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An in vitro model of neuronal ensembles

Author

Listed:
  • M. Angeles Rabadan

    (Columbia University)

  • Estanislao Daniel De La Cruz

    (Columbia University)

  • Sneha B. Rao

    (Columbia University)

  • Yannan Chen

    (Columbia University
    Columbia University)

  • Cheng Gong

    (Columbia University
    Columbia University)

  • Gregg Crabtree

    (Columbia University)

  • Bin Xu

    (Columbia University)

  • Sander Markx

    (Columbia University)

  • Joseph A. Gogos

    (Columbia University
    Columbia University
    Columbia University
    Columbia University)

  • Rafael Yuste

    (Columbia University
    Columbia University)

  • Raju Tomer

    (Columbia University
    Columbia University
    Columbia University
    Columbia University)

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.

Suggested Citation

  • 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 & Raju Tomer, 2022. "An in vitro model of neuronal ensembles," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31073-1
    DOI: 10.1038/s41467-022-31073-1
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    References listed on IDEAS

    as
    1. Johannes Friedrich & Pengcheng Zhou & Liam Paninski, 2017. "Fast online deconvolution of calcium imaging data," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-26, March.
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    3. Aparna Bhaduri & Madeline G. Andrews & Walter Mancia Leon & Diane Jung & David Shin & Denise Allen & Dana Jung & Galina Schmunk & Maximilian Haeussler & Jahan Salma & Alex A. Pollen & Tomasz J. Nowako, 2020. "Cell stress in cortical organoids impairs molecular subtype specification," Nature, Nature, vol. 578(7793), pages 142-148, February.
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    1. Tatsuya Osaki & Tomoya Duenki & Siu Yu A. Chow & Yasuhiro Ikegami & Romain Beaubois & Timothée Levi & Nao Nakagawa-Tamagawa & Yoji Hirano & Yoshiho Ikeuchi, 2024. "Complex activity and short-term plasticity of human cerebral organoids reciprocally connected with axons," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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