CHAPTER

Questioning the Cerebellar Doctrine

3

Elisa Galliano*,1, Chris I. De Zeeuw*,{,2 *

Department of Neuroscience, Erasmus MC Rotterdam, Rotterdam, The Netherlands Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts & Sciences, Amsterdam, The Netherlands 2 Corresponding author: Tel.: þ31-010-7043299; Fax: þ31-010-7044734, e-mail address: [email protected]

{

Abstract The basic principles of cerebellar function were originally described by Flourens, Cajal, and Marr/Albus/Ito, and they constitute the pillars of what can be considered to be the classic cerebellar doctrine. In their concepts, the main cerebellar function is to control motor behavior, Purkinje cells are the only cortical neuron receiving and integrating inputs from climbing fiber and mossy–parallel fiber pathways, and plastic modification at the parallel fiber synapses onto Purkinje cells constitutes the substrate of motor learning. Yet, because of recent technical advances and new angles of investigation, all pillars of the cerebellar doctrine now face regular reexamination. In this review, after summarizing the classic concepts and recent disputes, we attempt to synthesize an integrated view and propose a revisited version of the cerebellar doctrine.

Keywords distributed synergistic plasticity, climbing fibers, mossy fibers, input convergence, motor behavior, motor learning, cognitive and emotional behavior, timing control

1 THE CEREBELLAR DOCTRINE AND ITS THREE PILLARS The cerebellum has always beguiled anatomists, initially because of its recognizable gross morphology, immediately visible by the naked eye, and later because of its unique, organized, and conserved cellular organization. Scholars such as Galen (second century) and Vesalius and Varolio (sixteenth century) provided detailed cerebellar macroanatomical descriptions. During the second half of the nineteenth 1

Current address: MRC Centre for Developmental Neurobiology, King’s College London, London, UK.

Progress in Brain Research, Volume 210, ISSN 0079-6123, http://dx.doi.org/10.1016/B978-0-444-63356-9.00003-0 © 2014 Elsevier B.V. All rights reserved.

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century, in the period that can be considered the beginning of modern anatomy and physiology, numerous scientists interested in the brain started investigations focusing on the cerebellum. While the phrenologist Gall localized the controller of sexuality in the cerebellum, the physiologists Flourens, Rolando, and Luciani provided the first solid experimental evidence for a role of the cerebellum in motor control (Glickstein et al., 2009); thus, until the second half of the nineteenth century, the teaching of these first physiologists constituted the first of the three pillars of what can be considered to be the classic cerebellar doctrine (from Latin doctrina “teaching, learning,” from doctor “teacher”). The other two essential elements of this body of principles were added during the following century after Golgi’s invention of the black reaction, a histological procedure that stains a random, small percentage of neurons, allowing the identification and description of single elements in the network (Mazzarello, 2009). Golgi himself and his most enthusiastic seconder Ramon y Cajal systematically analyzed the cerebellar cortex and defined its components. Cajal further postulated the existence of synapses and identified the basic connectivity patterns in the circuit including virtually all cerebellar projection neurons and interneurons. His analysis was so precise and detailed that for a hundred years it has been considered exhaustive and comprehensive, constituting the second pillar of the cerebellar doctrine (Ramon y Cajal, 1995). Finally, after the elucidation of overall function and network anatomy, the third pillar of the cerebellar doctrine was erected during the second half of the twentieth century and, based on Cajal’s connectivity studies, clarified the cellular mechanisms involved in synaptic transmission between neurons, and the ability of these connections to be plastically modified, a process that is believed to be the molecular substrate of learning and memory (Marr, 1969). One particular synapse in the circuit, the parallel fiber to Purkinje cell synapse, with its peculiar physiological properties and its ability to modify its strength, became central in the “motor learning theory” expounded by Albus and Ito more than 40 years ago (Albus, 1971; Ito, 1982; Marr, 1969). This harmonious and well-described body of principles (see Fig. 1 for a schematic representation) has been considered for many decades to be the correct foundation on which to build in order to unravel cerebellar function. In recent years, however, all three pillars of cerebellar doctrine have been repeatedly challenged. Glickstein et al. (2009) stated in their recent historical paper in the passage recalling Vesalius’ disagreement with Galeno’s view on cerebellar macroscopical anatomy: “[he] was one of the first in a long tradition in cerebellar research of questioning the worth of your predecessor’s contribution.” Indeed, the history of cerebellar studies reflects what Kuhn (1962) proposed, namely that science progresses often not in a harmonious and continuous accumulation of discoveries, but by contraposition of new and old models. A cerebellum-relevant example is the innovative synaptic view proposed by Cajal, which stood in fierce opposition to the established theory of neurons being anatomically conjunct in an extended cytoplasmic syncytium (for a detailed description of this controversy, see Mazzarello et al., 2006). Probably because it has been passionately studied for 300 years, the cerebellum indeed offers many examples of new ideas supplanting the established ones. These

