A brain-computer interface (BCI) is a system that provides a separate output pathway for neurological signals whereby they can be interpreted to determine the user's intended cognitive action. Utilizing EEG-based sensorimotor rhythms (SMRs) generated in the motor cortex has allowed subjects to control virtual computer cursors in up to three dimensions by simply imagining the movement of a specified body part. Nevertheless, the scalp EEG signals are smeared by the volume conduction effect and measurement noise. The overall hypothesis of this study is that EEG-based virtual object control may help reveal optimal motor imagination tasks best used in a BCI.

The PI's hypotheses include: (1) The use of advanced signal processing techniques will better reveal characteristics of EEG signals that represent the underlying motor cognitive function of the subject; (2) BCI systems based on SMR generated using motor imaginations will allow effective control of a virtual object in real time; (3) EEG imaging techniques will provide insight into the areas of cortical activation during a motor imagery task that can be utilized to increase the spatial resolution of non-invasive BCI's.

The goal of the present study is to explore advanced signal processing techniques that will better reveal characteristics of EEG signals that represent the underlying motor cognitive function of the subject, and conduct experiments to better control an virtual object on the computer screen including a cursor or a helicopter.

The primary objective of this study is to test the above hypotheses (1) and (2) in a healthy subject population.This study will determine the ability of subjects with full cognitive function to control a non-invasive brain-computer interface by imagining a particular movement. Using non-invasive methods, we will investigate the neural processes that occur during the motor imagination tasks associated with controlling a virtual object. Using a variety of motor imaginations, we will determine which tasks are best used for BCI control by quantitative means of BCI performance and neurological dynamic system analysis.

Subjects for this study will be healthy, English speaking adult volunteers (18-64 years old) with no history of mental illness, neurological deficit, or traumatic brain injury.

Inclusion Criteria:

• Between the age of 18 and 64

Exclusion Criteria:

• History of traumatic brain injury/brain lesion, neurological deficit or neurodegenerative disorder

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