Cerebellar Modules and Their Role as Operational Cerebellar Processing Units

The compartmentalization of the cerebellum into modules is often used to discuss its function. What, exactly, can be considered a module, how do they operate, can they be subdivided and do they act individually or in concert are only some of the key questions discussed in this consensus paper. Experts studying cerebellar compartmentalization give their insights on the structure and function of cerebellar modules, with the aim of providing an up-to-date review of the extensive literature on this subject. Starting with an historical perspective indicating that the basis of the modular organization is formed by matching olivocorticonuclear connectivity, this is followed by consideration of anatomical and chemical modular boundaries, revealing a relation between anatomical, chemical, and physiological borders. In addition, the question is asked what the smallest operational unit of the cerebellum might be. Furthermore, it has become clear that chemical diversity of Purkinje cells also results in diversity of information processing between cerebellar modules. An additional important consideration is the relation between modular compartmentalization and the organization of the mossy fiber system, resulting in the concept of modular plasticity. Finally, examination of cerebellar output patterns suggesting cooperation between modules and recent work on modular aspects of emotional behavior are discussed. Despite the general consensus that the cerebellum has a modular organization, many questions remain. The authors hope that this joint review will inspire future cerebellar research so that we are better able to understand how this brain structure makes its vital contribution to behavior in its most general form

Function of Cerebellar Microcircuitry within a Closed-loop System during Control and Adaptation

The human motor control is both robust and stable, despite large delays and highly complex motor systems with an abundance of actuators, sensors and degrees of freedom. The cerebellum is thought help accomplish this by compensating for external loads and internal limitations and disturbances through adaptation, creating inverse models of the motor system dynamics. The cerebellum does also exhibit a generic relatively well described modular microcircuitry, making it a suitable neural circuitry to study. This thesis models a small part of the cerebellum, using detailed bio-physical models in combination with rate-based models, and uses the constructed network model to improve control of a planar double joint arm.The individual neuron models were calibrated using data from in vivo experiments. The response from the models when they were introduced to recorded primary afferent spike trains, originating from tactile stimulation, was used to validate their behaviour. Subsets of the complete network was also constructed to investigate possible functions of the granule cells and inhibitory connection patterns between interneurons within the molecular layer

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate realistic models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems

A Purkinje cell Timing Mechanism. On the Physical Basis of a Temporal Duration Memory.

The standard view of neural signaling is that a neuron can influence its target cell by exciting or inhibiting it. Learning is thought to involve strengthening or weakening synaptic connections. For most behaviors, the brain must learn to produce precisely timed activity patterns. Learned response timing is indispensable for a wide range of tasks and requires learning of interstimulus intervals (ISIs). The learning mechanism thought to accomplish this combines time-varying patterns of activity in the pre-synaptic neural network with changes in synaptic strength between the pre-synaptic neurons active at the end of the ISI and the post-synaptic neuron. Timing-dependent learning can be studied in eyeblink conditioning. If a neutral conditional stimulus is paired with an unconditional blink-eliciting stimulus, at an ISI of fixed duration, it acquires the ability to elicit a blink that peaks near the end of the ISI. Cerebellar Purkinje cells that control the blink acquire adaptively timed pauses in spontaneous firing, conditioned Purkinje cell responses, that interrupt their tonic inhibition of cerebellar nuclear cells and cause excitatory output that generates the overt blink. Most models assume the generation of a time code instantiated in varying patterns of activity in the presynaptic granule cells that represent the passage of time. However, we show here (paper I) that a cerebellar Purkinje cell can learn to respond to a specific input with adaptively timed pauses without such a temporally patterned input. Training Purkinje cells with direct stimulation of their presynaptic fibers, and pharmacological blocking of interneurons shows that the timing mechanism is intrinsic to the cell itself and not an emergent property of the network. That an individual neuron can learn temporal relationships suggests the existence of intracellular temporal duration memory. We demonstrate that this Purkinje cell memory is triggered by the metabotropic glutamate receptor 7 (paper II) and that the timed voltage response in large part is produced by the G-protein activated K+ channel family Kir3/GIRK (paper III). The implication is that a learned and adjustable timing of a metabotropic signaling cascade constitutes a physical memory of temporal duration. A theoretical model (paper IV) describes how this could be accomplished by a learning mechanism that selects among a finite number of regulatory proteins, those which bestow the intracellular signaling cascade with latencies to activation and deactivation that matches the ISI. The results presented in this thesis show that the traditional view of learning as a change in synaptic strength is insufficient. Finally, because Purkinje cells directly control the conditioned eyeblink we believe that, to our knowledge, this is the first time that a causal link can be shown between a learned and timing-dependent behavior and not only a single neuron’s memory, but also the specific activating receptor of said memory and the specific ion channel that puts it into effect

