Computational synthesis of cortical dendritic morphologies

Neuronal morphologies provide the foundation for the electrical behavior of neurons, the connectomes they form, and the dynamical properties of the brain. Comprehensive neuron models are essential for defining cell types, discerning their functional roles, and investigating structural alterations associated with diseased brain states. However, a lack of understanding of the principles underlying neuron morphologies has hindered attempts to computationally synthesize morphologies for decades. We introduce a novel synthesis algorithm based on a topological descriptor of neurons that we presented in an earlier publication, which overcomes the limitations of neuronal reconstruction techniques. This topology-guided synthesis generates dendrites that are indistinguishable from biological reconstructions in terms of both morpho-electrical and connectivity properties and enables the rapid digital reconstruction of entire brain regions from relatively few reference cells. This topological synthesis method offers an unprecedented opportunity to investigate the links between neuronal morphology and brain function across different spatio-temporal scales. Synthesized cortical networks based on structurally altered dendrites, like those associated with diverse brain pathologies, revealed principles linking branching properties to the structure of large-scale networks.

We provide here the original biological reconstructions, the artificially generated cells and related data (electrical traces, connectivity of artificial networks) that were used for the analysis of the paper "Computational synthesis of cortical dendritic morphologies".