UC Santa Cruz

In vitro cultures, including brain organoids, have advanced our understanding of neurodevelopment and disease. However, traditional methods for managing these cultures are labor- and data-intensive and prone to inconsistencies. This thesis presents an Internet of Things (IoT) based experimentation platform addressing these challenges in neuroscience research.

First, we created Piphys, an open-source neurophysiological recording platform with IoT-enabled software, lowering the barrier to entry for multichannel electrophysiology and introducing cloud-based recording for improved data management. Next, we developed a comprehensive IoT cloud laboratory architecture that supports multiple devices and offers software services for communication, data handling, and user interface. We created a generalized device software model and communication standard, establishing a foundation for rapid experiment development, integration, and feedback loops. Afterward, we applied this architecture in a 7-day integrated experiment with imaging, electrophysiology, and fluidics devices sustaining and monitoring cerebral cortex organoids, demonstrating that automation can match manual care results. Finally, in collaboration with UCSF, we developed a screening system for gene therapy using electrophysiology and optogenetic devices. We demonstrated the ability to suppress seizure-like activity with light in human hippocampal slices from epilepsy patients.

This platform enhances the ability to conduct multi-modal, multi-device experiments and bridges distances between collaborators. It unifies scientific instrumentation and interaction methodology for advancing research in brain development, neuroplasticity, and neurological disease.