1
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Garcia-Garcia MG, Kapoor A, Akinwale O, Takemaru L, Kim TH, Paton C, Litwin-Kumar A, Schnitzer MJ, Luo L, Wagner MJ. A cerebellar granule cell-climbing fiber computation to learn to track long time intervals. Neuron 2024:S0896-6273(24)00366-0. [PMID: 38870929 DOI: 10.1016/j.neuron.2024.05.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 03/31/2024] [Accepted: 05/16/2024] [Indexed: 06/15/2024]
Abstract
In classical cerebellar learning, Purkinje cells (PkCs) associate climbing fiber (CF) error signals with predictive granule cells (GrCs) that were active just prior (∼150 ms). The cerebellum also contributes to behaviors characterized by longer timescales. To investigate how GrC-CF-PkC circuits might learn seconds-long predictions, we imaged simultaneous GrC-CF activity over days of forelimb operant conditioning for delayed water reward. As mice learned reward timing, numerous GrCs developed anticipatory activity ramping at different rates until reward delivery, followed by widespread time-locked CF spiking. Relearning longer delays further lengthened GrC activations. We computed CF-dependent GrC→PkC plasticity rules, demonstrating that reward-evoked CF spikes sufficed to grade many GrC synapses by anticipatory timing. We predicted and confirmed that PkCs could thereby continuously ramp across seconds-long intervals from movement to reward. Learning thus leads to new GrC temporal bases linking predictors to remote CF reward signals-a strategy well suited for learning to track the long intervals common in cognitive domains.
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Affiliation(s)
- Martha G Garcia-Garcia
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA
| | - Akash Kapoor
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA
| | - Oluwatobi Akinwale
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA
| | - Lina Takemaru
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA
| | - Tony Hyun Kim
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Casey Paton
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA
| | - Ashok Litwin-Kumar
- Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Mark J Schnitzer
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA; Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
| | - Liqun Luo
- Department of Biology and Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Mark J Wagner
- National Institute of Neurological Disorders & Stroke, National Institutes of Health, Bethesda, MD 20894, USA.
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2
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Pali E, D’Angelo E, Prestori F. Understanding Cerebellar Input Stage through Computational and Plasticity Rules. BIOLOGY 2024; 13:403. [PMID: 38927283 PMCID: PMC11200477 DOI: 10.3390/biology13060403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 05/21/2024] [Accepted: 05/27/2024] [Indexed: 06/28/2024]
Abstract
A central hypothesis concerning brain functioning is that plasticity regulates the signal transfer function by modifying the efficacy of synaptic transmission. In the cerebellum, the granular layer has been shown to control the gain of signals transmitted through the mossy fiber pathway. Until now, the impact of plasticity on incoming activity patterns has been analyzed by combining electrophysiological recordings in acute cerebellar slices and computational modeling, unraveling a broad spectrum of different forms of synaptic plasticity in the granular layer, often accompanied by forms of intrinsic excitability changes. Here, we attempt to provide a brief overview of the most prominent forms of plasticity at the excitatory synapses formed by mossy fibers onto primary neuronal components (granule cells, Golgi cells and unipolar brush cells) in the granular layer. Specifically, we highlight the current understanding of the mechanisms and their functional implications for synaptic and intrinsic plasticity, providing valuable insights into how inputs are processed and reconfigured at the cerebellar input stage.
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Affiliation(s)
- Eleonora Pali
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy; (E.P.)
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy; (E.P.)
- Digital Neuroscience Center, IRCCS Mondino Foundation, 27100 Pavia, Italy
| | - Francesca Prestori
- Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy; (E.P.)
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3
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Montgomery JC. Roles for cerebellum and subsumption architecture in central pattern generation. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2024; 210:315-324. [PMID: 37130955 PMCID: PMC10994996 DOI: 10.1007/s00359-023-01634-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/04/2023]
Abstract
Within vertebrates, central pattern generators drive rhythmical behaviours, such as locomotion and ventilation. Their pattern generation is also influenced by sensory input and various forms of neuromodulation. These capabilities arose early in vertebrate evolution, preceding the evolution of the cerebellum in jawed vertebrates. This later evolution of the cerebellum is suggestive of subsumption architecture that adds functionality to a pre-existing network. From a central-pattern-generator perspective, what additional functionality might the cerebellum provide? The suggestion is that the adaptive filter capabilities of the cerebellum may be able to use error learning to appropriately repurpose pattern output. Examples may include head and eye stabilization during locomotion, song learning, and context-dependent alternation between learnt motor-control sequences.
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Affiliation(s)
- John C Montgomery
- Institute of Marine Science, University of Auckland, Auckland, New Zealand.
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4
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Bruel A, Abadía I, Collin T, Sakr I, Lorach H, Luque NR, Ros E, Ijspeert A. The spinal cord facilitates cerebellar upper limb motor learning and control; inputs from neuromusculoskeletal simulation. PLoS Comput Biol 2024; 20:e1011008. [PMID: 38166093 PMCID: PMC10786408 DOI: 10.1371/journal.pcbi.1011008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 01/12/2024] [Accepted: 12/12/2023] [Indexed: 01/04/2024] Open
Abstract
Complex interactions between brain regions and the spinal cord (SC) govern body motion, which is ultimately driven by muscle activation. Motor planning or learning are mainly conducted at higher brain regions, whilst the SC acts as a brain-muscle gateway and as a motor control centre providing fast reflexes and muscle activity regulation. Thus, higher brain areas need to cope with the SC as an inherent and evolutionary older part of the body dynamics. Here, we address the question of how SC dynamics affects motor learning within the cerebellum; in particular, does the SC facilitate cerebellar motor learning or constitute a biological constraint? We provide an exploratory framework by integrating biologically plausible cerebellar and SC computational models in a musculoskeletal upper limb control loop. The cerebellar model, equipped with the main form of cerebellar plasticity, provides motor adaptation; whilst the SC model implements stretch reflex and reciprocal inhibition between antagonist muscles. The resulting spino-cerebellar model is tested performing a set of upper limb motor tasks, including external perturbation studies. A cerebellar model, lacking the implemented SC model and directly controlling the simulated muscles, was also tested in the same. The performances of the spino-cerebellar and cerebellar models were then compared, thus allowing directly addressing the SC influence on cerebellar motor adaptation and learning, and on handling external motor perturbations. Performance was assessed in both joint and muscle space, and compared with kinematic and EMG recordings from healthy participants. The differences in cerebellar synaptic adaptation between both models were also studied. We conclude that the SC facilitates cerebellar motor learning; when the SC circuits are in the loop, faster convergence in motor learning is achieved with simpler cerebellar synaptic weight distributions. The SC is also found to improve robustness against external perturbations, by better reproducing and modulating muscle cocontraction patterns.
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Affiliation(s)
- Alice Bruel
- Biorobotics Laboratory, EPFL, Lausanne, Switzerland
| | - Ignacio Abadía
- Research Centre for Information and Communication Technologies, Department of Computer Engineering, Automation and Robotics, University of Granada, Granada, Spain
| | | | - Icare Sakr
- NeuroRestore, EPFL, Lausanne, Switzerland
| | | | - Niceto R. Luque
- Research Centre for Information and Communication Technologies, Department of Computer Engineering, Automation and Robotics, University of Granada, Granada, Spain
| | - Eduardo Ros
- Research Centre for Information and Communication Technologies, Department of Computer Engineering, Automation and Robotics, University of Granada, Granada, Spain
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5
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Wilson E. Adaptive Filter Model of Cerebellum for Biological Muscle Control With Spike Train Inputs. Neural Comput 2023; 35:1938-1969. [PMID: 37844325 DOI: 10.1162/neco_a_01617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 06/05/2023] [Indexed: 10/18/2023]
Abstract
Prior applications of the cerebellar adaptive filter model have included a range of tasks within simulated and robotic systems. However, this has been limited to systems driven by continuous signals. Here, the adaptive filter model of the cerebellum is applied to the control of a system driven by spiking inputs by considering the problem of controlling muscle force. The performance of the standard adaptive filter algorithm is compared with the algorithm with a modified learning rule that minimizes inputs and a simple proportional-integral-derivative (PID) controller. Control performance is evaluated in terms of the number of spikes, the accuracy of spike input locations, and the accuracy of muscle force output. Results show that the cerebellar adaptive filter model can be applied without change to the control of systems driven by spiking inputs. The cerebellar algorithm results in good agreement between input spikes and force outputs and significantly improves on a PID controller. Input minimization can be used to reduce the number of spike inputs, but at the expense of a decrease in accuracy of spike input location and force output. This work extends the applications of the cerebellar algorithm and demonstrates the potential of the adaptive filter model to be used to improve functional electrical stimulation muscle control.
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Affiliation(s)
- Emma Wilson
- School of Computing and Communications, Lancaster University, Lancaster LA1 4WA, U.K.
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6
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Masselink J, Cheviet A, Froment-Tilikete C, Pélisson D, Lappe M. A triple distinction of cerebellar function for oculomotor learning and fatigue compensation. PLoS Comput Biol 2023; 19:e1011322. [PMID: 37540726 PMCID: PMC10456158 DOI: 10.1371/journal.pcbi.1011322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 08/25/2023] [Accepted: 07/02/2023] [Indexed: 08/06/2023] Open
Abstract
The cerebellum implements error-based motor learning via synaptic gain adaptation of an inverse model, i.e. the mapping of a spatial movement goal onto a motor command. Recently, we modeled the motor and perceptual changes during learning of saccadic eye movements, showing that learning is actually a threefold process. Besides motor recalibration of (1) the inverse model, learning also comprises perceptual recalibration of (2) the visuospatial target map and (3) of a forward dynamics model that estimates the saccade size from corollary discharge. Yet, the site of perceptual recalibration remains unclear. Here we dissociate cerebellar contributions to the three stages of learning by modeling the learning data of eight cerebellar patients and eight healthy controls. Results showed that cerebellar pathology restrains short-term recalibration of the inverse model while the forward dynamics model is well informed about the reduced saccade change. Adaptation of the visuospatial target map trended in learning direction only in control subjects, yet without reaching significance. Moreover, some patients showed a tendency for uncompensated oculomotor fatigue caused by insufficient upregulation of saccade duration. According to our model, this could induce long-term perceptual compensation, consistent with the overestimation of target eccentricity found in the patients' baseline data. We conclude that the cerebellum mediates short-term adaptation of the inverse model, especially by control of saccade duration, while the forward dynamics model was not affected by cerebellar pathology.
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Affiliation(s)
- Jana Masselink
- Institute for Psychology & Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
| | - Alexis Cheviet
- IMPACT Team, Lyon Neuroscience Research Center, University Claude Bernard Lyon 1, Bron cedex, France
- Department of Psychology, Durham University, South Road, Durham, United Kingdom
| | - Caroline Froment-Tilikete
- IMPACT Team, Lyon Neuroscience Research Center, University Claude Bernard Lyon 1, Bron cedex, France
- Hospices Civils de Lyon—Pierre-Wertheimer Hospital, Neuro-Ophtalmology Unit, Bron cedex, France
| | - Denis Pélisson
- IMPACT Team, Lyon Neuroscience Research Center, University Claude Bernard Lyon 1, Bron cedex, France
| | - Markus Lappe
- Institute for Psychology & Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of Münster, Münster, Germany
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7
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Prescott TJ, Wilson SP. Understanding brain functional architecture through robotics. Sci Robot 2023; 8:eadg6014. [PMID: 37256968 DOI: 10.1126/scirobotics.adg6014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 05/05/2023] [Indexed: 06/02/2023]
Abstract
Robotics is increasingly seen as a useful test bed for computational models of the brain functional architecture underlying animal behavior. We provide an overview of past and current work, focusing on probabilistic and dynamical models, including approaches premised on the free energy principle, situating this endeavor in relation to evidence that the brain constitutes a layered control system. We argue that future neurorobotic models should integrate multiple neurobiological constraints and be hybrid in nature.
