Emergent topological structure in spontaneous brain-organoid activity

Persistent homology of MEA recordings from human (Lancaster) and mouse (Pasca) cortical organoids finds H1 loops rise above a rate- and population-preserving null in 14 of 18 datasets.

• Why it matters: Neural activity is thought to organize on low-dimensional structure, but it is unclear whether topological data analysis can recover structure at the node counts that recordings actually provide.
• What they did: The study built weighted correlation-space networks from 25–197 sorted units and computed Vietoris-Rips persistent homology, testing H1 and H2 against null models and perturbing unit removal.
• The result: Loops remain largely intact after random unit removal, but removing loop-forming units disrupts them more than removing equally connected units; H2 exceeds the null only in larger networks.

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