Abstract
BackgroundDuring planning and execution of reaching movements, the activity of cortical motor neurons is modulated by a diversity of motor, sensory, and cognitive signals. Brain-machine interfaces (BMIs) extract part of these modulations to directly control artificial actuators. However, cortical modulations that emerge in the novel context of operating the BMI are poorly understood.Methodology/Principal FindingsHere we analyzed the changes in neuronal modulations that occurred in different cortical motor areas as monkeys learned to use a BMI to control reaching movements. Using spike-train analysis methods we demonstrate that the modulations of the firing-rates of cortical neurons increased abruptly after the monkeys started operating the BMI. Regression analysis revealed that these enhanced modulations were not correlated with the kinematics of the movement. The initial enhancement in firing rate modulations declined gradually with subsequent training in parallel with the improvement in behavioral performance.Conclusions/SignificanceWe conclude that the enhanced modulations are related to computational tasks that are significant especially in novel motor contexts. Although the function and neuronal mechanism of the enhanced cortical modulations are open for further inquiries, we discuss their potential role in processing execution errors and representing corrective or explorative activity. These representations are expected to contribute to the formation of internal models of the external actuator and their decoding may facilitate BMI improvement.
Highlights
Brain Machine Interfaces (BMIs) hold promise for restoring motor functions in severely paralyzed patients [1,2,3,4,5,6,7]
Neural activity was recorded from Nn = 1002300 neurons in multiple cortical areas including the primary motor cortex (M1), dorsal premotor cortex (PMd), supplementary motor area (SMA), and primary somatorsensory cortex (S1) in one monkey and medial intraparietal (MIP) of the posterior parietal cortex (PP) in the second monkey
Our analyses indicate that cortical neurons that are used to control a Brain-machine interfaces (BMIs) modulate their activity more intensely during brain control than during pole control
Summary
Brain Machine Interfaces (BMIs) hold promise for restoring motor functions in severely paralyzed patients [1,2,3,4,5,6,7]. Movement related signals that modulate the activity of these neurons are extracted using neural decoding techniques and employed to control an external actuator. We analyzed the changes in neuronal modulations that occurred in different cortical motor areas as monkeys learned to use a BMI to control reaching movements. The function and neuronal mechanism of the enhanced cortical modulations are open for further inquiries, we discuss their potential role in processing execution errors and representing corrective or explorative activity. These representations are expected to contribute to the formation of internal models of the external actuator and their decoding may facilitate BMI improvement
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