Visuospatial performance and its neural substrates in Dementia with Lewy Bodies during a pointing task

Scritto il 21/10/2025
da Bosco Annalisa

Sci Rep. 2025 Oct 21;15(1):36711. doi: 10.1038/s41598-025-20671-w.

ABSTRACT

Dementia with Lewy Bodies (DLB) is characterized by motor and cognitive deficits that often overlap with other neurodegenerative disorders, complicating its diagnosis. This study combined linear mixed-effects modeling and machine learning to investigate key parameters of pointing movements, saccadic behavior, and superior parietal lobule (SPL) volumetry in differentiating DLB patients from controls. DLB patients exhibited distinct motor impairments, including increased movement times, greater pointing errors, and spatially modulated deficits in pointing accuracy. Saccadic analysis revealed prolonged saccade latencies, larger amplitudes, and pervasive hypermetria, with notable spatial asymmetries in accuracy and amplitude. Specifically, reduced hypermetria for upward-directed saccades suggests direction-specific modulation in DLB, highlighting potential disruptions in visuomotor pathways. Brain volumetric analysis demonstrated significant volumetric loss of SPL, particularly in the left hemisphere, further implicating this region in the visuospatial and motor deficits observed in DLB. Interestingly, an inverse relationship between SPL volumetry and task performance was found, more evident for hand-related parameters. The integration of behavioral, saccadic, and volumetric data revealed that a combined approach highlights the complementary contributions of motor, oculomotor, and neural changes in distinguishing patients from controls. This study provides novel insights into the visuomotor and neural substrates underlying DLB and emphasizes the importance of adopting a multimodal approach to its diagnosis. The results go beyond traditional visuospatial assessments, offering a robust framework for the identification of DLB-specific biomarkers. Future research should explore the generalizability of this combined model across other neurodegenerative conditions to refine diagnostic tools and improve patient outcomes.

PMID:41120602 | PMC:PMC12540648 | DOI:10.1038/s41598-025-20671-w