Towards a Biomarker of Motor Adaptation: Integration of Kinematic and Neural Factors

Abstract

We propose an experimental protocol for the integrated study of motor adaptation during target-based movements. We investigated how motor adaptation affects both cerebral activity and motor performance during the preparation and execution of a pointing task, under different conditions of external perturbation. Electroencephalography (EEG) and movement analysis were simultaneously recorded from 16 healthy subjects enrolled in the study. EEG signal was preprocessed by means of independent component analysis and empirical mode decomposition based Hilbert Huang transform, in order to extract event-related synchronization (ERS) and desynchronization (ERD) parameters. Movement analysis provided several kinematic indexes, such as movement durations, average jerk, and inter-quartile-ranges. Significant correlations between score, neural, and kinematic parameters were found. Specifically, the duration of the going phase of movement was found to correlate with synchronization in the beta brain rhythm, in both the planning and executive phases of movement. Inter-quartile ranges and average jerk showed correlations with executive brain parameters and ERS/ERDcueBeta, respectively. Results indicate the presence of links between the primary motor cortex and the farthest ending point of the upper limb. In the present study, we assessed significant relationship between neural and kinematic descriptors of motor adaptation, during a protocol requiring short-term learning, through the modulation of the external perturbations.

Experimental assessment of a coincident timing motor task of the arm under a passive mechanical perturbation

“…This interpretation is consistent with Molteni et al [15], that showed in their research that the statement that neural effort did not decrease trough conditions, but rather supported behavioral improvement.…”

“…It could be an indication of an increasing neural effort to refine the strategy, despite the improvement in behavioral performance. Therefore, this interpretation would lead to conclude that the neural control effort did not decrease through learning, but rather supported behavioral improvement [15]. These ideas can be considered in the design and applications of rehabilitation robots and exoskeletons.…”

“…Moreover, it can be noted that the behavioral improvement found in the execution of the task (reduced errors, decreased variability) was not associated to smoother motion patterns [15]. It could be an indication of an increasing neural effort to refine the strategy, despite the improvement in behavioral performance.…”

“…In this context, Molteni et al [15] showed that the elastic bands used as perturbations required an additional effort to complete the task. Moreover, it can be noted that the behavioral improvement found in the execution of the task (reduced errors, decreased variability) was not associated to smoother motion patterns [15].…”

Progressivity of Basic Elements of the Slovenian National Alpine Ski School

“…To achieve optimal results -this means the rapid learning of motor skills at a minimum risk of injury or other negative side effects in Alpine skiing -the process has to be appropriately structured (Molteni et al, 2012). The principle of progressivity in speed and complexity of movement is an important didactic principle according to which the individual is guided until they carry out a skiing element optimally (Winter, 2009).…”