Monoamine influences in cerebellar memory consolidation

An association between climbing fibre and mossy fibre/parallel fibre inputs to the Purkinje cell is critical for cerebellar learning. In addition to these two major afferent systems, the cerebellum also receives a range of neuromodulatory inputs; most prominent are the noradrenergic and serotonergic afferents. Early theoretical and empirical accounts support a role for noradrenergic input as providing an essential third, consolidation signal in learning. In comparison to the glutamatergic afferents very little is known about the anatomy, physiology and behavioural aspects of the neuromodulatory afferents. The distributions by cell type of β1- and β2-adrenoceptors in the cerebellar cortex and nuclei and of α1-adrenoceptors in the cerebellar cortex, are shown for the first time. Earlier work demonstrated the necessity for β-adrenoceptor activation in consolidation of classical conditioning of the nictitating membrane response (NMR). Here, a dissociation of β1- and β2-adrenoceptor expression was shown. β1-adrenoceptors are restricted to Purkinje cells and β2-adrenoceptors are restricted to Bergmann glial cells. The cerebellar cortical distributions of noradrenergic and serotonergic afferents were compared. In cortical vermis, individual noradrenergic afferents were limited in their medial-lateral extent to less than 300 µm but were more extended in the rostral-caudal plane by up to 800 µm. Serotonergic afferents ran orthogonal to the noradrenergic afferents, with extents up to 900 µm in the medial-lateral plane but less than 200 µm in the rostral-caudal plane. Recent work has demonstrated a critical role for Purkinje cell mGlu7 activation in regulating the pause in Purkinje cell simple spike activity believed to be the cellular mechanism underpinning the conditioned eyelid blink/ NMR. Attempts were made to assess the specific function of the β1-adrenoceptor and mGlu7 in consolidation and performance of NMR conditioning, respectively. However, methodological constraints left these questions unresolved. It is concluded that the noradrenaline consolidation signal may target limited cortical territories and modulate Purkinje cells or Bergmann glial cells. In contrast, the serotonin signal is diffuse and targets multiple cortical regions simultaneously to fulfil a role in cerebellar processing distinct from that of noradrenergic signalling

Ontogenetic and comparative aspects of cerebellar and motor development

During the course of development the motor repertoire of animals and humans alike go through dramatic changes. New motor patterns arise; movements become coordinated, improve in precision and are at the same time continuously calibrated to the changing body dimensions. The cerebellum is critical for movement coordination and adaptation in adults. Also, interfering with cerebellar development during early life causes behavioural deficits suggesting an important role of the cerebellum in the formation of motor synergies. Hence, to understand the dramatic change in motor competence that characterizes postnatal development it may be of particular interest to study processes underlying the formation and shaping of the cerebellar neuronal networks. Unfortunately, little is known about how the cerebellum actually contributes to motor development. In order to elucidate the relationships between cerebellar ontogenetic changes and postnatal motor development a suitable animal model for multiple levels of analysis is a prerequisite. In this thesis, we therefore sought to develop and evaluate an experimental model that is suitable for combined behavioural, structural and systems level electrophysiological investigations of cerebellar development. For a number of reasons, the postnatal ferret seemed to be a suitable candidate. Although the ferret is commonly used as an experimental model in developmental studies on sensory systems, the development of its motor systems and motor behaviour had not been previously investigated. As a first step, we characterized the postnatal motor development in ferret kits in daily sessions from postnatal day (P)2 to P63. A battery of motor tests spanning the entire developmental period was used to assess locomotor activity and ability and the maturation of postural dynamic reflexes. Secondly, we characterized the morphological development of the ferret cerebellum. Overall cerebellar size, foliation and thickness of cortical layers were quantified and Purkinje cell morphology was characterized from P1 to P63. Thirdly, we investigated the zonal organization of climbing fibre input to the cerebella of ferret kits; a fundamental and general physiological feature of cerebellar function in the adult animal. These studies provide the first investigations of motor behavioural and cerebellar morphological development in the ferret. The electrophysiological data obtained represent a first important step towards the understanding of cerebellar physiological processes in the course of motor development. We conclude that the ferret in many aspects is a particularly suitable animal model for the study of cerebellar mechanisms underlying motor development. In a parallel approach, we assessed how timescales of motor and cerebellar morphological development can be translated between species with differently long developmental time periods, such as the ferret and rat. Linear regression analyses were performed on time points defining the corresponding levels of motor development and cerebellar maturation in ferrets and rats (rat data from Altman and Bayer, 1997). The derived time-conversion equations describing cerebellar morphological development and motor development in ferret and rat were highly congruent. To extend the comparative analysis to also include humans a model was formulated that takes into consideration comparative time courses of neurogenesis and cerebellar morphogenesis and relative timing of birth. Using behavioural data from rats and ferrets as input, the model predicts corresponding motor developmental dates that fall within 10% of actual mean values for the human population. Such astonishing predictive accuracy indicates that motor development in animals and man is governed by very similar principles and that these principles are successfully captured by our model

