A theory for self-sustained balanced states in absence of strong external currents.

ABSTRACT: Recurrent neural networks with balanced excitation and inhibition exhibit irregular asynchronous dynamics, which is fundamental for cortical computations. Classical balance mechanisms require strong external input currents in order to sustain finite firing rates, thus raising concerns about their biological plausibility. Here, we investigate an alternative mechanism based on short-term synaptic depression (STD) acting on excitatory-excitatory synapses, which dynamically balances the network activity without the need of strong external driving. Using accurate numerical simulations and theoretical investigations we characterize the dynamics of a densely connected recurrent network made up of N rate-neuron models encompassing STD. Depending on the synaptic strength J0, the network exhibits tw

SUBMITTER: Angulo-Garcia D 

PROVIDER: S-EPMC12923148 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature