I did my Ph.D. work on the cerebellum and proposed a theoretical model of reinforcement learning and can add some context for why this is a "big deal".
First, it represents a fundamental shift in how the cerebellum learns. For a long time, it was thought that the cerebellum learned liked a perceptron neural network, i.e. that an error signal was computed and used to change the strength of synapses within the cerebellum to result in the correct output signal to guide motor control (and, we know now, cognitive control). In other words, the cerebellum was a supervised learning machine [1]. But how these error signals were actually computed using the neuronal circuitry was never made clear; most arguments centered around the microcircuitry of the inferior olive. In a perceptron, an error signal is the difference between the correct output and the predicted output. But how is the "correct output" supplied?
As far as I know the first to propose the cerebellum learned by reinforcement learning was the famed cerebellum researcher Richard Thompson [2]. Unfortunately, the idea was only vaguely sketched out the field didn't take this very seriously and continued on with the general belief that the cerebellum learned by supervised learning.
To me and my collaborator, Tadashi Yamazaki, it seemed a more natural signal that the nervous system could capably supply would be a graded reward signal. Moreover, this meant we could interpret the structure of the cerebellum within the theoretical frameworks of reinforcement learning such as the actor-critic framework [3,4]. This is the second reason these finding are a big deal: the paradigm shift to the cerebellum being a reinforcement learning machine, if correct, will be a boon for building better models of it. In the last few years there has been some impressive work done with reinforcement learning in artificial neural networks that could be applied to models of the cerebellum, especially within context of the brain at large.
[1] Doya, Kenji "What are the computations of the cerebellum, the basal ganglia and the cerebral cortex" (1999)
[2] Thompson, Richard "The nature of reinforcement in cerebellar learning" (1998).
[3] Lennon, William "Towards more biologically plausible computational models of the cerebellum with emphasis on the molecular layer interneurons" (2015)
[4] Yamazaki and Lennon "Revisiting a theory of cerebellar cortex" (2019)
This is a great example of a niche banking solution which is far better than any traditional bank can provide. I think we'll see a lot more of this as banking APIs become more available.
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Connecting this to the OP is that it looks like the stimulation is initially activating these CPGs -- all of the movement is happening based on control from the spinal cord alone. It's not clear how much communication is taking place between the motor cortex and the spinal cord in this patient.
Something to add to this that most non-neuroscientists don't realize is that the spinal cord is not just a bundle of wires that connect the brain to muscles. The spinal cord is a complex circuit that contains "central pattern generators" (CPG) that can produce rhythmic movement. When activated, these networks can be pushed into a dynamic state where they repeat the same movement repeatedly, e.g. walking. For more, look up the work by Sten Grillner on stingray CPGs.
One approximate way of looking at this is that the brain's motor cortex sends a "go" signal to the spinal cords CPGs and these start generating the signals to the muscles to walk. You can also think of motor control as hierarchical where as you go up the hierarchy. The bottom of the hierarchy are the muscles/actuators, then the neurons that stimulate the muscles, then the circuits in the spinal cord that have these CPGs and other "primitives", then primary motor cortex and further up the cortical hierarchy. At the higher levels of the cortical hierarchy are representations of whole movements, like moving your hand to mouth. As you descend the hierarchy, the neural signals control gradually more details components of the movement. For more, look up the work by Michael Graziano.
Indeed. What's new is what sort of information is conveyed from the gut to the brain via the vagus nerve. Note: information is also conveyed in the other direction from the brain to the gut.
This study shows that your gut is equipped with environmental sensors (enteroendocrine cells) that can convey nutritional information from the gut to the brain on short time scales (~seconds or faster). It's like your gut's "eye" in that it can "see" what's going on, like sugars are present, and convey this to your brain.
I'm not an expert on the gut-brain field but I've always wondered where food cravings come from, especially specific ones that pregnant women often exhibit. E.g. craving dirt. My conclusion is that your body must have a way of sensing what nutrients you're ingesting and missing.