Modeling memory consolidation during posttraining periods in cerebellovestibular learning

Horizontal, vertical, and torsional optokinetic responses and their adaptations in fish

Eye movements in vertebrates moving around stabilize retinal images, achieved through the vestibuloocular reflex (VOR) and the optokinetic response (OKR). Although VOR compensates for head velocity, its effectiveness declines with prolonged motion, necessitating the OKR. This study explores the three-dimensional (3-D) nature of the OKR in goldfish, focusing on horizontal (H), vertical (V), and torsional (T) responses and their adaptation. We found that naïve goldfish exhibited minimal V and TOKR unlike robust HOKR having low-pass characteristics. Through visual training, V and TOKR manifested with flatter frequency spectra, although TOKR toward intorsion unchanged. Memory retention revealed a slower decay of adapted TOKR compared with others. These are the first evaluation of V and TOKR in fish, demonstrating that while naïve goldfish do not rely on V and TOKR in their natural behavior, they retain adaptative capabilities. Vertical and torsional ocular ranges, measured through tilt VOR, well exceeded OKR movement ranges, indicating that minimal VOKR and TOKR are not due to ocular muscle limitations but inherent OKR properties. Head motion analysis in freely swimming goldfish and carp, a closely related species, revealed small, flat frequency spectra in roll and pitch, and large low-pass spectra in yaw in the former, and a significant pitch-down bias during foraging in the latter. These findings suggest that goldfish OKRs are adaptable across axes, reflecting the unique vestibular and visual experiences associated with goldfish locomotor behavior patterns. Notably, the asymmetrical adaptability of TOKR potentially linked to foraging behaviors.NEW & NOTEWORTHY This study provides the first comprehensive evaluation of vertical (V) and torsional (T) optokinetic responses (OKR) in fish, demonstrating that naïve animals exhibit minimal V and TOKR compared with robust horizontal (H) OKR. Visual training revealed adaptive capabilities, with V and TOKR gains increasing, although TOKR showed directional asymmetry. Notably, adapted TOKR exhibited slower memory decay than H and VOKR. These findings highlight the plasticity of OKR and its functional relevance to locomotor behaviors.

Synaptic weight dynamics underlying memory consolidation: Implications for learning rules, circuit organization, and circuit function

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We provide two biologically plausible implementations for this reset that propose functional roles in stabilizing consolidation for core elements of the cerebellar circuit.

Synaptic weight dynamics underlying memory consolidation: implications for learning rules, circuit organization, and circuit function

Systems consolidation is a common feature of learning and memory systems, in which a long-term memory initially stored in one brain region becomes persistently stored in another region. We studied the dynamics of systems consolidation in simple circuit architectures with two sites of plasticity, one in an early-learning and one in a late-learning brain area. We show that the synaptic dynamics of the circuit during consolidation of an analog memory can be understood as a temporal integration process, by which transient changes in activity driven by plasticity in the early-learning area are accumulated into persistent synaptic changes at the late-learning site. This simple principle naturally leads to a speed-accuracy tradeoff in systems consolidation and provides insight into how the circuit mitigates the stability-plasticity dilemma of storing new memories while preserving core features of older ones. Furthermore, it imposes two constraints on the circuit. First, the plasticity rule at the late-learning site must stably support a continuum of possible outputs for a given input. We show that this is readily achieved by heterosynaptic but not standard Hebbian rules. Second, to turn off the consolidation process and prevent erroneous changes at the late-learning site, neural activity in the early-learning area must be reset to its baseline activity. We propose two biologically plausible implementations for this reset that suggest novel roles for core elements of the cerebellar circuit.

Significance Statement

How are memories transformed over time? We propose a simple organizing principle for how long term memories are moved from an initial to a final site of storage. We show that successful transfer occurs when the late site of memory storage is endowed with synaptic plasticity rules that stably accumulate changes in activity occurring at the early site of memory storage. We instantiate this principle in a simple computational model that is representative of brain circuits underlying a variety of behaviors. The model suggests how a neural circuit can store new memories while preserving core features of older ones, and suggests novel roles for core elements of the cerebellar circuit.

Emergence of syntax and word prediction in an artificial neural circuit of the cerebellum

The cerebellum, interconnected with the cerebral neocortex, plays a vital role in human-characteristic cognition such as language processing, however, knowledge about the underlying circuit computation of the cerebellum remains very limited. To gain a better understanding of the computation underlying cerebellar language processing, we developed a biologically constrained cerebellar artificial neural network (cANN) model, which implements the recently identified cerebello-cerebellar recurrent pathway. We found that while cANN acquires prediction of future words, another function of syntactic recognition emerges in the middle layer of the prediction circuit. The recurrent pathway of the cANN was essential for the two language functions, whereas cANN variants with further biological constraints preserved these functions. Considering the uniform structure of cerebellar circuitry across all functional domains, the single-circuit computation, which is the common basis of the two language functions, can be generalized to fundamental cerebellar functions of prediction and grammar-like rule extraction from sequences, that underpin a wide range of cerebellar motor and cognitive functions. This is a pioneering study to understand the circuit computation of human-characteristic cognition using biologically-constrained ANNs.

Short-term learning of the vestibulo-ocular reflex induced by a custom interactive computer game

Retinal image slip during head rotation drives motor learning in the rotational vestibulo-ocular reflex (VOR) and forms the basis of gaze-stability exercises that treat vestibular dysfunction. Clinical exercises, however, are unengaging, cannot easily be titrated to the level of impairment, and provide neither direct feedback nor tracking of the patient's adherence, performance, and progress. To address this, we have developed a custom application for VOR training based on an interactive computer game. In this study, we tested the ability of this game to induce VOR learning in individuals with normal vestibular function, and we compared the efficacy of single-step and incremental learning protocols. Eighteen participants played the game twice on different days. All participants tolerated the game and were able to complete both sessions. The game scenario incorporated a series of brief head rotations, similar to active head impulses, that were paired with a dynamic acuity task and with a visual-vestibular mismatch (VVM) intended to increase VOR gain (single-step: 300 successful trials at ×1.5 viewing; incremental: 100 trials each of ×1.13, ×1.33, and ×1.5 viewing). Overall, VOR gain increased by 15 ± 4.7% (mean ± 95% CI, P < 0.001). Gains increased similarly for active and passive head rotations, and, contrary to our hypothesis, there was little effect of the learning strategy. This study shows that an interactive computer game provides robust VOR training and has the potential to deliver effective, engaging, and trackable gaze-stability exercises to patients with a range of vestibular dysfunctions.NEW & NOTEWORTHY This study demonstrates the feasibility and efficacy of a customized computer game to induce motor learning in the high-frequency rotational vestibulo-ocular reflex. It provides a physiological basis for the deployment of this technology to clinical vestibular rehabilitation.

