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 modelling-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 pre-symptomatic Alzheimer's disease-related cognitive changes.

Aging Cognition and Technology Group German Center for Neurodegenerative Diseases Magdeburg 39120 Germany

Center for Behavioural Brain Sciences Otto von Guericke University Magdeburg Magdeburg 39120 Germany

Department of Computer Science Indiana University Bloomington USA

Department of Psychological and Brain Sciences Indiana University Bloomington USA

Institute for Cognitive Neurology and Dementia Research Otto von Guericke University Magdeburg Germany

Institute for Computational Cancer Biology Faculty of Medicine and University Hospital Cologne University of Cologne Germany

The Czech Academy of Sciences Institute of Information Theory and Automation Prague Czech Republic

Zobrazit více v PubMed

Etienne A. S., Jeffery K. J., Path integration in mammals. Hippocampus 14, 180–192 (2004). PubMed

Wang R. F., Building a cognitive map by assembling multiple path integration systems. Psychon Bull Rev 23, 692–702 (2016). PubMed

Gil M., Ancau M., Schlesiger M. I., Neitz A., Allen K., Marco R. J. D., Monyer H., Impaired path integration in mice with disrupted grid cell firing. Nat Neurosci 21, 81–91 (2018). PubMed

Braak H., Braak E., Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 82, 239–259 (1991). PubMed

Ying J., Reboreda A., Yoshida M., Brandon M. P., Grid cell disruption in a mouse model of early Alzheimer’s disease reflects reduced integration of self-motion cues. Curr Biol 33, 2425–2437.e5 (2023). PubMed

Fu H., Rodriguez G. A., Herman M., Emrani S., Nahmani E., Barrett G., Figueroa H. Y., Goldberg E., Hussaini S. A., Duff K. E., Tau pathology induces excitatory neuron loss, grid cell dysfunction, and spatial memory deficits reminiscent of early alzheimer’s disease. Neuron 93, 533–541.e5 (2017). PubMed PMC

Bierbrauer A., Kunz L., Gomes C. A., Luhmann M., Deuker L., Getzmann S., Wascher E., Gajewski P. D., Hengstler J. G., Fernandez-Alvarez M., Atienza M., Cammisuli D. M., Bonatti F., Pruneti C., Percesepe A., Bellaali Y., Hanseeuw B., Strange B. A., Cantero J. L., Axmacher N., Unmasking selective path integration deficits in Alzheimer’s disease risk carriers. Sci Adv 6, eaba1394 (2020). PubMed PMC

Mokrisova I., Laczo J., Andel R., Gazova I., Vyhnalek M., Nedelska Z., Levcik D., Cerman J., Vlcek K., Hort J., Real-space path integration is impaired in Alzheimer’s disease and mild cognitive impairment. Behav Brain Res 307, 150–158 (2016). PubMed

Howett D., Castegnaro A., Krzywicka K., Hagman J., Marchment D., Henson R., Rio M., King J. A., Burgess N., Chan D., Differentiation of mild cognitive impairment using an entorhinal cortex-based test of virtual reality navigation. Brain 142, 1751–1766 (2019). PubMed PMC

Huang L.-K., Kuan Y.-C., Lin H.-W., Hu C.-J., Clinical trials of new drugs for Alzheimer disease: a 2020–2023 update. J Biomed Sci 30, 83 (2023). PubMed PMC

van Dyck C. H., Swanson C. J., Aisen P., Bateman R. J., Chen C., Gee M., Kanekiyo M., Li D., Reyderman L., Cohen S., Froelich L., Katayama S., Sabbagh M., Vellas B., Watson D., Dhadda S., Irizarry M., Kramer L. D., Iwatsubo T., Lecanemab in early alzheimer’s disease. N Engl J Med 388, 9–21 (2023). PubMed

Mitchell A. J., Beaumont H., Ferguson D., Yadegarfar M., Stubbs B., Risk of dementia and mild cognitive impairment in older people with subjective memory complaints: meta-analysis. Acta Psychiatr Scand 130, 439–451 (2014). PubMed

