Visual awareness and the cerebellum: possible role of decorrelation control.

The two roles in awareness most often suggested for the cerebellum are (i) keeping the details of motor skills away from forebrain computation, and (ii) signaling to the forebrain when a sensory event is not predictable from prior motor commands. However, it is unclear how current models of the cerebellum could carry out these roles. Their architecture, based on the seminal ideas of Marr and Albus, appears to need 'motor error' to learn correct motor commands. However, since motor error is the difference between the actual motor command and what the command should have been, it is a signal unavailable to the organism in principle. We propose a possible solution to this problem, termed decorrelation control, in which the cerebellum learns to decorrelate the motor command sent to the muscles from the sensory consequences of motor error. This method was tested in a linear model of oculomotor plant compensation in the vestibulo-ocular reflex. A copy of the eye-movement command was sent as mossy-fiber input to the flocculus, represented as a simple adaptive filter version of the Marr-Albus architecture. The sensory consequences of motor error were retinal slip, delivered as climbing fiber input to the flocculus. A standard anti-Hebbian learning rule was used to decorrelate the two. Simulations of the linearized problem showed the method to be effective and robust for plant compensation. Decorrelation control is thus a candidate algorithm for the basic cerebellar microcircuit, indicating how it could achieve motor learning using only signals available to the system. Such learning might then enable the cerebellum to free up visual awareness, and also, by providing a sensory signal decorrelated from motor command, supply awareness with crucial information about the external world.