Connectivity concepts in neuronal network modeling

Sustainable research on computational models of neuronal networks requires published models to be understandable, reproducible, and extendable. Missing details or ambiguities about mathematical concepts and assumptions, algorithmic implementations, or parameterizations hinder progress. Such flaws are unfortunately frequent and one reason is a lack of readily applicable standards and tools for model description. Our work aims to advance complete and concise descriptions of network connectivity but also to guide the implementation of connection routines in simulation software and neuromorphic hardware systems. We first review models made available by the computational neuroscience community in the repositories ModelDB and Open Source Brain, and investigate the corresponding connectivity structures and their descriptions in both manuscript and code. The review comprises the connectivity of networks with diverse levels of neuroanatomical detail and exposes how connectivity is abstracted in existing description languages and simulator interfaces. We find that a substantial proportion of the published descriptions of connectivity is ambiguous. Based on this review, we derive a set of connectivity concepts for deterministically and probabilistically connected networks and also address networks embedded in metric space. Beside these mathematical and textual guidelines, we propose a unified graphical notation for network diagrams to facilitate an intuitive understanding of network properties. Examples of representative network models demonstrate the practical use of the ideas. We hope that the proposed standardizations will contribute to unambiguous descriptions and reproducible implementations of neuronal network connectivity in computational neuroscience.

Opposing actions of CRF-R1 and CB1 receptor on facial stimulation-induced MLI-PC plasticity in mouse cerebellar cortex

BACKGROUND

Corticotropin-releasing factor (CRF) is the major neuromodulator orchestrating the stress response, and is secreted by neurons in various regions of the brain. Cerebellar CRF is released by afferents from inferior olivary neurons and other brainstem nuclei in response to stressful challenges, and contributes to modulation of synaptic plasticity and motor learning behavior via its receptors. We recently found that CRF modulates facial stimulation-evoked molecular layer interneuron-Purkinje cell (MLI-PC) synaptic transmission via CRF type 1 receptor (CRF-R1) in vivo in mice, suggesting that CRF modulates sensory stimulation-evoked MLI-PC synaptic plasticity. However, the mechanism of how CRF modulates MLI-PC synaptic plasticity is unclear. We investigated the effect of CRF on facial stimulation-evoked MLI-PC long-term depression (LTD) in urethane-anesthetized mice by cell-attached recording technique and pharmacological methods.

RESULTS

Facial stimulation at 1 Hz induced LTD of MLI-PC synaptic transmission under control conditions, but not in the presence of CRF (100 nM). The CRF-abolished MLI-PC LTD was restored by application of a selective CRF-R1 antagonist, BMS-763,534 (200 nM), but it was not restored by application of a selective CRF-R2 antagonist, antisauvagine-30 (200 nM). Blocking cannabinoid type 1 (CB1) receptor abolished the facial stimulation-induced MLI-PC LTD, and revealed a CRF-triggered MLI-PC long-term potentiation (LTP) via CRF-R1. Notably, either inhibition of protein kinase C (PKC) with chelerythrine (5 µM) or depletion of intracellular Ca²⁺ with cyclopiazonic acid (100 µM), completely prevented CRF-triggered MLI-PC LTP in mouse cerebellar cortex in vivo.

CONCLUSIONS

The present results indicated that CRF blocked sensory stimulation-induced opioid-dependent MLI-PC LTD by triggering MLI-PC LTP through CRF-R1/PKC and intracellular Ca²⁺ signaling pathway in mouse cerebellar cortex. These results suggest that activation of CRF-R1 opposes opioid-mediated cerebellar MLI-PC plasticity in vivo in mice.

Localization of long-term synaptic plasticity defects in cerebellar circuits using optokinetic reflex learning profile

Objective.Functional maps of the central nervous system attribute the coordination and control of many body movements directly or indirectly to the cerebellum. Despite this general picture, there is little information on the function of cerebellar neural components at the circuit level. The presence of multiple synaptic junctions and the synergistic action of different types of plasticity make it virtually difficult to determine the distinct contribution of cerebellar neural processes to behavioral manifestations. In this study, investigating the effect of long-term synaptic changes on cerebellar motor learning, we intend to provide quantitative criteria for localizing defects in the major forms of synaptic plasticity in the cerebellum.Approach.To this end, we develop a firing rate model of the cerebellar circuits to simulate learning of optokinetic reflex (OKR), one of the most well-known cerebellar-dependent motor tasks. In the following, by comparing the simulated OKR learning profile for normal and pathosynaptic conditions, we extract the learning features affected by long-term plasticity disorders. Next, conducting simulation with different massed (continuous with no rest) and spaced (interleaved with rest periods) learning paradigms, we estimate the detrimental impact of plasticity defects at corticonuclear synapses on short- and long-term motor memory.Main results.Our computational approach predicts a correlation between location and grade of the defect with some learning factors such as the rate of formation and retention of motor memory, baseline performance, and even cerebellar motor reserve capacity. Further, spacing analysis reveal the dependence of learning paradigm efficiency on the spatiotemporal characteristic of defect in the network. Indeed, defects in cortical memory formation and nuclear memory consolidation mainly harm massed and spaced learning, respectively. This result is used to design a differential assay for identifying the faulty phases of cerebellar learning.Significance.The proposed computational framework can help develop neural-screening systems and prepare meso-scale functional maps of the cerebellar circuits.