Jessen F., Amariglio R. E., van Boxtel M., Breteler M., Ceccaldi M., Chételat G., Dubois B., Dufouil C., Ellis K. A., van der Flier W. M., Glodzik L., van Harten A. C., de Leon M. J., McHugh P., Mielke M. M., Molinuevo J. L., Mosconi L., Osorio R. S., Perrotin A., Petersen R. C., Rabin L. A., Rami L., Reisberg B., Rentz D. M., Sachdev P. S., de la Sayette V., Saykin A. J., Scheltens P., Shulman M. B., Slavin M. J., Sperling R. A., Stewart R., Uspenskaya O., Vellas B., Visser P. J., Wagner M., S. C. D. I. (SCD-I. W. Group, A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimers Dement 10, 844–852 (2014). PubMed PMC

Buckley R. F., Hanseeuw B., Schultz A. P., Vannini P., Aghjayan S. L., Properzi M. J., Jackson J. D., Mormino E. C., Rentz D. M., Sperling R. A., Johnson K. A., Amariglio R. E., Region-Specific Association of Subjective Cognitive Decline With Tauopathy Independent of Global β-Amyloid Burden. JAMA Neurol 74, 1455–1463 (2017). PubMed PMC

Lappe M., Stiels M., Frenz H., Loomis J. M., Keeping track of the distance from home by leaky integration along veering paths. Exp Brain Res 212, 81–89 (2011). PubMed

Lappe M., Jenkin M., Harris L. R., Travel distance estimation from visual motion by leaky path integration. Exp Brain Res 180, 35–48 (2007). PubMed

Stangl M., Kanitscheider I., Riemer M., Fiete I., Wolbers T., Sources of path integration error in young and aging humans. Nat Commun 11, 2626 (2020). PubMed PMC

Townsend J. T., Busemeyer J. R., Kruschke J. K., Vanpaemel W., “Bayesian estimation in hierarchical models” in The Oxford Handbook of Computational and Mathematical Psychology, [“Townsend James T. and Busemeyer Jerome R.”], Eds. (Oxford University Press, 2015; http://www.oxfordhandbooks.com/view/10.1093/oxfordhb/9780199957996.001.0001/oxfordhb-9780199957996-e-13). DOI

Segen V., Ying J., Morgan E., Brandon M., Wolbers T., Path integration in normal aging and Alzheimer’s disease. Trends Cogn Sci (Regul Ed) 26, 142–158 (2022). PubMed

Wiener J. M., Berthoz A., Wolbers T., Dissociable cognitive mechanisms underlying human path integration. Exp Brain Res 208, 61–71 (2011). PubMed

Sadalla E. K., Montello D. R., Remembering changes in direction. Environ Behav 21, 346–363 (1989).

Castegnaro A., Ji Z., Rudzka K., Chan D., Burgess N., Overestimation in angular path integration precedes Alzheimer’s dementia. Curr Biol 33, 4650–4661.e7 (2023). PubMed PMC

Mahmood O., Adamo D., Briceno E., Moffat S. D., Age differences in visual path integration. Behav Brain Res 205, 88–95 (2009). PubMed

Wrisley D. M., Marchetti G. F., Kuharsky D. K., Whitney S. L., Reliability, internal consistency, and validity of data obtained with the functional gait assessment. Phys Ther 84, 906–918 (2004). PubMed

Duffy C. J., Wurtz R. H., Response of monkey MST neurons to optic flow stimuli with shifted centers of motion. J Neurosci 15, 5192–5208 (1995). PubMed PMC

Lappe M., Bremmer F., van den Berg AV, Perception of self-motion from visual flow. Trends Cogn Sci (Regul Ed) 3, 329–336 (1999). PubMed

Hoffman M. D., Gelman A., The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research, 1593–1623 (2014).

Vehtari A., Gelman A., Gabry J., Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat Comput 27, 1413–1432 (2017).

Kruschke J. K., Rejecting or Accepting Parameter Values in Bayesian Estimation. Adv. Methods Pr. Psychol. Sci. 1, 270–280 (2018).

van Arendonk J., Wolters F. J., Neitzel J., Vinke E. J., Vernooij M. W., Ghanbari M., Ikram M. A., Plasma neurofilament light chain in relation to 10-year change in cognition and neuroimaging markers: a population-based study. Geroscience 46, 57–70 (2024). PubMed PMC

Baiardi S., Quadalti C., Mammana A., Dellavalle S., Zenesini C., Sambati L., Pantieri R., Polischi B., Romano L., Suffritti M., Bentivenga G. M., Randi V., Stanzani-Maserati M., Capellari S., Parchi P., Diagnostic value of plasma p-tau181, NfL, and GFAP in a clinical setting cohort of prevalent neurodegenerative dementias. Alzheimers Res Ther 14, 153 (2022). PubMed PMC

