Molteni, E., Cimolin, V., Preatoni, E., Rodano, R., Galli, M. and Bianchi, A. M., 2012. Towards a Biomarker of Motor Adaptation: Integration of Kinematic and Neural Factors. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20 (3), pp. 258-267.
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.
|Item Type ||Articles|
|Creators||Molteni, E., Cimolin, V., Preatoni, E., Rodano, R., Galli, M. and Bianchi, A. M.|
|Departments||Faculty of Humanities & Social Sciences > Health|
|Publisher Statement||Preatoni_TNSRE_2012_20_3_258.pdf: © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works|
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