Login / Signup

Internet-connected cortical organoids for project-based stem cell and neuroscience education.

Matthew A T ElliottHunter E SchweigerAsh RobbinsSamira Vera-ChoqqueccotaDrew EhrlichSebastian HernandezKateryna VoitiukJinghui GengJess L SevetsonCordero CoreYohei M RosenMircea TeodorescuNico O WagnerDavid HausslerMohammed A Mostajo-Radji
Published in: eNeuro (2023)
The introduction of internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell-derived cortical organoids in two different settings: Using microscopy to monitor organoid growth in an introductory tissue culture course and using high density multielectrode arrays to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training. Significance Statement The use of stem cell-derived cortical organoid models in academia and biotechnology has drastically increased in recent years. Given these trends, there is a critical need for students to be trained in organoid culture, differentiation, and analysis. To date, education curricula that focus on organoids are theoretical. Taking advantage of cloud technologies, such as internet-connected microscopes and multielectrode arrays, we propose approaches to introduce students to cortical organoids using live experiments. We show that these approaches develop interest in the field and prospects in students in biology and other STEM disciplines, such as mathematics and computer science.
Keyphrases
  • high school
  • stem cells
  • high density
  • quality improvement
  • healthcare
  • health information
  • public health
  • deep learning
  • resistance training
  • machine learning
  • climate change
  • high speed
  • medical education
  • data analysis