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Diversity-enabled sweet spots in layered architectures and speed–accuracy trade-offs in sensorimotor control

Nakahira, Yorie and Liu, Quanying and Sejnowski, Terrence J. and Doyle, John C. (2021) Diversity-enabled sweet spots in layered architectures and speed–accuracy trade-offs in sensorimotor control. Proceedings of the National Academy of Sciences of the United States of America, 118 (22). Art. No. e1916367118. ISSN 0027-8424. PMCID PMC8179159. doi:10.1073/pnas.1916367118.

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Nervous systems sense, communicate, compute, and actuate movement using distributed components with severe trade-offs in speed, accuracy, sparsity, noise, and saturation. Nevertheless, brains achieve remarkably fast, accurate, and robust control performance due to a highly effective layered control architecture. Here, we introduce a driving task to study how a mountain biker mitigates the immediate disturbance of trail bumps and responds to changes in trail direction. We manipulated the time delays and accuracy of the control input from the wheel as a surrogate for manipulating the characteristics of neurons in the control loop. The observed speed–accuracy trade-offs motivated a theoretical framework consisting of two layers of control loops—a fast, but inaccurate, reflexive layer that corrects for bumps and a slow, but accurate, planning layer that computes the trajectory to follow—each with components having diverse speeds and accuracies within each physical level, such as nerve bundles containing axons with a wide range of sizes. Our model explains why the errors from two control loops are additive and shows how the errors in each control loop can be decomposed into the errors caused by the limited speeds and accuracies of the components. These results demonstrate that an appropriate diversity in the properties of neurons across layers helps to create “diversity-enabled sweet spots,” so that both fast and accurate control is achieved using slow or inaccurate components.

Item Type:Article
Related URLs:
URLURL TypeDescription Information Paper ItemData CentralArticle
Nakahira, Yorie0000-0003-3324-4602
Liu, Quanying0000-0002-2501-7656
Sejnowski, Terrence J.0000-0002-0622-7391
Doyle, John C.0000-0002-1828-2486
Additional Information:© 2021 National Academy of Sciences. Published under the PNAS license. Contributed by Terrence J. Sejnowski, March 29, 2021 (sent for review March 29, 2019; reviewed by Terry Sanger and Rodolphe Sepulchre). This research was supported by NSF Grants NCS-FO (Integrative Strategies for Understanding Neural and Cognitive Systems) 1735004 and 1735003 and the Swartz Foundation. Q.L. was supported by a Boswell fellowship. This paper is based on the theoretical doctoral research of Y.N. and on the experimental research of Q.L. Data Availability: All data and programs used to analyze the data are available at GitHub ( Author contributions: Y.N., Q.L., T.J.S., and J.C.D. designed research; Y.N. and Q.L. performed research; Y.N. and Q.L. analyzed data; and Y.N., Q.L., T.J.S., and J.C.D. wrote the paper. Reviewers: T.S., University of Southern California; and R.S., University of Cambridge. The authors declare no competing interest. This article contains supporting information online at
Funding AgencyGrant Number
Swartz FoundationUNSPECIFIED
James G. Boswell FoundationUNSPECIFIED
Subject Keywords:speed–accuracy trade-off; vestibulo-ocular reflex; distributed control; layered architecture; sensorimotor control
Issue or Number:22
PubMed Central ID:PMC8179159
Record Number:CaltechAUTHORS:20210510-141357701
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Official Citation:Diversity-enabled sweet spots in layered architectures and speed–accuracy trade-offs in sensorimotor control. Yorie Nakahira, Quanying Liu, Terrence J. Sejnowski, John C. Doyle. Proceedings of the National Academy of Sciences Jun 2021, 118 (22) e1916367118; DOI: 10.1073/pnas.1916367118
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:109059
Deposited By: George Porter
Deposited On:10 May 2021 22:00
Last Modified:08 Feb 2022 23:34

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