Visually evoked potentials have attracted great attention in the last two decades for the purpose of brain computer interface design. Visually evoked P300 response is a major signal of interest that has been widely studied. Steady state visual evoked potentials that occur in response to periodically flickering visual stimuli have been primarily investigated as an alternative. There also exists some work on the use of an m-sequence and its shifted versions to induce responses that are primarily in the visual cortex but are not periodic. In this paper, we study the use of multiple m-sequences for intent discrimination in the brain interface, as opposed to a single m-sequence whose shifted versions are to be discriminated from each other. Specifically, we used four different m-sequences of length 31. Our main goal is to study if the bit presentation rate of the m-sequences have an impact on classification accuracy and speed. In this initial study, where we compared two basic classifier schemes using EEG data acquired with 15Hz and 30Hz bit presentation rates, our results are mixed; while on one subject, we got promising results indicating bit presentation rate could be increased without decrease in classification accuracy; thus leading to a faster decision-rate in the brain interface, on our second subject, this conclusion is not supported. Further detailed experimental studies as well as signal processing methodology design, especially for information fusion across EEG channels, will be conducted to investigate this question further.