A severe physical disability has a dramatic impact on a person's life, whether it is caused by a neuro-degenerative disease such as amyotrophic lateral sclerosis (ALS), a brainstem stroke, or a spinal cord injury. Someone with these conditions may be effectively "locked-in," retaining their cognitive ability, but unable to perform any movement except possibly the most basic eye movements. Among people with such disabilities, there is a keen interest in technology that can be operated "just by thinking." Short of a cure for the particular condition causing their disability, technology of this type, called a brain-computer interface (BCI), is the best option for restoration of function. A BCI could be used to operate a communication device, wheelchair, or a prosthetic limb. For someone who is locked-in, such technology may offer the only option for communication and self-determination, while for someone with ALS, it would provide a desirable alternative method of control that could potentially be retained as other functional abilities deteriorate. Operation of a BCI would rely on detection and processing of voluntary brain activity such as the ability to attempt or imagine movements such as tapping a finger, or moving a leg, brain activity that survives the condition resulting in the disability. However, the affect of ALS progression on the cortical areas that produce this brain activity is not well understood. The proposed research will use neuro-imaging techniques to map and longitudinally study regions of cortex in persons with ALS that could provide controls signals for a BCI. Using functional magnetic resonance imaging (fMRI) in conjunction with a series of motor control experiments over a period of several years we will longitudinally map brain activation patterns to examine functional stability, atrophy and plasticity. By using state of the art medical imaging, this project will further the understanding of amyotrophic lateral sclerosis (ALS), also commonly known as "Lou Gehrig's Disease", and the disease's effect on the human brain and central nervous system. This knowledge will contribute to the biomedical engineering effort to build devices to allow people with ALS to directly control computers and assistive technologies with their brains.