The detrusor, a key component of the urinary bladder wall, is a densely innervated syncytial smooth muscle tissue. Random spontaneous release of neurotransmitter at neuromuscular junctions (NMJs) in the detrusor gives rise to spontaneous excitatory junction potentials (SEJPs). These sub-threshold passive signals not only offer insights into the syncytial nature of the tissue, their spatio-temporal integration is critical to the generation of spontaneous neurogenic action potentials which lead to focal contractions during the filling phase of the bladder. Given the structural complexity and the contractile nature of the tissue, electrophysiological investigations on spatio-temporal integration of SEJPs in the detrusor are technically challenging. Here we report a biophysically constrained computational model of a detrusor syncytium overlaid with spatially distributed innervation, using which we explored salient features of the integration of SEJPs in the tissue and the key factors that contribute to this integration. We validated our model against experimental data, ascertaining that observations were congruent with theoretical predictions. With the help of comparative studies, we propose that the amplitude of the spatio-temporally integrated SEJP is most sensitive to the inter-cellular coupling strength in the detrusor, while frequency of observed events depends more strongly on innervation density. An experimentally testable prediction arising from our study is that spontaneous release frequency of neurotransmitter may be implicated in the generation of detrusor overactivity. Set against histological observations, we also conjecture possible changes in the electrical activity of the detrusor during pathology involving patchy denervation. Our model thus provides a physiologically realistic, heuristic framework to investigate the spread and integration of passive potentials in an innervated syncytial tissue under normal conditions and in pathophysiology.