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Related Experiment Video

Updated: Jun 13, 2026

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Quantifying Infra-slow Dynamics of Spectral Power and Heart Rate in Sleeping Mice

Published on: August 2, 2017

Spectral Features of Heart Rate Variability in Williams Syndrome During Sleep.

Bence Schneider¹, Ferenc Gombos^2,3, Ilona Kovács^4,5

¹Institute of Behavioural Sciences, Semmelweis University, 1085 Budapest, Hungary.

Journal of Clinical Medicine

|June 12, 2026

Summary

Heart rate variability (HRV) spectral analysis reveals significant differences in Williams syndrome (WS) compared to typically developing individuals, particularly in fractal properties and autonomic regulation during sleep.

Keywords:

Williams syndrome fractals heart rate variability spectral analysis

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Area of Science:

Cardiology
Neuroscience
Genetics

Background:

Williams syndrome (WS) is a genetic disorder with known cardiovascular implications.
Altered heart rate variability (HRV) is observed in WS, but its spectral and fractal properties during sleep remain underexplored.
Understanding these alterations is crucial for assessing autonomic nervous system function in WS.

Purpose of the Study:

To analyze spectral alterations of HRV in Williams syndrome (WS) during sleep.
To investigate the multi-fractal properties of RR-interval spectra in WS, considering age and sleep structure.
To identify potential biomarkers for autonomic deregulation in WS.

Main Methods:

ECG recordings from 20 subjects with WS and matched typically developing (TD) controls.
Computation of fractal and oscillatory spectral components of RR-intervals using a broken power-law model.
Analysis of breakpoint frequency, slope, intercept, and peak prominence in LF and HF bands.

Main Results:

Significant differences in fractal parameters (breakpoint frequency, high domain slope, intercept, HF peak prominence) between WS and TD groups.
Reduced LF peak frequency in WS, independent of age, contrasting with a slight age-dependent decrease in TD.
Principal component analysis identified a main fractal component characteristic of WS, associated with sleep structure.

Conclusions:

The broken power-law model effectively characterizes RR-interval spectra in WS, reflecting altered cardiac regulation.
Fractal parameters of HRV show promise as biomarkers for the extent of general autonomic deregulation in Williams syndrome.
This study provides novel insights into autonomic nervous system function in WS during sleep.