Systems biology perspectives on cerebellar long-term depression

50 Years Since the Marr, Ito, and Albus Models of the Cerebellum

Fifty years have passed since David Marr, Masao Ito, and James Albus proposed seminal models of cerebellar functions. These models share the essential concept that parallel-fiber-Purkinje-cell synapses undergo plastic changes, guided by climbing-fiber activities during sensorimotor learning. However, they differ in several important respects, including holistic versus complementary roles of the cerebellum, pattern recognition versus control as computational objectives, potentiation versus depression of synaptic plasticity, teaching signals versus error signals transmitted by climbing-fibers, sparse expansion coding by granule cells, and cerebellar internal models. In this review, we evaluate different features of the three models based on recent computational and experimental studies. While acknowledging that the three models have greatly advanced our understanding of cerebellar control mechanisms in eye movements and classical conditioning, we propose a new direction for computational frameworks of the cerebellum, that is, hierarchical reinforcement learning with multiple internal models.

Realization of Direction Selective Motor Learning in the Artificial Cerebellum: Simulation on the Vestibuloocular Reflex Adaptation

The vestibule-ocular reflex (VOR) has been one of the most popular model systems to investigate the role of the cerebellum in adaptive motor control. VOR motor learning can be experimentally induced by continuous application of combination of head rotating stimulus and optokinetic stimulus. For instance, in phase application of those stimuli decreases VOR gain defined by eye velocity of VOR in the dark divided by head velocity, while out of phase of those increases VOR gain. It has been known that VOR gain is modifiable context-dependently. Namely, VOR gains for leftward and rightward head rotations can be respectively increased and decreased simultaneously. The cerebellar signal processing underlying the context dependent VOR motor learning, however, is not fully uncovered. In the present study, we simulated direction selective VOR motor learning, using the artificial cerebellar neuronal network model that we developed to understand the origin of the cerebellar motor learning.

Challenges in Reproducibility, Replicability, and Comparability of Computational Models and Tools for Neuronal and Glial Networks, Cells, and Subcellular Structures

The possibility to replicate and reproduce published research results is one of the biggest challenges in all areas of science. In computational neuroscience, there are thousands of models available. However, it is rarely possible to reimplement the models based on the information in the original publication, let alone rerun the models just because the model implementations have not been made publicly available. We evaluate and discuss the comparability of a versatile choice of simulation tools: tools for biochemical reactions and spiking neuronal networks, and relatively new tools for growth in cell cultures. The replicability and reproducibility issues are considered for computational models that are equally diverse, including the models for intracellular signal transduction of neurons and glial cells, in addition to single glial cells, neuron-glia interactions, and selected examples of spiking neuronal networks. We also address the comparability of the simulation results with one another to comprehend if the studied models can be used to answer similar research questions. In addition to presenting the challenges in reproducibility and replicability of published results in computational neuroscience, we highlight the need for developing recommendations and good practices for publishing simulation tools and computational models. Model validation and flexible model description must be an integral part of the tool used to simulate and develop computational models. Constant improvement on experimental techniques and recording protocols leads to increasing knowledge about the biophysical mechanisms in neural systems. This poses new challenges for computational neuroscience: extended or completely new computational methods and models may be required. Careful evaluation and categorization of the existing models and tools provide a foundation for these future needs, for constructing multiscale models or extending the models to incorporate additional or more detailed biophysical mechanisms. Improving the quality of publications in computational neuroscience, enabling progressive building of advanced computational models and tools, can be achieved only through adopting publishing standards which underline replicability and reproducibility of research results.

