ArticlePloS one2012
A computational mechanism for unified gain and timing control in the cerebellum.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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Who cites it
29 citing papers in PubMed, 71 citations in OpenAlex.
- Interactions between circuit architecture and plasticity in a closed-loop cerebellar system.eLife · 2024Article
- Emergence of brain-inspired small-world spiking neural network through neuroevolution.iScience · 2024Article
- Dual STDP processes at Purkinje cells contribute to distinct improvements in accuracy and speed of saccadic eye movements.PLoS computational biology · 2022Article
- Influence of various temporal recoding on pavlovian eyeblink conditioning in the cerebellum.Cognitive neurodynamics · 2021Article
- Real-Time Simulation of a Cerebellar Scaffold Model on Graphics Processing Units.Frontiers in cellular neuroscience · 2021Article
- Towards a Bio-Inspired Real-Time Neuromorphic Cerebellum.Frontiers in cellular neuroscience · 2021Article
- Translation information processing is regulated by protein kinase C-dependent mechanism in Purkinje cells in murine posterior vermis.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Simulation of a Human-Scale Cerebellar Network Model on the K Computer.Frontiers in neuroinformatics · 2020Article
- I See Your Effort: Force-Related BOLD Effects in an Extended Action Execution-Observation Network Involving the Cerebellum.Cerebral cortex (New York, N.Y. : 1991) · 2019Article
- Reconstruction and Simulation of a Scaffold Model of the Cerebellar Network.Frontiers in neuroinformatics · 2019Article
- The Emerging Concept of Intrinsic Plasticity: Activity-dependent Modulation of Intrinsic Excitability in Cerebellar Purkinje Cells and Motor Learning.Experimental neurobiology · 2018Review
- Modeling the Encoding of Saccade Kinematic Metrics in the Purkinje Cell Layer of the Cerebellar Vermis.Frontiers in computational neuroscience · 2018Article
- A spiking neural model of adaptive arm control.Proceedings. Biological sciences · 2016Article
- Distributed Circuit Plasticity: New Clues for the Cerebellar Mechanisms of Learning.Cerebellum (London, England) · 2016Review
- Real-World-Time Simulation of Memory Consolidation in a Large-Scale Cerebellar Model.Frontiers in neuroanatomy · 2016Article
- Distributed Cerebellar Motor Learning: A Spike-Timing-Dependent Plasticity Model.Frontiers in computational neuroscience · 2016Article
- Stochastic Synchronization in Purkinje Cells with Feedforward Inhibition Could Be Studied with Equivalent Phase-Response Curves.Journal of mathematical neuroscience · 2015Article
- At the Edge of Chaos: How Cerebellar Granular Layer Network Dynamics Can Provide the Basis for Temporal Filters.PLoS computational biology · 2015Article
- Modeling memory consolidation during posttraining periods in cerebellovestibular learning.Proceedings of the National Academy of Sciences of the United States of America · 2015Article
- The 40-year history of modeling active dendrites in cerebellar Purkinje cells: emergence of the first single cell "community model".Frontiers in computational neuroscience · 2015Review
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precise gain and timing control is the goal of cerebellar motor learning. Because the basic neural circuitry of the cerebellum is homogeneous throughout the cerebellar cortex, a single computational mechanism may be used for simultaneous gain and timing control. Although many computational models of the cerebellum have been proposed for either gain or timing control, few models have aimed to unify them. In this paper, we hypothesize that gain and timing control can be unified by learning of the complete waveform of the desired movement profile instructed by climbing fiber signals. To justify our hypothesis, we adopted a large-scale spiking network model of the cerebellum, which was originally developed for cerebellar timing mechanisms to explain the experimental data of Pavlovian delay eyeblink conditioning, to the gain adaptation of optokinetic response (OKR) eye movements. By conducting large-scale computer simulations, we could reproduce some features of OKR adaptation, such as the learning-related change of simple spike firing of model Purkinje cells and vestibular nuclear neurons, simulated gain increase, and frequency-dependent gain increase. These results suggest that the cerebellum may use a single computational mechanism to control gain and timing simultaneously.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.