Abstract
While remarkable progress has been made in brain-machine interfaces (BMIs) over the past two decades, it is still difficult to utilize neural signals to drive artificial actuators to produce predictive movements in response to dynamic stimuli. In contrast to naturalistic limb movements largely based on forward planning, brain-controlled neuroprosthetics mainly rely on feedback without prior trajectory formation. As an important sensorimotor interface integrating multisensory inputs and efference copy, the posterior parietal cortex (PPC) might play a proactive role in predictive motor control. Here it is proposed that predictive neural activity in PPC could be decoded to provide prosthetic control signals for guiding BMI systems in dynamic environments.
Highlights
To interact with a changing world, such as in tracking and intercepting moving objects, the brain must overcome pervasive sensorimotor delays (Nijhawan, 2008; Franklin and Wolpert, 2011)
It has been proposed that compensating for these inherent delays is based on bottom-up sensory extrapolation, the prevalent view of sensorimotor control posits that action planning relies on forward models based on an intimate interplay between sensory inflow and motor outflow, rather than a hierarchical transformation from extrinsic stimuli to intrinsic muscular activity (Wolpert et al, 1995; Shadmehr and Mussa-Ivaldi, 2012)
Even if predictive activity embodied in the posterior parietal cortex (PPC) can provide useful neural signals for open-loop prosthetic control of movements, important issues remained to be addressed
Summary
To interact with a changing world, such as in tracking and intercepting moving objects, the brain must overcome pervasive sensorimotor delays (Nijhawan, 2008; Franklin and Wolpert, 2011). It has been proposed that compensating for these inherent delays is based on bottom-up sensory extrapolation (e.g., the flash-lag effect, Nijhawan, 1994; Nijhawan and Wu, 2009), the prevalent view of sensorimotor control posits that action planning relies on forward models based on an intimate interplay between sensory inflow and motor outflow, rather than a hierarchical transformation from extrinsic stimuli to intrinsic muscular activity (Wolpert et al, 1995; Shadmehr and Mussa-Ivaldi, 2012)
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