Quantifying memory in complex physiological time-series

PLoS One. 2013 Sep 5;8(9):e72854. doi: 10.1371/journal.pone.0072854. eCollection 2013.

Abstract

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Asthma / physiopathology
  • Healthy Volunteers
  • Heart Rate
  • Humans
  • Liver Cirrhosis / physiopathology
  • Memory / physiology*
  • Models, Biological*
  • Models, Statistical
  • Probability
  • Respiration
  • Time Factors
  • Young Adult

Grants and funding

This work was partially supported by grants from the University of Padova to A.R. Mani and P. Amodio, the Italian Ministry of Health to S. Montagnese (Giovani Ricercatori 2009) and Tarbiat Modares University to M.R. Raoufy. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.