Computer vision powered automation of rodent arena for assessment of early Alzheimer's disease.

NIH RePORTER · NIH · R43 · $245,148 · view on reporter.nih.gov ↗

Abstract

Project summary Alzheimer's disease (AD) is the most common cause of age-related neurodegenerative disease and dementia. Despite its prevalence and deliberating health consequence, early diagnosis of AD is a serious unmet need. The current proposal seeks to develop a behavior biomarker that differentiates AD from a normal ageing process. The project proposes to develop an automated rodent behavior testing system for non-invasively assessing the early AD, based on strong evidence from AD imaging studies and neurophysiology research on a specific type of innate defensive behavior across a variety of species. The midbrain structure governing the sensorimotor computation of looming stimuli can trigger defensive behaviors, such as freezing and escape, in rodents. Interestingly, a number of clinical studies have shown that the midbrain region is affected very early in AD. Taking the findings from the two areas together, it is conceivable that the defensive behaviors triggered by looming stimuli can serve as a biomarker for early AD. MPI Drs. Chen and Luo’s preliminary study with AD mice has provided a proof of concept. In this SBIR grant, we propose to develop an automated defensive behavior testing system, and conduct rigorous studies to show the association between AD pathology and defensive behaviors. We believe the system can help accelerate AD research, by providing a novel assessment of early AD and saving cost.

Key facts

NIH application ID
11007099
Project number
1R43AG090213-01
Recipient
EYENEXO LLC
Principal Investigator
Dong Feng Chen
Activity code
R43
Funding institute
NIH
Fiscal year
2024
Award amount
$245,148
Award type
1
Project period
2024-09-10 → 2026-08-31