This study focuses on the synchronization problem of N-coupled Hindmarsh-Rose (H-R) neuronal model with constant delays through a sampled-data control (SDC) approach. In literature, the stability of the H-R model is determined without solving the nonlinearities of the model. However, the present study investigates the stability of the model without changing the dynamical behavior of the original model by employing the T-S fuzzy approach. The T-S fuzzy-based H-R model, without any desired controlled input, serves as the master model, with controlled input serves as the slave model. In this regard, the present study designs the SDC scheme in the form of a discrete-time type with a zero-order holder (ZOH) technique for handling discrete-time control actions. The closed-loop error dynamics were obtained from the master and slave model, namely the error model. Synchronization analysis for the proposed error model is analyzed by employing the Lyapunov stability theory. In this regard, the Lyapunov-Krasovskii Functional (LKF) is constructed to derive the sufficient condition for the proposed error model. The sufficient conditions are derived from the derivative of the LKF in terms of linear matrix inequalities (LMIs). LMIs are solved with the help of the MATLAB YALMIP toolbox. The sufficient condition ensures the global asymptotic stability of the proposed error model. Finally, the numerical simulation shows the effectiveness of the theoretical framework.