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Affiliation(s)
- Tony J Prescott
- Department of Computer Science, University of Sheffield, Sheffield, UK
| | - Stuart P Wilson
- Department of Computer Science, University of Sheffield, Sheffield, UK
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8
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miR-34a regulates silent synapse and synaptic plasticity in mature hippocampus. Prog Neurobiol 2023; 222:102404. [PMID: 36642095 DOI: 10.1016/j.pneurobio.2023.102404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/26/2022] [Accepted: 01/11/2023] [Indexed: 01/15/2023]
Abstract
AMPAR-lacking silent synapses are prevailed and essential for synaptic refinement and synaptic plasticity in developing brains. In mature brain, they are sparse but could be induced under several pathological conditions. How they are regulated molecularly is far from clear. miR-34a is a highly conserved and brain-enriched microRNA with age-dependent upregulated expression profile. Its neuronal function in mature brain remains to be revealed. Here by analyzing synaptic properties of the heterozygous miR-34a knock out mice (34a_ht), we have discovered that mature but not juvenile 34a_ht mice have more silent synapses in the hippocampus accompanied with enhanced synaptic NMDAR but not AMPAR function and increased spine density. As a result, 34a_ht mice display enhanced long-term potentiation (LTP) in the Schaffer collateral synapses and better spatial learning and memory. We further found that Creb1 is a direct target of miR-34a, whose upregulation and activation may mediate the silent synapse increment in 34a_ht mice. Hence, we reveal a novel physiological role of miR-34a in mature brains and provide a molecular mechanism underlying silent synapse regulation.
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9
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Xiao N, Wu G, Zhou Z, Yao J, Wu B, Sui J, Tin C. Positive feedback of efferent copy via pontine nucleus facilitates cerebellum-mediated associative learning. Cell Rep 2023; 42:112072. [PMID: 36735531 DOI: 10.1016/j.celrep.2023.112072] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/07/2022] [Accepted: 01/19/2023] [Indexed: 02/04/2023] Open
Abstract
The cerebellum is critical for motor coordination and learning. However, the role of feedback circuitry in this brain region has not been fully explored. Here, we characterize a nucleo-ponto-cortical feedback pathway in classical delayed eyeblink conditioning (dEBC) of rats. We find that the efference copy is conveyed from the interposed cerebellar nucleus (Int) to cerebellar cortex through pontine nucleus (PN). Inhibiting or exciting the projection from the Int to the PN can decelerate or speed up acquisition of dEBC, respectively. Importantly, we identify two subpopulations of PN neurons (PN1 and PN2) that convey and integrate the feedback signals with feedforward sensory signals. We also show that the feedforward and feedback pathways via different types of PN neurons contribute to the plastic changes and cooperate synergistically to the learning of dEBC. Our results suggest that this excitatory nucleo-ponto-cortical feedback plays a significant role in modulating associative motor learning in cerebellum.
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Affiliation(s)
- Na Xiao
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong; Advanced Biomedical Instrumentation Centre, Shatin, N.T., Hong Kong; Department of Mechanical Engineering, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Guangyan Wu
- Experimental Center of Basic Medicine, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Zhanhong Zhou
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong
| | - Juan Yao
- Experimental Center of Basic Medicine, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Bing Wu
- Experimental Center of Basic Medicine, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China
| | - Jianfeng Sui
- Experimental Center of Basic Medicine, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China; Department of Physiology, College of Basic Medical Sciences, Army Medical University, Chongqing 400038, China.
| | - Chung Tin
- Department of Biomedical Engineering, City University of Hong Kong, Kowloon Tong, Hong Kong.
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10
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Barri A, Wiechert MT, Jazayeri M, DiGregorio DA. Synaptic basis of a sub-second representation of time in a neural circuit model. Nat Commun 2022; 13:7902. [PMID: 36550115 PMCID: PMC9780315 DOI: 10.1038/s41467-022-35395-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
Temporal sequences of neural activity are essential for driving well-timed behaviors, but the underlying cellular and circuit mechanisms remain elusive. We leveraged the well-defined architecture of the cerebellum, a brain region known to support temporally precise actions, to explore theoretically whether the experimentally observed diversity of short-term synaptic plasticity (STP) at the input layer could generate neural dynamics sufficient for sub-second temporal learning. A cerebellar circuit model equipped with dynamic synapses produced a diverse set of transient granule cell firing patterns that provided a temporal basis set for learning precisely timed pauses in Purkinje cell activity during simulated delay eyelid conditioning and Bayesian interval estimation. The learning performance across time intervals was influenced by the temporal bandwidth of the temporal basis, which was determined by the input layer synaptic properties. The ubiquity of STP throughout the brain positions it as a general, tunable cellular mechanism for sculpting neural dynamics and fine-tuning behavior.
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Affiliation(s)
- A. Barri
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
| | - M. T. Wiechert
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
| | - M. Jazayeri
- grid.116068.80000 0001 2341 2786McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA USA
| | - D. A. DiGregorio
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
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11
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Bae H, Park SY, Kim SJ, Kim CE. Cerebellum as a kernel machine: A novel perspective on expansion recoding in granule cell layer. Front Comput Neurosci 2022; 16:1062392. [PMID: 36618271 PMCID: PMC9815768 DOI: 10.3389/fncom.2022.1062392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
Sensorimotor information provided by mossy fibers (MF) is mapped to high-dimensional space by a huge number of granule cells (GrC) in the cerebellar cortex's input layer. Significant studies have demonstrated the computational advantages and primary contributor of this expansion recoding. Here, we propose a novel perspective on the expansion recoding where each GrC serve as a kernel basis function, thereby the cerebellum can operate like a kernel machine that implicitly use high dimensional (even infinite) feature spaces. We highlight that the generation of kernel basis function is indeed biologically plausible scenario, considering that the key idea of kernel machine is to memorize important input patterns. We present potential regimes for developing kernels under constrained resources and discuss the advantages and disadvantages of each regime using various simulation settings.
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Affiliation(s)
- Hyojin Bae
- Department of Physiology, Gachon University College of Korean Medicine, Seongnam, South Korea
| | - Sa-Yoon Park
- Department of Physiology, Gachon University College of Korean Medicine, Seongnam, South Korea
| | - Sang Jeong Kim
- Department of Physiology, Seoul National University College of Medicine, Seoul, South Korea,*Correspondence: Sang Jeong Kim,
| | - Chang-Eop Kim
- Department of Physiology, Gachon University College of Korean Medicine, Seongnam, South Korea,Chang-Eop Kim,
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12
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Cerminara NL, Garwicz M, Darch H, Houghton C, Marple-Horvat DE, Apps R. Neuronal activity patterns in microcircuits of the cerebellar cortical C3 zone during reaching. J Physiol 2022; 600:5077-5099. [PMID: 36254104 PMCID: PMC10099968 DOI: 10.1113/jp282928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 10/07/2022] [Indexed: 01/06/2023] Open
Abstract
The cerebellum is the largest sensorimotor structure in the brain. A fundamental organizational feature of its cortex is its division into a series of rostrocaudally elongated zones. These are defined by their inputs from specific parts of the inferior olive and Purkinje cell output to specific cerebellar and vestibular nuclei. However, little is known about how patterns of neuronal activity in zones, and their microcircuit subdivisions, microzones, are related to behaviour in awake animals. In the present study, we investigated the organization of microzones within the C3 zone and their activity during a skilled forelimb reaching task in cats. Neurons in different microzones of the C3 zone, functionally determined by receptive field characteristics, differed in their patterns of activity during movement. Groups of Purkinje cells belonging to different receptive field classes, and therefore belonging to different microzones, were found to collectively encode different aspects of the reach controlled by the C3 zone. Our results support the hypothesis that the cerebellar C3 zone is organized and operates within a microzonal frame of reference, with a specific relationship between the sensory input to each microzone and its motor output. KEY POINTS: A defining feature of cerebellar organization is its division into a series of zones and smaller subunits termed microzones. Much of how zones and microzones are organized has been determined in anaesthetized preparations, and little is known about their function in awake animals. We recorded from neurons in the forelimb part of the C3 zone 'in action' by recording from single cerebellar cortical neurons located in different microzones defined by their peripheral receptive field properties during a forelimb reach-retrieval task in cats. Neurons from individual microzones had characteristic patterns of activity during movement, indicating that function is organized in relation to microcomplexes.
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Affiliation(s)
- Nadia L Cerminara
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Martin Garwicz
- Neuronano Research Centre and Birgit Rausing Centre for Medical Humanities, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Henry Darch
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
| | - Conor Houghton
- Department of Computer Science, University of Bristol, Bristol, UK
| | | | - Richard Apps
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, UK
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13
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Vijayan A, Diwakar S. A cerebellum inspired spiking neural network as a multi-model for pattern classification and robotic trajectory prediction. Front Neurosci 2022; 16:909146. [DOI: 10.3389/fnins.2022.909146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 11/02/2022] [Indexed: 11/29/2022] Open
Abstract
Spiking neural networks were introduced to understand spatiotemporal information processing in neurons and have found their application in pattern encoding, data discrimination, and classification. Bioinspired network architectures are considered for event-driven tasks, and scientists have looked at different theories based on the architecture and functioning. Motor tasks, for example, have networks inspired by cerebellar architecture where the granular layer recodes sparse representations of the mossy fiber (MF) inputs and has more roles in motor learning. Using abstractions from cerebellar connections and learning rules of deep learning network (DLN), patterns were discriminated within datasets, and the same algorithm was used for trajectory optimization. In the current work, a cerebellum-inspired spiking neural network with dynamics of cerebellar neurons and learning mechanisms attributed to the granular layer, Purkinje cell (PC) layer, and cerebellar nuclei interconnected by excitatory and inhibitory synapses was implemented. The model’s pattern discrimination capability was tested for two tasks on standard machine learning (ML) datasets and on following a trajectory of a low-cost sensor-free robotic articulator. Tuned for supervised learning, the pattern classification capability of the cerebellum-inspired network algorithm has produced more generalized models than data-specific precision models on smaller training datasets. The model showed an accuracy of 72%, which was comparable to standard ML algorithms, such as MLP (78%), Dl4jMlpClassifier (64%), RBFNetwork (71.4%), and libSVM-linear (85.7%). The cerebellar model increased the network’s capability and decreased storage, augmenting faster computations. Additionally, the network model could also implicitly reconstruct the trajectory of a 6-degree of freedom (DOF) robotic arm with a low error rate by reconstructing the kinematic parameters. The variability between the actual and predicted trajectory points was noted to be ± 3 cm (while moving to a position in a cuboid space of 25 × 30 × 40 cm). Although a few known learning rules were implemented among known types of plasticity in the cerebellum, the network model showed a generalized processing capability for a range of signals, modulating the data through the interconnected neural populations. In addition to potential use on sensor-free or feed-forward based controllers for robotic arms and as a generalized pattern classification algorithm, this model adds implications to motor learning theory.