Computational Theory Underlying Acute Vestibulo-ocular Reflex Motor Learning with Cerebellar Long-Term Depression and Long-Term Potentiation

The vestibulo-ocular reflex (VOR) can be viewed as an adaptive control system that maintains compensatory eye movements during head motion. As the cerebellar flocculus is intimately involved in this adaptive motor control of the VOR, the VOR has been a popular model system for investigating cerebellar motor learning. Long-term depression (LTD) and long-term potentiation (LTP) at the parallel fiber-Purkinje cell synapses are considered to play major roles in cerebellar motor learning. A recent study using mutant mice demonstrated cerebellar motor learning with hampered LTD; the study concluded that the parallel fiber-Purkinje cell LTD is not essential. More recently, multiple forms of plasticity have been found in the cerebellum, and they are believed to contribute to cerebellar motor learning. However, it is still unclear how synaptic plasticity modifies the signal processing that underlies motor learning in the flocculus. A computational simulation suggested that the plasticity present in mossy fiber-granule cell synapses improves VOR-related sensory-motor information transferred into granule cells, whereas the plasticity in the molecular layer stores this information as a memory under guidance from climbing fiber teaching signals. Thus, motor learning and memory are thought to be induced mainly by LTD and LTP at parallel fiber-Purkinje cell synapses and by rebound potentiation at molecular interneuron-Purkinje cell synapses among the multiple forms of plasticity in the cerebellum. In this study, we focused on the LTD and LTP at parallel fiber-Purkinje cell synapses. Based on our simulation, we propose that acute VOR motor learning accomplishes by simultaneous enhancement of eye movement signals via LTP and suppression of vestibular signals via LTD to increase VOR gain (gain-up learning). To decrease VOR gain (gain-down learning), these two signals are modified in the opposite directions; namely, LTD suppresses eye movement signals, whereas LTP enhances vestibular signals.

Muscarinic acetylcholine receptor in cerebellar cortex participates in acetylcholine-mediated blood depressor response in rats

Our previous investigations have revealed that cerebellar cholinergic innervation is involved in cardiovascular regulation. This study was performed to examine the effects of the muscarinic cholinergic receptor (mAChR) in the cerebellar cortex on blood pressure (BP) modulation in rats. Acetylcholine (ACh, 100mM), nonselective mAChR agonist (oxotremorine M; Oxo-M, 10, 30 and 100mM) and 100mM ACh mixed with nonselective mAChR antagonist atropine (1, 3 and 10mM) were microinjected into the cerebellar cortex of anesthetized rats. Mean arterial pressure (MAP), maximal decreased MAP (MDMAP), and reaction time (duration required for BP to return to basal values) were measured and analyzed. The results showed that Oxo-M dose-dependently decreased MAP, increased MDMAP, and prolonged reaction time, which displayed a homodromous effect of ACh-mediated blood depressor response; meanwhile, atropine concentration-dependently blocked the effect of ACh on the BP regulation. In conclusion, the present study showed for the first time that mAChRs in cerebellar cortex could modulate somatic BP by participation in ACh-mediated depressor response.

Computational neurobiology is a useful tool in translational neurology: the example of ataxia

Hereditary ataxia, or motor incoordination, affects approximately 150,000 Americans and hundreds of thousands of individuals worldwide with onset from as early as mid-childhood. Affected individuals exhibit dysarthria, dysmetria, action tremor, and diadochokinesia. In this review, we consider an array of computational studies derived from experimental observations relevant to human neuropathology. A survey of related studies illustrates the impact of integrating clinical evidence with data from mouse models and computational simulations. Results from these studies may help explain findings in mice, and after extensive laboratory study, may ultimately be translated to ataxic individuals. This inquiry lays a foundation for using computation to understand neurobiochemical and electrophysiological pathophysiology of spinocerebellar ataxias and may contribute to development of therapeutics. The interdisciplinary analysis suggests that computational neurobiology can be an important tool for translational neurology.

