The researchers grew small brain organoids from cells of patients with schizophrenia, bipolar disorder and from healthy donors and monitored their electrical activity using multiple electrodes[1]. The organoids reached approximately 3 mm in diameter and contained multiple types of neural cells, including myelin, which allowed the measurement of complex EEG-like electrical activity[1]. Using electrical signal analysis, the researchers identified distinct firing patterns of neurons that formed specific electrophysical signatures for schizophrenia and for bipolar disorder[1][2]. Machine learning classified organoids according to these signatures with 83% accuracy without stimulation and with up to 92% accuracy after gentle electrical stimulation that highlighted neural activity[1][2]. Thus, the main finding of the study is that differential electrical patterns in patient organoids serve as potential biomarkers for the two disorders[1][2]. The authors published the results in the peer-reviewed journal APL Bioengineering and describe the method as a tool to study the mechanisms of the disorders and to test drugs in tissue derived from specific patients[1][3].