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14
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Salazar Leon LE, Sillitoe RV. Potential Interactions Between Cerebellar Dysfunction and Sleep Disturbances in Dystonia. DYSTONIA 2022; 1. [PMID: 37065094 PMCID: PMC10099477 DOI: 10.3389/dyst.2022.10691] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2023]
Abstract
Dystonia is the third most common movement disorder. It causes debilitating twisting postures that are accompanied by repetitive and sometimes intermittent co- or over-contractions of agonist and antagonist muscles. Historically diagnosed as a basal ganglia disorder, dystonia is increasingly considered a network disorder involving various brain regions including the cerebellum. In certain etiologies of dystonia, aberrant motor activity is generated in the cerebellum and the abnormal signals then propagate through a “dystonia circuit” that includes the thalamus, basal ganglia, and cerebral cortex. Importantly, it has been reported that non-motor defects can accompany the motor symptoms; while their severity is not always correlated, it is hypothesized that common pathways may nevertheless be disrupted. In particular, circadian dysfunction and disordered sleep are common non-motor patient complaints in dystonia. Given recent evidence suggesting that the cerebellum contains a circadian oscillator, displays sleep-stage-specific neuronal activity, and sends robust long-range projections to several subcortical regions involved in circadian rhythm regulation, disordered sleep in dystonia may result from cerebellum-mediated dysfunction of the dystonia circuit. Here, we review the evidence linking dystonia, cerebellar network dysfunction, and cerebellar involvement in sleep. Together, these ideas may form the basis for the development of improved pharmacological and surgical interventions that could take advantage of cerebellar circuitry to restore normal motor function as well as non-motor (sleep) behaviors in dystonia.
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Affiliation(s)
- Luis E. Salazar Leon
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, Texas, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, Texas, 77030, USA
| | - Roy V. Sillitoe
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, Texas, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, Texas, USA
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
- Development, Disease Models & Therapeutics Graduate Program, Baylor College of Medicine, Houston, Texas, USA
- Jan and Dan Duncan Neurological Research Institute at Texas Children’s Hospital, Houston, Texas, 77030, USA
- Address correspondence to: Dr. Roy V. Sillitoe, Tel: 832-824-8913, Fax: 832-825-1251,
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15
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Fruzzetti L, Kalidindi HT, Antonietti A, Alessandro C, Geminiani A, Casellato C, Falotico E, D’Angelo E. Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and speed of saccadic eye movements. PLoS Comput Biol 2022; 18:e1010564. [PMID: 36194625 PMCID: PMC9565489 DOI: 10.1371/journal.pcbi.1010564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 10/14/2022] [Accepted: 09/13/2022] [Indexed: 11/18/2022] Open
Abstract
Saccadic eye-movements play a crucial role in visuo-motor control by allowing rapid foveation onto new targets. However, the neural processes governing saccades adaptation are not fully understood. Saccades, due to the short-time of execution (20-100 ms) and the absence of sensory information for online feedback control, must be controlled in a ballistic manner. Incomplete measurements of the movement trajectory, such as the visual endpoint error, are supposedly used to form internal predictions about the movement kinematics resulting in predictive control. In order to characterize the synaptic and neural circuit mechanisms underlying predictive saccadic control, we have reconstructed the saccadic system in a digital controller embedding a spiking neural network of the cerebellum with spike timing-dependent plasticity (STDP) rules driving parallel fiber-Purkinje cell long-term potentiation and depression (LTP and LTD). This model implements a control policy based on a dual plasticity mechanism, resulting in the identification of the roles of LTP and LTD in regulating the overall quality of saccade kinematics: it turns out that LTD increases the accuracy by decreasing visual error and LTP increases the peak speed. The control policy also required cerebellar PCs to be divided into two subpopulations, characterized by burst or pause responses. To our knowledge, this is the first model that explains in mechanistic terms the visual error and peak speed regulation of ballistic eye movements in forward mode exploiting spike-timing to regulate firing in different populations of the neuronal network. This elementary model of saccades could be extended and applied to other more complex cases in which single jerks are concatenated to compose articulated and coordinated movements.
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Affiliation(s)
- Lorenzo Fruzzetti
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera (Pisa), Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy
| | - Hari Teja Kalidindi
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, Universite Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium
- Institute of Neuroscience, Universite Catholique de Louvain, Ottignies-Louvain-la-Neuve, Belgium
- * E-mail: (HK); (EF)
| | - Alberto Antonietti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | - Cristiano Alessandro
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
- School of Medicine and Surgery/Sport and Exercise Medicine, University of Milano-Bicocca, Milan, Italy
| | - Alice Geminiani
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Claudia Casellato
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant’Anna, Pontedera (Pisa), Italy
- Department of Excellence in Robotics and AI, Scuola Superiore Sant’Anna, Pisa, Italy
- * E-mail: (HK); (EF)
| | - Egidio D’Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, Italy
- IRCCS Mondino Foundation, Pavia, Italy
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16
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Yang S, Wang J, Zhang N, Deng B, Pang Y, Azghadi MR. CerebelluMorphic: Large-Scale Neuromorphic Model and Architecture for Supervised Motor Learning. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2022; 33:4398-4412. [PMID: 33621181 DOI: 10.1109/tnnls.2021.3057070] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The cerebellum plays a vital role in motor learning and control with supervised learning capability, while neuromorphic engineering devises diverse approaches to high-performance computation inspired by biological neural systems. This article presents a large-scale cerebellar network model for supervised learning, as well as a cerebellum-inspired neuromorphic architecture to map the cerebellar anatomical structure into the large-scale model. Our multinucleus model and its underpinning architecture contain approximately 3.5 million neurons, upscaling state-of-the-art neuromorphic designs by over 34 times. Besides, the proposed model and architecture incorporate 3411k granule cells, introducing a 284 times increase compared to a previous study including only 12k cells. This large scaling induces more biologically plausible cerebellar divergence/convergence ratios, which results in better mimicking biology. In order to verify the functionality of our proposed model and demonstrate its strong biomimicry, a reconfigurable neuromorphic system is used, on which our developed architecture is realized to replicate cerebellar dynamics during the optokinetic response. In addition, our neuromorphic architecture is used to analyze the dynamical synchronization within the Purkinje cells, revealing the effects of firing rates of mossy fibers on the resonance dynamics of Purkinje cells. Our experiments show that real-time operation can be realized, with a system throughput of up to 4.70 times larger than previous works with high synaptic event rate. These results suggest that the proposed work provides both a theoretical basis and a neuromorphic engineering perspective for brain-inspired computing and the further exploration of cerebellar learning.
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17
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Enander JMD, Loeb GE, Jorntell H. A Model for Self-Organization of Sensorimotor Function: Spinal Interneuronal Integration. J Neurophysiol 2022; 127:1478-1495. [PMID: 35475709 PMCID: PMC9293245 DOI: 10.1152/jn.00054.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Control of musculoskeletal systems depends on integration of voluntary commands and somatosensory feedback in the complex neural circuits of the spinal cord. Particular connectivity patterns have been identified experimentally, and it has been suggested that these may result from the wide variety of transcriptional types that have been observed in spinal interneurons. We ask instead whether the details of these connectivity patterns (and perhaps many others) can arise as a consequence of Hebbian adaptation during early development. We constructed an anatomically simplified model plant system with realistic muscles and sensors and connected it to a recurrent, random neuronal network consisting of both excitatory and inhibitory neurons endowed with Hebbian learning rules. We then generated a wide set of randomized muscle twitches typical of those described during fetal development and allowed the network to learn. Multiple simulations consistently resulted in diverse and stable patterns of activity and connectivity that included subsets of the interneurons that were similar to 'archetypical' interneurons described in the literature. We also found that such learning led to an increased degree of cooperativity between interneurons when performing larger limb movements on which it had not been trained. Hebbian learning gives rise to rich sets of diverse interneurons whose connectivity reflects the mechanical properties of the plant. At least some of the transcriptomic diversity may reflect the effects of this process rather than the cause of the connectivity. Such a learning process seems better suited to respond to the musculoskeletal mutations that underlie the evolution of new species.
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Affiliation(s)
- Jonas M D Enander
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, Lund, Sweden
| | - Gerald E Loeb
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Henrik Jorntell
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, Lund, Sweden
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18
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Spaeth L, Isope P. What Can We Learn from Synaptic Connectivity Maps about Cerebellar Internal Models? THE CEREBELLUM 2022; 22:468-474. [PMID: 35391650 PMCID: PMC10126018 DOI: 10.1007/s12311-022-01392-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 03/05/2022] [Indexed: 11/26/2022]
Abstract
Abstract
The cerebellum is classically associated with fine motor control, motor learning, and timing of actions. However, while its anatomy is well described and many synaptic plasticity have been identified, the computation performed by the cerebellar cortex is still debated. We, here, review recent advances on how the description of the functional synaptic connectivity between granule cells and Purkinje cells support the hypothesis that the cerebellum stores internal models of the body coordinates. We propose that internal models are specific of the task and of the locomotor context of each individual.
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Affiliation(s)
- Ludovic Spaeth
- Institut des Neurosciences Cellulaires et Intégratives, CNRS, Université de Strasbourg, 67084, Strasbourg, France
- Dominick P Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Philippe Isope
- Institut des Neurosciences Cellulaires et Intégratives, CNRS, Université de Strasbourg, 67084, Strasbourg, France.
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19
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Enander JMD, Jones AM, Kirkland M, Hurless JC, Jorntell H, Loeb GE. A Model for Self-Organization of Sensorimotor Function: The Spinal Monosynaptic Loop. J Neurophysiol 2022; 127:1460-1477. [PMID: 35264006 PMCID: PMC9208450 DOI: 10.1152/jn.00242.2021] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Recent spinal cord literature abounds with descriptions of genetic preprogramming and the molecular control of circuit formation. In this paper, we explore to what extent circuit formation based on learning rather than preprogramming could explain the selective formation of the monosynaptic projections between muscle spindle primary afferents and homonymous motoneurons. We adjusted the initially randomized gains in the neural network according to a Hebbian plasticity rule while exercising the model system with spontaneous muscle activity patterns similar to those observed during early fetal development. Normal connectivity patterns developed only when we modeled β motoneurons, which are known to innervate both intrafusal and extrafusal muscle fibers in vertebrate muscles but were not considered in previous literature regarding selective formation of these synapses in animals with paralyzed muscles. It was also helpful to correctly model the greatly reduced contractility of extrafusal muscle fibers during early development. Stronger and more coordinated muscle activity patterns such as observed later during neonatal locomotion impaired projection selectivity. These findings imply a generic functionality of a musculoskeletal system to imprint important aspects of its mechanical dynamics onto a neural network, without specific preprogramming other than setting a critical period for the formation and maturation of this general pattern of connectivity. Such functionality would facilitate the successful evolution of new species with altered musculoskeletal anatomy, and it may help to explain patterns of connectivity and associated reflexes that appear during abnormal development. NEW & NOTEWORTHY A novel model of self-organization of early spinal circuitry based on a biologically realistic plant, sensors, and neuronal plasticity in conjunction with empirical observations of fetal development. Without explicit need for guiding genetic rules, connection matrices emerge that support functional self-organization of the mature pattern of Ia to motoneuron connectivity in the spinal circuitry.
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Affiliation(s)
- Jonas M D Enander
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, Lund, Sweden
| | - Adam M Jones
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Matthieu Kirkland
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Jordan Cole Hurless
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
| | - Henrik Jorntell
- Department of Experimental Medical Science, Faculty of Medicine, Lund University, Lund, Sweden
| | - Gerald E Loeb
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States
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20
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Spaeth L, Bahuguna J, Gagneux T, Dorgans K, Sugihara I, Poulain B, Battaglia D, Isope P. Cerebellar connectivity maps embody individual adaptive behavior in mice. Nat Commun 2022; 13:580. [PMID: 35102165 PMCID: PMC8803868 DOI: 10.1038/s41467-022-27984-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 12/13/2021] [Indexed: 11/16/2022] Open
Abstract
The cerebellar cortex encodes sensorimotor adaptation during skilled locomotor behaviors, however the precise relationship between synaptic connectivity and behavior is unclear. We studied synaptic connectivity between granule cells (GCs) and Purkinje cells (PCs) in murine acute cerebellar slices using photostimulation of caged glutamate combined with patch-clamp in developing or after mice adapted to different locomotor contexts. By translating individual maps into graph network entities, we found that synaptic maps in juvenile animals undergo critical period characterized by dissolution of their structure followed by the re-establishment of a patchy functional organization in adults. Although, in adapted mice, subdivisions in anatomical microzones do not fully account for the observed spatial map organization in relation to behavior, we can discriminate locomotor contexts with high accuracy. We also demonstrate that the variability observed in connectivity maps directly accounts for motor behavior traits at the individual level. Our findings suggest that, beyond general motor contexts, GC-PC networks also encode internal models underlying individual-specific motor adaptation. The variability in synaptic connectivity observed at the cerebellar granule cell - Purkinje cell connection in mice accounts for motor behavior traits at the individual level, suggesting that cerebellar networks encode internal models underlying individual-specific motor adaptation.