Integration of modeling with experimental and clinical findings synthesizes and refines the central role of inositol 1,4,5-trisphosphate receptor 1 in spinocerebellar ataxia

A suite of models was developed to study the role of inositol 1,4,5-trisphosphate receptor 1 (IP3R1) in spinocerebellar ataxias (SCAs). Several SCAs are linked to reduced abundance of IP3R1 or to supranormal sensitivity of the receptor to activation by its ligand inositol 1,4,5-trisphosphate (IP3). Detailed multidimensional models have been created to simulate biochemical calcium signaling and membrane electrophysiology in cerebellar Purkinje neurons. In these models, IP3R1-mediated calcium release is allowed to interact with ion channel response on the cell membrane. Experimental findings in mice and clinical observations in humans provide data input for the models. The SCA modeling suite helps interpret experimental results and provides suggestions to guide experiments. The models predict IP3R1 supersensitivity in SCA1 and compensatory mechanisms in SCA1, SCA2, and SCA3. Simulations explain the impact of calcium buffer proteins. Results show that IP3R1-mediated calcium release activates voltage-gated calcium-activated potassium channels in the plasma membrane. The SCA modeling suite unifies observations from experiments in a number of SCAs. The cadre of simulations demonstrates the central role of IP3R1.

Developmental hypothyroxinemia caused by mild iodine deficiency leads to HFS-induced LTD in rat hippocampal CA1 region: involvement of AMPA receptor

Hypothyroidism induced by severe iodine deficiency (ID) during developmental period seriously damages the central nervous system function. In addition to developmental hypothyroidism induced by severe ID, developmental hypothyroxinemia induced by mild ID is potentially damaging for neurodevelopment and learning and memory in children. Wistar rats were treated with iodine-deficient diet or methimazole (MMZ) during pregnancy and lactation to induce developmental hypothyroxinemia or hypothyroidism in the present study. Pups were weaned on postnatal day (PN) 21 and used for electrophysiological recordings on PN80. It is generally accepted that long-term depression (LTD) is induced at low-frequency stimulation (LFS) in hippocampal CA1 region. Surprisingly, we observed developmental hypothyroxinemia as well as developmental hypothyroidism led to high-frequency stimulation (HFS)-induced LTD in hippocampal CA1 region. The abnormal HFS-induced LTD suggests not only developmental hypothyroidism but also developmental hypothyroxinemia impairs learning and memory. To explore the mechanisms responsible for the HFS-induced LTD, the phosphorylation status of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs) was investigated. The results showed that developmental hypothyroxinemia as well as developmental hypothyroidism decreased the phosphorylation of AMPAR subunit glutamate receptor 1 (GluR1) at serine 831 and serine 845 in hippocampal CA1 region. Neither developmental hypothyroxinemia nor developmental hypothyroidism altered the phosphorylation of AMPAR subunit glutamate receptor 2 (GluR2) at serine 880. Increased levels of protein phosphatase-1 (PP1) were also observed in hippocampal CA1 regions of pups subjected to developmental hypothyroxinemia or hypothyroidism. Taken together, our results suggest that the increased levels of PP1 caused by developmental hypothyroxinemia or hypothyroidism may account for the dephosphorylation of GluR1 at serine 831 and serine 845, which may contribute to HFS-induced LTD in hippocampal CA1 region.

Acute and chronic effects of ethanol on learning-related synaptic plasticity

Alcoholism is associated with acute and long-term cognitive dysfunction including memory impairment, resulting in substantial disability and cost to society. Thus, understanding how ethanol impairs cognition is essential for developing treatment strategies to dampen its adverse impact. Memory processing is thought to involve persistent, use-dependent changes in synaptic transmission, and ethanol alters the activity of multiple signaling molecules involved in synaptic processing, including modulation of the glutamate and gamma-aminobutyric acid (GABA) transmitter systems that mediate most fast excitatory and inhibitory transmission in the brain. Effects on glutamate and GABA receptors contribute to ethanol-induced changes in long-term potentiation (LTP) and long-term depression (LTD), forms of synaptic plasticity thought to underlie memory acquisition. In this paper, we review the effects of ethanol on learning-related forms of synaptic plasticity with emphasis on changes observed in the hippocampus, a brain region that is critical for encoding contextual and episodic memories. We also include studies in other brain regions as they pertain to altered cognitive and mental function. Comparison of effects in the hippocampus to other brain regions is instructive for understanding the complexities of ethanol's acute and long-term pharmacological consequences.

