A feedback-driven brain organoid platform enables automated maintenance and high-resolution neural activity monitoring
Published in Internet of Things, 2025
Authors: Kateryna Voitiuk, Spencer T Seiler, Mirella Pessoa de Melo, Jinghui Geng, Tjitse van der Molen, Sebastian Hernandez, Hunter E Schweiger, Jess L Sevetson, David F Parks, Ash Robbins, Sebastian Torres-Montoya, Drew Ehrlich, Matthew AT Elliott, Tal Sharf, David Haussler, Mohammed A Mostajo-Radji, Sofie R Salama, Mircea Teodorescu
Longitudinal live cell imaging is valuable for characterizing dynamic morphological and phenotypic changes in biological systems. However, conventional approaches rely on manual microscope operation, which is labor-intensive, limits imaging frequency, and disrupts the cellular environment. These constraints reduce scalability, increase experimental variability, and restrict both the duration and temporal resolution of continuous imaging. Although automated imaging platforms partially address these limitations, existing solutions are often constrained by the cost, footprint, and inflexibility of in-incubator microscopes or stage-top incubators. Here, we present an automated in-incubator epifluorescence microscope designed for long-term operation. The system features a modular architecture with optional multi-fluorescence imaging, automated plate scanning, configurable light sources, and compatibility with multiple plate formats, including integration with fluidic automation devices. By positioning the light sources and control electronics outside the incubator, the platform improves thermal stability and long-term operational reliability. This approach enables continuous, high-frequency imaging over extended durations, providing a source of rich data for quantifying time-dependent tissue phenotypes, morphological remodeling, and transient biological processes.
Paper Link: https://www.sciencedirect.com/science/article/pii/S2542660525001854