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21
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Sival DA, Noort SAMV, Tijssen MAJ, de Koning TJ, Verbeek DS. Developmental neurobiology of cerebellar and Basal Ganglia connections. Eur J Paediatr Neurol 2022; 36:123-129. [PMID: 34954622 DOI: 10.1016/j.ejpn.2021.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 10/03/2021] [Accepted: 12/01/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND The high prevalence of mixed phenotypes of Early Onset Ataxia (EOA) with comorbid dystonia has shifted the pathogenetic concept from the cerebellum towards the interconnected cerebellar motor network. This paper on EOA with comorbid dystonia (EOA-dystonia) explores the conceptual relationship between the motor phenotype and the cortico-basal-ganglia-ponto-cerebellar network. METHODS In EOA-dystonia, we reviewed anatomic-, genetic- and biochemical-studies on the comorbidity between ataxia and dystonia. RESULTS In a clinical EOA cohort, the prevalence of dystonia was over 60%. Both human and animal studies converge on the underlying role for the cortico-basal-ganglia-ponto-cerebellar network. Genetic -clinical and -in silico network studies reveal underlying biological pathways for energy production and neural signal transduction. CONCLUSIONS EOA-dystonia phenotypes are attributable to the cortico-basal-ganglia-ponto-cerebellar network, instead of to the cerebellum, alone. The underlying anatomic and pathogenetic pathways have clinical implications for our understanding of the heterogeneous phenotype, neuro-metabolic and genetic testing and potentially also for new treatment strategies, including neuro-modulation.
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Affiliation(s)
- Deborah A Sival
- Department of Pediatrics, University of Groningen, Groningen, the Netherlands.
| | - Suus A M van Noort
- Department of Neurology and University of Groningen, Groningen, the Netherlands
| | - Marina A J Tijssen
- Department of Neurology and University of Groningen, Groningen, the Netherlands
| | - Tom J de Koning
- Department of Neurology and University of Groningen, Groningen, the Netherlands
| | - Dineke S Verbeek
- Genetics University Medical Center, University of Groningen, Groningen, the Netherlands
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22
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Gilbert M. The Shape of Data: a Theory of the Representation of Information in the Cerebellar Cortex. THE CEREBELLUM 2021; 21:976-986. [PMID: 34902112 PMCID: PMC9596575 DOI: 10.1007/s12311-021-01352-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 11/28/2021] [Indexed: 11/30/2022]
Abstract
This paper presents a model of rate coding in the cerebellar cortex. The pathway of input to output of the cerebellum forms an anatomically repeating, functionally modular network, whose basic wiring is preserved across vertebrate taxa. Each network is bisected centrally by a functionally defined cell group, a microzone, which forms part of the cerebellar circuit. Input to a network may be from tens of thousands of concurrently active mossy fibres. The model claims to quantify the conversion of input rates into the code received by a microzone. Recoding on entry converts input rates into an internal code which is homogenised in the functional equivalent of an imaginary plane, occupied by the centrally positioned microzone. Homogenised means the code exists in any random sample of parallel fibre signals over a minimum number. The nature of the code and the regimented architecture of the cerebellar cortex mean that the threshold can be represented by space so that the threshold can be met by the physical dimensions of the Purkinje cell dendritic arbour and planar interneuron networks. As a result, the whole population of a microzone receives the same code. This is part of a mechanism which orchestrates functionally indivisible behaviour of the cerebellar circuit and is necessary for coordinated control of the output cells of the circuit. In this model, fine control of Purkinje cells is by input rates to the system and not by learning so that it is in conflict with the for-years-dominant supervised learning model.
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Affiliation(s)
- Mike Gilbert
- School of Psychology, University of Birmingham, Birmingham, UK.
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23
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Gilbert M. Gating by Memory: a Theory of Learning in the Cerebellum. THE CEREBELLUM 2021; 21:926-943. [PMID: 34757585 DOI: 10.1007/s12311-021-01325-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 08/24/2021] [Indexed: 11/30/2022]
Abstract
This paper presents a model of learning by the cerebellar circuit. In the traditional and dominant learning model, training teaches finely graded parallel fibre synaptic weights which modify transmission to Purkinje cells and to interneurons that inhibit Purkinje cells. Following training, input in a learned pattern drives a training-modified response. The function is that the naive response to input rates is displaced by a learned one, trained under external supervision. In the proposed model, there is no weight-controlled graduated balance of excitation and inhibition of Purkinje cells. Instead, the balance has two functional states-a switch-at synaptic, whole cell and microzone level. The paper is in two parts. The first is a detailed physiological argument for the synaptic learning function. The second uses the function in a computational simulation of pattern memory. Against expectation, this generates a predictable outcome from input chaos (real-world variables). Training always forces synaptic weights away from the middle and towards the limits of the range, causing them to polarise, so that transmission is either robust or blocked. All conditions teach the same outcome, such that all learned patterns receive the same, rather than a bespoke, effect on transmission. In this model, the function of learning is gating-that is, to select patterns that trigger output merely, and not to modify output. The outcome is memory-operated gate activation which operates a two-state balance of weight-controlled transmission. Group activity of parallel fibres also simultaneously contains a second code contained in collective rates, which varies independently of the pattern code. A two-state response to the pattern code allows faithful, and graduated, control of Purkinje cell firing by the rate code, at gated times.
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Affiliation(s)
- Mike Gilbert
- School of Psychology, University of Birmingham, Birmingham, UK.
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24
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Ho S, Lajaunie R, Lerat M, Le M, Crépel V, Loulier K, Livet J, Kessler JP, Marcaggi P. A stable proportion of Purkinje cell inputs from parallel fibers are silent during cerebellar maturation. Proc Natl Acad Sci U S A 2021; 118:e2024890118. [PMID: 34740966 PMCID: PMC8609448 DOI: 10.1073/pnas.2024890118] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/23/2021] [Indexed: 11/18/2022] Open
Abstract
Cerebellar Purkinje neurons integrate information transmitted at excitatory synapses formed by granule cells. Although these synapses are considered essential sites for learning, most of them appear not to transmit any detectable electrical information and have been defined as silent. It has been proposed that silent synapses are required to maximize information storage capacity and ensure its reliability, and hence to optimize cerebellar operation. Such optimization is expected to occur once the cerebellar circuitry is in place, during its maturation and the natural and steady improvement of animal agility. We therefore investigated whether the proportion of silent synapses varies over this period, from the third to the sixth postnatal week in mice. Selective expression of a calcium indicator in granule cells enabled quantitative mapping of presynaptic activity, while postsynaptic responses were recorded by patch clamp in acute slices. Through this approach and the assessment of two anatomical features (the distance that separates adjacent planar Purkinje dendritic trees and the synapse density), we determined the average excitatory postsynaptic potential per synapse. Its value was four to eight times smaller than responses from paired recorded detectable connections, consistent with over 70% of synapses being silent. These figures remained remarkably stable across maturation stages. According to the proposed role for silent synapses, our results suggest that information storage capacity and reliability are optimized early during cerebellar maturation. Alternatively, silent synapses may have roles other than adjusting the information storage capacity and reliability.
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Affiliation(s)
- Shu Ho
- Aix-Marseille Université, INSERM, INMED, Marseille 13009, France
| | - Rebecca Lajaunie
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom
| | - Marion Lerat
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris F-75012, France
| | - Mickaël Le
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris F-75012, France
| | - Valérie Crépel
- Aix-Marseille Université, INSERM, INMED, Marseille 13009, France
| | - Karine Loulier
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris F-75012, France
| | - Jean Livet
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris F-75012, France
| | - Jean-Pierre Kessler
- Aix-Marseille Université, CNRS, Institut de Biologie du Développement de Marseille, UMR 7288, Marseille 13288, France
| | - Païkan Marcaggi
- Aix-Marseille Université, INSERM, INMED, Marseille 13009, France;
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom
- Unité de Neurobiologie des Canaux Ioniques et de la Synapse, UMR 1072, INSERM, Aix-Marseille Université, Marseille 13015, France
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25
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Guo C, Huson V, Macosko EZ, Regehr WG. Graded heterogeneity of metabotropic signaling underlies a continuum of cell-intrinsic temporal responses in unipolar brush cells. Nat Commun 2021; 12:5491. [PMID: 34620856 PMCID: PMC8497507 DOI: 10.1038/s41467-021-22893-8] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 04/02/2021] [Indexed: 02/08/2023] Open
Abstract
Many neuron types consist of populations with continuously varying molecular properties. Here, we show a continuum of postsynaptic molecular properties in three types of neurons and assess the functional correlates in cerebellar unipolar brush cells (UBCs). While UBCs are generally thought to form discrete functional subtypes, with mossy fiber (MF) activation increasing firing in ON-UBCs and suppressing firing in OFF-UBCs, recent work also points to a heterogeneity of response profiles. Indeed, we find a continuum of response profiles that reflect the graded and inversely correlated expression of excitatory mGluR1 and inhibitory mGluR2/3 pathways. MFs coactivate mGluR2/3 and mGluR1 in many UBCs, leading to sequential inhibition-excitation because mGluR2/3-currents are faster. Additionally, we show that DAG-kinase controls mGluR1 response duration, and that graded DAG kinase levels correlate with systematic variation of response duration over two orders of magnitude. These results demonstrate that continuous variations in metabotropic signaling can generate a stable cell-autonomous basis for temporal integration and learning over multiple time scales.
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Affiliation(s)
- Chong Guo
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Vincent Huson
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Evan Z Macosko
- Broad Institute of Harvard and MIT, Stanley Center for Psychiatric Research, 450 Main St., Cambridge, MA, USA
| | - Wade G Regehr
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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26
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Stöckel A, Stewart TC, Eliasmith C. Connecting Biological Detail With Neural Computation: Application to the Cerebellar Granule-Golgi Microcircuit. Top Cogn Sci 2021; 13:515-533. [PMID: 34146453 DOI: 10.1111/tops.12536] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 04/21/2021] [Accepted: 04/22/2021] [Indexed: 11/29/2022]
Abstract
Neurophysiology and neuroanatomy constrain the set of possible computations that can be performed in a brain circuit. While detailed data on brain microcircuits is sometimes available, cognitive modelers are seldom in a position to take these constraints into account. One reason for this is the intrinsic complexity of accounting for biological mechanisms when describing cognitive function. In this paper, we present multiple extensions to the neural engineering framework (NEF), which simplify the integration of low-level constraints such as Dale's principle and spatially constrained connectivity into high-level, functional models. We focus on a model of eyeblink conditioning in the cerebellum, and, in particular, on systematically constructing temporal representations in the recurrent granule-Golgi microcircuit. We analyze how biological constraints impact these representations and demonstrate that our overall model is capable of reproducing key properties of eyeblink conditioning. Furthermore, since our techniques facilitate variation of neurophysiological parameters, we gain insights into why certain neurophysiological parameters may be as observed in nature. While eyeblink conditioning is a somewhat primitive form of learning, we argue that the same methods apply for more cognitive models as well. We implemented our extensions to the NEF in an open-source software library named "NengoBio" and hope that this work inspires similar attempts to bridge low-level biological detail and high-level function.
