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Record W4407719727 · doi:10.3389/fnagi.2025.1501082

Alterations in brain function in patients with post-stroke cognitive impairment: a resting-state functional magnetic resonance imaging study

2025· article· en· W4407719727 on OpenAlexaboutno aff
Kaiyue Han, Linghui Dong, Xingxing Liao, Junzi Long, Jiarou Chen, Haitao Lu, Hao Zhang

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional magnetic resonance imagingMagnetic resonance imagingResting state fMRICognitive impairmentCognitionStroke (engine)NeuroscienceMedicineBrain functionPsychologyFunctional magnetic resonance spectroscopy of the brainCardiologyPhysical medicine and rehabilitationPhysicsRadiology

Abstract

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Background: Cognitive impairment is a common dysfunction following stroke, significantly affecting patients' quality of life. Studies suggest that post-stroke cognitive impairment (PSCI) may be related to neural activity in specific brain regions. However, the neural mechanisms remain to be further explored. This study aimed to investigate the alterations in brain function in patients with PSCI. Methods: This was a case-control study. Thirty patients with PSCI, thirty with non-PSCI (NPSCI), and thirty age- and gender-matched healthy controls (HCs) were selected in a 1:1:1 ratio. Resting-state functional magnetic resonance imaging (rs-fMRI) were acquired from all participants to study the potential neural mechanisms of PSCI patients by comparing the differences in fractional amplitude of low-frequency fluctuation (fALFF), Kendall's coefficient of concordance-regional homogeneity (KCC-ReHo), and seed-based functional connectivity (FC). Additionally, the Montreal Cognitive Assessment (MoCA) scores of PSCI patients were collected, and Pearson correlation was used to analyze the correlation between functional indicators and cognitive performance in PSCI patients. Results: fALFF analysis revealed that the PSCI group had decreased zfALFF values in the left caudate, right inferior temporal gyrus (ITG), anterior cingulate cortex (ACC), left putamen, and left superior temporal gyrus. In contrast, increased zfALFF values were observed in the right Cerebellum_6. KCC-ReHo analysis indicated that the PSCI group had decreased SzKCC-ReHo values in the right middle frontal gyrus (MFG) and left postcentral lobe, while increased SzKCC-ReHo values in the left cerebellum_ crus 1, and left cerebellum_4-5. Furthermore, seed-based FC analysis revealed decreased zFC values between brain regions in the PSCI group, especially between the angular gyrus and precuneus. Additionally, correlation analysis showed that the zfALFF value of ACC was positively correlated with MoCA scores in the PSCI group. Conclusion: This study demonstrated significant changes in the spontaneous neural activity intensity, regional homogeneity, and FC of multiple cognition-related brain regions in PSCI patients, shedding light on the underlying neural mechanisms of brain function in PSCI.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.238
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2025
Admission routes1
Has abstractyes

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