title: Theory and simulation in neuroscience.
abstract: Modeling work in neuroscience can be classified using two different criteria. The first one is the complexity of the model, ranging from simplified conceptual models that are amenable to mathematical analysis to detailed models that require simulations in order to understand their properties. The second criterion is that of direction of workflow, which can be from microscopic to macroscopic scales (bottom-up) or from behavioral target functions to properties of components (top-down). We review the interaction of theory and simulation using examples of top-down and bottom-up studies and point to some current developments in the fields of computational and theoretical neuroscience.
authors.affiliation: School of Computer and Communication Sciences and Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland. wulfram.gerstner@epfl.ch
authors.forename: Wulfram
authors.initials: W
authors.lastname: Gerstner
authors.forename: Henning
authors.initials: H
authors.lastname: Sprekeler
authors.forename: Gustavo
authors.initials: G
authors.lastname: Deco
mesh_terms: D000818:Animals; D001519:Behavior; D003198:Computer Simulation; D003657:Decision Making; D006801:Humans; D007858:Learning; D008568:Memory; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009488:Neurosciences / Q000379:methods*; D012201:Reward