Noise, nonlinear dynamics and the timecourse of affective disorders

Affective disorders, such as depression or mania, tend to be recurrent and progressive. Typically, disease patterns evolve from isolated episodes to rhythmic and finally accelerated “chaotic” mood patterns during the longitudinal course. Concepts from dynamical systems have been considered to explai...

Full description

Saved in:
Bibliographic Details
Published in:Chaos, solitons and fractals solitons and fractals, 2000, Vol.11 (12), p.1923-1928
Main Authors: Huber, M.T., Krieg, J.C., Braun, H.A.
Format: Article
Language:English
Subjects:
Chaos theory
Mathematical models
Random processes
Spurious signal noise
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Affective disorders, such as depression or mania, tend to be recurrent and progressive. Typically, disease patterns evolve from isolated episodes to rhythmic and finally accelerated “chaotic” mood patterns during the longitudinal course. Concepts from dynamical systems have been considered to explain this progression. However, most natural systems are not only nonlinear but also affected by noise. For this reason it seems important to incorporate cooperative stochastic–dynamic effects into current conceptional models for the course and neurobiology of such disorders. We use a computational perspective and describe behaviors of a simple mathematical model which result from interactions between random and deterministic dynamics. In particular, we focus on a scenario for illness progression that relies on noise enhancement of feedback instabilities. We suggest that noise amplification of subclinical neurobiological vulnerabilities could represent a relevant disease mechanism.
ISSN:0960-0779
1873-2887
DOI:10.1016/S0960-0779(99)00130-7