Evidence map›Paper›PMID 42010440›Full record

ArticleAlzheimer's research & therapy2026

VR-based path integration predicts individual risk of rapid cortical decline: a one-year longitudinal study in cognitively unimpaired adults.

Kazuya Kawabata, Sayuri Shima, Reiko Ohdake, Epifanio Bagarinao, Yasuaki Mizutani, Harutsugu Tatebe, Riki Koike, Atsushi Kasai, Akihiro Ueda, Mizuki Ito and 6 more

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Kazuya Kawabata *Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Sayuri Shima *Department of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Reiko OhdakeDepartment of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Epifanio BagarinaoBrain and Mind Research Center, Nagoya University, Nagoya, Aichi, Japan.
Yasuaki MizutaniDepartment of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Harutsugu TatebeDepartment of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan.
Riki KoikeDepartment of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan.
Atsushi KasaiMIG (Medical Innovation Group) Inc., Tokyo, Japan.
Akihiro UedaDepartment of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Mizuki ItoDepartment of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Junichi HataGraduate School of Human Health Sciences, Tokyo Metropolitan University, Tokyo, Japan.
Shinsuke IshigakiMolecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga, Japan.
Hiroshi ToyamaDepartment of Radiology, Fujita Health University Hospital, Toyoake, Aichi, Japan.
Takahiko TokudaDepartment of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan.
Akihiko TakashimaDepartment of Life Science, Faculty of Science, Laboratory for Alzheimer's Disease, Gakushuin University, Tokyo, Japan.
Hirohisa WatanabeDepartment of Neurology, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan. hirohisa.watanabe@fujita-hu.ac.jp.

Funding

Japan Agency for Medical Research and Development JP21wm0425016Japan Agency for Medical Research and Development JP22dk0207055Japan Society for the Promotion of Science JPJS00420240019
6 · The paper itself

Abstract

backgroundPath integration (PI) is a navigational computation that can be affected by aging and Alzheimer’s disease (AD). Virtual-reality PI (VR-PI) preferentially engages medial temporal circuits and can reveal subtle changes that occur prior to overt impairment. Nevertheless, the longitudinal association between PI performance and structural brain changes remains unclear.

methodsIn a 1-year longitudinal cohort of 71 cognitively unimpaired adults, we assessed baseline VR-PI performance (PI error and angular error), AD-related plasma biomarkers (p-tau181 and glial fibrillary acidic protein [GFAP]), and longitudinal cortical thickness and volume from MRI scans acquired one year apart, to examine whether baseline PI performance was associated with both plasma biomarkers and subsequent structural brain changes. Linear mixed-effects (LME) models were used to assess whether baseline PI performance predicted time-dependent regional thinning and atrophy.

resultsGreater baseline PI error was associated with greater longitudinal cortical thinning and volume decline in the parahippocampal gyrus, middle temporal gyrus, posterior cingulate cortex, and caudal middle frontal gyrus. Similar spatial patterns were observed for angular error, indicating consistent associations across PI measures. Sensitivity analyses using extended models that additionally included either APOE ε4 status or the baseline age × time interaction, as well as analyses restricted to participants aged ≥ 40 years, did not materially alter the pattern of results. Both baseline PI error and angular error were associated with plasma p-tau181 (r = 0.38 for both, 95% confidence interval [CI]: 0.16–0.56), and PI error was associated with GFAP levels (r = 0.36, 95% CI: 0.14–0.55). Receiver operating characteristic (ROC) curve analyses showed that baseline PI error best discriminated individuals with accelerated parahippocampal thinning (10% threshold; cross-validated AUC = 0.87).

conclusionsBaseline VR-PI performance was associated with longitudinal cortical thinning and volume decline in AD-vulnerable regions, along with additional associations with plasma p-tau181 and GFAP levels. VR-PI performance may reflect both molecular (blood biomarker) and structural (MRI) signatures preceding overt clinical impairment.

Indexed as

Cerebral CortexSpatial NavigationVirtual RealityAgedBiomarkersFemaleGlial Fibrillary Acidic ProteinHumansLongitudinal StudiesMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological Teststau ProteinsBiomarkersGFAP protein, humanGlial Fibrillary Acidic Proteintau ProteinsCortical atrophyMRINavigationPath integrationVirtual reality

Identifiers

PMID42010440
PMCPMC13227782

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.