2 The First Pillar: The Sole Cerebellar Function

FIGURE 1 The cerebellar doctrine: schematic representation of the three main pillars (and their asserters), which dominated cerebellar research during the last century.

bursts of debates have happened cyclically, after relatively long periods of general consensus (e.g., Flourens opposing the localizationism of Gall, or Cajal with his revolutionary synaptic views). After a couple of decades of relative quietness, we are now in the full swing of the latest controversial burst against the classic cerebellar doctrine, of which salient points have been previously summarized. Indeed, evidence is emerging that motor control is not the only global task of the cerebellum (Middleton and Strick, 1997; Schmahmann and Sherman, 1997), that the network connectivity with the two well-defined input pathways converging on one single neuronal type is more complex than assumed (Mathews et al., 2012; Szapiro and Barbour, 2007), and that cerebellar function can be explained only by considering the contribution of all elements of the network with all their plastic mechanisms (Gao et al., 2012). Following these global trends, this review tries to provide an overview of the main points of the classic cerebellar doctrine and the challenges posed to them.

2 THE FIRST PILLAR: THE SOLE CEREBELLAR FUNCTION IS TO CONTROL MOTOR BEHAVIOR One of the main features of the cerebellar network is its ability to modify ongoing behavior in response to incoming sensory information. Which behaviors are controlled by the cerebellum constitutes a long-standing debate that has lately converged into two main streams. The one initiated by Flourens, which states that the one and only cerebellar function is motor control, constitutes the central behavioral doctrine (Fig. 1) (Glickstein et al., 2009). The new challenging view, which has its roots in clinical studies of patients with cerebellar damage who show cognitive and/or

