Characterization of synchronized bursts in cultured hippocampal neuronal networks with learning training on microelectrode arrays.

Spontaneous synchronized bursts seem to play a key role in brain functions such as learning and memory. Still controversial is the characterization of spontaneous synchronized bursts in neuronal networks after learning training, whether depression or promotion. By taking advantages of the main features of the microelectrode array (MEA) technology (i.e. multisite recordings, stable and long-term coupling with the biological preparation), we analyzed changes of spontaneous synchronized bursts in cultured hippocampal neuronal networks after learning training. And for this purpose, a learning model at networking level on MEA system was constructed, and analysis of spontaneous synchronized burst activity modulation was presented. Preliminary results show that, the number of burst was increased by 154%, burst duration was increased by 35%, and the number of spikes per burst was increased by 124%, while interburst interval decreased by 44% with learning. In particular, correlation and synchrony of neuronal activities in networks were enhanced by 51% and 36%, respectively, with learning. In contrast, dynamic properties of neuronal networks were not changed much when the network was under "non-learning" condition. These results indicate that firing, association and synchrony of spontaneous bursts in neuronal networks were promoted by learning. Furthermore, from these observations, we are encouraged to think of a more engineered system based on in vitro hippocampal neurons, as a novel sensitive system for electrophysiological evaluations.