Recently

brain network method

which based on grapy theory

has played an important role in cognitive science research.And the traditional lie detection methods

which based on ERP signals

usually focus on the EEG from one channel

this has some shortcomings

that use few channels are not able to reflect the whole cognitive characteristic underlying lie condition.In this paper

we proposed a method based on brain network characteristics.We used the auditory stimuli to evoke the ERP signals and it was recorded from different channels.In order to build the functional brain network

we calculated the phase lag index between these channels

and seven network parameters were calculated as the index for lie detection.Those network parameters were compared between guilty and innocent subjects

and support vector machine was used as the classifier to the test date.The result shows that this method has a higher identify accuracy than the average accuracy of existing method

proved the validity of the method.