0638625 20260224162857.020250904235959.9 105015048097 001562541400019 10.1126/sciadv.adw6404 16 s. P cav_un_epca*04800432375-254811American Association for the Advancement of Science Subjective cognitive decline Alzheimer’s disease Bayesian computational model cav_un_auth*0494631 Segen V. DE cav_un_auth*0494632 Kabir M. R. US cav_un_auth*0494633 Streck A. DE cav_un_auth*0370372 Slavík Jakub UTIA-B Stochastická informatika Department of Stochastic Informatics SI SI CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0494636 Glanz W. DE cav_un_auth*0494637 Butryn M. DE cav_un_auth*0494638 Newman E. US cav_un_auth*0494639 Tiganj Z. US cav_un_auth*0494640 Wolbers T. DE https://library.utia.cas.cz/separaty/2025/SI/slavik-0638625.pdf https://www.science.org/doi/10.1126/sciadv.adw6404 Path integration, the ability to track one’s position using self-motion cues, is critically dependent on the grid cell network in the entorhinal cortex, a region vulnerable to early Alzheimer’s disease pathology. In this study, we examined path integration performance in individuals with subjective cognitive decline (SCD), a group at increased risk for Alzheimer’s disease, and healthy controls using an immersive virtual reality task. We developed a Bayesian computational model to decompose path integration errors into distinct components. SCD participants exhibited significantly higher path integration error, primarily driven by increased memory leak, while other modeling-derived error sources, such as velocity gain, sensory, and reporting noise, remained comparable across groups. Our findings suggest that path integration deficits, specifically memory leak, may serve as an early marker of neurodegeneration in SCD and highlight the potential of self-motion–based navigation tasks for detecting presymptomatic Alzheimer’s disease–related cognitive changes. WOS FH 30000 30100 30103 2026 RVO:67985556 https://hdl.handle.net/11104/0370054 S eadw6404 C MULTIDISCIPLINARYSCIENCES 14.1 2.4 4.1 0.36776 4.868 181324 288 4.324 69.4 12.06 80733 Q1 12.300 2263 Q1 92 2.82 Q1 91.5 2025 105015048097 SCOPUS PUBMED 001562541400019 WOS cav_un_epca*0480043 Science Advances Roč. 11 č. 36 2025 2375-2548 2375-2548 American Association for the Advancement of Science