Analysis of transition and reproducibility of spontaneous electrical activity pattern in a living neuronal network

The representations of outer world in the brain are considered to be undertaken by spatiotemporal activity patterns of neuronal circuits. In this study, we analyzed the transition of the internal states of the circuit of rat hippocampal neurons cultured on a multi-electrodes-array-dish. We analyzed transition of center of gravity and 64-dimensional feature-vectors of electrical activity patterns. Electrical activity pattern at a certain 5-ms-width-time-window was represented as a 64 dimensional “0-1” feature vector, and analyzed the stability. We confirmed that the reproducibility of the neuronal network activity increased during culture days. In addition, we applied similarity analysis to 64-dimensional feature vectors of neuronal activity. Using X-means algorithm, feature vectors were classified into “pattern repertories” based on the spatial distribution of activity.