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emotional symptoms, proposes that the computational possibilities of the cerebellum go beyond motor coordination to encompass higher cognitive functions (Schmahmann and Sherman, 1997). Even though not yet fully proven at the anatomo-functional level in all species (Ramnani, 2006; Strick et al., 2009), this motor-cognitive postulate has gathered supporters quickly. Whereas the involvement of the cerebellum in cognitive and emotional functions is still under discussion, there is consensus on its pivotal role in controlling movements’ precision and timing in all vertebrates (De Zeeuw et al., 2011; Welsh and Llinas, 1997; Welsh et al., 1995). The motor control ranges from relatively simple tasks such as control of posture and muscle tone, to much more complicated ones such as multi-joint limb movements and acquisition of finely timed motor sequences. Standardized motor tests for laboratory rodents have been optimized and are commonly used to assess cerebellar function in genetically modified mice. Among those of particular interest are the basic locomotion test, in which mice are monitored while let free to explore an open field (Galliano et al., 2013c); the motor coordination test, in which mice have to balance on an accelerating rotating rod (Crawley, 2007); the eyeblink conditioning task, which is a form of cerebellum-dependent Pavlovian conditioning, in which mice have to learn to close their eyelid in response to a conditioned stimulus, such as an acoustic stimulus (Boele et al., 2010); and finally adaptation of compensatory eye movements, which has been extensively employed as a readout of both motor performance and motor learning (De Zeeuw et al., 2011; Gao et al., 2012). The latter paradigm is considered by many cerebellar scientists as an ideal paradigm, because of tractability for both input and output as well as the neuronal activity in between. As vertebrates progressively switched from relying mostly on chemical senses to relying on vision, the sensory and motor systems sustaining compensatory eye movements further evolved. Indeed, in order to ensure proper vision, the eyes must be moved rapidly in order to follow a moving target, and they should be able to counterbalance any body movement, which destabilizes the visual focus. These gaze-holding movements are automatic reflexes, called optokinetic responses (OKR—moving target) and vestibulo-ocular reflexes (VOR—moving body). Both reflex systems can be easily and accurately investigated in experimental animals by rotation of the animal itself in the dark (VOR) or by rotating a well-lighted random dotted pattern around the animal (OKR). By rotating the animal in the light, vestibular and optokinetic information are both available and eye movement responses are most accurately performed under these circumstances (visual-enhanced vestibulo-ocular reflex, VVOR). The additional characteristics that make them an excellent paradigm to study cerebellar-dependent behavior are their adaptability, both in terms of movement amplitude (gain of the eye movement) and timing (phase of the eye movement). Additionally, electrophysiological responses of Purkinje cells and interneurons can be measured during both baseline eye movement behavior and learning; in general, the simple spike (SS) and complex spike (CS) activities of Purkinje cells modulate reciprocally in response to natural, combined visual and vestibular stimulation (Badura et al., 2013). By changing the modulation amplitude and phase of these activities, both gain and phase of the eye movements can be modified (Gao et al., 2012).

2 The First Pillar: The Sole Cerebellar Function

Interestingly, the role of the cerebellum in motor behavior is not only evident from studies on the molecular layer (Seja et al., 2012; Wulff et al., 2009; see also below) but also from those on the granular layer. In a recent study, we employed a whole range of motor tasks in an attempt to link motor performance and motor learning to granule cell computation (Fig. 2) (Galliano et al., 2013b). In humans, seven of eight of all CNS neurons are cerebellar granule cells (Williams, 2000; Williams and Herrup, 1988). Why do we need so many? Are they all essential to perform fundamental motor tasks? While it has classically been proposed that this extreme granule cell abundance is essential to encode the wide range of information presented to the cerebellar cortex into an adaptable output that controls motor behavior (Chadderton et al., 2004; Ekerot and Jorntell, 2008; Rothman et al., 2009), this remained to be proven directly. We addressed this question by genetically silencing the majority of granule cells using Cre-lox technology knocking out P/Q-type voltage-gated calcium channels encoded by the Cacna1a gene (Galliano et al., 2013b). The advantage of this approach was that the basic cerebellar morphology was not compromised and that corollary deficits in other neurons were not directly induced. Although silencing 75% of the granule cells had no impact on motor performance and adaptation of simple motor tasks, a vast majority of functional granule cells turned out to be required for demanding forms of motor learning (Fig. 2) (Galliano et al., 2013b). These results are in line with a model proposed by Schweighofer predicting that a subset of granule cells is sufficient to ensure baseline motor performance, while the full computational power of the granular layer is essential to exploit the advantages of sparse coding in terms of memory storage capacity (Schweighofer et al., 2001). Considering this computational power and the remarkable granule cell count in humans (70 billion; Lange, 1975) together with the fact that this number is the result of an evolutionary trend of increase during vertebrate phylogeny (Herculano-Houzel, 2009), one cannot fail to appreciate how adaptation of complex movements and motor memory retention formed apparently an advantageous feature, which has been positively selected (Onuki et al., 2013). In trying to explain this evolutionary trend, anthropologists have put forward a hypothesis according to which in apes the increased cerebellar size and the consequent refined control of complex motor sequences for foraging and tool-making provided the foundation of gestural communication and later verbal communication (Barton, 2012). Indeed, there is an emerging body of evidence supporting the involvement of the cerebellum in nonmotor, cognitive, and emotional functions, particularly in higher mammals. The first evidence dates back to the 1980s, when reciprocal connections between the cerebellum and the autonomic nervous system were identified (Dietrichs, 1984). In the 1990s, the neurologist Schmahmann coined the term cerebellar cognitive affective syndrome (or dysmetria of thought) to describe a set of behavioral abnormalities found in cerebellar patients (Schmahmann and Sherman, 1997). These symptoms include problems in language production, diminished attention, personality change with preponderance of disinhibited behaviors, impairments in executive functions, perseveration, and impairments in spatial memory. The basic idea underlying this novel theory, which challenges the original postulate, is that as motor functions are controlled and optimized by specific cerebrocerebellar loops, so

