An interaction graph approach to gain new insights into mechanisms that modulate cerebrovascular tone

Area of Science:

• Neuroscience
• Physiology
• Biomedical Engineering

Background:

• Cerebrovascular tone modulation involves numerous interconnected, spatially dependent mechanisms.
• Complexity in these pathways hinders experimental design, interpretation, and mechanistic modeling.
• Incomplete understanding of these pathways adds to the challenge.

Purpose of the Study:

• To propose interaction graphs as a method to simplify the complexity of cerebrovascular tone modulation.
• To maintain a holistic view of these mechanisms despite the breakdown of complexity.
• To provide new insights into neurovascular coupling, cerebral autoregulation, and cerebral reactivity.

Main Methods:

• Development and application of interaction graphs.
• Analysis of competing processes including neurovascular coupling, cerebral autoregulation, and cerebral reactivity.
• Utilizing graph visualization to represent complex biological interactions.

Main Results:

• Interaction graphs effectively break down the complexity of cerebrovascular tone modulation.
• These graphs highlight the interplay between neurovascular coupling, cerebral autoregulation, and cerebral reactivity.
• Analysis revealed new insights into these competing processes.

Conclusions:

• Interaction graphs offer a valuable tool for studying cerebrovascular tone.
• The approach provides a holistic yet simplified view of complex mechanisms.
• Findings suggest new research directions for neurovascular coupling, mechanistic modeling, and dementia research.