Speed-accuracy tradeoffs, velocity profiles, and physiological tremor are fundamental characteristics of human movement. The principles underlying these phenomena have long attracted major interest and controversy. Each is well established experimentally but as yet they have no common theoretical basis. It is proposed that these three phenomena occur as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of adaptive model theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (i) analysing sensory information, (ii) planning a desired optimal response, and (iii) executing that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory of variable duration, or horizon, to connect the actual response with the predicted future state of the target and compensate for executional error. BUMP model simulation studies show that intermittent adaptive optimal control employing two extremes of variable horizon predictive control reproduces almost exactly findings from several authoritative human experiments. On the one extreme, simulating spatially-constrained movements, a receding horizon strategy results in a logarithmic speed-accuracy tradeoff and accompanying asymmetrical velocity profiles. On the other extreme, simulating temporally-constrained movements, a fixed horizon strategy results in a linear speed-accuracy tradeoff and accompanying symmetrical velocity profiles. Furthermore, simulating ramp movements, a receding horizon strategy closely reproduces experimental observations of 10 Hz physiological tremor. A 100 ms planning interval yields waveforms and power spectra equivalent to those of joint-angle, angular velocity and electromyogram signals recorded for several speeds, directions, and skill levels of finger movement. While other models of response planning account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.

Speed-accuracy tradeoffs, velocity profiles, and physiological tremor are fundamental characteristics of human movement. The principles underlying these phenomena have long attracted major interest and controversy. Each is well established experimentally but as yet they have no common theoretical basis. It is proposed that these three phenomena occur as the direct consequence of a movement response planning system that acts as an intermittent optimal controller operating at discrete intervals of ~100 ms. The BUMP model of response planning describes such a system. It forms the kernel of adaptive model theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (i) analysing sensory information, (ii) planning a desired optimal response, and (iii) executing that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete time interval in which to generate a minimum acceleration trajectory of variable duration, or horizon, to connect the actual response with the predicted future state of the target and compensate for executional error. BUMP model simulation studies show that intermittent adaptive optimal control employing two extremes of variable horizon predictive control reproduces almost exactly findings from several authoritative human experiments. On the one extreme, simulating spatially-constrained movements, a receding horizon strategy results in a logarithmic speed-accuracy tradeoff and accompanying asymmetrical velocity profiles. On the other extreme, simulating temporally-constrained movements, a fixed horizon strategy results in a linear speed-accuracy tradeoff and accompanying symmetrical velocity profiles. Furthermore, simulating ramp movements, a receding horizon strategy closely reproduces experimental observations of 10 Hz physiological tremor. A 100 ms planning interval yields waveforms and power spectra equivalent to those of joint-angle, angular velocity and electromyogram signals recorded for several speeds, directions, and skill levels of finger movement. While other models of response planning account for one or other set of experimentally observed features of speed-accuracy tradeoffs, velocity profiles, and physiological tremor, none accounts for all three. The BUMP model succeeds in explaining these disparate movement phenomena within a single framework, strengthening this approach as the foundation for a unified theory of motor control and planning.