This paper employs statistical complexity measure (SCM) to investigate the occurrence of stochastic multiresonance (SMR) induced by noise and time delay in small-world neural networks coupled with FitzHugh-Nagumo (FHN) neurons. Our findings reveal that SCM exhibits four local maxima for four optimal noise levels, providing evidence for the occurrence of quadruple stochastic resonances. Additionally, the research uncovers a series of optimal time delays for different noise intensities, where SCM shows several local maxima, indicating the appearance of SMR induced by time delay. Intriguingly, these optimal time delays are characterized by some small values of time delay, nTe as well as nTe-2 with n being a positive integer and Te being the period of subthreshold signal, respectively. Furthermore, the study demonstrates that the presence of time delay, coupled with the assistance of moderate noise, effectively enhances the detection capability of the subthreshold signal. These results provide a precise method to comprehend weak signal detection and information propagation in neural systems.