Requirements of Postnatal proBDNF in the Hippocampus for Spatial Memory Consolidation and Neural Function

Mature brain-derived neurotrophic factor (BDNF) and its downstream signaling pathways have been implicated in regulating postnatal development and functioning of rodent brain. However, the biological role of its precursor pro-brain-derived neurotrophic factor (proBDNF) in the postnatal brain remains unknown. The expression of hippocampal proBDNF was blocked in postnatal weeks, and multiple behavioral tests, Western blot and morphological techniques, and neural recordings were employed to investigate how proBDNF played a role in spatial cognition in adults. The peak expression and its crucial effects were found in the fourth but not in the second or eighth postnatal week. Blocking proBDNF expression disrupted spatial memory consolidation rather than learning or memory retrieval. Structurally, blocking proBDNF led to the reduction in spine density and proportion of mature spines. Although blocking proBDNF did not affect N-methyl-D-aspartate (NMDA) receptor (NMDAR) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunits, the learning-induced phosphorylation of the GluN2B subunit level declined significantly. Functionally, paired-pulse facilitation, post-low-frequency stimulation (LFS) transiently enhanced depression, and GluN2B-dependent short-lasting long-term depression in the Schaffer collateral-CA1 pathway were weakened. The firing rate of pyramidal neurons was significantly suppressed around the target region during the memory test. Furthermore, the activation of GluN2B-mediated signaling could effectively facilitate neural function and mitigate memory impairment. The findings were consistent with the hypothesis that postnatal proBDNF played an essential role in synaptic and cognitive functions.

Adaptive control of movement deceleration during saccades

As you read this text, your eyes make saccades that guide your fovea from one word to the next. Accuracy of these movements require the brain to monitor and learn from visual errors. A current model suggests that learning is supported by two different adaptive processes, one fast (high error sensitivity, low retention), and the other slow (low error sensitivity, high retention). Here, we searched for signatures of these hypothesized processes and found that following experience of a visual error, there was an adaptive change in the motor commands of the subsequent saccade. Surprisingly, this adaptation was not uniformly expressed throughout the movement. Rather, after experience of a single error, the adaptive response in the subsequent trial was limited to the deceleration period. After repeated exposure to the same error, the acceleration period commands also adapted, and exhibited resistance to forgetting during set-breaks. In contrast, the deceleration period commands adapted more rapidly, but suffered from poor retention during these same breaks. State-space models suggested that acceleration and deceleration periods were supported by a shared adaptive state which re-aimed the saccade, as well as two separate processes which resembled a two-state model: one that learned slowly and contributed primarily via acceleration period commands, and another that learned rapidly but contributed primarily via deceleration period commands.

Diversity and dynamism in the cerebellum

The past several years have brought revelations and paradigm shifts in research on the cerebellum. Historically viewed as a simple sensorimotor controller with homogeneous architecture, the cerebellum is increasingly implicated in cognitive functions. It possesses an impressive diversity of molecular, cellular and circuit mechanisms, embedded in a dynamic, recurrent circuit architecture. Recent insights about the diversity and dynamism of the cerebellum provide a roadmap for the next decade of cerebellar research, challenging some old concepts, reinvigorating others and defining major new research directions.

Human-scale Brain Simulation via Supercomputer: A Case Study on the Cerebellum

Performance of supercomputers has been steadily and exponentially increasing for the past 20 years, and is expected to increase further. This unprecedented computational power enables us to build and simulate large-scale neural network models composed of tens of billions of neurons and tens of trillions of synapses with detailed anatomical connections and realistic physiological parameters. Such "human-scale" brain simulation could be considered a milestone in computational neuroscience and even in general neuroscience. Towards this milestone, it is mandatory to introduce modern high-performance computing technology into neuroscience research. In this article, we provide an introductory landscape about large-scale brain simulation on supercomputers from the viewpoints of computational neuroscience and modern high-performance computing technology for specialists in experimental as well as computational neurosciences. This introduction to modeling and simulation methods is followed by a review of various representative large-scale simulation studies conducted to date. Then, we direct our attention to the cerebellum, with a review of more simulation studies specific to that region. Furthermore, we present recent simulation results of a human-scale cerebellar network model composed of 86 billion neurons on the Japanese flagship supercomputer K (now retired). Finally, we discuss the necessity and importance of human-scale brain simulation, and suggest future directions of such large-scale brain simulation research.

Efficacy of spaced learning in adaptation of optokinetic response

INTRODUCTION

The superiority of spaced training, in which repeated training sessions are given with resting intervals, over massed training in learning efficacy has been well established. However, longer duration of total training time has been required for spaced training than massed training because spacing intervals intervene between training sessions in spaced training. Thus, the learning efficacy may not be simply compared between spaced and massed training in terms of "time efficiency." The aim of the present study was to investigate the efficacy of spaced and massed training using adaptation of horizontal optokinetic reflex (hOKR) in mice.

METHODS

Training paradigms were categorized into seven groups according to the duration of spacing interval, keeping total duration of hOKR training including spacing almost equal in all training paradigms.

RESULTS

The amount of short-term hOKR gain increase immediately after the 60 min hOKR training was not significantly different among seven training paradigms. The hOKR adaptation was still in progress during a spacing interval, and the increment in hOKR gain tended to be greater with the longer spacing interval. The increase in hOKR gain was maintained until 48 hr after the end of training in both massed and spaced training.

CONCLUSION

The short-term learning effect was not significantly different among training paradigms regardless of spacing interval in hOKR adaptation, which suggests that the spacing effect is robust enough to overcome the shortage of optokinetic training cycles in hOKR adaptation.

Molecular Layer Interneurons: Key Elements of Cerebellar Network Computation and Behavior

Molecular layer interneurons (MLIs) play an important role in cerebellar information processing by controlling Purkinje cell (PC) activity via inhibitory synaptic transmission. A local MLI network, constructed from both chemical and electrical synapses, is organized into spatially structured clusters that amplify feedforward and lateral inhibition to shape the temporal and spatial patterns of PC activity. Several recent in vivo studies indicate that such MLI circuits contribute not only to sensorimotor information processing, but also to precise motor coordination and cognitive processes. Here, we review current understanding of the organization of MLI circuits and their roles in the function of the mammalian cerebellum.

Ocular Reflex Adaptation as an Experimental Model of Cerebellar Learning -- In Memory of Masao Ito -

Masao Ito proposed a cerebellar learning hypothesis with Marr and Albus in the early 1970s. He suggested that cerebellar flocculus (FL) Purkinje cells (PCs), which directly inhibit the vestibular nuclear neurons driving extraocular muscle motor neurons, adaptively control the horizontal vestibulo-ocular reflex (HVOR) through the modification of mossy and parallel fiber-mediated vestibular responsiveness by visual climbing fiber (CF) inputs. Later, it was suggested that the same FL PCs adaptively control the horizontal optokinetic response (HOKR) in the same manner through the modification of optokinetic responsiveness in rodents and rabbits. In 1982, Ito and his colleagues discovered the plasticity of long-term depression (LTD) at parallel fiber (PF)-PC synapses after conjunctive stimulation of mossy or parallel fibers with CFs. Long-term potentiation (LTP) at PF-PC synapses by weak PF stimulation alone was found later. Many lines of experimental evidence have supported their hypothesis using various experimental methods and materials for the past 50 years by many research groups. Although several controversial findings were presented regarding their hypothesis, the reasons underlying many of them were clarified. Today, their hypothesis is considered as a fundamental mechanism of cerebellar learning. Furthermore, it was found that the memory of adaptation is transferred from the FL to vestibular nuclei for consolidation by repetition of adaptation through the plasticity of vestibular nuclear neurons. In this article, after overviewing their cerebellar learning hypothesis, I discuss possible roles of LTD and LTP in gain-up and gain-down HVOR/HOKR adaptations and refer to the expansion of their hypothesis to cognitive functions.

