Rhythmic Motor Behavior

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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]

Eva Siehmann wins best thesis award

Eva Siehmann won the Lorenz-Wegen award for best thesis at her university, Westfälischen Hochschule. She did her thesis project at the LIMBS lab during Spring-Summer 2013.

siehmannAward 

In her thesis, Eva Siehmann focused on decoding the neural circuitry for extracting features called ‘envelopes’, which are present in a lot of sensory signals. Her work was specifically on envelope extraction in the electrosensory system of weakly electric fish. Eva attempted to deduce, through a task-level experiment, whether the nonlinear mechanism in question is half-wave or full-wave rectifier with a low-pass filter following it.

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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