Severe motor disabilities such as amyotrophic lateral sclerosis (ALS), brainstem stroke, cerebral palsy, and spinal cord injury reduce or eliminate neuromuscular control and deprive affected patients of communication and control that is vital to their mental and physical health. Recent advances in noninvasive EEG-based brain-computer interfaces (BCIs) have given these patients new hope for communication and control of their environment that is not provided by other assistive devices. BCIs succeed where other devices fail because they use a control technology that depends directly on neuronal signals without any requirement for neuromuscular control. Despite the promise provided by these devices improvements in several areas are necessary to translate the technology to the target population on a large scale. The current proposal will address three factors that can significantly improve P300-based BCI performance. First, we will manipulate matrix size from the traditional 6x6 to an 8x9 matrix. Based on preliminary data, we expect matrix size to increase amplitude of the P300 response, thereby making the system more accurate. Second, we will use mindfulness meditation and induction (MMI) to increase users'attentional focus. Via increases in attentional control, we expect that MMI will also increase P300 amplitude, decrease response latencies associated with BCI use, and reduce eye movements from the target that undermine BCI performance (which will be monitored via eye tracking hardware).Third, we will test the performance of the improved standard system to a novel BCI presentation method, referred to as the checkerboard paradigm (CBP). Whereas the standard paradigm presents groups of stimuli arranged as rows and columns (i.e., the row/column paradigm or the RCP), the CBP presents quasi-random groups of stimuli derived from a checkerboard style layout. We expect that the MMI and CBP will mitigate the effects of attention being diverted to non-targets, and consecutive target flashes. We also hypothesize that the subjects will prefer the CBP over the RCP. Collectively, these improvements offer the potential to increase the robustness and usability of the BCI system, which is particularly important for those without other means of communication.
This purpose of this research proposal is to advance performance and usability of brain- computer interface (BCI) technology. BCIs use the electroencephalogram (EEG) instead of normal muscular output pathways for communication. Because they do not depend on neuromuscular control, BCIs provide a means of communication for people with severe neuromuscular disabilities such as amyotrophic lateral sclerosis (Lou Gehrig's Disease), which ultimately render these people locked-in to their bodies. Thus, BCIs can restore the ability to communicate and interact with others.