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.

Diagnosis and remediation of blink inefficiency

To examine the role of incomplete blinking in contributing to blink inefficiency, symptoms of dry eye and ocular surface disease. To review methods for diagnosing blink inefficiency (including both reduced overall blink rate and increased incomplete blink rate) and the role of remediation for efficient complete blinking as an essential part of the lacrimal functional unit in maintaining tear homeostasis. Diagnosis and remediation of blink inefficiency appear to have been somewhat misunderstood in the management of dry eye disease. To the extent that a high incomplete blink rate ranks in significance with low blink frequency in contributing to blink inefficiency, measures and remediation of only total blink rate are of reduced usefulness in the diagnosis and treatment of blink inefficiency-related ocular surface exposure, dry eye symptoms and ocular surface disease. In addition, a patient's blink performance during a biomicroscopy or any other clinical assessment of blink efficiency, is unlikely to be characteristic of or relevant to the blink inefficiency that develops and causes symptoms during their various day-to-day activities. There appears to be a strong case for prescribing blink efficiency exercises in the management of many cases of dry eye symptoms and ocular surface disease. Remediation of spontaneous blink inefficiency may require that a motor memory of voluntary complete, rapid, relaxed and natural looking blink formation is established and maintained as the basis for efficient spontaneous blinking. Voluntary forceful blinking may undermine the motor memory of efficient blinking and risk the depletion of any reserves of lipid.

Intrinsic Plasticity of Cerebellar Purkinje Cells Contributes to Motor Memory Consolidation

Intrinsic plasticity of cerebellar Purkinje cells (PCs) has recently been demonstrated in cerebellar local circuits; however, its physiological impact on cerebellar learning and memory remains elusive. Here, we suggest that intrinsic plasticity of PCs is tightly involved in motor memory consolidation based on findings from PC-specific STIM1 knockout male mice, which show severe memory consolidation deficiency in vestibulo-ocular reflex memory. Gain-up training of the vestibulo-ocular reflex produced a decrease in the synaptic weight of PCs in both the WT and KO groups. However, intrinsic plasticity was impaired only in the knockout mice. Furthermore, the observed defects in the intrinsic plasticity of PCs led to the formation of aberrant neural plasticity in the vestibular nucleus neurons. Our results suggest that synergistic modulation of intrinsic and synaptic plasticity in PCs is required for the changes in downstream plasticity in the vestibular nucleus, and thereby contributing to the long-term storage of motor memory.SIGNIFICANCE STATEMENT Synaptic plasticity is a well-known mechanism for learning and memory. Although plasticity of excitability, intrinsic plasticity, of the cerebellar Purkinje cell has been reported in both directions (potentiation and depression), the physiological role of intrinsic plasticity still remains ambiguous. In this study, we suggest that both synaptic and intrinsic plasticity are required for successful memory consolidation in cerebellar eye movement learning. Despite successful induction and maintenance of synaptic plasticity, we found deficits of memory consolidation when there were defects in intrinsic plasticity. Our results suggest that intrinsic plasticity of cerebellar Purkinje cell has a significant role in motor memory consolidation.

Simulation of a Human-Scale Cerebellar Network Model on the K Computer

Computer simulation of the human brain at an individual neuron resolution is an ultimate goal of computational neuroscience. The Japanese flagship supercomputer, K, provides unprecedented computational capability toward this goal. The cerebellum contains 80% of the neurons in the whole brain. Therefore, computer simulation of the human-scale cerebellum will be a challenge for modern supercomputers. In this study, we built a human-scale spiking network model of the cerebellum, composed of 68 billion spiking neurons, on the K computer. As a benchmark, we performed a computer simulation of a cerebellum-dependent eye movement task known as the optokinetic response. We succeeded in reproducing plausible neuronal activity patterns that are observed experimentally in animals. The model was built on dedicated neural network simulation software called MONET (Millefeuille-like Organization NEural neTwork), which calculates layered sheet types of neural networks with parallelization by tile partitioning. To examine the scalability of the MONET simulator, we repeatedly performed simulations while changing the number of compute nodes from 1,024 to 82,944 and measured the computational time. We observed a good weak-scaling property for our cerebellar network model. Using all 82,944 nodes, we succeeded in simulating a human-scale cerebellum for the first time, although the simulation was 578 times slower than the wall clock time. These results suggest that the K computer is already capable of creating a simulation of a human-scale cerebellar model with the aid of the MONET simulator.

Principles of Neurorehabilitation After Stroke Based on Motor Learning and Brain Plasticity Mechanisms

What are the principles underlying effective neurorehabilitation? The aim of neurorehabilitation is to exploit interventions based on human and animal studies about learning and adaptation, as well as to show that the activation of experience-dependent neuronal plasticity augments functional recovery after stroke. Instead of teaching compensatory strategies that do not reduce impairment but allow the patient to return home as soon as possible, functional recovery might be more sustainable as it ensures a long-term reduction in impairment and an improvement in quality of life. At the same time, neurorehabilitation permits the scientific community to collect valuable data, which allows inferring about the principles of brain organization. Hence neuroscience sheds light on the mechanisms of learning new functions or relearning lost ones. However, current rehabilitation methods lack the exact operationalization of evidence gained from skill learning literature, leading to an urgent need to bridge motor learning theory and present clinical work in order to identify a set of ingredients and practical applications that could guide future interventions. This work aims to unify the neuroscientific literature relevant to the recovery process and rehabilitation practice in order to provide a synthesis of the principles that constitute an effective neurorehabilitation approach. Previous attempts to achieve this goal either focused on a subset of principles or did not link clinical application to the principles of motor learning and recovery. We identified 15 principles of motor learning based on existing literature: massed practice, spaced practice, dosage, task-specific practice, goal-oriented practice, variable practice, increasing difficulty, multisensory stimulation, rhythmic cueing, explicit feedback/knowledge of results, implicit feedback/knowledge of performance, modulate effector selection, action observation/embodied practice, motor imagery, and social interaction. We comment on trials that successfully implemented these principles and report evidence from experiments with healthy individuals as well as clinical work.

