Using kinematic analysis of movement to predict the time occurrence of an evoked potential associated with a motor command. Issue 2 (20th January 2013)

• Record Type: Journal Article
• Authors: O'Reilly, Christian; Plamondon, Réjean; Landou, Mohamed K.; Stemmer, Brigitte
• Is Part Of: European journal of neuroscience. Volume 37:Issue 2(2013:Jan.)
• Page Start: 173
• Page End: 180
• Publication Date: 2013-01-20
• Subjects: Nervous system -- Periodicals; 612.8
• DOI: 10.1111/ejn.12039
• Languages: English
• ISSNs: 0953-816X

Abstract

<abstract abstract-type="main" id="ejn12039-abs-0001"> <title>Abstract</title> <p>This article presents an exploratory study investigating the possibility of predicting the time occurrence of a motor event related potential (ERP) from a kinematic analysis of human movements. Although the response‐locked motor potential may link the ERP components to the recorded response, to our knowledge no previous attempt has been made to predict <italic>a priori</italic> (i.e. before any contact with the electroencephalographic data) the time occurrence of an ERP component based only on the modeling of an overt response. The proposed analysis relies on the delta‐lognormal modeling of velocity, as proposed by the kinematic theory of rapid human movement used in several studies of motor control. Although some methodological aspects of this technique still need to be fine‐tuned, the initial results showed that the model‐based kinematic analysis allowed the prediction of the time occurrence of a motor command ERP in most participants in the experiment. The average map of the motor command ERPs showed that this signal was stronger in electrodes close to the contra‐lateral motor area (Fz, FCz, FC1, and FC3). These results seem to support the claims made by the kinematic theory that a motor command is emitted at time <italic>t</italic><sub>0</sub>, the time reference parameter of the model. This article proposes a new time marker directly associated with a cerebral event (i.e. the emission of a motor command) that can be used for the development of new data analysis methodologies and for the elaboration of new experimental protocols based on ERP.</p> </abstract>