title: Using Strahler's analysis to reduce up to 200-fold the run time of realistic neuron models.
abstract: The cellular mechanisms underlying higher brain functions/dysfunctions are extremely difficult to investigate experimentally, and detailed neuron models have proven to be a very useful tool to help these kind of investigations. However, realistic neuronal networks of sizes appropriate to study brain functions present the major problem of requiring a prohibitively high computational resources. Here, building on our previous work, we present a general reduction method based on Strahler's analysis of neuron morphologies. We show that, without any fitting or tuning procedures, it is possible to map any morphologically and biophysically accurate neuron model into an equivalent reduced version. Using this method for Purkinje cells, we demonstrate how run times can be reduced up to 200-fold, while accurately taking into account the effects of arbitrarily located and activated synaptic inputs.
authors.affiliation: Department of Mathematics and Applications "R. Caccioppoli", University of Naples Federico II, Naples, Italy.
authors.forename: Addolorata
authors.initials: A
authors.lastname: Marasco
authors.forename: Alessandro
authors.initials: A
authors.lastname: Limongiello
authors.forename: Michele
authors.initials: M
authors.lastname: Migliore
mesh_terms: D000200:Action Potentials; D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological; D009474:Neurons / Q000166:cytology* / Q000502:physiology*; D011689:Purkinje Cells / Q000502:physiology