Network effects of synaptic modifications

In this paper, we use computational models of varying complexity to investigate the role of synaptic modifications for cortical network properties. In particular, we study how the dynamics can be regulated by neuromodulators, intrinsic noise and chemical agents. We focus on the complex neurodynamics and its modulation, and how this is related to the neural circuitry, where connectivity enhancement and pruning is considered. The emphasis is on the overall network structures, with feedforward and feedback loops between excitatory and inhibitory neurons at several layers and distances, and less details at the synaptic level. Our models aim at linking processes at a molecular and cellular (microscale), with processes at a network level (mesoscale), which in turn are linked to the mental processes and cognitive functions (macroscale). We also discuss the relevance of these results for clinical and experimental neuroscience, with applications to learning, memory, arousal, and mental disorders.