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2 The First Pillar: The Sole Cerebellar Function

may cognitive and emotional functions be. These functions are proposed to be regulated by modules connecting the phylogenetically newer parts of the cerebellum (i.e., hemispheres and dentate nucleus) via nonmotor thalamic nuclei to the prefrontal cortex (Schmahmann, 2010; Schraa-Tam et al., 2012; Voogd et al., 2012). The cerebellum assumes therefore the role of a parallel processor, which lends to the cerebral cortex its computational power in comparing and regulating precise timing, independently of the ultimate function (D’Angelo and Casali, 2012; De Zeeuw et al., 2011). Vertebrate comparative studies on evolution of brain areas and increase in the number of neurons highlight how the cerebral and cerebellar cortex have been enlarging in parallel up to reaching their (so far) maximum point during primates phylogeny (Herculano-Houzel, 2009; Williams and Herrup, 1988). However, the size and neuron density of the two structures by themselves are not sufficient to postulate reciprocal communication and complementary processing: the parts of the two cortices that are involved in cognitive and emotional regulation have to be reciprocally connected, just as they are in reciprocal modules involved the motor loops (Shmuelof and Krakauer, 2011). Up to date, clear anatomical connections between cerebellar nuclei and nonmotor cortical area have been partially but consistently identified in primates (Ramnani, 2006; Strick et al., 2009; Timmann et al., 2010). Since rodents, and particularly mice, are the preferred animal models for performing extensive behavioral research, a systematic study of the cerebrocerebellar connections is due. In the meantime, genetically modified mice with localized lesions in subsets of cerebellar neurons have been subjected in different laboratories to behavioral tasks aimed at investigating the same functions that have been observed to be impaired in cerebellar patients (Baudouin et al., 2012; Lalonde and Strazielle, 2003; Rochefort et al., 2013; Sacchetti et al., 2009; Tsai et al., 2012). Such functional studies of mice in the cognitive domain include spatial learning (tested with the standard Morris water maze test, in which mice are placed in a pool and have to use environmental clues

FIGURE 2 Motor performance and motor learning in a6-Cacna1a KO mice, which lack P/Q-type voltage-gated calcium channels in 70–80% of cerebellar granule cells thus rendering such majority unable to release glutamate and to evoke long-term plasticity at their synapses with PCs (while intrinsic plasticity remains intact). a6-Cacna1a KO mice’s motor performance is unaffected in terms of locomotion measured in an open field (A), balance on the accelerating rotarod (B), and baseline optokinetic reflex [OKR, (C)] and vestibulo-ocular reflex [VOR, (D)]. a6-Cacna1a KO animals can perform simple motor learning tests such as VOR gain decrease, but when tested 24 h after the training session, they clearly show that they cannot consolidate the newly formed memory (E). Moreover, a6-Cacna1a KO mice are unable to both learn and consolidate more demanding forms of motor learning, such as VOR phase reversal over four consecutive days (F). Figure adapted from Galliano et al. (2013b).

