bioRxivNeurosciencePreprint
A foundation model for brain organoid network dynamics uncovers intrinsic computation and convergent disease phenotypes
H. SchweigeriD, Ash RobbinsiD, Sebastian HernandeziD, Avelina Moreno-OchandoiD, Isabel ClineiD, Kivilcim E DoganyigitiD, Matilda MouzayaiD, Kamran HussainiD, Zhiping P. PangiD, Jubao DuaniD, Sofie R. SalamaiD, Alex A. PolleniD, Aparna BhaduriiD, David H. HaussleriD, Mircea TeodorescuiD, Mohammed A. Mostajo-RadjiiD
Abstract
Brain organoids develop self-organizing neural networks that can be used to model neurodevelopment and disease. Here we introduce PULSE, a foundation model developed using over 900 hours of high-density microelectrode array recordings of in vitro and ex vivo neural tissue. We show that this single model can address two open questions: how disease-associated variants alter network development, and how naive circuits encode information. PULSE revealed accelerated network maturation in held-out human 16p11.2-deletion organoids. It also revealed a change in network coordination shared with SHANK3 deficiency. Because organoids develop without sensory input, they let us ask how circuits encode information before any representation is learned. Closed-loop control of a virtual inverted pendulum engaged existing spontaneous activity patterns rather than creating new ones. PULSE provides a common reference frame for neural circuits across genotypes, protocols and tasks.
- organism: human
- assay: spatial transcriptomics
- assay: electronic health records
- research focus: cell type annotation
- research focus: trajectory inference
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: deep learning
- approach: experimental assay
- Citations
- 0
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