From time-series to complex networks: Application to the cerebrovascular flow patterns in atrial fibrillation
arXiv:1709.09087 · doi:10.1063/1.5003791
Abstract
A network-based approach is presented to investigate the cerebrovascular flow patterns during atrial fibrillation (AF) with respect to normal sinus rhythm (NSR). AF, the most common cardiac arrhythmia with faster and irregular beating, has been recently and independently associated with the increased risk of dementia. However, the underlying hemodynamic mechanisms relating the two pathologies remain mainly undetermined so far; thus the contribution of modeling and refined statistical tools is valuable. Pressure and flow rate temporal series in NSR and AF are here evaluated along representative cerebral sites (from carotid arteries to capillary brain circulation), exploiting reliable artificially built signals recently obtained from an in silico approach. The complex network analysis evidences, in a synthetic and original way, a dramatic signal variation towards the distal/capillary cerebral regions during AF, which has no counterpart in NSR conditions. At the large artery level, networks obtained from both AF and NSR hemodynamic signals exhibit elongated and chained features, which are typical of pseudo-periodic series. These aspects are almost completely lost towards the microcirculation during AF, where the networks are topologically more circular and present random-like characteristics. As a consequence, all the physiological phenomena at microcerebral level ruled by periodicity - such as regular perfusion, mean pressure per beat, and average nutrient supply at cellular level - can be strongly compromised, since the AF hemodynamic signals assume irregular behaviour and random-like features. Through a powerful approach which is complementary to the classical statistical tools, the present findings further strengthen the potential link between AF hemodynamic and cognitive decline.
12 pages, 10 figures
References in corpus (10)
- From time series to complex networks: the visibility graph
- Complex networks in climate dynamics - Comparing linear and nonlinear network construction methods
- Network Structure of Two-Dimensional Decaying Isotropic Turbulence
- Transient cerebral hypoperfusion and hypertensive events during atrial fibrillation: a plausible mechanism for cognitive impairment
- Impact of atrial fibrillation on the cardiovascular system through a lumped-parameter approach
- Complex Networks Unveiling Spatial Patterns in Turbulence
- Alteration of cerebrovascular haemodynamic patterns due to atrial fibrillation: an in silico investigation
- A Computational Study on the Relation between Resting Heart Rate and Atrial Fibrillation Hemodynamics under Exercise
- Rate Control Management of Atrial Fibrillation: May a Mathematical Model Suggest an Ideal Heart Rate?
- Computational fluid dynamics modelling of left valvular heart diseases during atrial fibrillation