Computational model of developmental self-assembly of a cortical microcircuit
Umar AbubacariD, Cayla R Harris, Ryan Bournes, Roman BaueriD
Abstract
Cortical microcircuits emerge from local developmental interactions, yet large-scale computational models typically prescribe connectivity rather than explain its formation. Here we use BioDynaMo to simulate the self-assembly of ~70,000 cortical neurons from 1,200 progenitors in 3D physical space through migration, neurite growth and contact-based synapse formation. With one calibrated filling fraction per connection type, the locally formed synapses reproduce experimentally measured connectivity across 64 connection types (mean absolute error 0.0062) without prescribing individual connections. The grown spiking networks sustain stable, inhibition-dominated activity, and the same developmental rules, given different targets, generate both a canonical cortical microcircuit and a visual-cortex variant. Inverting the migration programme produces a reeler-like column whose aberrant connectivity destabilises network activity. Together, these findings provide a mechanistic link between local developmental processes and the emergence of cortical anatomy, connectivity and function.
02 /Specification & Classification
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