Diverse Neuron Properties and Complex Network Dynamics in the Cerebellar Cortical Inhibitory Circuit

Neuronal inhibition can be defined as a spatiotemporal restriction or suppression of local microcircuit activity. The importance of inhibition relies in its fundamental role in shaping signal processing in single neurons and neuronal circuits. In this context, the activity of inhibitory interneurons proved the key to endow networks with complex computational and dynamic properties. In the last 50 years, the prevailing view on the functional role of cerebellar cortical inhibitory circuits was that excitatory and inhibitory inputs sum spatially and temporally in order to determine the motor output through Purkinje cells (PCs). Consequently, cerebellar inhibition has traditionally been conceived in terms of restricting or blocking excitation. This assumption has been challenged, in particular in the cerebellar cortex where all neurons except granule cells (and unipolar brush cells in specific lobules) are inhibitory and fire spontaneously at high rates. Recently, a combination of electrophysiological recordings in vitro and in vivo, imaging, optogenetics and computational modeling, has revealed that inhibitory interneurons play a much more complex role in regulating cerebellar microcircuit functions: inhibition shapes neuronal response dynamics in the whole circuit and eventually regulate the PC output. This review elaborates current knowledge on cerebellar inhibitory interneurons [Golgi cells, Lugaro cells (LCs), basket cells (BCs) and stellate cells (SCs)], starting from their ontogenesis and moving up to their morphological, physiological and plastic properties, and integrates this knowledge with that on the more renown granule cells and PCs. We will focus on the circuit loops in which these interneurons are involved and on the way they generate feed-forward, feedback and lateral inhibition along with complex spatio-temporal response dynamics. In this perspective, inhibitory interneurons emerge as the real controllers of cerebellar functioning.

Corticotropin-releasing factor depolarizes rat lateral vestibular nuclear neurons through activation of CRF receptors 1 and 2

Corticotropin-releasing factor (CRF) is a neuropeptide mainly synthesized in the hypothalamic paraventricular nucleus and has been traditionally implicated in stress and anxiety. Intriguingly, genetic or pharmacological manipulation of CRF receptors affects locomotor activity as well as motor coordination and balance in rodents, suggesting an active involvement of the central CRFergic system in motor control. Yet little is known about the exact role of CRF in central motor structures and the underlying mechanisms. Therefore, in the present study, we focused on the effect of CRF on the lateral vestibular nucleus (LVN) in the brainstem vestibular nuclear complex, an important center directly contributing to adjustment of muscle tone for both postural maintenance and the alternative change from the extensor to the flexor phase during locomotion. The results show that CRF depolarizes and increases the firing rate of neurons in the LVN. Tetrodotoxin does not block the CRF-induced depolarization and inward current on LVN neurons, suggesting a direct postsynaptic action of the neuropeptide. The CRF-induced depolarization on LVN neurons was partly blocked by antalarmin or antisauvagine-30, selective antagonists for CRF receptors 1 (CRFR1) and 2 (CRFR2), respectively. Furthermore, combined application of antalarmin and antisauvagine-30 totally abolished the CRF-induced depolarization. Immunofluorescence results show that CRFR1 and CRFR2 are co-localized in the rat LVN. These results demonstrate that CRF excites the LVN neurons by co-activation of both CRFR1 and CRFR2, suggesting that via the direct modulation on the LVN, the central CRFergic system may actively participate in the central vestibular-mediated postural and motor control.

Spaced training improves learning in Ts65Dn and Ube3a mouse models of intellectual disabilities

Benefits of distributed learning strategies have been extensively described in the human literature, but minimally investigated in intellectual disability syndromes. We tested the hypothesis that training trials spaced apart in time could improve learning in two distinct genetic mouse models of neurodevelopmental disorders characterized by intellectual impairments. As compared to training with massed trials, spaced training significantly improved learning in both the Ts65Dn trisomy mouse model of Down syndrome and the maternally inherited Ube3a mutant mouse model of Angelman syndrome. Spacing the training trials at 1 h intervals accelerated acquisition of three cognitive tasks by Ts65Dn mice: (1) object location memory, (2) novel object recognition, (3) water maze spatial learning. Further, (4) spaced training improved water maze spatial learning by Ube3a mice. In contrast, (5) cerebellar-mediated rotarod motor learning was not improved by spaced training. Corroborations in three assays, conducted in two model systems, replicated within and across two laboratories, confirm the strength of the findings. Our results indicate strong translational relevance of a behavioral intervention strategy for improving the standard of care in treating the learning difficulties that are characteristic and clinically intractable features of many neurodevelopmental disorders.

Plasticity leading to cerebellum-dependent learning: two different regions, two different types

In memory research, studying cerebellum-dependent memory is advantageous due to its relatively simple neural architecture compared with that of other memory circuits. To understand how cerebellum-dependent memory develops and is stored in this circuit, numerous hypotheses have been proposed. These hypotheses are generally able to adequately explain most learning and memory processes; however, several reported results are still poorly understood. Recently, the importance of intrinsic plasticity (i.e., plasticity of intrinsic excitability) has been highlighted in several studies. Because the classical view of cerebellum-dependent eye movement learning was focused on synaptic plasticity, it is valuable to consider the intrinsic plasticity for deeper understanding. In the present review, we re-examine the utility and limitations of previous hypotheses, from classic to recent, and propose an updated hypothesis. Integrating intrinsic plasticity into current models of the vestibulo-ocular reflex (VOR) circuit may facilitate deeper understanding of the VOR adaptation process. In particular, during the period of memory transfer, dynamic changes in excitability in both cerebellar Purkinje cells and vestibular nuclear neurons illuminate the role of intrinsic plasticity in the circuit.

