Dynamic transitions in global network activity influenced by the balance of excitation and inhibition

Abstract

The conditions under which spontaneous activity is self-sustaining in network models may be important for understanding information processing in brain activity. We explored the influence of the membrane time-constant and cellular threshold potential on spontaneous network activity through parameter searches in a large-scale neural network of horizontally interconnected excitatory and inhibitory units. We show here that a wide range of activity patterns and behaviours emerge in a network where only the threshold potential and membrane time-constant vary. These simulations revealed a region within the parameter space for membrane time-constant and threshold potential where the balance of postsynaptic excitation and inhibition enables the network to make transitions rapidly between different activity states. Cross-correlograms showed the influence of global excitation and inhibition on the interactions of pairs of cells within a subnetwork. These cross-correlations indicate that, when a balance of excitation and inhibition exists, the contribution of the postsynaptic potentials to the membrane potential and the integration time determined by the membrane time-constant may play a key role in forming spatio-temporal representations.