Quantifying memory in complex physiological time-series.

Autor: 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
Jazyk: angličtina
Rok vydání: 2013
Předmět:
Zdroj: PLoS ONE, Vol 8, Iss 9, p e72854 (2013)
Druh dokumentu: article
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0072854
Popis: 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.
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