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

> **NIH NIH R21** · ALBANY RESEARCH INSTITUTE, INC. · 2024 · $204,000

## Abstract

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 a...

## Key facts

- **NIH application ID:** 10952944
- **Project number:** 1R21EB036221-01
- **Recipient organization:** ALBANY RESEARCH INSTITUTE, INC.
- **Principal Investigator:** JAMES John Stanley NORTON
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $204,000
- **Award type:** 1
- **Project period:** 2024-08-06 → 2027-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10952944

## Citation

> US National Institutes of Health, RePORTER application 10952944, Brain-computer interface (BCI)-based identification of color vision deficiencies (CVDs) related to Parkinson’s Disease (PD) (1R21EB036221-01). Retrieved via AI Analytics 2026-06-12 from https://api.ai-analytics.org/grant/nih/10952944. Licensed CC0.

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