Motor cortex is using a plasticity framework that supports 'procedural' memory formation. This type of learning is relatively slow and relies on small incremental changes (for ML people, maybe this is similar to having your nn regularization parameter cranked way up).
Other areas of cortex can support 'declarative' memory formation. For example you can learn things like the definition of a new word (lang), features of a novel object (vis), where you parked your car outside your new apartment (spatial/episodic), within just a few seconds.
For the control of prosthetic limbs, there is perhaps no better brain-computer interface than motor cortex. Despite its relatively laborious procedural-type learning framework, limb movement is precisely what PMC has been optimized for. Since we've been digging around PMC for a while and have managed to make these electronic prosthetics work well, it's only natural to see what other tasks we can perform with those PMC-embedded electrodes. We should however keep in mind, though, the human brain has a wondrous variety of subregions optimized via evolution to perform all manner of computations, to support some subtype of behavior or mental capacity, with varying degrees of task-specificity. All I'm really saying is that... we will likely find out that a PMC-computer interface is garbage at doing some of the things we imagine should be possible, like typing words into a text box using thoughts. While it's likely possible (motor cortex could think about moving virtual fingers typing on a keyboard, and the computer interface could pick up on these signal patterns), there is another set of brain regions better suited for this task that could be tapped-into. But yes, "Some Brain Regions Cling to Old Habits When Learning New Tricks".