Revisiting a theory of cerebellar cortex

Long-term depression at parallel fiber-Purkinje cell synapses plays a principal role in learning in the cerebellum, which acts as a supervised learning machine. Recent experiments demonstrate various forms of synaptic plasticity at different sites within the cerebellum. In this article, we take into consideration synaptic plasticity at parallel fiber-molecular layer interneuron synapses as well as at parallel fiber-Purkinje cell synapses, and propose that the cerebellar cortex performs reinforcement learning, another form of learning that is more capable than supervised learning. We posit that through the use of reinforcement learning, the need for explicit teacher signals for learning in the cerebellum is eliminated; instead, learning can occur via responses from evaluative feedback. We demonstrate the learning capacity of cerebellar reinforcement learning using simple computer simulations of delay eyeblink conditioning and the cart-pole balancing task.

Spike burst-pause dynamics of Purkinje cells regulate sensorimotor adaptation

Cerebellar Purkinje cells mediate accurate eye movement coordination. However, it remains unclear how oculomotor adaptation depends on the interplay between the characteristic Purkinje cell response patterns, namely tonic, bursting, and spike pauses. Here, a spiking cerebellar model assesses the role of Purkinje cell firing patterns in vestibular ocular reflex (VOR) adaptation. The model captures the cerebellar microcircuit properties and it incorporates spike-based synaptic plasticity at multiple cerebellar sites. A detailed Purkinje cell model reproduces the three spike-firing patterns that are shown to regulate the cerebellar output. Our results suggest that pauses following Purkinje complex spikes (bursts) encode transient disinhibition of target medial vestibular nuclei, critically gating the vestibular signals conveyed by mossy fibres. This gating mechanism accounts for early and coarse VOR acquisition, prior to the late reflex consolidation. In addition, properly timed and sized Purkinje cell bursts allow the ratio between long-term depression and potentiation (LTD/LTP) to be finely shaped at mossy fibre-medial vestibular nuclei synapses, which optimises VOR consolidation. Tonic Purkinje cell firing maintains the consolidated VOR through time. Importantly, pauses are crucial to facilitate VOR phase-reversal learning, by reshaping previously learnt synaptic weight distributions. Altogether, these results predict that Purkinje spike burst-pause dynamics are instrumental to VOR learning and reversal adaptation.

Cerebellar Purkinje cells regulate accurate eye movement coordination. However, it remains unclear how cerebellar-dependent oculomotor adaptation depends on the interplay between Purkinje cell characteristic response patterns: tonic, high frequency bursting, and post-complex spike pauses. We explore the role of Purkinje spike burst-pause dynamics in VOR adaptation. A biophysical model of Purkinje cell is at the core of a spiking network model, which captures the cerebellar microcircuit properties and incorporates spike-based synaptic plasticity mechanisms at different cerebellar sites. We show that Purkinje spike burst-pause dynamics are critical for (1) gating the vestibular-motor response association during VOR acquisition; (2) mediating the LTD/LTP balance for VOR consolidation; (3) reshaping synaptic efficacy distributions for VOR phase-reversal adaptation; (4) explaining the reversal VOR gain discontinuities during sleeping.

Effect of Specific Over Nonspecific VR-Based Rehabilitation on Poststroke Motor Recovery: A Systematic Meta-analysis

Background. Despite the rise of virtual reality (VR)-based interventions in stroke rehabilitation over the past decade, no consensus has been reached on its efficacy. This ostensibly puzzling outcome might not be that surprising given that VR is intrinsically neutral to its use—that is, an intervention is effective because of its ability to mobilize recovery mechanisms, not its technology. As VR systems specifically built for rehabilitation might capitalize better on the advantages of technology to implement neuroscientifically grounded protocols, they might be more effective than those designed for recreational gaming. Objective. We evaluate the efficacy of specific VR (SVR) and nonspecific VR (NSVR) systems for rehabilitating upper-limb function and activity after stroke. Methods. We conducted a systematic search for randomized controlled trials with adult stroke patients to analyze the effect of SVR or NSVR systems versus conventional therapy (CT). Results. We identified 30 studies including 1473 patients. SVR showed a significant impact on body function (standardized mean difference [SMD] = 0.23; 95% CI = 0.10 to 0.36; P = .0007) versus CT, whereas NSVR did not (SMD = 0.16; 95% CI = −0.14 to 0.47; P = .30). This result was replicated in activity measures. Conclusions. Our results suggest that SVR systems are more beneficial than CT for upper-limb recovery, whereas NSVR systems are not. Additionally, we identified 6 principles of neurorehabilitation that are shared across SVR systems and are possibly responsible for their positive effect. These findings may disambiguate the contradictory results found in the current literature.

The Emerging Concept of Intrinsic Plasticity: Activity-dependent Modulation of Intrinsic Excitability in Cerebellar Purkinje Cells and Motor Learning

What is memory? How does the brain process the sensory information and modify an organism's behavior? Many neuroscientists have focused on the activity- and experience-dependent modifications of synaptic functions in order to solve these fundamental questions in neuroscience. Recently, the plasticity of intrinsic excitability (called intrinsic plasticity) has emerged as an important element for information processing and storage in the brain. As the cerebellar Purkinje cells are the sole output neurons in the cerebellar cortex and the information is conveyed from a neuron to its relay neurons by forms of action potential firing, the modulation of the intrinsic firing activity may play a critical role in the cerebellar learning. Many voltage-gated and/or Ca2+-activated ion channels are involved in shaping the spiking output as well as integrating synaptic inputs to finely tune the cerebellar output. Recent studies suggested that the modulation of the intrinsic excitability and its plasticity in the cerebellar Purkinje cells might function as an integrator for information processing and memory formation. Moreover, the intrinsic plasticity might also determine the strength of connectivity to the sub-cortical areas such as deep cerebellar nuclei and vestibular nuclei to trigger the consolidation of the cerebellar-dependent memory by transferring the information.

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.

