Analysis of signal components < 500 Hz in brain organoids coupled to microelectrode arrays: A reliable test-bed for preclinical seizure liability assessment of drugs and screening of antiepileptic drugs

Brain organoids with three-dimensional structure and tissue-like function are highly demanded for brain disease research and drug evaluation. However, to our knowledge, methods for measuring and analyzing brain organoid function have not been developed yet. This study focused on the frequency components of an obtained waveform below 500 Hz using planner microelectrode array (MEA) and evaluated the response to the convulsants pentylenetetrazol (PTZ) and strychnine as well as the antiepileptic drugs (AEDs) perampanel and phenytoin. Sudden and persistent seizure-like firing was observed with PTZ administration, displaying a concentration-dependent periodic activity with the frequency component enhanced even in one oscillation characteristic. On the other hand, in the administration of AEDs, the frequency of oscillation decreased in a concentrationdependent manner and the intensity of the frequency component in one oscillation also decreased. Interestingly, at low doses of phenytoin, a group of synchronized bursts was formed, which was different from the response to the perampanel. Frequency components contained information on cerebral organoid function, and MEA was proven useful in predicting the seizure liability of drugs and evaluating the effect of AEDs with a different mechanism of action. In addition, frequency component analysis of brain organoids using MEA is an important analysis method to perform in vitro to in vivo extrapolation in the future, which will help explore the function of the organoid itself, study human brain developments, and treat various brain diseases.

Automated summary

This study focused on analyzing the frequency components of brain organoids using MEA, and evaluated the response to convulsants and antiepileptic drugs. The results showed that the frequency components changed in different drug conditions, demonstrating the usefulness of MEA in predicting drug seizure liability and evaluating the effects of AEDs with different mechanisms.