Abstract

Applications of Brain-Model Technology to Study Neuro-developmental Disorders

Cleber Trujillo, Project Scientist, University of California San Diego

The complexity of the human brain permits the development of sophisticated behavioral repertoires, such as language, tool use, self-awareness, and consciousness. Understanding what produces neuronal diversification during brain development has been a longstanding challenge for neuroscientists and may bring insights into the evolution of human cognition. We have been using stem cell-derived brain model technology to gain insights into several biological processes, such as human neurodevelopment and autism spectrum disorders. The reconstruction of human synchronized network activity in a dish can help to understand how neural network oscillations might contribute to the social brain. Here, we developed cortical organoids that exhibit low-frequency network-synchronized oscillations. Periodic and highly regularized oscillatory network events emerged after 4 months, followed by a transition to irregular and spatiotemporally complex activity by 8 months, mimicking features of late-stage preterm infant electroencephalography. Furthermore, we found that the Methyl-CpG-binding protein 2 (MECP2) is essential for the emergence of network oscillations, suggesting that functional maturation might be compromised at early stages of neurodevelopment in MECP2-related disorders, such as Rett syndrome, autism, and schizophrenia. As evidence of potential network maturation, oscillatory activity subsequently transitioned to more spatiotemporally irregular patterns, capturing features observed in preterm human electroencephalography (EEG). These results show that the development of structured network activity in the human neocortex may follow stable genetic programming, even in the absence of external or subcortical inputs. Our model provides novel opportunities for investigating and manipulating the role of network activity in the developing human cortex.