A study into the structure of blood vascular network structure found that it is dynamic and can adapt to external factors, resulting in a kind of memory of certain events such as an ischaemic stroke. In particular, the study researchers found that rarely used connections incrementally weaken until they disappear eventually.
Researchers from the Max Planck Institute for Dynamics and Self-Organization in Göttingen and the Technical University of Munich used computer simulations to model vascular networks and identified adaptation rules for their connections.
“We found that the strength of a connection within a network depends on the local flow,” explained Karen Alim, corresponding author of the study. “This means that links with a low flow below a certain threshold will decay more and more until they eventually vanish,” she continued. Since the limited amount of material available to build the vascular system needs to be efficiently used, this mechanism offers an elegant way to streamline the vascular system.
Persistent changes in the network
Once a connection has become very weak due to a low flow rate, recovering that connection is very difficult. For example, a blood vessel blockage of the type that could lead to an ischaemic stroke. During an ischaemic stroke, some blood vessels in the affected region are weakened by the blockage.
“We found that in such a case, adaptations in the network are permanent and are maintained after the obstacle is removed. One can say that the network prefers to reroute the flow through existing stronger connections instead of re-growing weaker connections – even if the flow would require the opposite,” explained Komal Bhattacharyya, principal author of the study.
The researchers have thus shown that blood flow permanently changes even after successful removal of the clot. This memory capability of networks can also be found in other living systems: for example, the slime mould Physarum polycephalum uses its adaptive network to navigate its environment based on imprints by food stimuli, as demonstrated previously.
The study was published in Physical Review Letters.
Source: Max Planck Institute for Dynamics and Self-Organization