Nitric oxide in the nervous system: biochemical, developmental, and neurobiological aspects

Nitric oxide (NO) is a very reactive molecule, and its short half-life would make it virtually invisible until its discovery. NO activates soluble guanylyl cyclase (sGC), increasing 3',5'-cyclic guanosine monophosphate levels to activate PKGs. Although NO triggers several phosphorylation cascades due to its ability to react with Fe II in heme-containing proteins such as sGC, it also promotes a selective posttranslational modification in cysteine residues by S-nitrosylation, impacting on protein function, stability, and allocation. In the central nervous system (CNS), NO synthesis usually requires a functional coupling of nitric oxide synthase I (NOS I) and proteins such as NMDA receptors or carboxyl-terminal PDZ ligand of NOS (CAPON), which is critical for specificity and triggering of selected pathways. NO also modulates CREB (cAMP-responsive element-binding protein), ERK, AKT, and Src, with important implications for nerve cell survival and differentiation. Differences in the regulation of neuronal death or survival by NO may be explained by several mechanisms involving localization of NOS isoforms, amount of NO being produced or protein sets being modulated. A number of studies show that NO regulates neurotransmitter release and different aspects of synaptic dynamics, such as differentiation of synaptic specializations, microtubule dynamics, architecture of synaptic protein organization, and modulation of synaptic efficacy. NO has also been associated with synaptogenesis or synapse elimination, and it is required for long-term synaptic modifications taking place in axons or dendrites. In spite of tremendous advances in the knowledge of NO biological effects, a full description of its role in the CNS is far from being completely elucidated.

A new look at cytoskeletal NOS-1 and β-dystroglycan changes in developing muscle and brain in control and mdx dystrophic mice

BACKGROUND

Loss of dystrophin profoundly affects muscle function and cognition. Changes in the dystrophin-glycoprotein complex (DGC) including disruption of nitric oxide synthase (NOS-1) may result from loss of dystrophin or secondarily after muscle damage. Disruptions in NOS-1 and beta-dystroglycan (bDG) were examined in developing diaphragm, quadriceps, and two brain regions between control and mdx mice at embryonic day E18 and postnatal days P1, P10, and P28. Age-dependent differential muscle loading allowed us to test the hypothesis that DGC changes are dependent on muscle use.

RESULTS

Muscle development, including loss of central nucleation and the localization of NOS-1 and bDG, was earlier in diaphragm than quadriceps; these features were differentially disrupted in dystrophic muscles. The NOS-1/bDG ratio, an index of DGC stability, was higher in dystrophic diaphragm (P10-P28) and quadriceps (P28) than controls. There were also distinct regional differences in NOS-1 and bDG in brain tissues with age and strain. NOS-1 increased with age in control forebrain and cerebellum, and in mdx cerebellum; NOS-1 and bDG were higher in control than mdx mouse forebrain.

CONCLUSIONS

Important developmental changes in structure and muscle DGC preceded the hallmarks of dystrophy, and are consistent with the impact of muscle-specific differential loading during maturation.

