This paper investigates the synchronization of reaction-diffusion neural networks (RDNNs) with distributed delay via quantized boundary control. To reduce the communication burden, a novel control strategy combined boundary control and logarithmic quantizer is proposed, and two controllers respectively subject to constant and adaptive coefficients are carried out. Worth mentioning that the adaptive feedback gain is a matrix in this paper rather than a one-dimensional variable in most of the existing literatures. Using the Lyapunov functional, the sufficient conditions for delay-dependent synchronization are obtained through linear matrix inequalities. The effectiveness of the proposed control strategy is illustrated via two examples.

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