Scaling vs. nonscaling methods of assessing autonomic tone in streptozotocin-induced diabetic rats

Itay Perlstein, Nir Sapir, Joshua Backon, Dan Sapoznikov, Roman Karasik, Shlomo Havlin, Amnon Hoffman*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

We studied heart rate variability in rats by power scaling spectral analysis (PSSA), autoregressive modeling (AR), and detrended fluctuation analysis (DFA), assessed stability by coefficient of variation between consecutive 6-h epochs, and then compared cross-correlation among techniques. These same parameters were checked from baseline conditions through acute and chronic disease states (streptozotocin-induced diabetes) followed by therapeutic intervention (insulin). Cross-correlation between methods over the entire time period was r = 0.94 (DFA and PSSA), r = 0.81 (DFA and AR), and r = 0.77 (AR and PSSA). Under baseline conditions the scaling parameter measured by DFA and PSSA and the high-frequency (HF) component measured by AR fluctuated around an average value, but these fluctuations were different for the three methods. After diabetes induction, a strong correlation was found between the HF power and the shortterm scaling parameter. Despite their differences in methodology, DFA and PSSA assess changes in parasympathetic tone as detected by autoregressive modeling.

Original languageAmerican English
Pages (from-to)H1142-H1149
JournalAmerican Journal of Physiology - Heart and Circulatory Physiology
Volume283
Issue number3 52-3
DOIs
StatePublished - 2002

Keywords

  • Autoregressive modeling
  • Circasemiseptan rhythm
  • Detrended fluctuation analysis
  • Heart rate variability
  • Power scaling spectral analysis

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