Jürgen Konczak and Johannes Dichgans
Tobias Kalenscher, Karl-Theodor Kalveram, and Jürgen Konczak
This study investigated force adaptation in humans during goal-directed flexion forearm motion. The ability of the motor system to adapt to changes in internal or external forces is essential for the successful control of voluntary movement. In a first experiment, we examined how under- or overdamping differentially affected the length of the adaptation and the arm kinematics between force transitions. We found that transitions diverging from a null-force produced larger transition effects than transitions converging to a null force condition, indicating that re-adaptation was less error-prone. Whether the subjects had previously experienced underdamping or the null-force had no significant impact on the spatial trajectory after switching to overdamping. That is, prior force experience had no differential effect on the spatial transition kinematics. However, the transitions underdamping-to-overdamping and underdamping-to–null force did produce differently strong transition effects. These results indicate that exposure to the new force rather than previous force-field experience is responsible for transition- and after-effects. In a second experiment, we investigated whether learning was law-like—that is, whether it generalized to unvisited workspace. Subjects were tested in new, unvisited workspaces in the null-force condition after sufficient training in either force condition. The occurrence of transferred after-effects indicated that adaptation to both positive and negative damping was mediated by rule-based rather than exclusive associative processes.
Jürgen Konczak, Kai Brommann, and Karl Theodor Kalveram
Knowledge of how stiffness, damping, and the equilibrium position of specific limbs change during voluntary motion is important for understanding basic strategies of neuromotor control. Presented here is an algorithm for identifying time-dependent changes in joint stiffness, damping, and equilibrium position of the human forearm. The procedure requires data from only a single trial. The method relies neither on an analysis of the resonant frequency of the arm nor on the presence of an external bias force. Its validity was tested with a simulated forward model of the human forearm. Using the parameter estimations as forward model input, the angular kinematics (model output) were reconstructed and compared to the empirically measured data. Identification of mechanical impedance is based on a least-squares solution of the model equation. As a regularization technique and to improve the temporal resolution of the identification process, a moving temporal window with a variable width was imposed. The method's performance was tested by (a) identifying a priori known hypothetical time-series of stiffness, damping, and equilibrium position, and (b) determining impedance parameters from recorded single-joint forearm movements during a hold and a goal-directed movement task. The method reliably reconstructed the original angular kinematics of the artificial and human data with an average positional error of less than 0.05 rad for movement amplitudes of up to 0.9 rad, and did not yield hypermetric trajectories like previous procedures not accounting for damping.
Yu-Ting Tseng, Sanaz Khosravani, Arash Mahnan, and Jürgen Konczak
This review addresses the role of exercise as an intervention for treating neurological disease. It focuses on three major neurological diseases that either present in acute or neurodegenerative forms—Parkinson’s disease, cerebellar ataxia, and cortical stroke. Each of the diseases affects primarily different brain structures, namely the basal ganglia, the cerebellum, and the cerebrum. These structures are all known to be involved in motor control, and the dysfunction of each structure leads to distinct movement deficits. The review summarizes current knowledge on how exercise can aid rehabilitation or therapeutic efforts. In addition, it addresses the role of robotic devices in enhancing available therapies by reviewing how robot-aided therapies may promote the recovery for stroke survivors. It highlights recent scientific evidence in support of exercise as a treatment for brain dysfunction, but also outlines the still open challenges for unequivocally demonstrating the benefits of exercise.