Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
2009-08-27
Physics
Condensed Matter
Disordered Systems and Neural Networks
Revised following initial peer review. Current version 28 pages and 7 figures. A slightly modified version has been accepted t
Scientific paper
We present a framework for simulating signal propagation in geometric networks (i.e. networks that can be mapped to geometric graphs in some space) and for developing algorithms that estimate (i.e. map) the state and functional topology of complex dynamic geometric net- works. Within the framework we define the key features typically present in such networks and of particular relevance to biological cellular neural networks: Dynamics, signaling, observation, and control. The framework is particularly well-suited for estimating functional connectivity in cellular neural networks from experimentally observable data, and has been implemented using graphics processing unit (GPU) high performance computing. Computationally, the framework can simulate cellular network signaling close to or faster than real time. We further propose a standard test set of networks to measure performance and compare different mapping algorithms.
Buibas Marius
Silva Gabriel A.
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