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Affiliation(s)
| | - Terrence C Stewart
- National Research Council of Canada, University of Waterloo Collaboration Centre
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27
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Abadia I, Naveros F, Garrido JA, Ros E, Luque NR. On Robot Compliance: A Cerebellar Control Approach. IEEE TRANSACTIONS ON CYBERNETICS 2021; 51:2476-2489. [PMID: 31647453 DOI: 10.1109/tcyb.2019.2945498] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The work presented here is a novel biological approach for the compliant control of a robotic arm in real time (RT). We integrate a spiking cerebellar network at the core of a feedback control loop performing torque-driven control. The spiking cerebellar controller provides torque commands allowing for accurate and coordinated arm movements. To compute these output motor commands, the spiking cerebellar controller receives the robot's sensorial signals, the robot's goal behavior, and an instructive signal. These input signals are translated into a set of evolving spiking patterns representing univocally a specific system state at every point of time. Spike-timing-dependent plasticity (STDP) is then supported, allowing for building adaptive control. The spiking cerebellar controller continuously adapts the torque commands provided to the robot from experience as STDP is deployed. Adaptive torque commands, in turn, help the spiking cerebellar controller to cope with built-in elastic elements within the robot's actuators mimicking human muscles (inherently elastic). We propose a natural integration of a bioinspired control scheme, based on the cerebellum, with a compliant robot. We prove that our compliant approach outperforms the accuracy of the default factory-installed position control in a set of tasks used for addressing cerebellar motor behavior: controlling six degrees of freedom (DoF) in smooth movements, fast ballistic movements, and unstructured scenario compliant movements.
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28
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Purkinje Neurons with Loss of STIM1 Exhibit Age-Dependent Changes in Gene Expression and Synaptic Components. J Neurosci 2021; 41:3777-3798. [PMID: 33737457 DOI: 10.1523/jneurosci.2401-20.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 02/26/2021] [Accepted: 03/01/2021] [Indexed: 12/13/2022] Open
Abstract
The stromal interaction molecule 1 (STIM1) is an ER-Ca2+ sensor and an essential component of ER-Ca2+ store operated Ca2+ entry. Loss of STIM1 affects metabotropic glutamate receptor 1 (mGluR1)-mediated synaptic transmission, neuronal Ca2+ homeostasis, and intrinsic plasticity in Purkinje neurons (PNs). Long-term changes of intracellular Ca2+ signaling in PNs led to neurodegenerative conditions, as evident in individuals with mutations of the ER-Ca2+ channel, the inositol 1,4,5-triphosphate receptor. Here, we asked whether changes in such intrinsic neuronal properties, because of loss of STIM1, have an age-dependent impact on PNs. Consequently, we analyzed mRNA expression profiles and cerebellar morphology in PN-specific STIM1 KO mice (STIM1PKO ) of both sexes across ages. Our study identified a requirement for STIM1-mediated Ca2+ signaling in maintaining the expression of genes belonging to key biological networks of synaptic function and neurite development among others. Gene expression changes correlated with altered patterns of dendritic morphology and greater innervation of PN dendrites by climbing fibers, in aging STIM1PKO mice. Together, our data identify STIM1 as an important regulator of Ca2+ homeostasis and neuronal excitability in turn required for maintaining the optimal transcriptional profile of PNs with age. Our findings are significant in the context of understanding how dysregulated calcium signals impact cellular mechanisms in multiple neurodegenerative disorders.SIGNIFICANCE STATEMENT In Purkinje neurons (PNs), the stromal interaction molecule 1 (STIM1) is required for mGluR1-dependent synaptic transmission, refilling of ER Ca2+ stores, regulation of spike frequency, and cerebellar memory consolidation. Here, we provide evidence for a novel role of STIM1 in maintaining the gene expression profile and optimal synaptic connectivity of PNs. Expression of genes related to neurite development and synaptic organization networks is altered in PNs with persistent loss of STIM1. In agreement with these findings the dendritic morphology of PNs and climbing fiber innervations on PNs also undergo significant changes with age. These findings identify a new role for dysregulated intracellular calcium signaling in neurodegenerative disorders and provide novel therapeutic insights.
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Short-Term Synaptic Plasticity Makes Neurons Sensitive to the Distribution of Presynaptic Population Firing Rates. eNeuro 2021; 8:ENEURO.0297-20.2021. [PMID: 33579731 PMCID: PMC8035045 DOI: 10.1523/eneuro.0297-20.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 01/14/2021] [Accepted: 01/19/2021] [Indexed: 12/25/2022] Open
Abstract
The ability to discriminate spikes that encode a particular stimulus from spikes produced by background activity is essential for reliable information processing in the brain. We describe how synaptic short-term plasticity (STP) modulates the output of presynaptic populations as a function of the distribution of the spiking activity and find a strong relationship between STP features and sparseness of the population code, which could solve this problem. Furthermore, we show that feedforward excitation followed by inhibition (FF-EI), combined with target-dependent STP, promote substantial increase in the signal gain even for considerable deviations from the optimal conditions, granting robustness to this mechanism. A simulated neuron driven by a spiking FF-EI network is reliably modulated as predicted by a rate analysis and inherits the ability to differentiate sparse signals from dense background activity changes of the same magnitude, even at very low signal-to-noise conditions. We propose that the STP-based distribution discrimination is likely a latent function in several regions such as the cerebellum and the hippocampus.
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Tang Y, An L, Yuan Y, Pei Q, Wang Q, Liu JK. Modulation of the dynamics of cerebellar Purkinje cells through the interaction of excitatory and inhibitory feedforward pathways. PLoS Comput Biol 2021; 17:e1008670. [PMID: 33566820 PMCID: PMC7909957 DOI: 10.1371/journal.pcbi.1008670] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 02/26/2021] [Accepted: 01/04/2021] [Indexed: 01/08/2023] Open
Abstract
The dynamics of cerebellar neuronal networks is controlled by the underlying building blocks of neurons and synapses between them. For which, the computation of Purkinje cells (PCs), the only output cells of the cerebellar cortex, is implemented through various types of neural pathways interactively routing excitation and inhibition converged to PCs. Such tuning of excitation and inhibition, coming from the gating of specific pathways as well as short-term plasticity (STP) of the synapses, plays a dominant role in controlling the PC dynamics in terms of firing rate and spike timing. PCs receive cascade feedforward inputs from two major neural pathways: the first one is the feedforward excitatory pathway from granule cells (GCs) to PCs; the second one is the feedforward inhibition pathway from GCs, via molecular layer interneurons (MLIs), to PCs. The GC-PC pathway, together with short-term dynamics of excitatory synapses, has been a focus over past decades, whereas recent experimental evidence shows that MLIs also greatly contribute to controlling PC activity. Therefore, it is expected that the diversity of excitation gated by STP of GC-PC synapses, modulated by strong inhibition from MLI-PC synapses, can promote the computation performed by PCs. However, it remains unclear how these two neural pathways are interacted to modulate PC dynamics. Here using a computational model of PC network installed with these two neural pathways, we addressed this question to investigate the change of PC firing dynamics at the level of single cell and network. We show that the nonlinear characteristics of excitatory STP dynamics can significantly modulate PC spiking dynamics mediated by inhibition. The changes in PC firing rate, firing phase, and temporal spike pattern, are strongly modulated by these two factors in different ways. MLIs mainly contribute to variable delays in the postsynaptic action potentials of PCs while modulated by excitation STP. Notably, the diversity of synchronization and pause response in the PC network is governed not only by the balance of excitation and inhibition, but also by the synaptic STP, depending on input burst patterns. Especially, the pause response shown in the PC network can only emerge with the interaction of both pathways. Together with other recent findings, our results show that the interaction of feedforward pathways of excitation and inhibition, incorporated with synaptic short-term dynamics, can dramatically regulate the PC activities that consequently change the network dynamics of the cerebellar circuit. It is well known that the dynamics of neuronal networks are controlled by various types of neural pathways that are interactively routing excitation and inhibition converged to postsynaptic neurons. In addition, gating of a specific neural pathway is enhanced by short-term plasticity of the synapses between neurons. However, it remains unclear how a combination of these factors, the strengths of excitation and inhibition, and their short-term dynamics respectively, contributes to the dynamics of single cells and neuronal networks. Using a network model of cerebellar Purkinje cells embedded with the feedforward excitatory pathway from granule cells and feedforward inhibition pathway of molecular layer interneurons. We show that the dynamics of firing rate, firing phase, and temporal spike pattern are notably yet differently modulated by these two pathways. At the single cell level, excitatory short-term plasticity nonlinearly modulates the input-output relationship of firing activity. At the network level, the diversity of synchronization and pause response is governed not only by the balance of excitation and inhibition, but also by synaptic short-term dynamics. Only when both neural pathways are incorporated, there is a strong pause response shown in the network. Our results, together with recent in vivo experimental observations in the cerebellum, show that the interaction of feedforward pathways of excitation and inhibition, together with synaptic short-term dynamics, can dramatically change the network dynamics of Purkinje cells.
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Affiliation(s)
- Yuanhong Tang
- School of Computer Science and Technology, Xidian University, Xi’an, China
| | - Lingling An
- School of Computer Science and Technology, Xidian University, Xi’an, China
- * E-mail: (LA); (JKL)
| | - Ye Yuan
- School of Computer Science and Technology, Xidian University, Xi’an, China
| | - Qingqi Pei
- School of Telecommunication Engineering, Xidian University, Xi’an, China
| | - Quan Wang
- School of Computer Science and Technology, Xidian University, Xi’an, China
| | - Jian K. Liu
- Centre for Systems Neuroscience, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, United Kingdom
- * E-mail: (LA); (JKL)
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Gilbert M, Chris Miall R. How and Why the Cerebellum Recodes Input Signals: An Alternative to Machine Learning. Neuroscientist 2021; 28:206-221. [PMID: 33559532 PMCID: PMC9136479 DOI: 10.1177/1073858420986795] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Mossy fiber input to the cerebellum is received by granule cells where it is thought to be recoded into internal signals received by Purkinje cells, which alone carry the output of the cerebellar cortex. In any neural network, variables are contained in groups of signals as well as signals themselves—which cells are active and how many, for example, and statistical variables coded in rates, such as the mean and range, and which rates are strongly represented, in a defined population. We argue that the primary function of recoding is to confine translation to an effect of some variables and not others—both where input is recoded into internal signals and the translation downstream of internal signals into an effect on Purkinje cells. The cull of variables is harsh. Internal signaling is group coded. This allows coding to exploit statistics for a reliable and precise effect despite needing to work with high-dimensional input which is a highly unpredictably variable. An important effect is to normalize eclectic input signals, so that the basic, repeating cerebellar circuit, preserved across taxa, does not need to specialize (within regional variations). With this model, there is no need to slavishly conserve or compute data coded in single signals. If we are correct, a learning algorithm—for years, a mainstay of cerebellar modeling—would be redundant.
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Affiliation(s)
- Mike Gilbert
- School of Psychology, University of Birmingham, Birmingham, UK
| | - R Chris Miall
- School of Psychology, University of Birmingham, Birmingham, UK
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32
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Wilson ED, Assaf T, Rossiter JM, Dean P, Porrill J, Anderson SR, Pearson MJ. A multizone cerebellar chip for bioinspired adaptive robot control and sensorimotor processing. J R Soc Interface 2021; 18:20200750. [PMID: 33499769 DOI: 10.1098/rsif.2020.0750] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The cerebellum is a neural structure essential for learning, which is connected via multiple zones to many different regions of the brain, and is thought to improve human performance in a large range of sensory, motor and even cognitive processing tasks. An intriguing possibility for the control of complex robotic systems would be to develop an artificial cerebellar chip with multiple zones that could be similarly connected to a variety of subsystems to optimize performance. The novel aim of this paper, therefore, is to propose and investigate a multizone cerebellar chip applied to a range of tasks in robot adaptive control and sensorimotor processing. The multizone cerebellar chip was evaluated using a custom robotic platform consisting of an array of tactile sensors driven by dielectric electroactive polymers mounted upon a standard industrial robot arm. The results demonstrate that the performance in each task was improved by the concurrent, stable learning in each cerebellar zone. This paper, therefore, provides the first empirical demonstration that a synthetic, multizone, cerebellar chip could be embodied within existing robotic systems to improve performance in a diverse range of tasks, much like the cerebellum in a biological system.