STIM1 Regulates Somatic Ca2+ Signals and Intrinsic Firing Properties of Cerebellar Purkinje Neurons

Control of Ca²⁺ flux between the cytosol and intracellular Ca²⁺ stores is essential for maintaining normal cellular function. It has been well established in both neuronal and non-neuronal cells that stromal interaction molecule 1 (STIM1) initiates and regulates refilling Ca²⁺ into the ER. Here, we describe a novel, additional role for STIM1, the regulation of free cytosolic Ca²⁺, and the consequent control of spike firing in neurons. Among central neurons, cerebellar Purkinje neurons express the highest level of STIM1, and they fire continuously in the absence of stimulation, making somatic Ca²⁺ homeostasis of particular importance. By using Purkinje neuron-specific STIM1 knock-out (STIM1^PKO) male mice, we found that the deletion of STIM1 delayed clearance of cytosolic Ca²⁺ in the soma during ongoing neuronal firing. Deletion of STIM1 also reduced the Purkinje neuronal excitability and impaired intrinsic plasticity without affecting long-term synaptic plasticity. In vestibulo-ocular reflex learning, STIM1^PKO male mice showed severe deficits in memory consolidation, whereas they were normal in memory acquisition. Our results suggest that STIM1 is critically involved in the regulation of the neuronal excitability and the intrinsic plasticity of the Purkinje neurons as well as cerebellar memory consolidation.SIGNIFICANCE STATEMENT Stromal interaction molecule 1 (STIM1), which regulates the refilling of ER Ca²⁺, has been investigated in several systems including the CNS. In addition to a previous study showing that STIM1 regulates dendritic ER Ca²⁺ refilling and mGluR1-mediated synaptic transmission, we provide compelling evidence describing a novel role of STIM1 in spike firing Purkinje neurons. We found that STIM1 regulates cytosolic Ca²⁺ clearance of the soma during spike firing, and the interruption of this cytosolic Ca²⁺ clearing disrupts neuronal excitability and cerebellar memory consolidation. Our results provide new insights into neuronal functions of STIM1 from single neuronal Ca²⁺ dynamics to behavior level.

Long-Term Depression of Intrinsic Excitability Accompanied by Synaptic Depression in Cerebellar Purkinje Cells

Long-term depression (LTD) at the parallel fiber (PF)-to-cerebellar Purkinje cell (PC) synapse is implicated in the output of PCs, the sole output of the cerebellar cortex. In addition to synaptic plasticity, intrinsic excitability is also one of the components that determines PC output. Although long-term potentiation of intrinsic excitability (LTP-IE) has been suggested, it has yet to be investigated how PF-PC LTD modifies intrinsic excitability of PCs. Here, we show that pairing of the PF and climbing fiber (CF) for PF-PC LTD induction evokes LTD-IE in cerebellar PCs from male C57BL/6 mice. Interestingly, this intrinsic plasticity showed different kinetics from synaptic plasticity, but both forms of plasticity share Ca²⁺ signaling and protein kinase C pathway as their underlying mechanism. Although small-conductance Ca²⁺-activated K⁺ channels play important roles in LTP-IE, no direct implication has been found. After PF-PC LTD induction, neither the temporal summation of dendritic EPSP nor the power of spike frequency adaptation is changed, indicating that cerebellar LTD executes the information processing in a quantitative way without quality changes of synaptic integration and generation of output signals. Our results suggest that LTD-IE may have a synergistic effect with synaptic depression on the total net output of neurons by amplifying the modification of PF synaptic transmission.SIGNIFICANCE STATEMENT Although the output of Purkinje cells (PCs) is a critical component of cerebellum-dependent learning and memory, the changes of PC excitability when synaptic LTD occurs are unclear. Here, we show that the induction of PF-PC LTD evokes LTD-IE in PCs. Our observation complements previous intrinsic plasticity phenomenon of long-term potentiation of intrinsic excitability (LTP-IE), providing evidence for the idea that intrinsic plasticity has bidirectionality as synaptic plasticity. LTD-IE occurs together with synaptic LTD and both phenomena are dependent on the Ca²⁺ signaling pathway. Furthermore, our findings raise the prospect that this synaptic and intrinsic plasticity acts synergistically in PCs to modify neuronal activity in the same direction when learning occurs.

The Sleeping Cerebellum

We sleep almost one-third of our lives and sleep plays an important role in critical brain functions like memory formation and consolidation. The role of sleep in cerebellar processing, however, constitutes an enigma in the field of neuroscience; we know little about cerebellar sleep-physiology, cerebro-cerebellar interactions during sleep, or the contributions of sleep to cerebellum-dependent memory consolidation. Likewise, we do not understand why cerebellar malfunction can lead to changes in the sleep-wake cycle and sleep disorders. In this review, we evaluate how sleep and cerebellar processing may influence one another and highlight which scientific routes and technical approaches could be taken to uncover the mechanisms underlying these interactions.

Long-Lasting Visuo-Vestibular Mismatch in Freely-Behaving Mice Reduces the Vestibulo-Ocular Reflex and Leads to Neural Changes in the Direct Vestibular Pathway

Calibration of the vestibulo-ocular reflex (VOR) depends on the presence of visual feedback. However, the cellular mechanisms associated with VOR modifications at the level of the brainstem remain largely unknown. A new protocol was designed to expose freely behaving mice to a visuo-vestibular mismatch during a 2-week period. This protocol induced a 50% reduction of the VOR. In vivo pharmacological experiments demonstrated that the VOR reduction depends on changes located outside the flocculus/paraflocculus complex. The cellular mechanisms associated with the VOR reduction were then studied in vitro on brainstem slices through a combination of vestibular afferent stimulation and patch-clamp recordings of central vestibular neurons. The evoked synaptic activity demonstrated that the efficacy of the synapses between vestibular afferents and central vestibular neurons was decreased. In addition, a long-term depression protocol failed to further decrease the synapse efficacy, suggesting that the VOR reduction might have occurred through depression-like mechanisms. Analysis of the intrinsic membrane properties of central vestibular neurons revealed that the synaptic changes were supplemented by a decrease in the spontaneous discharge and excitability of a subpopulation of neurons. Our results provide evidence that a long-lasting visuo-vestibular mismatch leads to changes in synaptic transmission and intrinsic properties of central vestibular neurons in the direct VOR pathway. Overall, these results open new avenues for future studies on visual and vestibular interactions conducted in vivo and in vitro.

