We are taking advantage of large neurocognitive and neuroimaging datasets on patients that carry specific gene mutations. The team collects samples from these patients which is converted into stem cells and neurons. This enables the researchers to correlate neural traits observed in the patient-derived neurons in the laboratory with clinical features of the same patients.

We use high-throughput screening platforms to investigate the functions >100 genes in brain cells. We study how loss of function or gain of function of genes, affect neurons grown from stem cells in the lab.

We study how genetic risk factors for autism and schizophrenia impact brain development using brain organoids—three-dimensional cell culture models that mimic human brain structure and function. These models allow us to observe brain development at the cellular level, providing insight into how genetic changes affect brain wiring and structure. The findings are compared to patient brain scans and activity measurements from patients to better understand how these mutations manifest in the human brain.

We analyze data on genes, pathways and neuronal function. Using a variety of statistical and machine-learning approaches, we identify convergent pathways and neurodevelopmental traits between hundreds of genes associated with conditions like schizophrenia and autism. This could help explain how gene mutations influence behaviors and cognitive function, deepening our understanding of these disorders.