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1 Physics, UCSD, La Jolla, CA, USA
2 Physics, UCSD, La Jolla, CA, USA; Graduate Program in Neurosciences, UCSD, La Jolla, CA, USA
* To whom correspondence should be addressed. E-mail: dk{at}physics.ucsd.edu.
The rhythmic motor activity of the vibrissae that rodents use for the tactile localization of objects provides a model system for understanding patterned motor activity in mammals. Evidence suggests that neural circuitry in the brainstem provides rhythmic drive to the vibrissae. Yet multiple brain structures at higher levels of organization, including vibrissa primary motor cortex (M1), have direct projections to brainstem nuclei that are implicated in whisking. We thus asked if output from M1 can control vibrissa movement on the ~10 Hz scale of the natural rhythmic movement of the vibrissae. Our assay of cortical control made use of periodic intracortical microstimulation (ICMS) to excite a region of vibrissa M1 cortex in awake, behaving animals and measurements of the stimulus-locked electromyogram (EMG) in both the intrinsic and extrinsic muscles that drive the vibrissae. We observed that ICMS evoked a prompt activation of the extrinsic muscles and a delayed and prolonged response in the intrinsic muscles. The relative timing and shape of these waveforms approximates the EMG waveforms seen during natural exploratory whisking. We further observed prompt activation of the intrinsic muscles, an occurrence not seen during exploratory whisking. Despite the latter difference in muscular activation, the motion of the vibrissae evoked by periodic ICMS strongly resembled the motion during natural, exploratory whisking. Interestingly, the extent of the movement was proportional to the level of arousal, as quantified by the amplitude of hippocampal activity in the theta-requency band. We interpret these data as demonstrating that M1 cortex can, in principal, control the full pattern of whisking on a cycle-by-cycle basis in aroused animals. Beyond issues of natural motor control, our result may bear on the design of algorithms for neuroprosthetic control of motor output.
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