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Connecting the Speed-Accuracy Trade-Offs in Sensorimotor Control and Neurophysiology Reveals Diversity Sweet Spots in Layered Control Architectures


Nakahira, Yorie (2019) Connecting the Speed-Accuracy Trade-Offs in Sensorimotor Control and Neurophysiology Reveals Diversity Sweet Spots in Layered Control Architectures. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/VYQY-DF47.


Nervous systems sense, communicate, compute, and actuate movement using distributed components with trade-offs in speed, accuracy, sparsity, noise, and saturation. Nevertheless, the resulting control can achieve remarkably fast, accurate, and robust performance due to a highly effective layered control architecture. However, this architecture has received little attention from the existing research. This is in part because of the lack of theory that connects speed-accuracy trade-offs (SATs) in the components neurophysiology with system-level sensorimotor control and characterizes the overall system performance when different layers (planning vs. reflex layer) act work jointly. In thesis, we present a theoretical framework that provides a synthetic perspective of both levels and layers. We then use this framework to clarify the properties of effective layered architectures and explain why there exists extreme diversity across layers (planning vs. reflex layers) and within levels (sensorimotor versus neural/muscle hardware levels). The framework characterizes how the sensorimotor SATs are constrained by the component SATs of neurons communicating with spikes and their sensory and muscle endpoints, in both stochastic and deterministic models. The theoretical predictions are also verified using driving experiments. Our results lead to a novel concept, termed ``diversity sweet spots (DSSs)'': the appropriate diversity in the properties of neurons and muscles across layers and within levels help create systems that are both fast and accurate despite being built from components that are individually slow or inaccurate. At the component level, this concept explains why there are extreme heterogeneities in the neural or muscle composition. At the system level, DSSs explain the benefits of layering to allow extreme heterogeneities in speed and accuracy in different sensorimotor loops. Similar issues and properties also extend down to the cellular level in biology and outward to our most advanced network technologies from smart grid to the Internet of Things. We present our initial step in expanding our framework to that area and widely-open area of research for future direction.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:Robust control, Sensorimotor control, Neurophysiology, Speed-accuracy tradeoffs
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Control and Dynamical Systems
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Doyle, John Comstock
Thesis Committee:
  • Murray, Richard M. (chair)
  • Adami, Christoph Carl
  • Burdick, Joel Wakeman
  • Doyle, John Comstock
Defense Date:13 May 2019
Record Number:CaltechTHESIS:06072019-083145024
Persistent URL:
Related URLs:
URLURL TypeDescription's research website with links to her papers ItemArticle adapted for ch.6 adapted for ch.4 adapted for ch.10 adapted for ch.9 adapted for ch.8 adapted for ch.3 adapted for ch.7
Nakahira, Yorie0000-0003-3324-4602
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:11705
Deposited By: Yorie Nakahira
Deposited On:07 Jun 2019 22:12
Last Modified:04 Oct 2019 00:26

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