Reconstructing Neuronal Network Dynamics Using Data Assimilation
Date
2015
Authors
Hamilton, Franz William
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Abstract
Understanding the dynamics of the in vivo brain under normal and diseased states is one of the great challenges of modern scientific study. The overall complexity and dimension of the brain though can make this problem intractable. In an effort to study these dynamics in a more controlled, manageable setting, in vitro experimental and computational models have developed. Additionally, the advancement of mathematical analysis and techniques has led to a prominent role for data-assisted modeling whereby experimental data is fused with computational models allowing for data-driven predictions.
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Keywords
Mathematics, Neurosciences, Electrical engineering, Data assimilation, Ensemble Kalman filter, Microelectrode array, Neuronal networks