Work

Diversity Deconstrains Component Limitations in Sensorimotor Control

Year: 2025

Type: article

Abstract: Human sensorimotor control is remarkably fast and accurate at the system level despite severe speed-accuracy trade-offs at the component level. The discrepancy between the contrasting speed-accuracy trade-offs at these two levels is a paradox. Meanwhile, speed accuracy trade-offs, heterogeneity, and layered architectures are ubiquitous in nerves, skeletons, and muscles, but they have only been studied in isolation using domain-specific models. In this article, we develop a mechanistic model for how component speed-accuracy trade-offs constrain sensorimotor control that is consistent with Fitts' law for reaching. The model suggests that diversity among components deconstrains the limitations of individual components in sensorimotor control. Such diversity-enabled sweet spots (DESSs) are ubiquitous in nature, explaining why large heterogeneities exist in the components of biological systems and how natural selection routinely evolves systems with fast and accurate responses using imperfect components.

Source: Neural Computation

DOI: 10.1162/neco.a.24

Authors: Yorie Nakahira, Quanying Liu, Xiyu Deng, Terrence J. Sejnowski, John C. Doyle

Institutions: Carnegie Mellon University, Southern University of Science and Technology, Salk Institute for Biological Studies, University of California San Diego, California Institute of Technology

Language: English

Topic: Motor Control and Adaptation

Subfield: Cognitive Neuroscience

Field: Neuroscience

Domain: Life Sciences

Open Access status: green

Funder: National Science Foundation

Awards: NCS-FO: Collaborative Research: Integrative Foundations for Interactions of Complex Neural and Neuro-inspired Systems with Realistic Environments, NCS-FO: Collaborative Research: Integrative Foundations for Interactions of Complex Neural and Neuro-Inspired Systems with Realistic Environments