Biomedical subjects

David M Santucci

Publications and source records attributed to David M Santucci.

2 recordsLinked to original sources

PubMed2005

Frontal and parietal cortical ensembles predict single-trial muscle activity during reaching movements in primates.

Previously we have shown that the kinematic parameters of reaching movements can be extracted from the activity of cortical ensembles. Here we used cortical ensemble activity to predict electromyographic (EMG) signals of four arm muscles in New World monkeys. The overall shape of the EMG envelope was predicted, as well as trial-to-trial variations in the amplitude and timing of bursts of muscle activity. Predictions of EMG patterns exhibited during reaching movements could be obtained not only from primary motor cortex, but also from dorsal premotor, primary somatosensory and posterior parietal cortices. These results suggest that these areas represent signals correlated to EMGs of arm muscles in a distributed manner, and that the larger the population sampled, the more reliable the predictions. We propose that, in the future, recordings from multiple cortical areas and the extraction of muscle patterns from these recordings will help to restore limb mobility in paralysed patients.

Algorithms↗

PubMed2003

Learning to control a brain-machine interface for reaching and grasping by primates.

Reaching and grasping in primates depend on the coordination of neural activity in large frontoparietal ensembles. Here we demonstrate that primates can learn to reach and grasp virtual objects by controlling a robot arm through a closed-loop brain-machine interface (BMIc) that uses multiple mathematical models to extract several motor parameters (i.e., hand position, velocity, gripping force, and the EMGs of multiple arm muscles) from the electrical activity of frontoparietal neuronal ensembles. As single neurons typically contribute to the encoding of several motor parameters, we observed that high BMIc accuracy required recording from large neuronal ensembles. Continuous BMIc operation by monkeys led to significant improvements in both model predictions and behavioral performance. Using visual feedback, monkeys succeeded in producing robot reach-and-grasp movements even when their arms did not move. Learning to operate the BMIc was paralleled by functional reorganization in multiple cortical areas, suggesting that the dynamic properties of the BMIc were incorporated into motor and sensory cortical representations.

Animals↗