Title: Sustained sensorimotor control as intermittent decisions about prediction errors: Computational framework and application to ground vehicle steering,
Abstract: A conceptual and computational framework is proposed for modelling of human
sensorimotor control, and is exemplified for the sensorimotor task of steering
a car. The framework emphasises control intermittency, and extends on existing
models by suggesting that the nervous system implements intermittent control
using a combination of (1) motor primitives, (2) prediction of sensory outcomes
of motor actions, and (3) evidence accumulation of prediction errors. It is
shown that approximate but useful sensory predictions in the intermittent
control context can be constructed without detailed forward models, as a
superposition of simple prediction primitives, resembling neurobiologically
observed corollary discharges. The proposed mathematical framework allows
straightforward extension to intermittent behaviour from existing
one-dimensional continuous models in the linear control and ecological
psychology traditions. Empirical observations from a driving simulator provide
support for some of the framework assumptions: It is shown that human steering
control, in routine lane-keeping and in a demanding near-limit task, is better
described as a sequence of discrete stepwise steering adjustments, than as
continuous control. Furthermore, the amplitudes of individual steering
adjustments are well predicted by a compound visual cue signalling steering
error, and even better so if also adjusting for predictions of how the same cue
is affected by previous control. Finally, evidence accumulation is shown to
explain observed covariability between inter-adjustment durations and
adjustment amplitudes, seemingly better so than the type of threshold
mechanisms that are typically assumed in existing models of intermittent
control.