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FIGURE 3 Cerebellar contribution to cognitive and emotional behavior in mice with impaired motor learning but normal motor performance. (A) Four nonataxic cerebellar cell-specific knock-out and transgenic mouse lines, namely a6-Cacna1a KO with 20–30% of functional PF–PC synapses (Galliano et al., 2013b), L7-g2 KO with PCs receiving no inhibitory inputs

2 The First Pillar: The Sole Cerebellar Function

to learn to locate a submerged platform), decision making (tested by analyzing the strategy used to explore the water maze and locate the platform), and behavioral flexibility (tested by investigating the ability to extinguish acquired behaviors). Emotional processing can be tested in rodents by subjecting them to fear conditioning paradigms, in which the unconditioned stimulus is either the environment or an acoustic cue. To shed light on the debate of the role of the cerebellum in nonmotor behaviors, we performed extensive series of experiments in which four nonataxic mouse lines, each bearing a different genetic lesion specifically affecting Purkinje cell processing, were subjected to a battery of cognitive and emotional tests including Morris water maze, social recognition tests, and various forms of fear conditioning (for a schematic representation of mouse lines and tests, see Fig. 3) (Galliano et al., 2013c). Seemingly in contrast with the growing body of evidence collected in primates advocating a role for the cerebellum in cognitive and emotional processes, none of the four mouse lines showed any phenotype in any of these tasks, which were all testing cognitive and/or emotional behaviors, but all without stringent timing constraints. However, when we subjected some of the same mouse mutants to a whiskerbased cognitive decision task in which the timing is critical, we found a prominent phenotype in that fewer mice learned the task and that those that learned the task did so at a slower rate with an increased level of noise in the behavior (Rahmati et al., 2014). Thus, the role of the cerebellum in cognitive functions may be particularly essential when timing is critical. Moreover, when comparing cerebellar cognitive functions in mice and primates, one should not underestimate the potential impact of evolution on the ability of the cerebellum to enlarge its impact on cerebral cortical processing. As discussed above, both cerebellar size and neuronal numbers have increased dramatically during vertebrate phylogeny, and so did the reciprocal connectivity with the cerebral cortex

(Wulff et al., 2009), L7-PP2B KO with no PF–PC long-term potentiation (Schonewille et al., 2010), and L7-PKCi TG with no PF–PC long-term depression (De Zeeuw et al., 1998), were selected to undergo cognitive and emotional testing. (B) To test social behavior, the animal’s interaction with a novel mouse or an empty cage was taken as a measure of sociability, while the interaction with the just-explored mouse versus a new one indicated social recognition. (C) Spatial learning was tested with the standard Morris water maze paradigm. For 7 consecutive days, the animals were given two trials per day, during each of which the mouse was first placed on the hidden submerged platform, then placed in the water at a pseudo-random start position, and was given a maximum of 60 s to find the platform. On days 6 and 8, a probe trial was given to test spatial learning: mice were placed on the platform for 30 s, after which the platform was removed from the pool and the mice were placed in the pool on the side opposite to the previous platform position. The mice were then allowed to search for the platform for 60 s. After 2 weeks, another probe trial was performed to test long-term memory. (D) Emotional behavior was assessed with contextual and cued fear conditioning tests, in which the animals had to learn to associate either the context (cage A) or a neutral cue (tone) with a footshock.

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(Herculano-Houzel, 2009; Shmuelof and Krakauer, 2011). Thus, it might be possible that while this increased cerebellar computational power in primates has been beneficial for the advent of nonverbal communication and consequent involvement of corticocerebellar loops in cognitive functions, the murine cerebellum is relatively low on the evolutionary ladder and as a consequence less strongly involved in cognitive and/or emotional control.