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Affiliation(s)
- Emma D Wilson
- Lancaster University, School of Computing and Communications, Lancaster, UK
| | - Tareq Assaf
- University of Bath, Department of Electronic and Electrical Engineering, Bath, UK
| | | | - Paul Dean
- University of Sheffield, Department of Psychology, Sheffield, UK
| | - John Porrill
- University of Sheffield, Department of Psychology, Sheffield, UK
| | - Sean R Anderson
- University of Sheffield, Department of Automatic Control and Systems Engineering, Sheffield, UK
| | - Martin J Pearson
- University of the West of England, Bristol Robotics Laboratory, Bristol, UK
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Gating by Functionally Indivisible Cerebellar Circuits: a Hypothesis. THE CEREBELLUM 2021; 20:518-532. [PMID: 33464470 PMCID: PMC8360902 DOI: 10.1007/s12311-020-01223-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Accepted: 12/01/2020] [Indexed: 11/08/2022]
Abstract
The attempt to understand the cerebellum has been dominated for years by supervised learning models. The central idea is that a learning algorithm modifies transmission strength at repeatedly co-active synapses, creating memories stored as finely calibrated synaptic weights. As a result, Purkinje cells, usually the de facto output cells of these models, acquire a modified response to input in a remembered pattern. This paper proposes an alternative model of pattern memory in which the function of a match is permissive, allowing but not driving output, and accordingly controlling the timing of output but not the rate of firing by Purkinje cells. Learning does not result in graded synaptic weights. There is no supervised learning algorithm or memory of individual patterns, which, like graded weights, are unnecessary to explain the evidence. Instead, patterns are classed as simply either known or not, at the level of input to a functional population of 100s of Purkinje cells (a microzone). The standard is strict. If only a handful of Purkinje cells receive a mismatch output of the whole circuit is blocked. Only if there is a full and accurate match are projection neurons in deep nuclei, which carry the output of most circuits, released from default inhibitory restraint. Purkinje cell firing at those times is a linear function of input rates. There is no effect of modification of synaptic transmission except to either allow or block output.
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Effect of diverse recoding of granule cells on optokinetic response in a cerebellar ring network with synaptic plasticity. Neural Netw 2020; 134:173-204. [PMID: 33316723 DOI: 10.1016/j.neunet.2020.11.014] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 11/12/2020] [Accepted: 11/24/2020] [Indexed: 11/21/2022]
Abstract
We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varying the connection probability pc from Golgi to GR cells. For an optimal value of pc∗(=0.06), individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree Lg, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying pc from pc∗, we find that a plot of saturated learning gain degree Lg∗ versus pc forms a bell-shaped curve with a peak at pc∗ (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation.
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Dellatolas G, Câmara-Costa H. The role of cerebellum in the child neuropsychological functioning. HANDBOOK OF CLINICAL NEUROLOGY 2020; 173:265-304. [PMID: 32958180 DOI: 10.1016/b978-0-444-64150-2.00023-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
This chapter proposes a review of neuropsychologic and behavior findings in pediatric pathologies of the cerebellum, including cerebellar malformations, pediatric ataxias, cerebellar tumors, and other acquired cerebellar injuries during childhood. The chapter also contains reviews of the cerebellar mutism/posterior fossa syndrome, reported cognitive associations with the development of the cerebellum in typically developing children and subjects born preterm, and the role of the cerebellum in neurodevelopmental disorders such as autism spectrum disorders and developmental dyslexia. Cognitive findings in pediatric cerebellar disorders are considered in the context of known cerebellocerebral connections, internal cellular organization of the cerebellum, the idea of a universal cerebellar transform and computational internal models, and the role of the cerebellum in specific cognitive and motor functions, such as working memory, language, timing, or control of eye movements. The chapter closes with a discussion of the strengths and weaknesses of the cognitive affective syndrome as it has been described in children and some conclusions and perspectives.
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Affiliation(s)
- Georges Dellatolas
- GRC 24, Handicap Moteur et Cognitif et Réadaptation, Sorbonne Université, Paris, France.
| | - Hugo Câmara-Costa
- GRC 24, Handicap Moteur et Cognitif et Réadaptation, Sorbonne Université, Paris, France; Centre d'Etudes en Santé des Populations, INSERM U1018, Paris, France
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Longley M, Ballard J, Andres-Alonso M, Varatharajah RC, Cuthbert H, Yeo CH. A Patterned Architecture of Monoaminergic Afferents in the Cerebellar Cortex: Noradrenergic and Serotonergic Fibre Distributions within Lobules and Parasagittal Zones. Neuroscience 2020; 462:106-121. [PMID: 32949672 DOI: 10.1016/j.neuroscience.2020.09.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 08/28/2020] [Accepted: 09/01/2020] [Indexed: 12/23/2022]
Abstract
The geometry of the glutamatergic mossy-parallel fibre and climbing fibre inputs to cerebellar cortical Purkinje cells has powerfully influenced thinking about cerebellar functions. The compartmentation of the cerebellum into parasagittal zones, identifiable in olivo-cortico-nuclear projections, and the trajectories of the parallel fibres, transverse to these zones and following the long axes of the cortical folia, are particularly important. Two monoaminergic afferent systems, the serotonergic and noradrenergic, are major inputs to the cerebellar cortex but their architecture and relationship with the cortical geometry are poorly understood. Immunohistochemistry for the serotonin transporter (SERT) and for the noradrenaline transporter (NET) revealed strong anisotropy of these afferent fibres in the molecular layer of rat cerebellar cortex. Individual serotonergic fibres travel predominantly medial-lateral, along the long axes of the cortical folia, similar to parallel fibres and Zebrin II immunohistochemistry revealed that they can influence multiple zones. In contrast, individual noradrenergic fibres run predominantly parasagittally with rostral-caudal extents significantly longer than their medial-lateral deviations. Their local area of influence has similarities in form and size to those of identified microzones. Within the molecular layer, the orthogonal trajectories of these two afferent systems suggest different information processing. An individual serotonergic fibre must influence all zones and microzones within its medial-lateral trajectory. In contrast, noradrenergic fibres can influence smaller cortical territories, potentially as limited as a microzone. Evidence is emerging that these monoaminergic systems may not supply a global signal to all of their targets and their potential for cerebellar cortical functions is discussed.
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Affiliation(s)
- Michael Longley
- Dept. Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom.
| | - John Ballard
- Dept. Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom.
| | - Maria Andres-Alonso
- Dept. Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom.
| | | | - Hadleigh Cuthbert
- Dept. Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom.
| | - Christopher H Yeo
- Dept. Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6BT, United Kingdom.
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37
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Ma M, Futia GL, de Souza FMS, Ozbay BN, Llano I, Gibson EA, Restrepo D. Molecular layer interneurons in the cerebellum encode for valence in associative learning. Nat Commun 2020; 11:4217. [PMID: 32868778 PMCID: PMC7459332 DOI: 10.1038/s41467-020-18034-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 07/31/2020] [Indexed: 11/09/2022] Open
Abstract
The cerebellum plays a crucial role in sensorimotor and associative learning. However, the contribution of molecular layer interneurons (MLIs) to these processes is not well understood. We used two-photon microscopy to study the role of ensembles of cerebellar MLIs in a go-no go task where mice obtain a sugar water reward if they lick a spout in the presence of the rewarded odorant and avoid a timeout when they refrain from licking for the unrewarded odorant. In naive animals the MLI responses did not differ between the odorants. With learning, the rewarded odorant elicited a large increase in MLI calcium responses, and the identity of the odorant could be decoded from the differential response. Importantly, MLIs switched odorant responses when the valence of the stimuli was reversed. Finally, mice took a longer time to refrain from licking in the presence of the unrewarded odorant and had difficulty becoming proficient when MLIs were inhibited by chemogenetic intervention. Our findings support a role for MLIs in learning valence in the cerebellum.
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Affiliation(s)
- Ming Ma
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Gregory L Futia
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Fabio M Simoes de Souza
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
- Center for Mathematics, Computation and Cognition, Federal University of ABC, Sao Bernardo do Campo, SP, Brazil
| | - Baris N Ozbay
- Intelligent Imaging Innovations, Denver, CO, 80216, USA
| | - Isabel Llano
- Saints Pères Paris Institute for Neurosciences, Université Paris Descartes, 75006, Paris, France
| | - Emily A Gibson
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Diego Restrepo
- Neuroscience Graduate Program, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.
- Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA.
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Multiple signals evoked by unisensory stimulation converge onto cerebellar granule and Purkinje cells in mice. Commun Biol 2020; 3:381. [PMID: 32669638 PMCID: PMC7363865 DOI: 10.1038/s42003-020-1110-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/25/2020] [Indexed: 12/27/2022] Open
Abstract
The cerebellum receives signals directly from peripheral sensory systems and indirectly from the neocortex. Even a single tactile stimulus can activate both of these pathways. Here we report how these different types of signals are integrated in the cerebellar cortex. We used in vivo whole-cell recordings from granule cells and unit recordings from Purkinje cells in mice in which primary somatosensory cortex (S1) could be optogenetically inhibited. Tactile stimulation of the upper lip produced two-phase granule cell responses (with latencies of ~8 ms and 29 ms), for which only the late phase was S1 dependent. In Purkinje cells, complex spikes and the late phase of simple spikes were S1 dependent. These results indicate that individual granule cells combine convergent inputs from the periphery and neocortex and send their outputs to Purkinje cells, which then integrate those signals with climbing fiber signals from the neocortex.
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Translation information processing is regulated by protein kinase C-dependent mechanism in Purkinje cells in murine posterior vermis. Proc Natl Acad Sci U S A 2020; 117:17348-17358. [PMID: 32636261 DOI: 10.1073/pnas.2002177117] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The cerebellar posterior vermis generates an estimation of our motion (translation) and orientation (tilt) in space using cues originating from semicircular canals and otolith organs. Theoretical work has laid out the basic computations necessary for this signal transformation, but details on the cellular loci and mechanisms responsible are lacking. Using a multicomponent modeling approach, we show that canal and otolith information are spatially and temporally matched in mouse posterior vermis Purkinje cells and that Purkinje cell responses combine translation and tilt information. Purkinje cell-specific inhibition of protein kinase C decreased and phase-shifted the translation component of Purkinje cell responses, but did not affect the tilt component. Our findings suggest that translation and tilt signals reach Purkinje cells via separate information pathways and that protein kinase C-dependent mechanisms regulate translation information processing in cerebellar cortex output neurons.
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40
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Bao J, Graupner M, Astorga G, Collin T, Jalil A, Indriati DW, Bradley J, Shigemoto R, Llano I. Synergism of type 1 metabotropic and ionotropic glutamate receptors in cerebellar molecular layer interneurons in vivo. eLife 2020; 9:56839. [PMID: 32401196 PMCID: PMC7220378 DOI: 10.7554/elife.56839] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 04/27/2020] [Indexed: 11/16/2022] Open
Abstract
Type 1 metabotropic glutamate receptors (mGluR1s) are key elements in neuronal signaling. While their function is well documented in slices, requirements for their activation in vivo are poorly understood. We examine this question in adult mice in vivo using 2-photon imaging of cerebellar molecular layer interneurons (MLIs) expressing GCaMP. In anesthetized mice, parallel fiber activation evokes beam-like Cai rises in postsynaptic MLIs which depend on co-activation of mGluR1s and ionotropic glutamate receptors (iGluRs). In awake mice, blocking mGluR1 decreases Cai rises associated with locomotion. In vitro studies and freeze-fracture electron microscopy show that the iGluR-mGluR1 interaction is synergistic and favored by close association of the two classes of receptors. Altogether our results suggest that mGluR1s, acting in synergy with iGluRs, potently contribute to processing cerebellar neuronal signaling under physiological conditions.
