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Major remaining gaps in models of sensorimotor systems
Gerald E Loeb1, George A Tsianos2
1Department of Biomedical Engineering, University of Southern California Los Angeles, CA, USA.
Frontiers in Computational Neuroscience
|June 20, 2015
Summary
Mathematical models of sensorimotor systems reveal complexity and highlight knowledge gaps. This study identifies poorly understood components crucial for accurate system modeling.
Area of Science:
- Neuroscience
- Systems Biology
- Computational Neuroscience
Background:
- Detailed experimental data on sensorimotor system components is complex and hinders understanding of whole-system function.
- Mathematical modeling is increasingly used to study emergent properties of complex biological systems.
Purpose of the Study:
- To identify critical but poorly understood components of sensorimotor systems.
- To highlight how these omissions affect current mathematical models.
Main Methods:
- Review of existing literature on sensorimotor system anatomy and physiology.
- Analysis of common assumptions and omissions in mathematical models of sensorimotor systems.
Main Results:
- Many potentially important components of sensorimotor systems are poorly understood.
- These poorly understood elements are often omitted or implicitly assumed in mathematical models, limiting their accuracy and predictive power.
Conclusions:
- Mathematical models are valuable for revealing discrepancies between current knowledge and potential system behaviors.
- Further experimental investigation is needed for poorly understood sensorimotor system components to improve model validity.
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