Janelidze S., Mattsson N., Palmqvist S., Smith R., Beach T. G., Serrano G. E., Chai X., Proctor N. K., Eichenlaub U., Zetterberg H., Blennow K., Reiman E. M., Stomrud E., Dage J. L., Hansson O., Plasma P-tau181 in Alzheimer’s disease: relationship to other biomarkers, differential diagnosis, neuropathology and longitudinal progression to Alzheimer’s dementia. Nat Med 26, 379–386 (2020). PubMed

Corder E. H., Saunders A. M., Strittmatter W. J., Schmechel D. E., Gaskell P. C., Small G. W., Roses A. D., Haines J. L., Pericak-Vance M. A., Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 261, 921–923 (1993). PubMed

Adamo D. E., Briceño E. M., Sindone J. A., Alexander N. B., Moffat S. D., Age differences in virtual environment and real world path integration. Front Aging Neurosci 4, 26 (2012). PubMed PMC

Allen G. L., Kirasic K. C., Rashotte M. A., Haun D. B. M., Aging and path integration skill: kinesthetic and vestibular contributions to wayfinding. Percept Psychophys 66, 170–179 (2004). PubMed

Newton C., Pope M., Rua C., Henson R., Ji Z., Burgess N., Rodgers C. T., Stangl M., Dounavi M.-E., Castegnaro A., Koychev I., Malhotra P., Wolbers T., Ritchie K., Ritchie C. W., O’Brien J., Su L., Chan D., Programme P. D. R., Entorhinal-based path integration selectively predicts midlife risk of Alzheimer’s disease. Alzheimers Dement 20, 2779–2793 (2024). PubMed PMC

Vandierendonck A., Kemps E., Fastame M. C., Szmalec A., Working memory components of the Corsi blocks task. Br. J. Psychol. 95, 57–79 (2004). PubMed

Gómez-Isla T., Price J. L., McKeel D. W., Morris J. C., Growdon J. H., Hyman B. T., Profound loss of layer II entorhinal cortex neurons occurs in very mild Alzheimer’s disease. J Neurosci 16, 4491–4500 (1996). PubMed PMC

Kunz L., Schröder T. N., Lee H., Montag C., Lachmann B., Sariyska R., Reuter M., Stirnberg R., Stöcker T., Messing-Floeter P. C., Fell J., Doeller C. F., Axmacher N., Reduced grid-cell–like representations in adults at genetic risk for Alzheimer’s disease. Science 350, 430–433 (2015). PubMed

Jun H., Bramian A., Soma S., Saito T., Saido T. C., Igarashi K. M., Disrupted Place Cell Remapping and Impaired Grid Cells in a Knockin Model of Alzheimer’s Disease. Neuron 107, 1095–1112.e6 (2020). PubMed PMC

Ying J., Keinath A. T., Lavoie R., Vigneault E., Mestikawy S. E., Brandon M. P., Disruption of the grid cell network in a mouse model of early Alzheimer’s disease. Nature Communications 13, 886 (2022). PubMed PMC

Burak Y., Fiete I., Accurate path integration in continuous attractor network models of grid cells. PLoS Comput Biol 5 (2009). PubMed PMC

Verret L., Mann E. O., Hang G. B., Barth A. M. I., Cobos I., Ho K., Devidze N., Masliah E., Kreitzer A. C., Mody I., Mucke L., Palop J. J., Inhibitory interneuron deficit links altered network activity and cognitive dysfunction in Alzheimer model. Cell 149, 708–721 (2012). PubMed PMC

Pastoll H., Solanka L., van Rossum M. C. W., Nolan M. F., Feedback Inhibition Enables Theta-Nested Gamma Oscillations and Grid Firing Fields. Neuron 77, 141–154 (2013). PubMed

Rodríguez-Martín T., Pooler A. M., Lau D. H. W., Mórotz G. M., Vos K. J. D., Gilley J., Coleman M. P., Hanger D. P., Reduced number of axonal mitochondria and tau hypophosphorylation in mouse P301L tau knockin neurons. Neurobiol Dis 85, 1–10 (2016). PubMed PMC

