  Brain-computer interfaces (BCIs) have the potential to significantly change
the ways in which humans interact with technology, the environment, and even
each other. Unfortunately, BCI technologies are seldom robust enough for use in
real-world applications, in part due to the large amount of data that must be
collected, processed, and classified in order to develop models of task-related
neural activity that account for two of the most important and least-understood
drivers of BCI illiteracy: individual differences in neural signals and
intra-individual differences across interdependent, time-varying neural states.
This paper describes the feasibility of using a game with a purpose (GWAP) as a
viable instrument for collecting data from BCI-relevant research tasks. By
leveraging game-related reward processes to maintain participant interest and
engagement, this approach will enable large amounts of BCI data to be acquired,
both across many individuals and longitudinally from specific individuals as
neural states vary naturally over time. Pilot and technical testing results are
presented here to demonstrate that the BCI-relevant tasks embedded within the
research game elicit neural signals similar to those that would be expected
from more traditional BCI tasks. These preliminary data provide support and
validation of the use of GWAPs as promising tools to enable long-term
collection of BCI-relevant data in an engaging environment.
