Interfacing sensory input with motor output: does the control architecture converge to a serial process along a single channel?

Abstract

Modular organization in control architecture may underlie the versatility of human motor control; but the nature of the interface relating sensory input through task-selection in the space of performance variables to control actions in the space of the elemental variables is currently unknown. Our central question is whether the control architecture converges to a serial process along a single channel? In discrete reaction time experiments, psychologists have firmly associated a serial single channel hypothesis with refractoriness and response selection [psychological refractory period (PRP)]. Recently, we developed a methodology and evidence identifying refractoriness in sustained control of an external single degree-of-freedom system. We hypothesize that multi-segmental whole-body control also shows refractoriness. Eight participants controlled their whole body to ensure a head marker tracked a target as fast and accurately as possible. Analysis showed enhanced delays in response to stimuli with close temporal proximity to the preceding stimulus. Consistent with our preceding work, this evidence is incompatible with control as a linear time invariant process. This evidence is consistent with a single-channel serial ballistic process within the intermittent control paradigm with an intermittent interval of around 0.5 s. A control architecture reproducing intentional human movement control must reproduce refractoriness. Intermittent control is designed to provide computational time for an online optimization process and is appropriate for flexible adaptive control. For human motor control we suggest that parallel sensory input converges to a serial, single channel process involving planning, selection, and temporal inhibition of alternative responses prior to low dimensional motor output. Such design could aid robots to reproduce the flexibility of human control.

Intermittent control of unstable multivariate systems

“…Within the continuous optimal feedback control paradigm discrete decision making is restricted typically to an undeclared, higher process which passes optimised control parameters to a lower continuous regulatory loop [7][8][9]. The continuous regulatory loop models the fast, reflexive spinal, brainstem and trans-cortical responses that have been studied extensively by physiologists [10,11].…”

Intermittent Control in Man and Machine

“…It seems likely that understanding the control mechanisms behind human balance and motion control van de Kamp et al, 2013a,b) and stick balancing will have applications in robotics. In particular, as discussed by van de Kamp et al (2013a), robots, like humans contain redundant possibilities within a multi-segmental structure. Thus the multivariable constrained intermittent control methods illustrated in Section 7, and the adaptive versions illustrated in Section 11 may well be applicable to the control of autonomous robots.…”

Event-Based Data Acquisition and Reconstruction—Mathematical Background

“…It seems likely that understanding the control mechanisms behind human balance and motion control van de Kamp et al, 2013a,b) and stick balancing will have applications in robotics. In particular, as discussed by van de Kamp et al (2013a), robots, like humans contain redundant possibilities within a multi-segmental structure. Thus the multivariable constrained intermittent control methods illustrated in Section 7, and the adaptive versions illustrated in Section 11 may well be applicable to the control of autonomous robots.…”

“…The length of the intermittent interval gives a trade-off between continuous control (zero intermittent interval) and intermittency. Continuous control maximises the frequency bandwidth and stability margins at the cost of reduced flexibility whereas intermittent control provides time in the loop for optimisation and selection (van de Kamp et al, 2013a; at the cost of reduced frequency bandwidth and reduced stability margins. The rationale for intermittent control is that it confers online flexibility and adaptability.…”

“…The unstable second order system had a time-constant equivalent to a standing human. Since the zero order system has no dynamics requiring ongoing control, step changes in target produce discrete Control of the hand muscles may be more refined, specialised and more intentional than control of the muscles serving the legs and trunk (van de Kamp et al, 2013a). Using online visual feedback (< 100 ms delay) of a marker on the head, participants were asked to track…”