Feedback inhibition underlies new computational functions of cerebellar interneurons.

The function of a feedback inhibitory circuit between cerebellar Purkinje cells and molecular layer interneurons (MLIs) was defined by combining optogenetics, neuronal activity recordings both in cerebellar slices and in vivo, and computational modeling. Purkinje cells inhibit a subset of MLIs in the inner third of the molecular layer. This inhibition is non-reciprocal, short-range (less than 200 µm) and is based on convergence of one to two Purkinje cells onto MLIs. During learning-related eyelid movements in vivo, the activity of a subset of MLIs progressively increases as Purkinje cell activity decreases, with Purkinje cells usually leading the MLIs. Computer simulations indicate that these relationships are best explained by the feedback circuit from Purkinje cells to MLIs and that this feedback circuit plays a central role in making cerebellar learning efficient.

Cerebellar implementation of movement sequences through feedback.

Most movements are not unitary, but are comprised of sequences. Although patients with cerebellar pathology display severe deficits in the execution and learning of sequences (Doyon et al., 1997; Shin and Ivry, 2003), most of our understanding of cerebellar mechanisms has come from analyses of single component movements. Eyelid conditioning is a cerebellar-mediated behavior that provides the ability to control and restrict inputs to the cerebellum through stimulation of mossy fibers. We utilized this advantage to test directly how the cerebellum can learn a sequence of inter-connected movement components in rabbits. We show that the feedback signals from one component are sufficient to serve as a cue for the next component in the sequence. In vivo recordings from Purkinje cells demonstrated that all components of the sequence were encoded similarly by cerebellar cortex. These results provide a simple yet general framework for how the cerebellum can use simple associate learning processes to chain together a sequence of appropriately timed responses.

Cerebellar Processing Common to Delay and Trace Eyelid Conditioning.

Results from previous lesion studies have been interpreted as evidence that the cerebellar cortex plays different roles for delay and trace conditioning of eyelid responses. However, the cerebellar cortex is organized by parasagittal stripes of Purkinje cells (PCs) that converge onto common deep nucleus neurons and receive common or related climbing fiber inputs. Based on this organization, we hypothesized that cerebellar tasks involving the same response system, such as delay and trace eyelid conditioning, would engage the same PCs and that the relationships between PC activity and expression of behavioral responses would be similar for both tasks. To test these hypotheses, we used tetrode recordings from eyelid PCs in rabbits during expression of delay- and trace-conditioned eyelid responses. Previous recording studies during delay conditioning described a strong relationship between eyelid PC activity and the kinematics of conditioned eyelid responses. The present results replicate these findings for delay conditioning and show that the same relationship exists during trace eyelid conditioning. During transitions from delay to trace responding, the relationship between eyelid PCs and behavioral responses was relatively stable. We found that an inverse firing rate model tuned to predict PC activity during one training paradigm could then predict equally well the PC activity during the other training paradigm. These results provide strong evidence that cerebellar cortex processing is similar for delay and trace eyelid conditioning and that the parasagittal organization of the cerebellum, not the conditioning paradigm, dictate which neurons are engaged to produce adaptively timed conditioned responses.SIGNIFICANCE STATEMENT A variety of evidence from eyelid conditioning and other cerebellar-dependent behaviors indicates that the cerebellar cortex is necessary for learning and proper timing of cerebellar learned responses. Debates exist about whether trace eyelid conditioning data show that fundamentally different mechanisms operate in the cerebellum during tasks when input from the forebrain is necessary for learning. We show here that learning-related changes in a specific population of Purkinje cells control the timing and amplitude of cerebellar responses the same way regardless of the inputs necessary to learn the task. Our results indicate the parasagittal organization of the cerebellar cortex, not the complexity of inputs to the cerebellum, determines which neurons are engaged in the learning and execution of cerebellar-mediated responses.

A cerebellar adaptation to uncertain inputs.