Colgin L. L., Mechanisms and functions of theta rhythms. Annu Rev Neurosci 36, 295–312 (2013). PubMed

Brandon M. P., Bogaard A. R., libby C. P., connerney M. A., Gupta K., Hasselmo M. E., Reduction of theta rhythm dissociates grid cell spatial periodicity from directional tuning. Science (New York, NY) 332, 595–599 (2011). PubMed PMC

Koenig J., Linder A. N., Leutgeb J. K., Leutgeb S., The spatial periodicity of grid cells is not sustained during reduced theta oscillations. Science (New York, NY) 332, 592–595 (2011). PubMed

Hernández-Pérez J. J., Cooper K. W., Newman E. L., Medial entorhinal cortex activates in a traveling wave in the rat. eLife 9, 493 (2020). PubMed PMC

Venditto S. J. C., Le B., Newman E. L., Place cell assemblies remain intact, despite reduced phase precession, after cholinergic disruption. Hippocampus 31, 1065 (2019). PubMed PMC

Newman E. L., Venditto S. J. C., Climer J. R., Petter E. A., Gillet S. N., Levy S., Precise spike timing dynamics of hippocampal place cell activity sensitive to cholinergic disruption. Hippocampus 27, 1069–1082 (2017). PubMed PMC

Newman E. L., Hasselmo M. E., Grid cell firing properties vary as a function of theta phase locking preferences in the rat medial entorhinal cortex. Frontiers in systems neuroscience 8, 193 (2014). PubMed PMC

Nakazono T., Lam T. N., Patel A. Y., Kitazawa M., Saito T., Saido T. C., Igarashi K. M., Impaired In Vivo Gamma Oscillations in the Medial Entorhinal Cortex of Knock-in Alzheimer Model. Front Syst Neurosci 11, 48 (2017). PubMed PMC

Palop J. J., Mucke L., Network abnormalities and interneuron dysfunction in Alzheimer disease. Nat Rev Neurosci 17, 777–792 (2016). PubMed PMC

Hampel H., Mesulam M. M., Cuello A. C., Farlow M. R., Giacobini E., Grossberg G. T., Khachaturian A. S., Vergallo A., Cavedo E., Snyder P. J., Khachaturian Z. S., The cholinergic system in the pathophysiology and treatment of Alzheimer’s disease. Brain : a journal of neurology 141, 1917–1933 (2018). PubMed PMC

Newman E. L., Climer J. R., Hasselmo M. E., Grid cell spatial tuning reduced following systemic muscarinic receptor blockade. Hippocampus 24, 643–655 (2014). PubMed PMC

Newman E. L., Gillet S. N., Climer J. R., Hasselmo M. E., Cholinergic Blockade Reduces Theta-Gamma Phase Amplitude Coupling and Speed Modulation of Theta Frequency Consistent with Behavioral Effects on Encoding. The Journal of neuroscience : the official journal of the Society for Neuroscience 33, 19635–19646 (2013). PubMed PMC

Colmant L., Bierbrauer A., Bellaali Y., Kunz L., Dongen J. V., Sleegers K., Axmacher N., Lefèvre P., Hanseeuw B., Dissociating effects of aging and genetic risk of sporadic Alzheimer’s disease on path integration. Neurobiol Aging 131, 170–181 (2023). PubMed

Winter S. S., Clark B. J., Taube J. S., Spatial navigation. Disruption of the head direction cell network impairs the parahippocampal grid cell signal. Science 347, 870–874 (2015). PubMed PMC

Ma Y., Yu L., Olah M., Smith R., Oatman S. R., Allen M., Pishva E., Zhang B., Menon V., Ertekin‐Taner N., Lunnon K., Bennett D. A., Klein H., Jager P. L. D., Epigenomic features related to microglia are associated with attenuated effect of APOE PubMed PMC

Angelopoulou E., Paudel Y. N., Papageorgiou S. G., Piperi C., APOE Genotype and Alzheimer’s Disease: The Influence of Lifestyle and Environmental Factors. ACS Chem. Neurosci. 12, 2749–2764 (2021). PubMed

Marks J. D., Syrjanen J. A., Graff-Radford J., Petersen R. C., Machulda M. M., Campbell M. R., Algeciras-Schimnich A., Lowe V., Knopman D. S., Jack C. R., Vemuri P., Mielke M. M., A. D. N. Initiative, Comparison of plasma neurofilament light and total tau as neurodegeneration markers: associations with cognitive and neuroimaging outcomes. Alzheimers Res Ther 13, 199 (2021). PubMed PMC

