1. Event-driven simulation of neural population synchronization facilitated by electrical coupling
- Author
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Boris Barbour, Olivier J. M. D. Coenen, Richard R. Carrillo, Christian Boucheny, Eduardo Ros, Laboratoire de Neurobiologie (UMR 8544) (NEURO), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physiologie de la Perception et de l'Action (LPPA), and Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Statistics and Probability ,Scheme (programming language) ,Physical neural network ,Theoretical computer science ,Computer science ,[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Neurobiology ,Computation ,Models, Neurological ,Action Potentials ,02 engineering and technology ,Synaptic Transmission ,General Biochemistry, Genetics and Molecular Biology ,Random neural network ,Network simulation ,MESH: Neural Networks (Computer) ,03 medical and health sciences ,0302 clinical medicine ,MESH: Models, Neurological ,Synchronization (computer science) ,MESH: Synaptic Transmission ,0202 electrical engineering, electronic engineering, information engineering ,Evoked Potentials ,MESH: Action Potentials ,computer.programming_language ,Spiking neural network ,Quantitative Biology::Neurons and Cognition ,Applied Mathematics ,Systems Biology ,General Medicine ,MESH: Evoked Potentials ,MESH: Nerve Net ,MESH: Systems Biology ,Modeling and Simulation ,Table (database) ,020201 artificial intelligence & image processing ,Neural Networks, Computer ,Nerve Net ,computer ,Algorithm ,030217 neurology & neurosurgery - Abstract
Most neural communication and processing tasks are driven by spikes. This has enabled the application of the event-driven simulation schemes. However the simulation of spiking neural networks based on complex models that cannot be simplified to analytical expressions (requiring numerical calculation) is very time consuming. Here we describe briefly an event-driven simulation scheme that uses pre-calculated table-based neuron characterizations to avoid numerical calculations during a network simulation, allowing the simulation of large-scale neural systems. More concretely we explain how electrical coupling can be simulated efficiently within this computation scheme, reproducing synchronization processes observed in detailed simulations of neural populations.
- Published
- 2005