Comparison of models for IP3 receptor kinetics using stochastic simulations

Inositol 1,4,5-trisphosphate receptor (IP₃R) is a ubiquitous intracellular calcium (Ca²⁺) channel which has a major role in controlling Ca²⁺ levels in neurons. A variety of computational models have been developed to describe the kinetic function of IP₃R under different conditions. In the field of computational neuroscience, it is of great interest to apply the existing models of IP₃R when modeling local Ca²⁺ transients in dendrites or overall Ca²⁺ dynamics in large neuronal models. The goal of this study was to evaluate existing IP₃R models, based on electrophysiological data. This was done in order to be able to suggest suitable models for neuronal modeling. Altogether four models (Othmer and Tang, 1993; Dawson etal., 2003; Fraiman and Dawson, 2004; Doi etal., 2005) were selected for a more detailed comparison. The selection was based on the computational efficiency of the models and the type of experimental data that was used in developing the model. The kinetics of all four models were simulated by stochastic means, using the simulation software STEPS, which implements the Gillespie stochastic simulation algorithm. The results show major differences in the statistical properties of model functionality. Of the four compared models, the one by Fraiman and Dawson (2004) proved most satisfactory in producing the specific features of experimental findings reported in literature. To our knowledge, the present study is the first detailed evaluation of IP₃R models using stochastic simulation methods, thus providing an important setting for constructing a new, realistic model of IP₃R channel kinetics for compartmental modeling of neuronal functions. We conclude that the kinetics of IP₃R with different concentrations of Ca²⁺ and IP₃ should be more carefully addressed when new models for IP₃R are developed.

D-cycloserine facilitates procedural learning but not declarative learning in healthy humans: a randomized controlled trial of the effect of D-cycloserine and valproic acid on overnight properties in the performance of non-emotional memory tasks

Although D-cycloserine (DCS), a partial agonist of the N-methyl-d-aspartate (NMDA) receptor, and valproic acid (VPA), a histone deacetylase inhibitor, have been investigated for their roles in the facilitation of emotional learning, the effects on non-emotional declarative and procedural learning have not been clarified. We performed a randomized, blind, placebo-controlled, 4-arm clinical trial to determine the effects of DCS and VPA on the overnight properties of declarative and procedural learning in 60 healthy adults. Subjects were orally administrated a placebo, 100 mg DCS, 400 mg VPA, or a combination of 100 mg DCS and 400 mg VPA before they performed declarative and procedural learning tasks. Subjects then had their performance retested the following day. We observed that DCS facilitated procedural but not declarative learning and that VPA did not contribute to learning. Surprisingly, however, VPA attenuated the enhancement effect of DCS when coadministered with it. These results suggest that DCS acts as an enhancer of hippocampus-independent learning and that VPA may have an extinguishing pharmacological effect on excitatory post-synaptic action potentials that NMDA receptors regulate within procedural learning.

Cerebellar plasticity and the automation of first-order rules

Theories of corticocerebellar function propose roles for the cerebellum in automating motor control, a process thought to depend on plasticity in cerebellar circuits that exchange information with the motor cortex. Little is known, however, about automating behaviors beyond the motor domain. The present study tested the hypothesis that cerebellar plasticity also subserves the development of automaticity in behavior based on low-order rules. Human subjects were required to learn two sets of first-order rules in which visual stimuli of different shapes each arbitrarily instructed a particular finger movement. We used event-related functional magnetic resonance imaging to scan subjects while these response rules became increasingly automatic with practice, as assessed with a dual-task procedure. We found that the amplitude of the blood oxygenation level-dependent signal gradually decreased as a function of practice, as responses became increasingly automatic, and that this effect was greater for a set of rules that became automatic rapidly compared with a second set, which became automatic more slowly. These trial-by-trial activity changes occurred in Crus I of cerebellar cortical lobule HVIIA, in which neurons exchange information with the prefrontal cortex rather than the motor cortex. Activity in Crus I was time locked specifically to the processing of these rules, rather than to subsequent actions. The results support the hypothesis that decreases in cerebellar cortical activity underlie the automation of behavior, whether related to motor control and motor cortex or to response rules and prefrontal cortex.

The protein kinase Mζ network as a bistable switch to store neuronal memory

Background

Protein kinase Mζ (PKMζ), the brain-specific, atypical protein kinase C isoform, plays a key role in long-term maintenance of memory. This molecule is essential for long-term potentiation of the neuron and various modalities of learning such as spatial memory and fear conditioning. It is unknown, however, how PKMζ stores information for long periods of time despite molecular turnover.

