Juggling Study Highlighted in the News

Mert Ankarali’s paper was featured on the cover of the Journal of Neurophysiology:

M. Mert Ankaralı, H. Tutkun Şen, Avik De, Allison M. Okamura, and Noah J. Cowan. “Haptic feedback enhances rhythmic motor control by reducing variability, not improving convergence rate”. J Neurophysiol, 111(6):1286-1299, 2014. [pdf] [Download cover illustration]

It was also picked up in the news:

ankarali_cover

Rhythmic Motor Behavior

News articles:

Baltimore Sun

Johns Hopkins Engineering Magazine

Relevant Articles

M. M. Ankarali, H. Tutkun Şen, A. De, A. M. Okamura, and N. J. Cowan. “Haptic feedback enhances rhythmic motor control by reducing variability, not improving convergence rate”. J Neurophysiol, 111(6):1286-1299, 2014. [pdf]  [Download cover illustration]

M. M. Ankarali, S. Sefati, M. S. Madhav, A. Long, A. J. Bastian, and N. J. Cowan. “Walking dynamics are symmetric (enough)”. J. R. Soc. Interface, 12: 20150209, 2015. [pdf] [Data and Source Code]

Time for Control

In engineering and mathematics, t is the quintessential independent variable: an immutable quantity in terms of which all other variables depend. Most control systems do require a clock, but clocks have been engineered with such low drift rates that for all practical purposes, imperfections in chronometry have been largely ignored.

Biological systems do not have it so easy. Biological clocks were not “engineered” on top of a physical phenomenon like the oscillation of a quartz crystal. Rather, biological wetware must keep time over many scales using physiological, neural, and biochemical mechanisms. Biological clocks are typically described as nonlinear dynamical systems exhibiting limit cycle behavior where the phase of the system advances monotonically with the passage of time. For example, circadian rhythms and other longer-term processes highlight the importance of external cues in the timekeeping process. Circadian and circannual rhythms, for example, are regulated by changes in daylength, temperature, and other environmental cues.

So, while uncertainty in time is justifiably neglected in the design and analysis of most engineering control systems, perfect timekeeping is a poor assumption for the modeling and analysis of biological control systems. Indeed, timekeeping during simple human motor control tasks involves errors of around 10% of the movement cycle duration. Despite this extremely high level of temporal imprecision, the overwhelming majority of computational models of the human motor control makes the implicit assumptions that time is known. Who knows what happens to any of these analyses when our assumption about perfect timekeeping is relaxed?

These three papers begin to address this question:

S. M. LaValle and M. B. Egerstedt, “On time: Clocks, chronometers, and open-loop control,” in Proc. IEEE Int. Conf. on Decision Control, 2007, pp. 1916–1922.

S. G. Carver, E. S. Fortune, and N. J. Cowan, “State-estimation and cooperative control with uncertain time,” in Proc. Amer. Control Conf., 2013, in press.

A. Lamperski and N. J. Cowan, “Time-changed linear quadratic regulators,” in Proc. Euro. Control Conf., 2013, in press.

Written by Noah J. Cowan with Eric S. Fortune, Andrew Lamperski and Sean G. Carver.

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