3 THE SECOND PILLAR: INPUTS CONVERGE ONLY AT THE LEVEL OF PURKINJE CELLS The cerebellar cortex receives numerous sensory inputs, and it appears to be designed to process large amounts of information about the state of body parts with respect to each other, to the surrounding, and to ongoing activity in other parts of the brain. This information is processed through a diversified interneuronal circuit (Fig. 4). Structurally, the cerebellar cortex is a three-layered folded sheet of gray matter, containing a single type of efferent neuron, the inhibitory Purkinje cells,

FIGURE 4 Schematic representation of the cerebellar cortical circuit, with highlighted the most recent discoveries. Climbing fibers contact molecular layer interneurons (via spillover mechanisms), and while they do not seem to make direct synapses with Golgi cells, their activation has been shown in vivo to have an inhibitory effect on them (see main text). Molecular layer interneurons do not appear to be synaptically connected with Golgi cells, which however form both electrical and chemical synapses among themselves.

3 The Second Pillar: Inputs Converge Only at the Level of Purkinje Cells

and five main classes of interneurons, three of which are inhibitory, the stellate cells, basket cells, and Golgi cells, and two of which are excitatory, the granule cells and unipolar brush cells. There are two main afferents to the cerebellar cortex, both of which are excitatory: mossy fibers and climbing fibers. Anatomically and chemically speaking, mossy fibers form a heterogeneous population. They originate from precerebellar nuclei that project exclusively or nearly exclusively to the cerebellum (i.e., pontine nuclei) and from a multitude of regions that send collaterals to the cerebellum in addition to having major projections outside the cerebellum (Voogd, 2012; Voogd et al., 2012). In contrast, climbing fibers constitute a homogenous population of glutamatergic axons arising from inferior olivary neurons. Olivocortical projections are strictly organized in a modular fashion, with neighboring neurons in the inferior olive projecting to a specific sagittal band in the cerebellar cortex (De Zeeuw et al., 2011; Ruigrok, 2011; Voogd, 2011). Both types of input fibers pass through the granular layer, but whereas mossy fibers form excitatory glutamatergic synapses on all granular layer neurons via specific swellings called rosettes and terminate their course at this stage, climbing fibers proceed toward the upper layers (the Purkinje cell and molecular layers) without making synaptic contacts with any type of neuron besides Purkinje cells (Palay and Chan-Palay, 1974). According to the original descriptions by Cajal, the two input pathways are therefore anatomically separated and converge within the cerebellar cortex at one level only, that is, the Purkinje cell. As a consequence, the Purkinje cells may operate as an online comparator that, for example, integrates the difference between the state of a movement that is being executed (encoded by the mossy fibers) and the errors that occur during this movement (encoded by the climbing fibers) and subsequently forward the appropriate modification through its projections to the brainstem so as to minimize the error. Over the past decade, the classical idea that Purkinje cells are the only element of the cerebellar cortex contacted by climbing fibers has also been challenged. For example, we did obtain evidence for potential contacts between climbing fibers and interneurons in the molecular layer of the mouse using a light microscopic, double-labeling tracing immuno approach (Galliano et al., 2013a). Indeed, other laboratories have shown a climbing fiber influence on molecular layer interneurons at the physiological level, presumably through extrasynaptic release (Mathews et al., 2012; Szapiro and Barbour, 2007). Instead, our double-labeling approach mentioned above did not reveal potential contacts between climbing fibers and Golgi cells in the granular layer (Galliano et al., 2013a), nor did ultrastructural and electrophysiological studies on the inputs converging on Golgi cells (Cesana et al., 2013). The existence of such contacts was hypothesized by Scheibel and Scheibel (1954), when they described thin collaterals branching away from the main climbing fiber and terminating their course in the upper granular layer, where most Golgi cell somas are located. A possible explanation for the existence of such collaterals could be vestigial climbing fibers that lost the developmental competition in the process of elimination of multiple innervation of Purkinje cells but did not fully retract (Sugihara, 2006). At the physiological level, a recent paper from the Edgley laboratory indirectly confirmed the result previously obtained by Schulman and Bloom (1981): in the intact

