Abstract: Tactile perception is one of the five human senses. It plays an important role for human beings in object recognition. Tactile perception begins with the mechanical stimulation induced by friction and was processed in the somatosensory cortices of brain. In this study, the influence of surface roughness on the tactile perception was investigated from finger friction to brain activation using friction and event-related potentials methods. Samples with different arithmetic mean deviation (R_a) and arithmetic mean width (R_sm) of the roughness profile elements were chosen. The friction and ERP studies were performed using a 32-channel EEG-System and a home-made tribometer, respectively. Subjective evaluations of the samples were scored. The spectrum of vibration signals was obtained by fast Fourier transform. The original vibration signals were decomposed into ten intrinsic mode functions using the empirical mode decomposition method, then the noise signals derived from the tester and the environment were removed from the original vibration signals. The characteristic features of friction coefficient, spectral centroid, and vertical deviation were extracted from the vibration and friction signals.　The results indicated that as the decreasing of R_a and R_sm, the friction coefficient and spectral centroid increased, and the vertical deviation decreased. The large values of vertical deviation, spectral centroid, and coefficient of friction were corresponding to the strong roughness, well fineness, and large stickiness feelings of the perceived surfaces. The characteristic features of vertical deviation, spectral centroid, and friction coefficient can reflect the morphology characteristics of surface, which was consistent with the subjective perception evaluation of human. They can quantify the roughness, fineness, and stickiness feelings of the perceived surfaces. The P200 components of ERP waveform were related with perceived surface roughness. The larger surface roughness tended to evoke higher peak amplitude of P200. The P300 component was related to subjective cognitive judgment. The surface with strong roughness, poor fineness and low stickiness induced a high P300 peak and a short latency.　The comprehensive analysis indicated that when finger touching the surfaces with the large values of R_a and R_sm, the indentation of the asperities into the skin became large, then deformation friction derived from the viscoelastic loss fraction of skin and mechanical interlocking of asperities increased. The large deformation friction produced strong deformation and vibration that stimulate the mechanoreceptors embedded in skin. The cutaneous mechanoreceptors input the strong tactile stimulation to the corresponding sensing area of cerebral cortex. The strong tactile stimulations produced by the rough surface promote the neurotransmission, which in-turn enhanced the neuronal response properties and temporal processing, which reflected the high P200 and P300 peak amplitude, and the short P300 latency.　This study proved that the surface roughness of material can affect the brain activity and subjective evaluation of tactile perception by influencing the vibration and friction behavior of skin. The surface friction characteristics, the electrophysiological response of brain, and the subjective evaluation of tactile perception were correlated. The combination of them was an effective method to systematically study the tactile perception of rough surface. The study supported the tactile comfort and gripping reliability design on products, as well as the quantitative evaluation of tactile sensation.　It should be noted that we just investigated the influence of R_a and R_sm on the roughness feeling in this study. However, the roughness feeling is also related with the surface texture features, like the shape, height, and density of the textures. More work about texture features can be done to establish their effects on tactile perception of roughness.