Adaptive Control of Arm Movement based on Cerebellar Model

This study is an attempt to take advantage of a cerebellar model to control a biomimetic arm. Aware that a variety of cerebellar models with different levels of details has been developed, we focused on a high-level model called MOSAIC. This model is thought to be able to describe the cerebellar functionality without getting into the details of the neural circuitry. To understand where this model exactly fits, we glanced over the biology of the cerebellum and a few alternative models. Certainly, the arm control loop is composed of other components. We reviewed those elements with emphasis on modeling for our simulation. Among these models, the arm and the muscle system received the most attention. The musculoskeletal model tested independently and by means of optimization techniques, a human-like control of arm through muscle activations achieved. We have discussed how MOSAIC can solve a control problem and what drawbacks it has. Consequently, toward making a practical use of MOSAIC model, several ideas developed and tested. In this process, we borrowed concepts and methods from the control theory. Specifically, known schemes of adaptive control of a manipulator, linearization and approximation were utilized. Our final experiment dealt with a modified/adjusted MOSAIC model to adaptively control the arm. We call this model ORF-MOSAIC (Organized by Receptive Fields MOdular Selection And Identification for Control). With as few as 16 modules, we were able to control the arm in a workspace of 30 x 30 cm. The system was able to adapt to an external field as well as handling new objects despite delays. The discussion section suggests that there are similarities between microzones in the cerebellum and the modules of this new model

Memory consolidation in the cerebellar cortex

Several forms of learning, including classical conditioning of the eyeblink, depend upon the cerebellum. In examining mechanisms of eyeblink conditioning in rabbits, reversible inactivations of the control circuitry have begun to dissociate aspects of cerebellar cortical and nuclear function in memory consolidation. It was previously shown that post-training cerebellar cortical, but not nuclear, inactivations with the GABA(A) agonist muscimol prevented consolidation but these findings left open the question as to how final memory storage was partitioned across cortical and nuclear levels. Memory consolidation might be essentially cortical and directly disturbed by actions of the muscimol, or it might be nuclear, and sensitive to the raised excitability of the nuclear neurons following the loss of cortical inhibition. To resolve this question, we simultaneously inactivated cerebellar cortical lobule HVI and the anterior interpositus nucleus of rabbits during the post-training period, so protecting the nuclei from disinhibitory effects of cortical inactivation. Consolidation was impaired by these simultaneous inactivations. Because direct application of muscimol to the nuclei alone has no impact upon consolidation, we can conclude that post-training, consolidation processes and memory storage for eyeblink conditioning have critical cerebellar cortical components. The findings are consistent with a recent model that suggests the distribution of learning-related plasticity across cortical and nuclear levels is task-dependent. There can be transfer to nuclear or brainstem levels for control of high-frequency responses but learning with lower frequency response components, such as in eyeblink conditioning, remains mainly dependent upon cortical memory storage