Synaptic integration is crucial for inter-neuronal communication, and excitatory-inhibitory integration is utterly important in lateral superior olive (LSO) neurons, enabling sound localization. For this purpose, LSO neurons integrate excitatory inputs from the ipsilateral cochlear nucleus (CN) with inhibitory inputs from the medial nucleus of the trapezoid body (MNTB). The strength and number of excitatory and inhibitory inputs show notable differences. The convergence of multiple excitatory input fibers (~10‑40) is a source for synaptic noise in the spike driving inputs. We focused on how synaptic noise that arises from input strength variability and temporal jitter affects LSO neuron output. Modeled pre-synaptic spiking patterns were convolved into time-varying conductances and used for dynamic-clamp stimulations in whole-cell patch-clamp experiments of adult mouse LSO neurons (>P30). By distributing the total excitatory conductance to various numbers of converging inputs, we analyzed the influence of synaptic noise on the output rate and the temporal precision of LSO neurons. The stimulus onset was reliably encoded across stimulation paradigms. Few strong inputs induced high sustained spiking, which decreased with decreasing synaptic noise (4 inputs at 10 nS: 230 Hz; 40 inputs at 1 nS: 2 Hz). The spiking of LSO neurons to sinusoidal stimulations demonstrated bandpass filtering, optimal at 200-500 Hz. High synaptic noise increased spiking rates but reduced temporal precision. Taken together, to recapture in-vivo like LSO output, low synaptic noise is necessary, which increases synaptic filtering. Our results imply a coincidence detection mechanism by LSO neurons for computing sound source location in the LSO.