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Affiliation(s)
- Jin Bao
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France.,The Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Michael Graupner
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France
| | - Guadalupe Astorga
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France
| | - Thibault Collin
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France
| | - Abdelali Jalil
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France
| | - Dwi Wahyu Indriati
- Division of Cerebral Structure, National Institute for Physiological Sciences, The Graduate University for Advanced Studies (Sokendai), Okazaki, Japan
| | - Jonathan Bradley
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France.,Institut de Biologie de l'Ecole Normale Superieure (IBENS), Ecole Normale Superieure, CNRS, INSERM, PSL Research University, Paris, France
| | - Ryuichi Shigemoto
- Division of Cerebral Structure, National Institute for Physiological Sciences, The Graduate University for Advanced Studies (Sokendai), Okazaki, Japan.,IST Austria, Klosterneuburg, Austria
| | - Isabel Llano
- Université de Paris, CNRS, SPPIN - Saints-Pères Paris Institute for the Neurosciences, Paris, France
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Tanaka H, Ishikawa T, Lee J, Kakei S. The Cerebro-Cerebellum as a Locus of Forward Model: A Review. Front Syst Neurosci 2020; 14:19. [PMID: 32327978 PMCID: PMC7160920 DOI: 10.3389/fnsys.2020.00019] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 03/20/2020] [Indexed: 01/16/2023] Open
Abstract
This review surveys physiological, behavioral, and morphological evidence converging to the view of the cerebro-cerebellum as loci of internal forward models. The cerebro-cerebellum, the phylogenetically newest expansion in the cerebellum, receives convergent inputs from cortical, subcortical, and spinal sources, and is thought to perform the predictive computation for both motor control, motor learning, and cognitive functions. This predictive computation is known as an internal forward model. First, we elucidate the theoretical foundations of an internal forward model and its role in motor control and motor learning within the framework of the optimal feedback control model. Then, we discuss a neural mechanism that generates various patterns of outputs from the cerebro-cerebellum. Three lines of supporting evidence for the internal-forward-model hypothesis are presented in detail. First, we provide physiological evidence that the cerebellar outputs (activities of dentate nucleus cells) are predictive for the cerebellar inputs [activities of mossy fibers (MFs)]. Second, we provide behavioral evidence that a component of movement kinematics is predictive for target motion in control subjects but lags behind a target motion in patients with cerebellar ataxia. Third, we provide morphological evidence that the cerebellar cortex and the dentate nucleus receive separate MF projections, a prerequisite for optimal estimation. Finally, we speculate that the predictive computation in the cerebro-cerebellum could be deployed to not only motor control but also to non-motor, cognitive functions. This review concludes that the predictive computation of the internal forward model is the unifying algorithmic principle for understanding diverse functions played by the cerebro-cerebellum.
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Affiliation(s)
- Hirokazu Tanaka
- Japan Advanced Institute of Science and Technology, Nomi, Japan
| | | | | | - Shinji Kakei
- Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
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Wang Y, Xu Q, Zuo C, Zhao L, Hao L. Longitudinal Changes of Cerebellar Thickness in Autism Spectrum Disorder. Neurosci Lett 2020; 728:134949. [PMID: 32278028 DOI: 10.1016/j.neulet.2020.134949] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2020] [Revised: 03/24/2020] [Accepted: 03/30/2020] [Indexed: 10/24/2022]
Abstract
Many studies have reported abnormal cerebellar volume in patients with autism spectrum disorder (ASD) and that this abnormal volume can change with age. In the present study, we used CERES, an automated and reliable quantitative analysis tool, and adopted a longitudinal design to examine developmental changes in the cerebellar lobular thickness in ASD and quantified the relationship between cerebellar thickness development and clinical symptoms. Nineteen individuals with ASD (16 males; age, 12.53 ± 2.34 years at baseline, interval: 2.33 years) and 14 typically developing controls (TD; 12 males; age, 13.50 ± 1.77 years at baseline, interval: 2.31 years) underwent T1-weighted magnetic resonance imaging at two time points. To explore the relationship between cerebellar lobular thickness and the symptoms of ASD, the correlation of Autism Diagnostic Observation Schedule (ADOS) score with lobular thickness data was calculated. The cerebellar lobule thickness decreased in the right Crus II and the Crus II asymmetry was reduced in individuals with ASD. The reduction in lobular thickness and the asymmetry in Crus II were associated with the severity of stereotyped behavior symptoms. Structural differences and behavioral correlations were concentrated in the right cerebellar Crus II. These results emphasize the importance of the potential functional effect of structural differences in cerebellar subregions on ASD and suggest that the changes of thickness in the right cerebellar Crus II are related to the core profile of ASD.
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Affiliation(s)
- Yanpei Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Jiangsu Provincial Key Laboratory of Special Children's Impairment and Intervention, Nanjing Normal University of Special Education, Nanjing, China
| | - Qinfang Xu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Jiangsu Provincial Key Laboratory of Special Children's Impairment and Intervention, Nanjing Normal University of Special Education, Nanjing, China.
| | - Chenyi Zuo
- College of Educational Science, Anhui Normal University, Wuhu, China
| | - Liying Zhao
- Psychiatry Research Center, Beijing HuiLongGuan Hospital, Peking University, Beijing, China
| | - Lei Hao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
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Kobayashi T, Fukami H, Ishikawa E, Shibata K, Kubota M, Kondo H, Sahara Y. An fMRI Study of the Brain Network Involved in Teeth Tapping in Elderly Adults. Front Aging Neurosci 2020; 12:32. [PMID: 32256334 PMCID: PMC7090023 DOI: 10.3389/fnagi.2020.00032] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 02/03/2020] [Indexed: 11/18/2022] Open
Abstract
Cortical activity during jaw movement has been analyzed using various non-invasive brain imaging methods, but the contribution of orofacial sensory input to voluntary jaw movements remains unclear. In this study, we used functional magnetic resonance imaging (fMRI) to observe brain activities during a simple teeth tapping task in adult dentulous (AD), older dentulous (OD), and older edentulous subjects who wore dentures (OEd) or did not wear dentures (OE) to analyze their functional network connections. (1) To assess the effect of age on natural activation patterns during teeth tapping, a comparison of groups with natural dentition—AD and OD—was undertaken. A general linear model analysis indicated that the major activated site in the AD group was the primary sensory cortex (SI) and motor cortex (MI) (p < 0.05, family wise error corrected). In the OD group, teeth tapping induced brain activity at various foci (p < 0.05, family wise error corrected), including the SI, MI, insula cortex, supplementary motor cortex (SMC)/premotor cortex (PMA), cerebellum, thalamus, and basal ganglia in each group. (2) Group comparisons between the OD and OEd subjects showed decreased activity in the SI, MI, Brodmann’s area 6 (BA6), thalamus (ventral posteromedial nucleus, VPM), basal ganglia, and insular cortex (p ¡ 0.005, uncorrected). This suggested that the decreased S1/M1 activity in the OEd group was related to missing teeth, which led to reduced periodontal afferents. (3) A conjunction analysis in the OD and OEd/OE groups revealed that commonly activated areas were the MI, SI, cerebellum, BA6, thalamus (VPM), and basal ganglia (putamen; p < 0.05, FWE corrected). These areas have been associated with voluntary movements. (4) Psychophysiological interaction analysis (OEd vs OE) showed that subcortical and cortical structures, such as the MI, SI, DLPFC, SMC/PMA, insula cortex, basal ganglia, and cerebellum, likely function as hubs and form an integrated network that participates in the control of teeth tapping. These results suggest that oral sensory inputs are involved in the control of teeth tapping through feedforward control of intended movements, as well as feedback control of ongoing movements.
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Affiliation(s)
- T Kobayashi
- Department of Prosthodontics and Oral Implantology, School of Dentistry, Iwate Medical University, Morioka, Japan
| | - H Fukami
- Department of Physiology, School of Dentistry, Iwate Medical University, Shiwa-gun, Japan.,Department of Oral Health Sciences, Faculty of Nursing and Health Care, Baika Women's University, Osaka, Japan
| | - E Ishikawa
- Department of Physiology, School of Dentistry, Iwate Medical University, Shiwa-gun, Japan
| | - K Shibata
- Department of Physiology, School of Dentistry, Iwate Medical University, Shiwa-gun, Japan
| | - M Kubota
- Department of Prosthodontics and Oral Implantology, School of Dentistry, Iwate Medical University, Morioka, Japan
| | - H Kondo
- Department of Prosthodontics and Oral Implantology, School of Dentistry, Iwate Medical University, Morioka, Japan
| | - Y Sahara
- Department of Physiology, School of Dentistry, Iwate Medical University, Shiwa-gun, Japan
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Anderson SR, Porrill J, Dean P. World Statistics Drive Learning of Cerebellar Internal Models in Adaptive Feedback Control: A Case Study Using the Optokinetic Reflex. Front Syst Neurosci 2020; 14:11. [PMID: 32269515 PMCID: PMC7111124 DOI: 10.3389/fnsys.2020.00011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 02/07/2020] [Indexed: 01/06/2023] Open
Abstract
The cerebellum is widely implicated in having an important role in adaptive motor control. Many of the computational studies on cerebellar motor control to date have focused on the associated architecture and learning algorithms in an effort to further understand cerebellar function. In this paper we switch focus to the signals driving cerebellar adaptation that arise through different motor behavior. To do this, we investigate computationally the contribution of the cerebellum to the optokinetic reflex (OKR), a visual feedback control scheme for image stabilization. We develop a computational model of the adaptation of the cerebellar response to the world velocity signals that excite the OKR (where world velocity signals are used to emulate head velocity signals when studying the OKR in head-fixed experimental laboratory conditions). The results show that the filter learnt by the cerebellar model is highly dependent on the power spectrum of the colored noise world velocity excitation signal. Thus, the key finding here is that the cerebellar filter is determined by the statistics of the OKR excitation signal.
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Affiliation(s)
- Sean R. Anderson
- Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, United Kingdom
| | - John Porrill
- Department of Psychology, University of Sheffield, Sheffield, United Kingdom
| | - Paul Dean
- Department of Psychology, University of Sheffield, Sheffield, United Kingdom
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Straub I, Witter L, Eshra A, Hoidis M, Byczkowicz N, Maas S, Delvendahl I, Dorgans K, Savier E, Bechmann I, Krueger M, Isope P, Hallermann S. Gradients in the mammalian cerebellar cortex enable Fourier-like transformation and improve storing capacity. eLife 2020; 9:e51771. [PMID: 32022688 PMCID: PMC7002074 DOI: 10.7554/elife.51771] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 12/20/2019] [Indexed: 12/28/2022] Open
Abstract
Cerebellar granule cells (GCs) make up the majority of all neurons in the vertebrate brain, but heterogeneities among GCs and potential functional consequences are poorly understood. Here, we identified unexpected gradients in the biophysical properties of GCs in mice. GCs closer to the white matter (inner-zone GCs) had higher firing thresholds and could sustain firing with larger current inputs than GCs closer to the Purkinje cell layer (outer-zone GCs). Dynamic Clamp experiments showed that inner- and outer-zone GCs preferentially respond to high- and low-frequency mossy fiber inputs, respectively, enabling dispersion of the mossy fiber input into its frequency components as performed by a Fourier transformation. Furthermore, inner-zone GCs have faster axonal conduction velocity and elicit faster synaptic potentials in Purkinje cells. Neuronal network modeling revealed that these gradients improve spike-timing precision of Purkinje cells and decrease the number of GCs required to learn spike-sequences. Thus, our study uncovers biophysical gradients in the cerebellar cortex enabling a Fourier-like transformation of mossy fiber inputs.
