A stochastic multi-scale model of electrical function in normal and depleted ICC networks

Area of Science:

• Computational biology
• Physiology
• Gastrointestinal research

Background:

• Multi-scale modeling is crucial for understanding interstitial cells of Cajal (ICC) networks.
• Current limitations in large-scale ICC imaging data hinder modeling progress.

Purpose of the Study:

• To utilize and modify the SNESIM algorithm for generating realistic virtual ICC networks.
• To validate the SNESIM algorithm using network density and connectivity metrics.
• To simulate electrical activity in ICC networks with varying depletion levels.

Main Methods:

• Employed the SNESIM algorithm to create virtual ICC networks for wild-type and Htr2b(-/-) mice.
• Developed network density and connectivity metrics for algorithm validation.
• Modified SNESIM to simulate ICC network depletion and performed electrical activity simulations.

Main Results:

• Generated virtual ICC networks closely resembled real counterparts.
• Validated SNESIM algorithm performance using established metrics.
• Simulations demonstrated that increased network density correlated with higher maximum current density magnitude.

Conclusions:

• The SNESIM algorithm is a validated tool for creating realistic virtual ICC networks.
• The modified SNESIM algorithm, coupled with simulations, can quantify the physiological effects of ICC network depletion across scales.