Results

We hypothesized that PKMζ forms a bistable switch because it appears to constitute a positive feedback loop (PKMζ induces its local synthesis) part of which is ultrasensitive (PKMζ stimulates its synthesis through dual pathways). To examine this hypothesis, we modeled the biochemical network of PKMζ with realistic kinetic parameters. Bifurcation analyses of the model showed that the system maintains either the up state or the down state according to previous inputs. Furthermore, the model was able to reproduce a variety of previous experimental results regarding synaptic plasticity and learning, which suggested that it captures the essential mechanism for neuronal memory. We proposed in vitro and in vivo experiments that would critically examine the validity of the model and illuminate the pivotal role of PKMζ in synaptic plasticity and learning.

Conclusions

This study revealed bistability of the PKMζ network and supported its pivotal role in long-term storage of memory.

Postsynaptic signal transduction models for long-term potentiation and depression

More than a hundred biochemical species, activated by neurotransmitters binding to transmembrane receptors, are important in long-term potentiation (LTP) and long-term depression (LTD). To investigate which species and interactions are critical for synaptic plasticity, many computational postsynaptic signal transduction models have been developed. The models range from simple models with a single reversible reaction to detailed models with several hundred kinetic reactions. In this study, more than a hundred models are reviewed, and their features are compared and contrasted so that similarities and differences are more readily apparent. The models are classified according to the type of synaptic plasticity that is modeled (LTP or LTD) and whether they include diffusion or electrophysiological phenomena. Other characteristics that discriminate the models include the phase of synaptic plasticity modeled (induction, expression, or maintenance) and the simulation method used (deterministic or stochastic). We find that models are becoming increasingly sophisticated, by including stochastic properties, integrating with electrophysiological properties of entire neurons, or incorporating diffusion of signaling molecules. Simpler models continue to be developed because they are computationally efficient and allow theoretical analysis. The more complex models permit investigation of mechanisms underlying specific properties and experimental verification of model predictions. Nonetheless, it is difficult to fully comprehend the evolution of these models because (1) several models are not described in detail in the publications, (2) only a few models are provided in existing model databases, and (3) comparison to previous models is lacking. We conclude that the value of these models for understanding molecular mechanisms of synaptic plasticity is increasing and will be enhanced further with more complete descriptions and sharing of the published models.

Quantifying the effects of elastic collisions and non-covalent binding on glutamate receptor trafficking in the post-synaptic density

One mechanism of information storage in neurons is believed to be determined by the strength of synaptic contacts. The strength of an excitatory synapse is partially due to the concentration of a particular type of ionotropic glutamate receptor (AMPAR) in the post-synaptic density (PSD). AMPAR concentration in the PSD has to be plastic, to allow the storage of new memories; but it also has to be stable to preserve important information. Although much is known about the molecular identity of synapses, the biophysical mechanisms by which AMPAR can enter, leave and remain in the synapse are unclear. We used Monte Carlo simulations to determine the influence of PSD structure and activity in maintaining homeostatic concentrations of AMPARs in the synapse. We found that, the high concentration and excluded volume caused by PSD molecules result in molecular crowding. Diffusion of AMPAR in the PSD under such conditions is anomalous. Anomalous diffusion of AMPAR results in retention of these receptors inside the PSD for periods ranging from minutes to several hours in the absence of strong binding of receptors to PSD molecules. Trapping of receptors in the PSD by crowding effects was very sensitive to the concentration of PSD molecules, showing a switch-like behavior for retention of receptors. Non-covalent binding of AMPAR to anchored PSD molecules allowed the synapse to become well-mixed, resulting in normal diffusion of AMPAR. Binding also allowed the exchange of receptors in and out of the PSD. We propose that molecular crowding is an important biophysical mechanism to maintain homeostatic synaptic concentrations of AMPARs in the PSD without the need of energetically expensive biochemical reactions. In this context, binding of AMPAR with PSD molecules could collaborate with crowding to maintain synaptic homeostasis but could also allow synaptic plasticity by increasing the exchange of these receptors with the surrounding extra-synaptic membrane.

