An in vitro model of neuronal ensembles

M. Angeles Rabadan, Estanislao Daniel De La Cruz, Sneha B. Rao, Yannan Chen, Cheng Gong, Gregg Crabtree, Bin Xu, Sander Markx, Joseph A. Gogos, Rafael Yuste and Raju Tomer ()
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M. Angeles Rabadan: Columbia University
Estanislao Daniel De La Cruz: Columbia University
Sneha B. Rao: Columbia University
Yannan Chen: Columbia University
Cheng Gong: Columbia University
Gregg Crabtree: Columbia University
Bin Xu: Columbia University
Sander Markx: Columbia University
Joseph A. Gogos: Columbia University
Rafael Yuste: Columbia University
Raju Tomer: Columbia University

Nature Communications, 2022, vol. 13, issue 1, 1-17

Abstract: Abstract Advances in 3D neuronal cultures, such as brain spheroids and organoids, are allowing unprecedented in vitro access to some of the molecular, cellular and developmental mechanisms underlying brain diseases. However, their efficacy in recapitulating brain network properties that encode brain function remains limited, thereby precluding development of effective in vitro models of complex brain disorders like schizophrenia. Here, we develop and characterize a Modular Neuronal Network (MoNNet) approach that recapitulates specific features of neuronal ensemble dynamics, segregated local-global network activities and a hierarchical modular organization. We utilized MoNNets for quantitative in vitro modelling of schizophrenia-related network dysfunctions caused by highly penetrant mutations in SETD1A and 22q11.2 risk loci. Furthermore, we demonstrate its utility for drug discovery by performing pharmacological rescue of alterations in neuronal ensembles stability and global network synchrony. MoNNets allow in vitro modelling of brain diseases for investigating the underlying neuronal network mechanisms and systematic drug discovery.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31073-1

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DOI: 10.1038/s41467-022-31073-1

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