Before revision:  We then develop biophysical models of paired spike trains to reproduce the phenomenology of monosynaptic interactions observed in those data , including both fine-timescale spike-spike correlations and the irregular firing found in vivo . We use simulated data generated from these biophysical models to study the inference of small synaptic changes from spike data, despite the presence of rapidly-varying background network fluctuations.
After revision:  We then develop biophysical models of paired spike trains to reproduce the phenomenology of monosynaptic interactions observed in those data , including both fine-timescale spike-spike correlations and the irregular firing found in vivo . firing irregularity. A key characteristic of these models is that the paired neurons are coupled by rapidly-fluctuating background inputs. We quantify a monosynapse's causal effect by comparing the postsynaptic train with its counterfactual, when the monosynapse is removed. Subsequently, we develop statistical techniques for estimating this causal effect from the pre- and post-synaptic spike trains.