Preliminary study of simplification of Microelectrode array (MEA) data analysis method for in vitro convulsive risk detection

Abstract

Recently, in vitro studies using cultured neurons and microelectrode array (MEA) systems have been developing for detecting convulsion/seizure risks instead of in vivo studies. So far, we have detected the convulsive risk of the compounds by characterizing spontaneous neuronal activity with unique parameters and analyzing them using principal component analysis (PCA) and multivariate analysis of variance (MANOVA) for MEA data of rat primary neurons obtained at different facilities. Although this analysis method is accurate enough to estimate the mechanism of convulsion, it would not be used easily at this time. So, it was assumed that the usage would be limited.

To establish an analysis method for detecting the convulsion risks more easily, we focused on 76 parameters that are automatically calculated by MEA and shortened the time for parameter calculation. By cluster analysis, parameters that contributed significantly to detect the convulsive risk were extracted for each facility using multiple data. The types and numbers of extracted parameters were different among the facilities, but convulsive and non-convulsive compounds could be roughly separated by cluster analysis. Next, the above-mentioned parameters were compared, and the ones frequently selected were adopted as a common parameter set. As a result, the risk of convulsions was detectable with this parameter set, and which was proved by PCA and MANOVA. Although the accuracy of this analysis method was inferior to our previous analytical method, it was considered to be useful in screening tests and so on.