Brain-machine interfaces (BMIs) have been developed using a variety of neural signals, including neuron action-potentials and local field-potentials (LFPs). However, little is known about the neural dynamics underlying closed-loop BMI control in these systems, and whether they might be shaped by the signal used for control. Better understanding the relationship between neural signals in closed-loop BMI could inform the design of future systems. We analyzed spiking and LFP activity in pre- and primary-motor cortices as a nonhuman primate performed closed-loop BMI driven by either spiking or LFP signals. Spike- and LFP-based BMI were done on different days. and all comparisons of activity are indirect. Both LFP and spiking activity showed significant task-related modulations in both types of BMI control. However, the neural dynamics varied with the control signal type. LFP signals, in particular, showed more directional modulation when BMI was controlled with LFPs.
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