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animal, electrical stimulation of the inferior olive inhibits the firing of extracellularly recorded Golgi cells (Xu and Edgley, 2008). However, the mechanism underlying this form of inhibition remains unclear. The Golgi cell basic connectivity as described long ago by Cajal and confirmed later with ultrastructural studies by Palay (for historical review, see Galliano et al., 2010) has indeed been heavily questioned over the past decade. First, the discovery of electrical synapses connecting different Golgi cells revived the long-dismissed Golgian idea of the anatomical syncytium (Dugue et al., 2009; Vervaeke et al., 2010), offering a late synthesis of the divergent theories of cellular and diffuse networks. Furthermore, recent observations reporting that Golgi cells are inhibited by other Golgi cells and not by molecular layer interneurons (Hull and Regehr, 2012) and that the olivary influence on Golgi cells may be mediated by Purkinje cells through direct axonal collaterals (Frola et al., 2012) fully reopened the issue concerning the basic connectivity within the cerebellar cortex (Fig. 4). Indeed, the employment of technically advanced optical methods will be beneficial in complementing the classical anatomical description of the cerebellar circuitry in general.

4 THE THIRD PILLAR: DEPRESSION AT THE PARALLEL FIBER TO PURKINJE CELL SYNAPSE IS THE MOLECULAR SUBSTRATE OF CEREBELLAR LEARNING The ability of neurons to plastically modify themselves is one of the characteristics that make the brain more powerful and capable of learning. Specifically, it is of interest to know how the brain responds to incoming stimuli during both development and adulthood and uses such experiences to plastically modify itself at the cellular level, in a process that is thought to be the molecular basis of learning and memory. The first postulation of such plastic mechanisms carries the name of Donald Hebb and states that the strength of a connection between two neurons can be altered by the way in which that connection is activated (Hebb, 1949). As mentioned, cerebellar system physiology strongly relies on cellular plastic mechanisms to explain overall behavior, and it has been dominated during the last 50 years by the motor learning theory, initially predicted by Albus (1971) and Marr (1969) and later supported by experimental evidence provided by Ito (1982) and others (Aiba et al., 1994; De Zeeuw et al., 1998; Feil et al., 2003). The motor learning theory, which takes its inspiration from the unique cerebellar connectivity, postulates that cerebellar learning is supervised by climbing fiber activation, which, by acting as a teaching signal, depresses the parallel fiber to Purkinje cell synapse and thereby modulates Purkinje cell output. One of the main challenges to the motor learning doctrine was the proposal by Miles and Lisberger in the early 1980s, which advocated that the Purkinje cell to cerebellar or vestibular nuclei neuron synapse is an additional, if not the main, learning site (Miles and Lisberger, 1981). This proposal was supported by VOR

