Actually I think it’s unclear if the cerebellum does anything on it’s own—even motor control, because as explained above from a connectivity standpoint it doesn’t even make sense to talk about cerebellum outside of tightly coupled cortical-cerebellar-BG-thalami loop modules—those are the actual functional connectivity modules of the brain. The brain is essentially a large society of those modules. Humans lacking a cerebellum (or even with sudden cerebellum damage) do not completely lack any specific motor function, but instead show a wide range of mental deficits. But humans lacking motor cortex do show motor deficits (from what I recall).
However, the cerebellum as training/reversion module theories do generally predict that the cerebellum is much more important for motor vs sensor cortex, just due to the nature of the sensor → latent → motor process which is compressive (and thus mostly UL based) in the first stage and then expansive (and thus mostly RL based) in the latter stage. And those theories specifically correctly predict lack of cerebellum mapping in earliest sensor cortex (as there is no need to send training signal to retina) - which is exactly what you find. Other theories do not make these specific correct testable predictions.
That being said yes agreed it probably “learns to smooth out motor trajectories” probably as a subset of learning to backdrop fine grain credit assignment through time for the cortex. (much more important for motor than sensor).
And yes agreed on the BG role.
As for ‘huge number of neurons’ - this is a red herring. The unit of computation is the synapse, not the neuron. The tiny granule cells only have 3-4 synapses each, and it’s pretty clear they are doing some decompression/recoding of incoming channel/bandwidth constrained signals. Regardless their contribution to total compute power is minor—not even in the trillions of synapses.
Actually I think it’s unclear if the cerebellum does anything on it’s own—even motor control, because as explained above from a connectivity standpoint it doesn’t even make sense to talk about cerebellum outside of tightly coupled cortical-cerebellar-BG-thalami loop modules—those are the actual functional connectivity modules of the brain. The brain is essentially a large society of those modules. Humans lacking a cerebellum (or even with sudden cerebellum damage) do not completely lack any specific motor function, but instead show a wide range of mental deficits. But humans lacking motor cortex do show motor deficits (from what I recall).
However, the cerebellum as training/reversion module theories do generally predict that the cerebellum is much more important for motor vs sensor cortex, just due to the nature of the sensor → latent → motor process which is compressive (and thus mostly UL based) in the first stage and then expansive (and thus mostly RL based) in the latter stage. And those theories specifically correctly predict lack of cerebellum mapping in earliest sensor cortex (as there is no need to send training signal to retina) - which is exactly what you find. Other theories do not make these specific correct testable predictions.
That being said yes agreed it probably “learns to smooth out motor trajectories” probably as a subset of learning to backdrop fine grain credit assignment through time for the cortex. (much more important for motor than sensor).
And yes agreed on the BG role.
As for ‘huge number of neurons’ - this is a red herring. The unit of computation is the synapse, not the neuron. The tiny granule cells only have 3-4 synapses each, and it’s pretty clear they are doing some decompression/recoding of incoming channel/bandwidth constrained signals. Regardless their contribution to total compute power is minor—not even in the trillions of synapses.