Investigator: Yalda Shahriari, University of Rhode Island

Mentor: Walter Besio, University of Rhode Island

Scientific Theme: Neuroscience

Abstract: Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder that affects muscles and nerves. The average life expectancy of ALS is 2-5 years from the diagnosis. In recent years ALS has been recognized as a multi-system disorder, where not only the motor system degenerates but also the behavior and cognition (i.e. non-motor system) is affected. Non-motor impairment shortens the median survival rate of ALS patients by an average rate of one year. On the other hand, up to 15% of those receiving an ALS diagnosis are false positive (FP) and 40% of those receiving an ALS diagnosis are false negative (FN). Establishing a set of reliable non-motor brain biological markers (i.e. biomarkers), as indicative of ALS non-motor impairment state, can help us in a better understanding of ALS, and therefore, assist the clinicians in the early diagnosis of this disease. Providing a proper communication system for these patients is another challenge in this domain. To this matter, Brain-Computer Interface (BCI) systems, have been developed over the past several years. However, to have a more sophisticated BCI system, there is a need to consider the importance of ALS brain biomarkers in the design. The long-term goal of this study is providing a strong foundation for incorporating the ALS brain biomarkers into the existing clinical, diagnostic, and communication applications of ALS with the ultimate goal of improving the quality of life of such patients. The experimental setup in this project will focus on simultaneous recordings of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), as two complementary brain imaging modalities which can capture concurrent electrophysiological and hemodynamic activities of the brain. Aim 1 of this study, focuses on developing differential algorithms, between healthy and ALS brain patterns, and establishing a set of biomarkers that significantly can help clinicians in early diagnosis of ALS. To accomplish this aim, we will explore the neurophysiological biomarkers of ALS that are associated with their motor and non-motor dysfunction scores and significantly different from healthy population. In Aim 2, we will explore brain biomarkers associated with ALS cognitive and behavioral fluctuations. To do so, we will identify the within-groups significant biomarkers associated with their daily non-motor functions. The outcomes from this aim will provide the first steps towards establishing a set of biomarkers engaged with the ALS non-motor variations, which play an important role in the clinical management of ALS, patient survival rate, and proper design of an adaptive BCI system, for the communication application of ALS patients.

Human Health Relevance: The proposed study, will not only help us in a better understanding of ALS but also can be used as a guideline for developing novel techniques for early diagnosis and therapy of a wide range of neurological disorders. It will also boost the current knowledge in designing adaptive BCI systems for the communication applications of a wide range of patients with neuromuscular disorder that are unable to do any voluntary movement task but their brain function is still intact.