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Agent-based modelling of neuronal growth

Updated: Jul 20, 2020

Recently, we investigated how a specific type of mammalian neurons grows and extends axons.

The complexity of every brain develops from a single precursor cell. Agent-based modelling allows to study this process of neuronal self-organisation.

Every organism develops from a single precursor cell, the zygote. However, it is currently not well understood how the information of the genetic code (genotype) produces the final organism after development. Computer modelling and simulation offers an innovative and powerful method to better understand this mapping between the genotype and the phenotype.

Neuronal networks

In particular, neuronal networks of mammalian brains are extremely complex due to their highly intricate connectivities and neuronal morphologies, comprising billions of neurons in the case of the human brain. Also here, a better understanding of how the empirically observed structure develops would be very helpful to gain insights into the function of the networks.

Here, the growth of a single neuron is simulated using BioDynaMo ( The video was created as part of the BioDynaMo collaboration (courtesy Lukas Breitwieser and Jean de Montigny)


In addition to the tutorials on the BioDynaMo documentation site, I recently created a tutorial series on using BioDynaMo to simulate basic models of cancer growth. These videos allow new users to learn fundamental skills to create their own models. The Tutorial sheet pointing to the Youtube videos is available via this link here.

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