Anticipatory reaching motor behavior characterizes patients within the Alzheimer's disease continuum in a virtual...

Alzheimer's Disease (AD) is characterized by progressive declines in cognitive and motor functions, impairing daily activities. Traditionally, AD diagnosis relies on cognitive assessments, but emerging evidence highlights motor function deficits as early indicators of AD and Mild Cognitive Impairment (MCI). These motor declines, which often precede cognitive symptoms, include slower and less accurate reaching movements. This study explored reaching actions in a Virtual Reality (VR) environment in AD and MCI patients to identify motor deficits and their link to cognitive decline.

The study involved 61 right-handed participants (19 AD, 21 MCI, and 21 healthy age-matched controls), screened for cognitive health using a Mini-Mental State Examination (MMSE). Participants performed upper-limb motor tasks (sequentially reaching targets) in a Virtual Reality (VR). Kinematic data was recorded and analyzed focusing on task success rate, frequency of anticipatory responses, and direction of anticipatory responses. Statistical analysis was performed using Generalized Linear Mixed Models to differentiate the three groups of participants based on performance metrics, anticipation behavior, and the correlation between anticipation rate and MMSE score.

Both AD and MCI patients showed more anticipatory responses than healthy controls (HC), inversely related to success rates and cognitive function. AD patients exhibited lower success rates and a higher frequency of anticipatory responses, often biased toward previous trial targets, suggesting impaired motor planning or difficulty adapting to new cues. MCI patients showed an intermediate pattern, with more anticipatory responses than HC but comparable success rates. These results highlight the crucial role of anticipatory behavior in motor task performance, with AD patients displaying the most pronounced deficits.

This study highlights significant impairments of reaching movements in AD patients, particularly in terms of anticipatory behavior and success rates. The observed deficits suggest that kinematic metrics could serve as early biomarkers for diagnosis and intervention. These findings emphasize the importance of combining cognitive and sensorimotor assessments for the early detection of AD-related motor dysfunctions. Additionally, they highlight the potential of VR-based motor rehabilitation as a promising approach to address sensorimotor deficits in the AD continuum, improving both motor and cognitive outcomes.