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Quantifying memory in complex physiological time-series.

Authors :
Amir H Shirazi
Mohammad R Raoufy
Haleh Ebadi
Michele De Rui
Sami Schiff
Roham Mazloom
Sohrab Hajizadeh
Shahriar Gharibzadeh
Ahmad R Dehpour
Piero Amodio
G Reza Jafari
Sara Montagnese
Ali R Mani
Source :
PLoS ONE, Vol 8, Iss 9, p e72854 (2013)
Publication Year :
2013
Publisher :
Public Library of Science (PLoS), 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.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
8
Issue :
9
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.f976f94d9f024c518e431ce101b2f0a4
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0072854