Arranz J., Zhu N., Rubio-Guerra S., Rodríguez-Baz Í., Ferrer R., Carmona-Iragui M., Barroeta I., Illán-Gala I., Santos-Santos M., Fortea J., Lleó A., Tondo M., Alcolea D., Diagnostic performance of plasma pTau217, pTau181, Aβ1–42 and Aβ1–40 in the LUMIPULSE automated platform for the detection of Alzheimer disease. Alzheimers Res Ther 16, 139 (2024). PubMed PMC

Moore E. E., Hohman T. J., Badami F. S., Pechman K. R., Osborn K. E., Acosta L. M. Y., Bell S. P., Babicz M. A., Gifford K. A., Anderson A. W., Goldstein L. E., Blennow K., Zetterberg H., Jefferson A. L., Neurofilament relates to white matter microstructure in older adults. Neurobiol Aging 70, 233–241 (2018). PubMed PMC

Bells S., Lefebvre J., Prescott S. A., Dockstader C., Bouffet E., Skocic J., Laughlin S., Mabbott D. J., Changes in white matter microstructure impact cognition by disrupting the ability of neural assemblies to synchronize. J Neurosci 37, 8227–8238 (2017). PubMed PMC

Fjell A. M., Westlye L. T., Amlien I. K., Walhovd K. B., Reduced white matter integrity is related to cognitive instability. J Neurosci 31, 18060–18072 (2011). PubMed PMC

Maalmi H., Strom A., Petrera A., Hauck S. M., Strassburger K., Kuss O., Zaharia O.-P., Bönhof G. J., Rathmann W., Trenkamp S., Burkart V., Szendroedi J., Ziegler D., Roden M., Herder C., Group G., Serum neurofilament light chain: a novel biomarker for early diabetic sensorimotor polyneuropathy. Diabetologia 66, 579–589 (2023). PubMed PMC

Schmid N. S., Ehrensperger M. M., Berres M., Beck I. R., Monsch A. U., The Extension of the German CERAD Neuropsychological Assessment Battery with Tests Assessing Subcortical, Executive and Frontal Functions Improves Accuracy in Dementia Diagnosis. Dement. Geriatr. Cogn. Disord. Extra 4, 322–34 (2014). PubMed PMC

Nasreddine Z. S., Phillips N. A., Bédirian V., Charbonneau S., Whitehead V., Collin I., Cummings J. L., Chertkow H., The Montreal Cognitive Assessment, MoCA: A brief screening tool for mild cognitive impairment. J Am Geriatr Soc 53, 695–699 (2005). PubMed

Carson N., Leach L., Murphy K. J., A re-examination of Montreal Cognitive Assessment (MoCA) cutoff scores. Int J Geriatr Psychiatry 33, 379–388 (2018). PubMed

Stoet G., PsyToolkit: A software package for programming psychological experiments using Linux. Behav. Res. Methods 42, 1096–1104 (2010). PubMed

Xiao M.-F., Xu D., Craig M. T., Pelkey K. A., Chien C.-C., Shi Y., Zhang J., Resnick S., Pletnikova O., Salmon D., Brewer J., Edland S., Wegiel J., Tycko B., Savonenko A., Reeves R. H., Troncoso J. C., McBain C. J., Galasko D., Worley P. F., NPTX2 and cognitive dysfunction in Alzheimer’s Disease. eLife 6 (2017). PubMed PMC

Gelman A., Carlin J. B., Stern H. S., Dunson D. B., Vehtari A., Rubin D. B., Bayesian Data Analysis, Third Edition (Chapman and Hall/CRC, 2013; https://www.taylorfrancis.com/books/9781439898208).

Phan D., Pradhan N., Jankowiak M., Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro. arXiv, doi: 10.48550/arxiv.1912.11554 (2019). DOI

Ferretti M. T., Iulita M. F., Cavedo E., Chiesa P. A., Dimech A. S., Chadha A. S., Baracchi F., Girouard H., Misoch S., Giacobini E., Depypere H., Hampel H., and the A W. B. P.. P. M. Initiative, Sex differences in Alzheimer disease - the gateway to precision medicine. Nat Rev Neurol 14, 457–469 (2018). PubMed