beat-to-beat variations decays according to the power law [46]. If the average power spectrum of the filter bank decreases linearly with frequency (Fig. 8A), one can expect that the decoding filters modulate its input signal to have a falloff. Thus, could the decoding population itself give rise to long-range correlations close to the ones reported in physiological studies? One way to verify this is to convolve a temporal series drawn from a spectrally white random distribution with the decoding filters. After repetitions, the average response of the decoding filters (Fig. 8B) to a Gaussian white noise yields a slope that varies from to (, ). The variability at the low end of the spectrum is expected because of the limited duration of the analysis window ( samples) that precludes good estimation of the filters at the low end of the spectrum, again due to Gabor's uncertainty relation.

Bottom Line: Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm.We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation.Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

View Article: PubMed Central - PubMed

Affiliation: Biological Information Engineering Laboratory, Nagoya University, Nagoya, Aichi, Japan. lucena@ohnishi.nagoya-u.ac.jp

ABSTRACT
The heart integrates neuroregulatory messages into specific bands of frequency, such that the overall amplitude spectrum of the cardiac output reflects the variations of the autonomic nervous system. This modulatory mechanism seems to be well adjusted to the unpredictability of the cardiac demand, maintaining a proper cardiac regulation. A longstanding theory holds that biological organisms facing an ever-changing environment are likely to evolve adaptive mechanisms to extract essential features in order to adjust their behavior. The key question, however, has been to understand how the neural circuitry self-organizes these feature detectors to select behaviorally relevant information. Previous studies in computational perception suggest that a neural population enhances information that is important for survival by minimizing the statistical redundancy of the stimuli. Herein we investigate whether the cardiac system makes use of a redundancy reduction strategy to regulate the cardiac rhythm. Based on a network of neural filters optimized to code heartbeat intervals, we learn a population code that maximizes the information across the neural ensemble. The emerging population code displays filter tuning proprieties whose characteristics explain diverse aspects of the autonomic cardiac regulation, such as the compromise between fast and slow cardiac responses. We show that the filters yield responses that are quantitatively similar to observed heart rate responses during direct sympathetic or parasympathetic nerve stimulation. Our findings suggest that the heart decodes autonomic stimuli according to information theory principles analogous to how perceptual cues are encoded by sensory systems.

Show MeSH
Related in: MedlinePlus