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Behavioral learning is mediated by cellular plasticity such as changes in the strength of synapses at specific sites in neural circuits. The theory of cerebellar motor learning1,2,3 relies on movement errors signaled by climbing-fiber inputs to cause long-term depression of synapses from parallel fibers to Purkinje cells4,5. Yet, a recent review6 has called into question the widely-held view that the climbing fiber input is an “all-or-none” event. In anesthetized animals, there is wide variation in the duration of the complex-spike (CS) caused in Purkinje cells by a climbing fiber input7. Further, the duration of electrically-controlled bursts in climbing fibers grades the amount of plasticity in Purkinje cells8,9. The duration of bursts depends on the “state” of the inferior olive and therefore could be correlated across climbing fibers8,10. Here, we provide a potential functional context for these mechanisms during motor learning in behaving monkeys. The magnitudes of both plasticity and motor learning depend on the duration of the CS responses. Further, the duration of CS responses appears to be a meaningful signal that is correlated across the Purkinje cell population during motor learning. We suggest that during learning, longer bursts in climbing fibers lead to longer duration CS responses in Purkinje cells, more calcium entry into Purkinje cells, larger synaptic depression, and stronger learning. The same graded impact of instructive signals for plasticity and learning could occur throughout the nervous system.

Learning comprises multiple components that probably involve cellular and synaptic plasticity at multiple sites. Different neural sites may play their largest roles at different times during behavioral learning. We have used motor learning in smooth pursuit eye movements of monkeys to determine how and when different components of learning occur in a known cerebellar circuit. The earliest learning occurs when one climbing-fiber response to a learning instruction causes simple-spike firing rate of Purkinje cells in the floccular complex of the cerebellum to be depressed transiently at the time of the instruction on the next trial. Trial-over-trial depression and the associated learning in eye movement are forgotten in Ͻ6 s, but facilitate long-term behavioral learning over a time scale of ϳ5 min. During 100 repetitions of a learning instruction, simple-spike firing rate becomes progressively depressed in Purkinje cells that receive climbingfiber inputs from the instruction. In Purkinje cells that prefer the opposite direction of pursuit and therefore do not receive climbing-fiber inputs related to the instruction, simple-spike responses undergo potentiation, but more weakly and more slowly. Analysis of the relationship between the learned changes in simple-spike firing and learning in eye velocity suggests an orderly progression of plasticity: first on Purkinje cells with complex-spike (CS) responses to the instruction, later on Purkinje cells with CS responses to the opposite direction of instruction, and last in sites outside the cerebellar cortex. Climbing-fiber inputs appear to play a fast and primary, but nonexclusive, role in pursuit learning.

An efficient and general synthesis of hexahydropyrimidopyrimidinediones has been developed employing a low melting L‐(+)‐tartaric acid‐dimethylurea mixture as reaction medium. The melt acts at the same time as solvent, catalyst and reactant. Functionalized hexahydropyrimidopyrimidinediones are obtained in good to excellent yields after simple work‐up.

We commonly think of motor learning as a gradual process that makes small, adaptive steps in a consistent direction. We now report evidence that learning in pursuit eye movements could start with large, transient short-term alterations that stoke a more gradual long-term process. Monkeys tracked a target that started moving horizontally or vertically. After 250 ms of motion had produced a preinstruction eye velocity close to target velocity, an orthogonal component of target motion created an instructive change in target direction that was randomly in one of the two directions along the orthogonal axis. The preinstruction eye velocity in each trial expressed single-trial learning as a bias toward the direction of the instruction in the prior trial. The single-trial learning was forgotten within 4 to 10 s. Two observations implied that single-trial learning was not simply cognitive anticipation. First, the magnitude of the trial-over-trial change in eye velocity depended on the ongoing eye velocity at the time of the instruction in the prior trial. Single-trial learning was negligible if the prior trial had provided a well-timed cue without evoking any preinstruction eye velocity. Second, regular alternation of the direction of the instructive target motion caused reactive rather than anticipatory trial-over-trial changes in eye velocity. Humans showed very different responses that appeared to be based on cognitive anticipation rather than learning. We suggest that single-trial learning results from a low-level learning mechanism and may be a necessary prerequisite for longer-term modifications that are more permanent.

A saccadic eye movement causes a variety of transient perceptual sequelae that might be the results of corollary discharge. Here we describe the neural circuits for saccadic corollary discharge that modulates activity throughout the pigeon visual system. Saccades in pigeons caused inhibition that was mediated by corollary discharge followed by enhancement of firing activity in the telencephalic hyperpallium, visual thalamus and pretectal nucleus lentiformis mesencephali (nLM) with opposite responses in the accessory optic nucleus (nBOR). Inactivation of thalamic neurons eliminated saccadic responses in telencephalic neurons, and inactivation of both the nLM and the nBOR abolished saccadic responses in thalamic neurons. Saccade-related omnipause neurons in the brainstem raphe complex inhibited the nBOR and excited the nLM, whereas inactivation of raphe neurons eliminated saccadic responses in both optokinetic and thalamic neurons. It seems that saccadic responses in telencephalic neurons are generated by corollary discharge signals from brainstem neurons that are transmitted through optokinetic and thalamic neurons. These signals might have important roles in visual perception.

Motor learning occurs through interactions between the cerebellar circuit and cellular plasticity at different sites. Previous work has established plasticity in brain slices and suggested plausible sites of behavioral learning. We now reveal what actually happens in the cerebellum during short-term learning. We monitor the expression of plasticity in the simple-spike firing of cerebellar Purkinje cells during trial-over-trial learning in smooth pursuit eye movements of monkeys. Our findings imply that: 1) a single complex-spike response driven by one instruction for learning causes short-term plasticity in a Purkinje cell’s mossy fiber/parallel-fiber input pathways; 2) complex-spike responses and simple-spike firing rate are correlated across the Purkinje cell population; and 3) simple-spike firing rate at the time of an instruction for learning modulates the probability of a complex-spike response, possibly through a disynaptic feedback pathway to the inferior olive. These mechanisms may participate in long-term motor learning.DOI: http://dx.doi.org/10.7554/eLife.01574.001

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