2016/06/21 by Henning U. Voss, Voss, Henning U., Nigel Stepp +1
Biochemistry, Genetics and Molecular Biology · Engineering · Neuroscience · Physics and Astronomy · Psychology · #Adaptation and Self-Organizing Systems (nlin.AO) #Advanced Adaptive Filtering Techniques #Artificial intelligence #Computer science #Control (management) #Control engineering #Control theory (sociology) #Dynamics (music) #Engineering #FOS: Biological sciences #FOS: Physical sciences #Group (periodic table) #Group delay and phase delay #Motor Control and Adaptation #Negative feedback #Neural dynamics and brain function #Neurons and Cognition (q-bio.NC) #Physics #Psychology #Set (abstract data type) #Set point #Tracking (education) #nlin.AO #q-bio.NC
paper · pdf · doi:10.48550/arxiv.1606.06571
published as Journal of Computational Neuroscience, Volume 41, pages 295-304 (2016) · 6 pages, 1 table, 2 figures
openalex publication_date 2016/06/21 · arxiv created 2016/06/24 · openalex created_date 2025/10/10 · arxiv updated 2026/08/03 · openalex updated_date 2026/08/05
We propose that feedback-delayed manual tracking performance is limited by fundamental constraints imposed by the physics of negative group delay. To test this hypothesis, the results of an experiment in which subjects demonstrate both reactive and predictive dynamics are modeled by a linear system with delay-induced negative group delay. Although one of the simplest real-time predictors conceivable, this model explains key components of experimental observations. Most notably, it explains the observation that prediction time linearly increases with feedback delay, up to a certain point when tracking performance deteriorates. It also explains the transition from reactive to predictive behavior with increasing feedback delay. The model contains only one free parameter, the feedback gain, which has been fixed by comparison with one set of experimental observations for the reactive case. Our model provides quantitative predictions that can be tested in further experiments.