Before revision:  Deploying a novel, subsampling-invariant estimator, we find that in vivo dynamics do not comply with either hypothesis , but instead occupy a narrow "reverberating " state consistently across multiple mammalian species and cortical areas. A generic model tuned to this reverberating state predicts single neuron, pairwise, and population properties . With these predictions we first validate the model and then deduce network properties that are challenging to obtain experimentally, like the network timescale and strength of cortical input .
After revision:  Deploying a novel, subsampling-invariant estimator, we find that in vivo dynamics do not comply with either hypothesis , but instead identify a narrow reverberating regime. This approach enables us to predict yet unknown properties from very short recordings and for every circuit individually, including responses to minimal perturbations, intrinsic network timescales, and the strength of external input compared to recurrent activation - thereby informing about the underlying coding principles for each circuit, area, state and task .