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Brain-computer interface (BCI) is a system that utilizes electrographical correlates of focused brain states to establish communication with computer. Here we examine C-VEP BCI paradigm – BCI based on code-modulated visual evoked potentials. Within this approach, binary m-sequence is used as pattern of visual stimulation. Circular shift is introduced, and resulting shifted sequences are used to determine flashing pattern of stimuli. When user gazes at the elements, flashing this pattern, codemodulated response is generated. This response can be extracted using canonical correlation analysis, and used to identify the target that has been chosen by user. 20 healthy adults participated in the experiment. 32 targets were arranged as a matrix on LCD monitor. Each target was altering between black and white with pattern derived from 64-bit binary msequence. The time period of the sequence was 1 second. Two flashing modes were present: “straight pattern” and “inverse pattern”, produced by inverting the same m-sequence. Accuracy above 97% was achieved by several participants in online mode. Average length of EEG sample needed to discriminate between targets was 3.5 seconds. At the offline mode we managed to achieve ITR of 150 bits/min, further online testing is required. No significant difference in performance was present between ‘straight’ and ‘inverse’ sequences. Correlation coefficient between learning and online samples can rise up to 0.6 in average time of 2 seconds. Difference in characteristics of ‘straight’ and ‘inverse’ EP are not described with simple positive or negative correlation. The nature of differences between evoked patterns proposes complex mechanism of EP generation. We have successfully created BCI based on C-VEP paradigm. The characteristics of this type of BCIs, specifically number of commands, ITR and accuracy, make this type of interfaces a viable replacement for traditional and well-proven t-VEP P300 BCIs. C-VEP BCI is suitable for communication and device control.