Path integration impairments reveal early cognitive changes in Subjective Cognitive Decline

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Psychiatry

Background:

• Path integration relies on the entorhinal cortex grid cell network, which is vulnerable to early Alzheimer's disease (AD) pathology.
• Subjective cognitive decline (SCD) represents an at-risk group for AD, making it crucial to identify early cognitive markers.

Purpose of the Study:

• To investigate path integration performance in individuals with SCD compared to healthy controls.
• To utilize a computational model to dissect path integration errors into distinct components.
• To assess the potential of navigation tasks for detecting pre-symptomatic AD-related cognitive changes.

Main Methods:

• An immersive virtual reality navigation task was employed to assess path integration.
• A Bayesian computational model was developed to analyze and quantify sources of path integration error.
• Participants included individuals with SCD and age-matched healthy controls.

Main Results:

• SCD participants demonstrated significantly impaired path integration compared to controls.
• The primary driver of path integration deficits in SCD was an increased memory leak.
• Other error components, including velocity gain and sensory/reporting noise, were comparable between groups.

Conclusions:

• Impaired path integration, specifically memory leak, may serve as an early indicator of neurodegeneration in individuals with SCD.
• Self-motion-based navigation tasks show promise for detecting pre-symptomatic cognitive alterations associated with Alzheimer's disease.
• Computational modeling of navigation errors can provide sensitive biomarkers for early AD detection.