Protocol for characterization of spatiotemporal network dynamics in cortical and hippocampal assembloids
Asia R Guzman1, Colin M McCrimmon1, Daniel Toker1
1Department of Neurology, University of California, Los Angeles, David Geffen School of Medicine, Los Angeles, CA 90095, USA.
STAR Protocols
|March 29, 2026
Summary
This study details a protocol for creating neural assembloids from human stem cells to model brain circuitry. These assembloids enable the study of neuronal activity and network integration in a human brain model.
Area of Science:
- Neuroscience
- Stem Cell Biology
- Developmental Biology
Background:
- Human brain circuitry development is complex and challenging to model.
- Human induced pluripotent stem cells (hiPSCs) offer a promising source for generating brain organoids.
Purpose of the Study:
- To establish a protocol for generating functional neural assembloids from hiPSCs.
- To model human brain circuitry, including excitatory and inhibitory neuronal interactions.
- To enable the study of neuronal network integration and activity.
Main Methods:
- Differentiation of excitatory-predominant hippocampal (Hc) and cortical (Cx) organoids from hiPSCs.
- Fusion of Hc and Cx organoids with inhibitory interneuron-predominant ganglionic eminence (GE) organoids.
- Maintenance of assembloids to promote interneuron migration and network integration.
- Functional assessment using two-photon calcium imaging to measure neuronal activity.
Main Results:
- Successful generation of neural assembloids with integrated excitatory and inhibitory neurons.
- Demonstrated interneuron migration and network integration within the assembloids.
- Quantified neuronal activity and network function using advanced imaging techniques.
Conclusions:
- The developed protocol provides a robust method for creating human neural assembloids.
- These assembloids serve as a valuable model for studying human brain circuitry and development.
- This model system facilitates research into neurological disorders and therapeutic interventions.


