Realistic Modeling of Large-Scale Networks: Spatio-temporal Dynamics and Long-Term Synaptic Plasticity in the Cerebellum

large-scale computational model of the cerebellum granular layer has been adapted to generate long-term synaptic plasticity in response to afferent mossy fiber bursts. A simple learning rule was elaborated in order to link the average granule cell depolarization to LTP and LTD. Briefly, LTP was generated for membrane potentials >-40 mV and LTD for membrane potentials <-40 mV. The result was to generate LTP and stronger excitation in the core of active clusters, which were surrounded by LTD. These changes were accompanied by a faster and stronger spike generation compared to the surround. These results reproduce the experimental observations and provide a valuable and efficient tool for implementing autonomous learning algorithms in the cerebellar neuronal network.

[1]  Masao Ito.  Cerebellar circuitry as a neuronal machine , 2006, Progress in Neurobiology.

[2]  Egidio D'Angelo,et al.  Fast-Reset of Pacemaking and Theta-Frequency Resonance Patterns in Cerebellar Golgi Cells: Simulations of their Impact In Vivo , 2007, Frontiers in cellular neuroscience.

[3]  D. Linden,et al.  Polarity of Long-Term Synaptic Gain Change Is Related to Postsynaptic Spike Firing at a Cerebellar Inhibitory Synapse , 1998, Neuron.

[4]  Giovanni Naldi,et al.  Axonal Na+ channels ensure fast spike activation and back-propagation in cerebellar granule cells. , 2009, Journal of neurophysiology.

[5]  E. D’Angelo,et al.  Increased neurotransmitter release during long‐term potentiation at mossy fibre–granule cell synapses in rat cerebellum , 2004, The Journal of physiology.

[6]  Egidio D'Angelo,et al.  Presynaptic current changes at the mossy fiber-granule cell synapse of cerebellum during LTP. , 2002, Journal of neurophysiology.

[7]  R. Silver,et al.  Shunting Inhibition Modulates Neuronal Gain during Synaptic Excitation , 2003, Neuron.

[8]  Egidio D'Angelo,et al.  Differential induction of bidirectional long‐term changes in neurotransmitter release by frequency‐coded patterns at the cerebellar input , 2009, The Journal of physiology.

[9]  Egidio D'Angelo,et al.  Combinatorial responses controlled by synaptic inhibition in the cerebellum granular layer. , 2010, Journal of neurophysiology.

[10]  Egidio D'Angelo,et al.  Computational Reconstruction of Pacemaking and Intrinsic Electroresponsiveness in Cerebellar Golgi Cells , 2007, Frontiers in cellular neuroscience.

[11]  E. D’Angelo,et al.  Synaptic excitation of individual rat cerebellar granule cells in situ: evidence for the role of NMDA receptors. , 1995, The Journal of physiology.

[12]  V Taglietti,et al.  Ionic mechanism of electroresponsiveness in cerebellar granule cells implicates the action of a persistent sodium current. , 1998, Journal of neurophysiology.

[13]  S. Dieudonné,et al.  Submillisecond kinetics and low efficacy of parallel fibre‐Golgi cell synaptic currents in the rat cerebellum , 1998, The Journal of physiology.

[14]  R Angus Silver,et al.  The Contribution of Single Synapses to Sensory Representation in Vivo , 2008, Science.

[15]  J. Albus.  A Theory of Cerebellar Function , 1971 .

[16]  Henrik Jörntell,et al.  Properties of Somatosensory Synaptic Integration in Cerebellar Granule Cells In Vivo , 2006, The Journal of Neuroscience.

[17]  J. Eccles.  The cerebellum as a computer: patterns in space and time. , 1973, The Journal of physiology.

[18]  C. I. De Zeeuw,et al.  Timing in the cerebellum: oscillations and resonance in the granular layer , 2009, Neuroscience.

[19]  R Angus Silver,et al.  Synaptic and Cellular Properties of the Feedforward Inhibitory Circuit within the Input Layer of the Cerebellar Cortex , 2008, The Journal of Neuroscience.

[20]  D. Wilkin,et al.  Neuron , 2001, Brain Research.

[21]  E. D’Angelo,et al.  The cerebellar network: From structure to function and dynamics , 2011, Brain Research Reviews.

[22]  Egidio D'Angelo,et al.  Rebuilding Cerebellar Network Computations from Cellular Neurophysiology , 2010, Front. Cell. Neurosci..

[23]  V Taglietti,et al.  Theta-Frequency Bursting and Resonance in Cerebellar Granule Cells: Experimental Evidence and Modeling of a Slow K+-Dependent Mechanism , 2001, The Journal of Neuroscience.

[24]  Professor Dr. John C. Eccles,et al.  The Cerebellum as a Neuronal Machine , 1967, Springer Berlin Heidelberg.

[25]  Thierry Nieus,et al.  LTP regulates burst initiation and frequency at mossy fiber-granule cell synapses of rat cerebellum: experimental observations and theoretical predictions. , 2006, Journal of neurophysiology.

[26]  Thierry Nieus,et al.  A Realistic Large-Scale Model of the Cerebellum Granular Layer Predicts Circuit Spatio-Temporal Filtering Properties , 2009, Front. Cell. Neurosci..

[27]  K. Doya,et al.  Unsupervised learning of granule cell sparse codes enhances cerebellar adaptive control , 2001, Neuroscience.

[28]  Egidio D'Angelo,et al.  Intracellular Calcium Regulation by Burst Discharge Determines Bidirectional Long-Term Synaptic Plasticity at the Cerebellum Input Stage , 2005, The Journal of Neuroscience.

[29]  Egidio D'Angelo,et al.  The Critical Role of Golgi Cells in Regulating Spatio-Temporal Integration and Plasticity at the Cerebellum Input Stage , 2008, Front. Neurosci..

[30]  P. Dean,et al.  The cerebellar microcircuit as an adaptive filter: experimental and computational evidence , 2010, Nature Reviews Neuroscience.

[31]  M. Häusser,et al.  Integration of quanta in cerebellar granule cells during sensory processing , 2004, Nature.

[32]  D. Marr.  A theory of cerebellar cortex , 1969, The Journal of physiology.

[33]  Egidio D'Angelo,et al.  The Spatial Organization of Long-Term Synaptic Plasticity at the Input Stage of Cerebellum , 2007, The Journal of Neuroscience.

[34]  R. Silver,et al.  Fast vesicle reloading and a large pool sustain high bandwidth transmission at a central synapse , 2006, Nature.

[35]  L. Forti,et al.  Functional diversity of L-type calcium channels in rat cerebellar neurons , 1993, Neuron.

[36]  E. D’Angelo,et al.  Evidence for NMDA and mGlu receptor-dependent long-term potentiation of mossy fiber-granule cell transmission in rat cerebellum. , 1999, Journal of neurophysiology.

[37]  Angelo Arleo,et al.  How Synaptic Release Probability Shapes Neuronal Transmission: Information-Theoretic Analysis in a Cerebellar Granule Cell , 2010, Neural Computation.

[38]  M. Häusser,et al.  High-fidelity transmission of sensory information by single cerebellar mossy fibre boutons , 2007, Nature.

[39]  Kanichay Rt,et al.  Synaptic and Cellular Properties of the Feedforward Inhibitory Circuit within the Input Layer of the Cerebellar Cortex , 2008 .

[40]  Egidio D'Angelo,et al.  Frontiers in Cellular Neuroscience Cellular Neuroscience , 2022 .

[41]  Nicholas T. Carnevale,et al.  The NEURON Simulation Environment , 1997, Neural Computation.