ArticleFrontiers in computational neuroscience2019
Complex Electroresponsive Dynamics in Olivocerebellar Neurons Represented With Extended-Generalized Leaky Integrate and Fire Models.
Article in Frontiers in computational neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Region-specific mean field models enhance simulations of local and global brain dynamics.NPJ systems biology and applications · 2025Article
- Mesoscale simulations predict the role of synergistic cerebellar plasticity during classical eyeblink conditioning.PLoS computational biology · 2024Article
- An Adaptive Generalized Leaky Integrate-and-Fire Model for Hippocampal CA1 Pyramidal Neurons and Interneurons.Bulletin of mathematical biology · 2023Article
- A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics.PLoS computational biology · 2023Article
- Model simulations unveil the structure-function-dynamics relationship of the cerebellar cortical microcircuit.Communications biology · 2022Article
- An overview of brain-like computing: Architecture, applications, and future trends.Frontiers in neurorobotics · 2022Review
- Brain-Inspired Spiking Neural Network Controller for a Neurorobotic Whisker System.Frontiers in neurorobotics · 2022Article
- Cerebellum Involvement in Dystonia During Associative Motor Learning: Insights From a Data-Driven Spiking Network Model.Frontiers in systems neuroscience · 2022Article
- Towards a Bio-Inspired Real-Time Neuromorphic Cerebellum.Frontiers in cellular neuroscience · 2021Article
- Response Dynamics in an Olivocerebellar Spiking Neural Network With Non-linear Neuron Properties.Frontiers in computational neuroscience · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The neurons of the olivocerebellar circuit exhibit complex electroresponsive dynamics, which are thought to play a fundamental role for network entraining, plasticity induction, signal processing, and noise filtering. In order to reproduce these properties in single-point neuron models, we have optimized the Extended-Generalized Leaky Integrate and Fire (E-GLIF) neuron through a multi-objective gradient-based algorithm targeting the desired input-output relationships. In this way, E-GLIF was tuned toward the unique input-output properties of Golgi cells, granule cells, Purkinje cells, molecular layer interneurons, deep cerebellar nuclei cells, and inferior olivary cells. E-GLIF proved able to simulate the complex cell-specific electroresponsive dynamics of the main olivocerebellar neurons including pacemaking, adaptation, bursting, post-inhibitory rebound excitation, subthreshold oscillations, resonance, and phase reset. The integration of these E-GLIF point-neuron models into olivocerebellar Spiking Neural Networks will allow to evaluate the impact of complex electroresponsive dynamics at the higher scales, up to motor behavior, in closed-loop simulations of sensorimotor tasks.
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