One of the most accepted theories of information storage in neurons is that it is partially localized in the strength of synaptic contacts. Evidence suggests that at the cellular level, in combination with other cellular mechanisms, this is implemented by increasing or decreasing the concentration of a particular type of membrane molecules. Two opposing mechanisms have to coexist in synapses to allow them to store information. On one hand, synapses have to be flexible, to allow the storage of new memories. On the other hand, synapses have to be stable to preserve previously learned information. Although much is known about the molecular identity of synapses, the biophysical mechanisms by which molecules can enter, leave and remain in the synapse are unclear. Our modeling work uses fundamental biophysical principles to quantify the effects of molecular collisions and biochemical reactions. Our results show that molecular collisions alone, between the diffusing proteins with anchored molecules in the synapse, can replicate known experimental results. Molecular collision in combination with biochemical binding can be fundamental biophysical principles used by synapses for the formation and preservation of memories.

Past, present and future therapeutics for cerebellar ataxias

Cerebellar ataxias are a group of disabling neurological disorders. Patients exhibit a cerebellar syndrome and can also present with extra-cerebellar deficits, namely pigmentary retinopathy, extrapyramidal movement disorders, pyramidal signs, cortical symptoms (seizures, cognitive impairment/behavioural symptoms), and peripheral neuropathy. Recently, deficits in cognitive operations have been unraveled. Cerebellar ataxias are heterogeneous both at the phenotypic and genotypic point of view. Therapeutical trials performed during these last 4 decades have failed in most cases, in particular because drugs were not targeting a deleterious pathway, but were given to counteract putative defects in neurotransmission. The identification of the causative mutations of many hereditary ataxias, the development of relevant animal models and the recent identifications of the molecular mechanisms underlying ataxias are impacting on the development of new drugs. We provide an overview of the pharmacological treatments currently used in the clinical practice and we discuss the drugs under development.

Advances in visual perceptual learning and plasticity

Visual perceptual learning (VPL) is defined as a long-term improvement in performance on a visual task. In recent years, the idea that conscious effort is necessary for VPL to occur has been challenged by research suggesting the involvement of more implicit processing mechanisms, such as reinforcement-driven processing and consolidation. In addition, we have learnt much about the neural substrates of VPL and it has become evident that changes in visual areas and regions beyond the visual cortex can take place during VPL.

Functional roles of neuropeptides in cerebellar circuits

Whereas the cerebellum contains 22 different types of neuropeptides as presently known, their expression is generally weak and diffusely dispersed in cerebellar tissues, which often makes their functional significance doubtful. Nevertheless, our knowledge about certain neuropeptides has advanced to the extent that we can figure out their unique functional roles in cerebellar circuits. Throughout the cerebellum, CRF is contained in climbing fibers and its spontaneous release is required for the induction of cerebellar long-term depression (LTD), a cellular mechanism of motor learning. Corticotropin-releasing factor (CRF) is also expressed in the paraventricular nucleus-pituitary system and amygdala-lower brainstem system, both of which are involved in coping responses to stress. In view that motor learning requires stressful efforts for correcting errors in repeated trials, CRF in climbing fibers may imply that the olivocerebellar system is part of a large CRF-operated functional system that acts to cope with various stressors. Orexin, on the other hand, is contained in beaded fibers, which, originating from the hypothalamus, project to various brainstem nuclei and also to the cerebellum, exclusively the flocculus. Currently available evidence suggests that, in fight-or-flight situations, orexinergic neurons switch the state of cardiovascular control systems including the flocculus to secure blood supply to working muscles. Considerable knowledge has also been accumulated about angiotensin II, galanin, and cerebellin, but there is still a gap in defining their unique functional roles in cerebellar circuits.