Diversity of Dynamic States in Neural Networks induced by Homeostatic Plasticity

Dynamics of spiking neural networks exhibit clear differences, depending whether originating from living organisms or artificially grown cultures. In living organisms, the neural activity shows continuous, fluctuating dynamics, whereas cultured networks develop strong bursts separated by periods of silence. We propose that this is a result of an interplay between (1) network input, which is much weaker in isolated cultures than in the intact brain, and (2) homeostatic plasticity, a slow negative feedback mechanism adapting the neural spike rate. Based on our theoretical work, we predict that homeostasis can be harnessed to tune the dynamic state of a network by altering its input strength. Most importantly, this could allow to abolish the bursts in cultured neurons and render the dynamics brain-like instead -- a key prerequisite to study neurological and psychiatric disorders on the network level under laboratory conditions.