4 The Third Pillar: Depression at the Parallel Fiber to Purkinje Cell Synapse

adaptation tests, which showed that elimination of climbing fiber instructive signals did not prevent the learning completely (Ke et al., 2009), and by both VOR adaptation and eyeblink conditioning experiments in which the memory could still be retrieved even though the cerebellar cortex was lesioned only several hours after training (Attwell et al., 2002; Shutoh et al., 2006). Another challenge originally proposed by Fujita and recently revived by Dean and Porril is known as the adaptive filter model (Dean et al., 2010; Fujita, 1982). This model states that signals carried by mossy fibers are filtered twice, first at the level of granule cells and Golgi cells, and then at the Purkinje cell level. By selecting and adapting these signals with the use of bidirectional synaptic plasticity (Coesmans et al., 2004), Purkinje cells are presumed to compute the final output. Finally, we ourselves have elaborated on these concepts and we advocate distributed synergistic plasticity as the overarching view on cerebellar motor learning (Gao et al., 2012). This framework underlines: (a) the importance of spatiotemporal coding for fine-tuning of movements, which probably cannot be achieved by rate coding alone; (b) critical roles for the granular layer, molecular layer, and cerebellar nuclei in spreading diversity of spatiotemporal signals, selecting the optimal signals, and consolidating them, respectively; (c) the existence of different forms of plasticity widespread in the cerebellar cortical and nuclear network that are synergistically driven by climbing fiber activity; and (d) ample room for compensation explaining why blocking long-term depression at the parallel fiber to Purkinje cell synapse alone does not necessarily lead to a behavioral phenotype (Schonewille et al., 2011). Indeed, the emerging picture is more complex: on the one hand, the whole network is capable of synaptic plasticity, but on the other hand several additional classes of neuronal plasticity have been identified and characterized. These plastic mechanisms include both intrinsic functional (e.g., modification of a neuron’s intrinsic excitability and/or passive membrane properties; Turrigiano, 2011) and structural ones (e.g., formation and/or modification of presynaptic boutons and postsynaptic dendritic spines, growth or retraction of neurites, and plasticity of the axon initial segment; Boele et al., 2013; Bourne and Harris, 2008; Gogolla et al., 2007; Grubb and Burrone, 2010). Up to now, these processes have largely been studied in isolation or at best two at a time (Belmeguenai et al., 2010; Schonewille et al., 2010), but neurons do not singularly adopt plasticity mechanisms, and it has become of primary importance to understand how they integrate within individual cells and how they impact on network processing as a whole. While little is known about structural plasticity in the adult cerebellum (Boele et al., 2013), there is evidence linking intrinsic and synaptic plasticity at the level of both granule cells and Purkinje cells (Armano et al., 2000; Belmeguenai et al., 2010) showing that different classes of plasticity in the same neurons as well as in different network elements synergistically interact and compensate up to a point for each other’s absence to ensure an appropriate behavioral output (Galliano et al., 2012, 2013b,c). What appears clear now is that the classic idea according to which parallel fiber to Purkinje cell synaptic depression under climbing fiber control is the main mechanism underlying cerebellar learning is overly simplistic (Schonewille et al., 2011), and it needs to be implemented into a holistic plastic framework.

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5 CONCLUDING REMARKS For approximately two centuries, there has been a dominating doctrine in the scientific field about the basic principles of cerebellar functioning, which can be summarized as follows: the cerebellar main function is to control motor behavior; Purkinje cells are the only cortical neuron receiving and computing inputs from both incoming climbing fiber and mossy fiber pathways; plastic modification at such input synapses onto Purkinje cells constitutes the cellular substrate of motor learning. These concepts derived from classic anatomical and functional studies of Flourens, Cajal, and Marr/Albus/Ito constitute the pillars of what can be considered to be the classic cerebellar doctrine (Fig. 5). This classic cerebellar doctrine has been repeatedly challenged, and even though the basic principles described by the early cerebellar investigators long ago still hold true, they may need to be complemented and/or partially modified with discoveries that are now possible, thanks to the enormous technical advances that neuroscience made in the last decades. What also emerges is that it is now the time to take a step back from the serial exploitation of the reductionist potential of the scientific method and attempt a more careful synthesis, which takes into account the various components of the puzzle and does not neglect the ethological and evolutionary dimension of the research. The coming years of cerebellar studies will hopefully not see the explosion of a cerebellar scientific revolution following Kuhn’s model (1962) in that science hopefully progresses in harmony rather than by contraposition of new and old models. In line with the Russian-doll model of Ernst Nagel according to which preliminary theories converge into more comprehensive ones (Nagel, 1979), one might hope to witness the advent of a more holistic cerebellar theory built around the classic doctrine including the most recent findings.

FIGURE 5 The classic cerebellar doctrine (left) and its revision (right).

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