In vitro neural networks as self-organizing computational substrates

The structural organization of neural networks and the functional connectivity of synapses have been the basis for network neuroscience research for decades. Evolutionarily conserved mechanisms of neuroplasticity processes such as activity-dependent Hebbian plasticity and homeostatic plasticity work in tandem to coordinate network functionality and maintain normal neural network function as well as regulate network responses to perturbation. The drive to understand how different forms of plasticity may result in adaptive or maladaptive neural network responses demonstrated as changes in network structure and function, has led to the development of progressively more sophisticated empirical tools. With advanced protocols, some of the complex structural and functional properties of in vivo systems, including characteristic self-organization and emergence of functional activity of neural networks can be monitored and selectively manipulated in vitro using cultured neurons. Furthermore, advanced technologies such as microelectrode arrays (MEAs) have been established as a platform that can be used to map, record, analyze, and model elements and interactions of emergent electrophysiological behaviour of maturing neural networks in vitro. The MEA platform also allows electrical and/or chemical modulation of the network, while being compatible with chemo-and optogenetic techniques, which can be applied to selectively modulate network plasticity. Interfaced with microfluidic chambers, they allow the structuring of multi-nodal neural networks with definable afferent and efferent connectivity, thus creating experimental paradigms that capture fundamental features and dynamics of the function-structure relationships observed in different interconnected brain regions.