## 4 Discussion
### Control Strategy and Mechanism in 3D Tracking Movements  
In general, the human visuomotor control system requires approximately 200 ms to perform visually guided error correction because of the brain's neurotransmission, sensory processing, and refractoriness in the human neuromotor control [18; 19; 29]. Previous studies have established theories for control strategies by considering the delay time during visuomotor processing. Intermittent feedback (FB) control and feedforward (FF) control using an internal model have been suggested as typical theories for the control strategy [21; 22; 23; 24; 30]. These studies demonstrated that control strategies (i.e., FB and FF controls) and major control parameters in kinematic features (i.e., position or velocity) for tracking movements vary irrespective of the target trajectory being random or consistent [13; 17; 21; 22]. In other words, these studies reported that pseudorandom tracking movements are primarily controlled by intermittent FB control with position error (i.e., \(\Delta\theta\)) reduction. In addition, periodic sinusoidal tracking movements depend on more FF control with velocity error (i.e., \(\Delta\omega\)) reduction to predict future target motion. Our previous study examined the extent of the impact of the target visual information on the periodic circular tracking task control strategy as being the same in this study [14]. We also confirmed FF controls with velocity error (i.e., \(\Delta\omega\)) reduction in target-invisible regions for the periodic circular tracking task. In other words, the target visibility allows us to examine the impact of the target visual information on the control strategy by quantitatively comparing the three temporospatial parameters (\(\Delta R\), \(\Delta\theta\), and \(\Delta\omega\)) relative changes during the target-visible phase responsible for stable FB control with the target-invisible phase for FF control. In our future studies, we will examine the same periodic circular tracking task with different speeds and visibility of the target based on the same \(\Delta R\), \(\Delta\theta\), and \(\Delta\omega\) parameters to observe control strategy changes and major kinematic feature control parameters during 3D circular tracking movement tasks. For different movement types and target speeds, we should design different control strategies, considering cognition delay and visuomotor processing. Intermittent FB control and FF control, as an internal model, have been suggested as a suitable control strategy [13; 14; 15]. Based on previous studies in 2D space, FB control dominates when the target speed is slow; however, FF control dominates when the target speed is high [21; 22; 23; 24]. In this study, similar results were found for 3D target-tracking movements. Despite adding a countdown sound to announce the start of the target movement, the initial errors were greater when the target speed was higher, indicating imprecise FF control, as observed for 2D movements (Figure 2) [25]. Our previous studies demonstrated that increasing target speed makes it more difficult to synchronize the angle and angular velocities of the target and tracer temporally. Considering our previous studies [31; 32] showed the cerebellum plays an important role in the generation of motor commands for smooth velocity and position control, the method and analysis proposed in this study will apply to characterize the motor function of patients with cerebellar ataxia in the future. Our recent study demonstrated that the smooth tracking movement of the wrist joint consists of two components with distinct motor commands for velocity and position controls [33]. In other words, the major component in a lower frequent range (named by the F1 component) of the tracking movement played the primary role to reproduce both the velocity and position of the target motion in a predictive manner.