In one model of the cerebellar microcircuit, a sparse representation of time in the granule cell population

provides the excitatory drive for Purkinje cells. Different granule cells would provide inputs to Purkinje cells at different times during a movement so that visually-driven climbing fiber inputs could potentiate or depress the granule-Purkinje synapses that were active 100 ms prior to the arrival of the climbing fiber signal (Buonomano and Mauk, 1994). Thus, the cerebellum could act independently in learning motor timing, or inputs from the FEFSEM could contribute to the temporal sparseness of the granule cell population in a way that is enhanced by learning in the FEFSEM. Recent work also has highlighted the possibility that learning occurs on different time scales (Lee and Schweighofer, 2009, Ethier et al., 2008, Smith Doxorubicin mouse et al., 2006 and Yang and Lisberger, 2010) with the possibility of very rapid short-term

learning in the cerebellar cortex as a prelude to slower, longer-term changes in the FEFSEM. Neurophysiological studies of motor and perceptual learning reveal a common theme: changes are localized to neurons whose properties best capture the features of the training stimulus (Arce et al., 2010, Paz et al., 2003, Recanzone et al., 1993, Schoups et al., 2001 and Yang and Maunsell, 2004). In real life, the learning rule can be very complex. Thus, the dimensionality of the neural representation of movements limits the flexibility Selleck Screening Library of the motor system in terms of what can be learned quickly. For many years, it was commonly believed that the responses of motor

cortex neurons could be modeled by a time-invariant combination of limb kinematics and dynamics (Evarts, 1968, Georgopoulos et al., 1982 and Moran and Schwartz, 1999). Recently, examination of a broader population of neurons in primary motor cortex (M1), dorsal premotor cortex (PMd), and the FEFSEM has revealed considerable heterogeneity in movement-related neural responses (Hatsopoulos et al., 2007 and Churchland and Shenoy, 2007). Many neural response patterns are explained poorly by standard MTMR9 eye movement parameters such as acceleration, speed, and direction. We propose that the FEFSEM and other motor cortices are important for facilitating action selection. The FEFSEM encodes smooth pursuit movements flexibly along seemingly baroque but perhaps behaviorally relevant dimensions, such as time, so that error and reward signals can act selectively on a subregion within the movement space to drive rapid, precise motor learning. Two male rhesus monkeys (Macaca mulatta) aged 6 and 8 years, tracked smoothly moving targets in exchange for a water reward. Both monkeys had prior experience in experiments on pursuit, but neither had participated in learning studies.