Contrast Sensitivity Predicts Functional Brain Network Integrity in Cognitively Unimpaired Older Adults

Abstract

Purpose : Visually impaired older adults are prone to limitations in mobility function, yet the factors underlying this connection remain inadequately understood. The purpose of this study was to evaluate whether contrast sensitivity (CS) may predict future functional brain health in areas of the brain important not only to vision but also to mobility.

Methods : This analysis includes 172 cognitively unimpaired, community-dwelling older adults who had undergone binocular (CS) testing at baseline and completed a 30-month functional MRI scan. Functional MRI (fMRI) was captured at rest and during a motor imagery (MI) task. The brain’s functional networks were divided into communities defined by elements of the community being more connected to each other than the rest of the brain. We tested whether there was an association of baseline CS with 30-month community structure at rest and during the MI task within the visual network (VN), dorsal attention network (DAN), and default mode network (DMN), due to their roles in vision, visuospatial attention, and self-referential processes, respectively.

Results : Participant mean age was 76.4 +/- 4.8 years, with 56.4% female and 11.6% non-white or Hispanic. Worse CS at baseline predicted lower community structure integrity at 30 months in the DAN (p=0.0089), the VN (p<0.0001), and the DMN (p<0.0001) during rest. Worse CS was also associated with degraded DMN during the MI task (p=0.0002). These associations remained significant after controlling for baseline brain network community structure integrity, head motion, and sex.

Conclusions : These findings demonstrate that poor CS is predictive of decreased connectivity in networks of the brain important to vision, visuospatial attention and self-referential processing. These results may identify a subset of persons for testing interventions to improve CS and functional brain health in older adults.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.