Changes within bursts during learning in dissociated neural networks

We have studied the effect of imprinting a new stimulus-response (SR) relationship into a neuronal network cultured on a multi electrode array (MEA). We have used the Conditional Repetitive Stimulation (CRS) algorithm introduced by Shahaf et al in 2004. In this algorithm focal electrical stimulation is delivered at a low rate (<1 Hz) and is withdrawn when a desired response is observed. We confirmed that CRS could train the network to strengthen an initially weak SR relationship. With the acquisition of a new SR relationship, we studied its effect on network activity. Specifically, spontaneously occurring network bursts measured before, during and after training were analyzed. The total firing rate within bursts was estimated with a temporal resolution of milliseconds (burst profiles). We have shown earlier that these profiles change shape on a time base of several hours during spontaneous development. We show that the rate of change of the profiles during training (i.e. CRS) was higher than when no stimulation was applied.