Brain-computer interface (BCI)-based identification of color vision deficiencies (CVDs) related to Parkinson’s Disease (PD)

Project Summary/Abstract Parkinson’s disease (PD) reduces the voluntary movements, emotional expressions, and life expectancy of about one million Americans. Early identification and treatment of PD reduces costs and is associated with better therapeutic outcomes. There are putative signs of PD (i.e., prodromal PD) more than 20 years before clinical diagnosis (i.e., clinical PD). Given the 60,000 to 95,000 North Americans diagnosed with PD every year and the $52 billion annual cost of treating PD, new methods for early identification of PD are urgently needed. Color vision deficiencies (CVDs) may be a valuable biomarker of prodromal PD. PD-related changes in color vision (CV) remain unexplored, however, because present CV assessments are not sensitive/specific enough, or are unsuitable for people with PD-related cognitive impairments and/or motor deficits (CIs/MDs). We recently developed a brain-computer interface (BCI)-based CV assessment that has significant advantages over present behavior-based approaches. As a first step towards BCI-based CV assessment for the identification of prodromal PD, we propose to test whether BCI-based CV assessment can identify CVDs related to clinical PD. It is our hypothesis that the new BCI-based method has sufficient sensitivity/specificity and test-retest reliability to detect PD-related CVDs. To test this hypothesis, we have two specific aims: 1. Demonstrate the ability of the BCI-based CV assessment to more accurately identify CVDs related to PD than present behavior-based CV assessments. People with PD and controls will be recruited to complete BCI- and behavior-based CV assessments. We expect that BCI-based CV assessment will more accurately classify individuals with PD as having CVDs (i.e., have enhanced sensitivity) and individuals without PD as not having CVDs (i.e., have enhanced specificity) than behavior-based CV assessments. 2. Show that the test-retest reliability of BCI-based CV assessment is higher than the “gold-standard” behavior-based CV assessment in people with PD. People with PD and controls will be recruited to com- plete BCI- and “gold-standard” behavior-based CV assessments three times each; participants with PD will undergo a neurological evaluation. We will analyze the test-retest reliability of the CV assessments and cor- relations between test-retest reliability and PD stage, CIs, and MDs. We predict that the test-retest reliability of the BCI-based CV assessment will be higher in people with PD-related CIs/MDs. In summary, the purpose of this research is to identify PD-related changes in CV using a new BCI-based approach; it is hypothesized that this method will have enhanced sensitivity, specificity, and test-retest reliability compared to present behavior-based CV assessments. A sensitive/specific CV assessment for detecting PD- related CVDs would enable earlier detection and diagnosis of PD and improved monitoring of PD progression. In addition, a sensitive/specific CV assessment could enable detection of CVDs caused by other neurological disorders, including multiple sclerosis (MS) and Alzheimer’s disease (AD).