With the development of BCI technology, simple non-behavioral human-computer interaction has been achieved. However, due to the low signal-to-noise ratio and time-varying nature of EEG signals, the existing signal processing algorithms is inadequate for online applications. This has become the bottleneck that restricts the development of man-machine integrated system based on brain-computer interface technology.We realized that a single state of mind measurement technology would be very difficult to achieve efficient brain-computer integrated system, therefore, the multi-modality measurement fusion technology is an inevitable trend.At present, researches on affective recognition are mainly based on single signal, while the multi-modal emotion recognition combining with multiple signals needs to be further studied. This article describes a multi-modal synchronous acquisition cognitive experiment platform. The platform uses three independent signal acquisition and analysis systems of EEG, eye movement and expression monitoring, and realizes the accurate synchronization of three types of signals based on EEG with the self-developed synchronization module. The EEG, eye movement and facial expression information can be effectively and efficiently standardized to form a large-scale multi-ethnic cognitive database so as to facilitate the standardization of cognitive experiments, especially affective recognition.