Noise and variability are inherent and unavoidable features of neural processing. Despite this physiological challenge, brain systems function well, suggesting the existence of adaptations that cope with noise. We report a novel adaptation that the cerebellum implements to maintain correct responses in the face of ambiguous inputs. We found that under these conditions, the cerebellum used a probabilistic binary choice: Although the probability of behavioral response gradually increased or decreased depending on the degree of similarity between current and trained inputs, the size of response remained constant. That way the cerebellum kept responses adaptive to trained input corrupted by noise while minimizing false responses to novel stimuli. Recordings and analysis of Purkinje cells activity showed that the binary choice is made in the cerebellar cortex. Results from large-scale simulation suggest that internal feedback from cerebellar nucleus back to cerebellar cortex plays a critical role in implementation of binary choice.

Links Between Single-Trial Changes and Learning Rate in Eyelid Conditioning.

The discovery of single-trial learning effects, where the presence or absence (or the number) of climbing fiber inputs produces measureable changes in Purkinje cell response and in behavior, represents a major breakthrough in cerebellar learning. Among other things, these observations provide strong links between climbing fiber-mediated plasticity and cerebellar learning. They also demonstrate that cerebellar learning is stochastic, with each instantiation of a movement producing a small increment or decrement in gain. The sum of the small changes give rise to the macroscopic properties of cerebellar learning. We used a relatively large data set from another example of cerebellar-dependent learning, classical conditioning of eyelid responses, to attempt a behavioral replication and extension of single-trial learning effects. As a normal part of training, stimulus-alone trials provide instances where the climbing fiber response would be omitted, similar to non-climbing-fiber trials (gain down) during smooth pursuit training. The consequences of the stimulus-alone trial on the amplitude and timing of the conditioned response on the following paired trials were examined. We find that the amplitude of the conditioned response during the trial after a stimulus-alone trial (no climbing fiber input) was measurably smaller than the amplitude on the previous trials, and this single-trial effect on amplitude is larger for longer interstimulus intervals. The magnitude of the single-trial effect parallels the rate of extinction at different interstimulus intervals supporting the previously observed link between single-trial effects and learning.

Relating cerebellar purkinje cell activity to the timing and amplitude of conditioned eyelid responses.

How Purkinje cell (PC) activity may be altered by learning is central to theories of the cerebellum. Pavlovian eyelid conditioning, because of how directly it engages the cerebellum, has helped reveal many aspects of cerebellar learning and the underlying mechanisms. Theories of cerebellar learning assert that climbing fiber inputs control plasticity at synapses onto PCs, and thus PCs control the expression of learned responses. We tested this assertion by recording 184 eyelid PCs and 240 non-eyelid PCs during the expression of conditioned eyelid responses (CRs) in well trained rabbits. By contrasting the responses of eyelid and non-eyelid PCs and by contrasting the responses of eyelid PCs under conditions that produce differently timed CRs, we test the hypothesis that learning-related changes in eyelid PCs contribute to the learning and adaptive timing of the CRs. We used a variety of analyses to test the quantitative relationships between eyelid PC responses and the kinematic properties of the eyelid CRs. We find that the timing of eyelid PC responses varies systematically with the timing of the behavioral CRs and that there are differences in the magnitude of eyelid PC responses between larger-CR, smaller-CR, and non-CR trials. However, eyelid PC activity does not encode any single kinematic property of the behavioral CRs at a fixed time lag, nor does it linearly encode CR amplitude. Even so, the results are consistent with the hypothesis that learning-dependent changes in PC activity contribute to the adaptively timed expression of conditioned eyelid responses.

Cerebellar mechanisms of learning and plasticity revealed by delay eyelid conditioning.

The analysis of well-defined behaviors that require the cerebellum has helped reveal many key mechanisms operating in the cerebellum to mediate learning and feed-forward prediction. These systems include eyelid conditioning, adaptation of the vestibuloocular reflex, smooth pursuit eye movements, and arm-reaching tasks. This review focuses specifically on the variety of findings that have come from the use of eyelid conditioning to study the cerebellum. Phenomena discussed include sites and rules for plasticity, temporal coding and mechanisms of timing, cerebellar control of climbing fibers and its role in bidirectional learning, extinction of conditioned responses, and the phenomenon of savings.