Distribution and Structure of Synapses on Medial Vestibular Nuclear Neurons Targeted by Cerebellar Flocculus Purkinje Cells and Vestibular Nerve in Mice: Light and Electron Microscopy Studies

Adaptations of vestibulo-ocular and optokinetic response eye movements have been studied as an experimental model of cerebellum-dependent motor learning. Several previous physiological and pharmacological studies have consistently suggested that the cerebellar flocculus (FL) Purkinje cells (P-cells) and the medial vestibular nucleus (MVN) neurons targeted by FL (FL-targeted MVN neurons) may respectively maintain the memory traces of short- and long-term adaptation. To study the basic structures of the FL-MVN synapses by light microscopy (LM) and electron microscopy (EM), we injected green florescence protein (GFP)-expressing lentivirus into FL to anterogradely label the FL P-cell axons in C57BL/6J mice. The FL P-cell axonal boutons were distributed in the magnocellular MVN and in the border region of parvocellular MVN and prepositus hypoglossi (PrH). In the magnocellular MVN, the FL-P cell axons mainly terminated on somata and proximal dendrites. On the other hand, in the parvocellular MVN/PrH, the FL P-cell axonal synaptic boutons mainly terminated on the relatively small-diameter (< 1 μm) distal dendrites of MVN neurons, forming symmetrical synapses. The majority of such parvocellular MVN/PrH neurons were determined to be glutamatergic by immunocytochemistry and in-situ hybridization of GFP expressing transgenic mice. To further examine the spatial relationship between the synapses of FL P-cells and those of vestibular nerve on the neurons of the parvocellular MVN/PrH, we added injections of biotinylated dextran amine into the semicircular canal and anterogradely labeled vestibular nerve axons in some mice. The MVN dendrites receiving the FL P-cell axonal synaptic boutons often closely apposed vestibular nerve synaptic boutons in both LM and EM studies. Such a partial overlap of synaptic boutons of FL P-cell axons with those of vestibular nerve axons in the distal dendrites of MVN neurons suggests that inhibitory synapses of FL P-cells may influence the function of neighboring excitatory synapses of vestibular nerve in the parvocellular MVN/PrH neurons.

Psychological intervention with working memory training increases basal ganglia volume: A VBM study of inpatient treatment for methamphetamine use

BACKGROUND

Protracted methamphetamine (MA) use is associated with decreased control over drug craving and altered brain volume in the frontostriatal network. However, the nature of volumetric changes following a course of psychological intervention for MA use is not yet known.

METHODS

66 males (41 MA patients, 25 healthy controls, HC) between the ages of 18-50 were recruited, the MA patients from new admissions to an in-patient drug rehabilitation centre and the HC via public advertisement, both in Cape Town, South Africa. 17 MA patients received 4 weeks of treatment as usual (TAU), and 24 MA patients completed TAU plus daily 30-minute cognitive training (CT) using an N-back working memory task. Magnetic resonance imaging (MRI) at baseline and 4-week follow-up was acquired and voxel-based morphometry (VBM) was used for analysis.

RESULTS

TAU was associated with larger bilateral striatum (caudate/putamen) volume, whereas CT was associated with more widespread increases of the bilateral basal ganglia (incorporating the amygdala and hippocampus) and reduced bilateral cerebellum volume coinciding with improvements in impulsivity scores.

CONCLUSIONS

While psychological intervention is associated with larger volume in mesolimbic reward regions, the utilisation of additional working memory training as an adjunct to treatment may further normalize frontostriatal structure and function.

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.

Real-World-Time Simulation of Memory Consolidation in a Large-Scale Cerebellar Model

We report development of a large-scale spiking network model of the cerebellum composed of more than 1 million neurons. The model is implemented on graphics processing units (GPUs), which are dedicated hardware for parallel computing. Using 4 GPUs simultaneously, we achieve realtime simulation, in which computer simulation of cerebellar activity for 1 s completes within 1 s in the real-world time, with temporal resolution of 1 ms. This allows us to carry out a very long-term computer simulation of cerebellar activity in a practical time with millisecond temporal resolution. Using the model, we carry out computer simulation of long-term gain adaptation of optokinetic response (OKR) eye movements for 5 days aimed to study the neural mechanisms of posttraining memory consolidation. The simulation results are consistent with animal experiments and our theory of posttraining memory consolidation. These results suggest that realtime computing provides a useful means to study a very slow neural process such as memory consolidation in the brain.

A Model of In vitro Plasticity at the Parallel Fiber-Molecular Layer Interneuron Synapses

Theoretical and computational models of the cerebellum typically focus on the role of parallel fiber (PF)—Purkinje cell (PKJ) synapses for learned behavior, but few emphasize the role of the molecular layer interneurons (MLIs)—the stellate and basket cells. A number of recent experimental results suggest the role of MLIs is more important than previous models put forth. We investigate learning at PF—MLI synapses and propose a mathematical model to describe plasticity at this synapse. We perform computer simulations with this form of learning using a spiking neuron model of the MLI and show that it reproduces six in vitro experimental results in addition to simulating four novel protocols. Further, we show how this plasticity model can predict the results of other experimental protocols that are not simulated. Finally, we hypothesize what the biological mechanisms are for changes in synaptic efficacy that embody the phenomenological model proposed here.

Facial stimulation induces long-term depression at cerebellar molecular layer interneuron-Purkinje cell synapses in vivo in mice

Cerebellar long-term synaptic plasticity has been proposed to provide a cellular mechanism for motor learning. Numerous studies have demonstrated the induction and mechanisms of synaptic plasticity at parallel fiber–Purkinje cell (PF–PC), parallel fiber–molecular layer interneurons (PF–MLI) and mossy fiber–granule cell (MF–GC) synapses, but no study has investigated sensory stimulation-evoked synaptic plasticity at MLI–PC synapses in the cerebellar cortex of living animals. We studied the expression and mechanism of MLI–PC GABAergic synaptic plasticity induced by a train of facial stimulation in urethane-anesthetized mice by cell-attached recordings and pharmacological methods. We found that 1 Hz, but not a 2 Hz or 4 Hz, facial stimulation induced a long-term depression (LTD) of GABAergic transmission at MLI–PC synapses, which was accompanied with a decrease in the stimulation-evoked pause of spike firing in PCs, but did not induce a significant change in the properties of the sensory-evoked spike events of MLIs. The MLI–PC GABAergic LTD could be prevented by blocking cannabinoid type 1 (CB1) receptors, and could be pharmacologically induced by a CB1 receptor agonist. Additionally, 1 Hz facial stimulation delivered in the presence of a metabotropic glutamate receptor 1 (mGluR1) antagonist, JNJ16259685, still induced the MLI–PC GABAergic LTD, whereas blocking N-methyl-D-aspartate (NMDA) receptors during 1 Hz facial stimulation abolished the expression of MLI–PC GABAergic LTD. These results indicate that sensory stimulation can induce an endocannabinoid (eCB)-dependent LTD of GABAergic transmission at MLI–PC synapses via activation of NMDA receptors in cerebellar cortical Crus II in vivo in mice. Our results suggest that the sensory stimulation-evoked MLI–PC GABAergic synaptic plasticity may play a critical role in motor learning in animals.