Evidence map›Paper›PMID 42395576›Full record

ArticlebioRxiv : the preprint server for biology2026

Normative brain-state trajectories reveal deviation from healthy aging in AD.

Monireh Taimouri, Vikram Ravindra

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

2 authors.

Monireh TaimouriDepartment of Computer Science, University of Cincinnati, Clifton Ave., Cincinnati, 45221, Ohio, USA.
Vikram RavindraDepartment of Computer Science, University of Cincinnati, Clifton Ave., Cincinnati, 45221, Ohio, USA.

Funding

Project 1U19AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI Duygu Tosun-Turgut · 2016 to 2026
$226.7M
NIA NIH HHS U19 AG024904
6 · The paper itself

Abstract

introductionDistinguishing healthy brain aging from early neurodegenerative disruption remains a major challenge in Alzheimer's disease.

methodsUsing resting-state fMRI from the Alzheimer's Disease Neuroimaging Initiative (357 participants; cognitively normal, mild cognitive impairment, Alzheimer's disease), we trained a Hidden Markov Model exclusively on cognitively normal adults to define latent connectivity states. A generalized additive model estimated an age-adjusted reference trajectory of transition entropy, and subject-specific deviations from this trajectory were quantified.

resultsMild cognitive impairment and Alzheimer's disease showed progressively greater deviation from the normative reference, with the strongest disruption in Alzheimer's disease. A single absolute-deviation score retained much of the predictive information contained in higher-dimensional dynamic features. DISCUSSION: These findings suggest Alzheimer's disease is associated with measurable departure from healthy dynamic brain aging, providing an interpretable framework for future longitudinal and clinically validated studies.

Indexed as

Alzheimer’s diseasebiomarkerBrain agingdynamic functional connectivityHidden Markov Modelnormative modelingresting-state fMRItransition entropy

Identifiers

PMID42395576
PMCPMC13320867

What OpenQuestion holds

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Registered trials

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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.