title: Analog circuits for modeling biological neural networks: design and applications.
abstract: Computational neuroscience is emerging as a new approach in biological neural networks studies. In an attempt to contribute to this field, we present here a modeling work based on the implementation of biological neurons using specific analog integrated circuits. We first describe the mathematical basis of such models, then present analog emulations of different neurons. Each model is compared to its biological real counterpart as well as its numerical computation. Finally, we demonstrate the possible use of these analog models to interact dynamically with real cells through artificial synapses within hybrid networks. This method is currently used to explore neural networks dynamics.
authors.affiliation: Laboratoire de Microélectronique IXL, CNRS UMR 5818, ENSERB, Université Bordeaux, Talence, France. lemasson@ixl.u-bordeaux.fr
authors.forename: S
authors.initials: S
authors.lastname: Le Masson
authors.forename: A
authors.initials: A
authors.lastname: Laflaquière
authors.forename: T
authors.initials: T
authors.lastname: Bal
authors.forename: G
authors.initials: G
authors.lastname: Le Masson
mesh_terms: D000818:Animals; D003202:Computers, Analog; D003203:Computers, Hybrid; D007448:Invertebrates; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*; D009716:Numerical Analysis, Computer-Assisted; D015203:Reproducibility of Results; D014714:Vertebrates