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Front Hum Neurosci. 2014 Apr 29;8:271. doi: 10.3389/fnhum.2014.00271. eCollection 2014.

Linking motor-related brain potentials and velocity profiles in multi-joint arm reaching movements.

Frontiers in human neuroscience

Julià L Amengual, Josep Marco-Pallarés, Carles Grau, Thomas F Münte, Antoni Rodríguez-Fornells

Affiliations

  1. Cognition and Brain Plasticity Unit, Department of Basic Psychology, University of Barcelona Barcelona, Spain.
  2. Cognition and Brain Plasticity Unit, Department of Basic Psychology, University of Barcelona Barcelona, Spain ; Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat Spain.
  3. Neurodynamic Laboratory, Department of Psychiatry and Clinical Psychobiology, Universitat de Barcelona Barcelona, Spain.
  4. Department of Neurology, University of Lübeck Lübeck, Germany.
  5. Cognition and Brain Plasticity Unit, Department of Basic Psychology, University of Barcelona Barcelona, Spain ; Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat Spain ; Institució Catalana de Recerca i Estudis Avançats Barcelona, Spain.

PMID: 24808853 PMCID: PMC4010756 DOI: 10.3389/fnhum.2014.00271

Abstract

The study of the movement related brain potentials (MRPBs) needs accurate technical approaches to disentangle the specific patterns of bran activity during the preparation and execution of movements. During the last forty years, synchronizing the electromyographic activation (EMG) of the muscle with electrophysiological recordings (EEG) has been commonly ussed for these purposes. However, new clinical approaches in the study of motor diseases and rehabilitation suggest the demand of new paradigms that might go further into the study of the brain activity associated with the kinematics of movements. As a response to this call, we have used a 3-D hand-tracking system with the aim to record continuously the position of an ultrasonic sender attached to the hand during the performance of multi-joint self-paced movements. We synchronized time-series of position and velocity of the sender with the EEG recordings, obtaining specific patterns of brain activity as a function of the fluctuations of the kinematics during natural movement performance. Additionally, the distribution of the brain activity during the preparation and execution phases of movements was similar that reported previously using the EMG, suggesting the validity of our technique. We claim that this paradigm could be usable in patients because of its simplicity and the potential knowledge that can be extracted from clinical protocols.

Keywords: 3-D movement analyser; kinematics; motor activity; motor related brain potentials; self-paced movement; time-series analysis

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