Details

Autor(en) / Beteiligte

• Mattia, Donatella
• Cincotti, Febo
• Astolfi, Laura
• de Vico Fallani, Fabrizio
• Scivoletto, Giorgio
• Marciani, Maria Grazia
• Babiloni, Fabio

Titel

Motor cortical responsiveness to attempted movements in tetraplegia: Evidence from neuroelectrical imaging

Ist Teil von

• Clinical neurophysiology, 2009-01, Vol.120 (1), p.181-189

Ort / Verlag

Oxford: Elsevier Ireland Ltd

Erscheinungsjahr

2009

Quelle

Access via ScienceDirect (Elsevier)

Beschreibungen/Notizen

• Abstract Objective The maintenance of a motor cortical program in the temporal domain is relevant to current neuroinformatic efforts to use non-invasive EEG signals to control neuroprosthetic devices designed to restore natural movements of paralyzed body parts. Here we use an advance neuroelectrical imaging approach to examine the motor cortical responsiveness in human tetraplegia. Methods High resolution-electroencephalographic (EEG) recordings were performed in five subjects with tetraplegia due to chronic, complete spinal cord injuries (SCIs) while they attempted self-generated movements of a plegic body part (foot), and in five healthy subjects executing simple foot movements. Results Self-generated movement attempts induced significant EEG sources of activity in a set of motor-related areas (including the primary motor area, MI) similar to what observed during the preparatory stages of movement execution (control subjects). Functional connectivity showed a preferential interaction between the “non-primary” motor areas and the putative MI foot site, as estimated for both motor execution and attempt. Under this latter condition however, it could be observed an “enlargement” of the functional network by including the left superior parietal cortex. Conclusions Our findings indicate the existence of a functional circuit subserving the attempted motion in SCI subjects that encompasses a set of areas known to play a role in motor execution, yet reveals differences in the functional interaction between these areas. Significance The understanding of changes in the motor circuitry is relevant to current neuroinformatic efforts to use non-invasive EEG signals to control neuroprosthetic devices designed to benefit paralyzed persons.