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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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Population code optimized through heartbeat intervals derived from normal sinus rhythm volunteers.Each waveform was adapted upon a time window composed of 256 beat-intervals. (A) From a total number of 256, the plot illustrates a typical set of decoding filters organized from the highest to the lowest center frequency. Although the self-organization of the decoding population is not homogenous, it shows three different patterns. (B) Joint time-frequency plane representing the overlap of 245 contour plots. In this time-frequency tilling-like pattern representation, each “tile” was obtained from the amplitude envelope and spectral power of the optimized filters at 95% of the energy peak.
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pone-0020227-g002: Population code optimized through heartbeat intervals derived from normal sinus rhythm volunteers.Each waveform was adapted upon a time window composed of 256 beat-intervals. (A) From a total number of 256, the plot illustrates a typical set of decoding filters organized from the highest to the lowest center frequency. Although the self-organization of the decoding population is not homogenous, it shows three different patterns. (B) Joint time-frequency plane representing the overlap of 245 contour plots. In this time-frequency tilling-like pattern representation, each “tile” was obtained from the amplitude envelope and spectral power of the optimized filters at 95% of the energy peak.

Mentions: The decoding filters emerging from the statistical structures underlying the heartbeat intervals show (Fig. 2A) a wide variety of impulse response shapes. The vast majority are time localized, meaning that the analysis window was able to capture the timescale where the statistical regularities of the heartbeat intervals occurred. Despite the observed diversity of sinusoidal oscillations and amplitude envelopes of the filters, the population code has a distinct time-frequency organization (Fig. 3). This organization was not clear from the individual analysis of each filter, neither in frequency nor time, but became visible when the entire decoding population was distributed in the joint time and frequency plane (Fig. 2B). Moreover, a striking resemblance with the frequency band division of short-term heartbeat intervals emerges. This result is expected, since the encoding filters tend to match the statistical structures underlying the variations of the autonomic cardiac activity. However, nowhere in the algorithm was this structure programmed, i.e. it emerged from the data and the ICA methodology.


Statistical coding and decoding of heartbeat intervals.

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

Population code optimized through heartbeat intervals derived from normal sinus rhythm volunteers.Each waveform was adapted upon a time window composed of 256 beat-intervals. (A) From a total number of 256, the plot illustrates a typical set of decoding filters organized from the highest to the lowest center frequency. Although the self-organization of the decoding population is not homogenous, it shows three different patterns. (B) Joint time-frequency plane representing the overlap of 245 contour plots. In this time-frequency tilling-like pattern representation, each “tile” was obtained from the amplitude envelope and spectral power of the optimized filters at 95% of the energy peak.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3111410&req=5

pone-0020227-g002: Population code optimized through heartbeat intervals derived from normal sinus rhythm volunteers.Each waveform was adapted upon a time window composed of 256 beat-intervals. (A) From a total number of 256, the plot illustrates a typical set of decoding filters organized from the highest to the lowest center frequency. Although the self-organization of the decoding population is not homogenous, it shows three different patterns. (B) Joint time-frequency plane representing the overlap of 245 contour plots. In this time-frequency tilling-like pattern representation, each “tile” was obtained from the amplitude envelope and spectral power of the optimized filters at 95% of the energy peak.
Mentions: The decoding filters emerging from the statistical structures underlying the heartbeat intervals show (Fig. 2A) a wide variety of impulse response shapes. The vast majority are time localized, meaning that the analysis window was able to capture the timescale where the statistical regularities of the heartbeat intervals occurred. Despite the observed diversity of sinusoidal oscillations and amplitude envelopes of the filters, the population code has a distinct time-frequency organization (Fig. 3). This organization was not clear from the individual analysis of each filter, neither in frequency nor time, but became visible when the entire decoding population was distributed in the joint time and frequency plane (Fig. 2B). Moreover, a striking resemblance with the frequency band division of short-term heartbeat intervals emerges. This result is expected, since the encoding filters tend to match the statistical structures underlying the variations of the autonomic cardiac activity. However, nowhere in the algorithm was this structure programmed, i.e. it emerged from the data and the ICA methodology.

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