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Affiliation(s)
- Isabelle Straub
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Laurens Witter
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research (CNCR)VU UniversityAmsterdamNetherlands
| | - Abdelmoneim Eshra
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Miriam Hoidis
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Niklas Byczkowicz
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Sebastian Maas
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Igor Delvendahl
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Kevin Dorgans
- Institut des Neurosciences Cellulaires et IntégrativesCNRS, Université de StrasbourgStrasbourgFrance
| | - Elise Savier
- Institut des Neurosciences Cellulaires et IntégrativesCNRS, Université de StrasbourgStrasbourgFrance
| | - Ingo Bechmann
- Institute of Anatomy, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Martin Krueger
- Institute of Anatomy, Medical FacultyLeipzig UniversityLeipzigGermany
| | - Philippe Isope
- Institut des Neurosciences Cellulaires et IntégrativesCNRS, Université de StrasbourgStrasbourgFrance
| | - Stefan Hallermann
- Carl-Ludwig-Institute for Physiology, Medical FacultyLeipzig UniversityLeipzigGermany
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Andrews DS, Lee JK, Solomon M, Rogers SJ, Amaral DG, Nordahl CW. A diffusion-weighted imaging tract-based spatial statistics study of autism spectrum disorder in preschool-aged children. J Neurodev Disord 2019; 11:32. [PMID: 31839001 PMCID: PMC6913008 DOI: 10.1186/s11689-019-9291-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 11/11/2019] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND The core symptoms of autism spectrum disorder (ASD) are widely theorized to result from altered brain connectivity. Diffusion-weighted magnetic resonance imaging (DWI) has been a versatile method for investigating underlying microstructural properties of white matter (WM) in ASD. Despite phenotypic and etiological heterogeneity, DWI studies in majority male samples of older children, adolescents, and adults with ASD have largely reported findings of decreased fractional anisotropy (FA) across several commissural, projection, and association fiber tracts. However, studies in preschool-aged children (i.e., < 30-40 months) suggest individuals with ASD have increased measures of WM FA earlier in development. METHODS We analyzed 127 individuals with ASD (85♂, 42♀) and 54 typically developing (TD) controls (42♂, 26♀), aged 25.1-49.6 months. Voxel-wise effects of ASD diagnosis, sex, age, and their interaction on DWI measures of FA, mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) were investigated using tract-based spatial statistics (TBSS) while controlling mean absolute and relative motion. RESULTS Compared to TD controls, males and females with ASD had significantly increased measures of FA in eight clusters (threshold-free cluster enhancement p < 0.05) that incorporated several WM tracts including regions of the genu, body, and splenium of the corpus callosum, inferior frontal-occipital fasciculi, inferior and superior longitudinal fasciculi, middle and superior cerebellar peduncles, and corticospinal tract. A diagnosis by sex interaction was observed in measures of AD across six significant clusters incorporating areas of the body, genu, and splenium of the corpus collosum. In these tracts, females with ASD showed increased AD compared to TD females, while males with ASD showed decreased AD compared to TD males. CONCLUSIONS The current findings support growing evidence that preschool-aged children with ASD have atypical measures of WM microstructure that appear to differ in directionality from alterations observed in older individuals with the condition. To our knowledge, this study represents the largest sample of preschool-aged females with ASD to be evaluated using DWI. Microstructural differences associated with ASD largely overlapped between sexes. However, differential relationships of AD measures indicate that sex likely modulates ASD neuroanatomical phenotypes. Further longitudinal study is needed to confirm and quantify the developmental relationship of WM structure in ASD.
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Affiliation(s)
- Derek Sayre Andrews
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
| | - Joshua K. Lee
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
| | - Marjorie Solomon
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
| | - Sally J. Rogers
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
| | - David G. Amaral
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
| | - Christine Wu Nordahl
- The Medical Investigation of Neurodevelopmental Disorders (MIND) Institute and Department of Psychiatry and Behavioral Sciences, UC Davis School of Medicine, University of California Davis, Sacramento, CA USA
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Abstract
We here provide neural evidence that the cerebellar circuit can predict future inputs from present outputs, a hallmark of an internal forward model. Recent computational studies hypothesize that the cerebellum performs state prediction known as a forward model. To test the forward-model hypothesis, we analyzed activities of 94 mossy fibers (inputs to the cerebellar cortex), 83 Purkinje cells (output from the cerebellar cortex to dentate nucleus), and 73 dentate nucleus cells (cerebellar output) in the cerebro-cerebellum, all recorded from a monkey performing step-tracking movements of the right wrist. We found that the firing rates of one population could be reconstructed as a weighted linear sum of those of preceding populations. We then went on to investigate if the current outputs of the cerebellum (dentate cells) could predict the future inputs of the cerebellum (mossy fibers). The firing rates of mossy fibers at time t + t1 could be well reconstructed from as a weighted sum of firing rates of dentate cells at time t, thereby proving that the dentate activities contained predictive information about the future inputs. The average goodness-of-fit (R2) decreased moderately from 0.89 to 0.86 when t1 was increased from 20 to 100 ms, hence indicating that the prediction is able to compensate the latency of sensory feedback. The linear equations derived from the firing rates resembled those of a predictor known as Kalman filter composed of prediction and filtering steps. In summary, our analysis of cerebellar activities supports the forward-model hypothesis of the cerebellum.
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Tolu S, Capolei MC, Vannucci L, Laschi C, Falotico E, Hernández MV. A Cerebellum-Inspired Learning Approach for Adaptive and Anticipatory Control. Int J Neural Syst 2019; 30:1950028. [PMID: 31771377 DOI: 10.1142/s012906571950028x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The cerebellum, which is responsible for motor control and learning, has been suggested to act as a Smith predictor for compensation of time-delays by means of internal forward models. However, insights about how forward model predictions are integrated in the Smith predictor have not yet been unveiled. To fill this gap, a novel bio-inspired modular control architecture that merges a recurrent cerebellar-like loop for adaptive control and a Smith predictor controller is proposed. The goal is to provide accurate anticipatory corrections to the generation of the motor commands in spite of sensory delays and to validate the robustness of the proposed control method to input and physical dynamic changes. The outcome of the proposed architecture with other two control schemes that do not include the Smith control strategy or the cerebellar-like corrections are compared. The results obtained on four sets of experiments confirm that the cerebellum-like circuit provides more effective corrections when only the Smith strategy is adopted and that minor tuning in the parameters, fast adaptation and reproducible configuration are enabled.
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Affiliation(s)
- Silvia Tolu
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Richard Petersens Plads, Building 326, Kgs. Lyngby, 2800, Denmark
| | - Marie Claire Capolei
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Richard Petersens Plads, Building 326, Kgs. Lyngby, 2800, Denmark
| | - Lorenzo Vannucci
- The BioRobotics Institute, Scuola Superiore SantAnna, Viale Rinaldo Piaggio 34, Pontedera, 56025, Pisa, Italy
| | - Cecilia Laschi
- The BioRobotics Institute, Scuola Superiore SantAnna, Viale Rinaldo Piaggio 34, Pontedera, 56025, Pisa, Italy
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore SantAnna, Viale Rinaldo Piaggio 34, Pontedera, 56025, Pisa, Italy
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Massi E, Vannucci L, Albanese U, Capolei MC, Vandesompele A, Urbain G, Sabatini AM, Dambre J, Laschi C, Tolu S, Falotico E. Combining Evolutionary and Adaptive Control Strategies for Quadruped Robotic Locomotion. Front Neurorobot 2019; 13:71. [PMID: 31555118 PMCID: PMC6727738 DOI: 10.3389/fnbot.2019.00071] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Accepted: 08/14/2019] [Indexed: 11/13/2022] Open
Abstract
In traditional robotics, model-based controllers are usually needed in order to bring a robotic plant to the next desired state, but they present critical issues when the dimensionality of the control problem increases and disturbances from the external environment affect the system behavior, in particular during locomotion tasks. It is generally accepted that the motion control of quadruped animals is performed by neural circuits located in the spinal cord that act as a Central Pattern Generator and can generate appropriate locomotion patterns. This is thought to be the result of evolutionary processes that have optimized this network. On top of this, fine motor control is learned during the lifetime of the animal thanks to the plastic connections of the cerebellum that provide descending corrective inputs. This research aims at understanding and identifying the possible advantages of using learning during an evolution-inspired optimization for finding the best locomotion patterns in a robotic locomotion task. Accordingly, we propose a comparative study between two bio-inspired control architectures for quadruped legged robots where learning takes place either during the evolutionary search or only after that. The evolutionary process is carried out in a simulated environment, on a quadruped legged robot. To verify the possibility of overcoming the reality gap, the performance of both systems has been analyzed by changing the robot dynamics and its interaction with the external environment. Results show better performance metrics for the robotic agent whose locomotion method has been discovered by applying the adaptive module during the evolutionary exploration for the locomotion trajectories. Even when the motion dynamics and the interaction with the environment is altered, the locomotion patterns found on the learning robotic system are more stable, both in the joint and in the task space.
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Affiliation(s)
- Elisa Massi
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Lorenzo Vannucci
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Ugo Albanese
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Marie Claire Capolei
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
| | - Alexander Vandesompele
- AIRO, Electronics and Information Systems Department, Ghent University - imec, Ghent, Belgium
| | - Gabriel Urbain
- AIRO, Electronics and Information Systems Department, Ghent University - imec, Ghent, Belgium
| | - Angelo Maria Sabatini
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
| | - Joni Dambre
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Cecilia Laschi
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
| | - Silvia Tolu
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pontedera, Italy
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Capolei MC, Angelidis E, Falotico E, Lund HH, Tolu S. A Biomimetic Control Method Increases the Adaptability of a Humanoid Robot Acting in a Dynamic Environment. Front Neurorobot 2019; 13:70. [PMID: 31555117 PMCID: PMC6722230 DOI: 10.3389/fnbot.2019.00070] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2019] [Accepted: 08/12/2019] [Indexed: 11/13/2022] Open
Abstract
One of the big challenges in robotics is to endow agents with autonomous and adaptive capabilities. With this purpose, we embedded a cerebellum-based control system into a humanoid robot that becomes capable of handling dynamical external and internal complexity. The cerebellum is the area of the brain that coordinates and predicts the body movements throughout the body-environment interactions. Different biologically plausible cerebellar models are available in literature and have been employed for motor learning and control of simplified objects. We built the canonical cerebellar microcircuit by combining machine learning and computational neuroscience techniques. The control system is composed of the adaptive cerebellar module and a classic control method; their combination allows a fast adaptive learning and robust control of the robotic movements when external disturbances appear. The control structure is built offline, but the dynamic parameters are learned during an online-phase training. The aforementioned adaptive control system has been tested in the Neuro-robotics Platform with the virtual humanoid robot iCub. In the experiment, the robot iCub has to balance with the hand a table with a ball running on it. In contrast with previous attempts of solving this task, the proposed neural controller resulted able to quickly adapt when the internal and external conditions change. Our bio-inspired and flexible control architecture can be applied to different robotic configurations without an excessive tuning of the parameters or customization. The cerebellum-based control system is indeed able to deal with changing dynamics and interactions with the environment. Important insights regarding the relationship between the bio-inspired control system functioning and the complexity of the task to be performed are obtained.
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Affiliation(s)
- Marie Claire Capolei
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
| | - Emmanouil Angelidis
- Landesforschungsinstitut des Freistaats Bayern, An-Institut, Technical University of Munich, Munich, Germany
| | - Egidio Falotico
- The BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Henrik Hautop Lund
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
| | - Silvia Tolu
- Automation and Control Group, Department of Electrical Engineering, Technical University of Denmark, Copenhagen, Denmark
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