Learning to Balance an Inverted Pendulum at the Fingertip: A Window Into the Task and Context-Dependent Control of Unstable Dynamical Objects

Abstract

<p>Our ability to control unstable objects highlights the sophistication of voluntary motor behaviour. In this thesis, we used an inverted pendulum (i.e., stick) balancing paradigm to investigate the task, learning and context-dependent attributes of unstable object control. We hypothesized that learning would mediate the functional integration of posture and upper limb dynamics and expected changes in the task demand and context to be reflected in the control of posture and the upper limb. We found that training increased the average length of balancing trials and applied this result to further investigate the circumstantial properties of unstable object control.</p> <p>We investigated the temporal structure of posture and upper limb dynamics using statistical and nonlinear time series analysis. We demonstrated that subjects used an intermittent strategy to control the inverted pendulum (Chapters 3 and 5) and found that motor learning modulated the statistical and spatiotemporal attributes of posture (Chapter 5) and upper limb displacements (Chapters 2, 3 and 5). We confirmed the balance control strategy was intermittent by showing that posture and upper limb time series are composed of two independent timescale components: a fast component linked to small stochastic displacements and a slow component related to feedback control (Chapters 3, 4 and 5). The interplay between timescale components was affected by the balancing context (Chapter 3) and task demand (Chapter 4).</p> <p>Chapter 5 investigated the acquisition of individual and coupled posture-upper limb control mechanisms. We found that motor learning involved two independent adaptation processes. The first process modified the timescale composition of posture and upper limb displacements and was followed by incremental changes in the occurrence and duration of correlated posture-upper limb trajectories. In Chapter 6, we investigated learning-mediated changes in multijoint coordination and control. Motor learning led to the flexible, error-compensating recruitment of individual joints and we showed that the preferential constraint of destabilizing joint angle variance was the putative mechanism underlying performance.</p> <p>This thesis performed a detailed examination of unstable object control mechanisms. The undertaken studies have provided knowledge about the acquisition and adaptation of control mechanisms at multiple levels of the motor system. Our data provide convergent evidence that the control mechanisms governing complex human balancing tasks are intermittent and modulated by the task and context.</p>