With the rapid development of society, modern technologies such as artificial intelligence, the Internet, multimedia, 5G communication, and big data services have been widely used in national production and daily life. Moreover, the demand for computing power in the whole society is increasing at a rate of at least 20% every year, which brings unprecedented challenges to the computing power of present computing systems. At present, the traditional Von Neumann architecture based on the separation of storage and computing has encountered bottlenecks including storage, computing speed, power consumption, etc. In addition, Moore's Law has also encountered bottlenecks due to the limitations of CMOS technology, and the development of integrated circuits has entered into a post-Moore era. Consequently, the research and development of artificial neural networks have attracted much attention, and photonic neural networks based on silicon-based electronic devices or optical devices have become the focus issue. Photonic neural networks can overcome the limitations of the von Neumann architecture and have the advantages of low power consumption and high speed when dealing with complex artificial intelligence tasks, which can provide a new feasible solution for solving complex problems such as decision-making, deep learning and optimization, pattern recognition, and perceptual information processing. In recent years, photonic neural networks have become a research hotspot due to their obvious advantages over traditional electronic methods in terms of speed and energy efficiency. As a result, neuromorphic photonic devices have attracted extensive attention. Amongst of them, semiconductor lasers have become an ideal artificial neuron due to similar response behavior to biological neuron and ultrafast response speed. In particular, VCSELs possess these advantages of small size, low power consumption, low cost, and high coupling efficiency with optical fibers. Therefore, exploring the nonlinear dynamic behaviors of VCSEL and their applications in these fields related to neuromorphic computing is expected to promote innovative development in the field of artificial intelligence. Recently, the spiking dynamics of VCSEL photonic neurons under external stimuli has been reported theoretically and experimentally. It is worth noting that introducing an extra Saturable Absorber (SA) into VCSEL can constitute an integrated two-section excitable laser (VCSEL-SA). Compared with the traditional photonic neuron model, this integrated photonic neuron can be used as a LIF model. Moreover, the spatiotemporal information can be encoded in the output spike signals of VCSEL-SA and the characteristics of biological neurons can be better simulated. In addition, VCSEL-SA can excite a shorter sub-nanosecond light pulse and its excitation threshold can also be flexibly controlled within a certain range. Therefore, the research and application of VCSEL-SA in the related fields of photonic neural network has become increasingly important.At present, optoelectronic hybrid information processing technology is still an important development direction for the future information technology field. Optoelectronic logic gate, as a key functional element in an optoelectronic hybrid system, can be applied to functional modules such as payload coding, parity checking, generation of ultra-high-speed pseudo-random sequences, and optical computing. So far, logic operation based on optoelectronic method has been realized. However, the traditional scheme usually has some disadvantages such as complex structure, multi-step or requiring relatively high power. Combining the cost efficiency of reconfigurable logic devices for future large-scale integration and unique advantages of VCSEL-SA, the optoelectronic logic gate based on VCSEL-SA can open a new path for future optoelectronic hybrid processing platform. In this paper, we propose a reconfigurable optoelectronic logic gate (NOT, NAND, NOR, XOR) based on the VCSEL-SA under the combined action of current modulation and optical injection, then the spiking dynamics of VCSEL-SA under current modulation are numerically studied, and the logic operation performance of VCSEL-SA is realized by the combined action of current modulation and optical injection. The research results show that, for the optical injection VCSEL-SA under current modulation, the optoelectronic logic gate can be realized within a certain bias current range. By selecting an appropriate modulation current, reconfigurable logic operations (NAND, NOR) can be realized, and the time delay between the two modulation signals has little effect on its performance. By changing the input mode of the current modulation signal and removing the optical injection signal, the VCSEL-SA can realize the XOR logic operation. In addition, the reconfigurable logic operation based on VCSEL-SA has good robustness to noise. These research results can provide a certain theoretical basis for future neuromorphic photonic networks to solve complex tasks.