ArticleScientific reports2013
Using Strahler's analysis to reduce up to 200-fold the run time of realistic neuron models.
Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- The Neural Analysis Toolkit Unifies Semi-Analytical Techniques to Simplify, Understand, and Simulate Dendrites.Neuroinformatics · 2026Article
- Article
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- Regulation of XOR function of reduced human L2/3 pyramidal neurons.Cognitive neurodynamics · 2024Article
- Data-driven reduction of dendritic morphologies with preserved dendro-somatic responses.eLife · 2021Article
- An efficient analytical reduction of detailed nonlinear neuron models.Nature communications · 2020Article
- Coding Capacity of Purkinje Cells With Different Schemes of Morphological Reduction.Frontiers in computational neuroscience · 2019Article
- Synaptic Activation of a Detailed Purkinje Cell Model Predicts Voltage-Dependent Control of Burst-Pause Responses in Active Dendrites.Frontiers in cellular neuroscience · 2017Article
- Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue.Frontiers in cellular neuroscience · 2016Review
- Simulation of alcohol action upon a detailed Purkinje neuron model and a simpler surrogate model that runs >400 times faster.BMC neuroscience · 2015Article
- Action potential processing in a detailed Purkinje cell model reveals a critical role for axonal compartmentalization.Frontiers in cellular neuroscience · 2015Article
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3 authors.
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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.
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