MétaCan
Menu
Back to cohort

Cerebellum abnormalities in vascular mild cognitive impairment with depression symptom patients: A multimodal magnetic resonance imaging study

2025· article· en· W4406405264 on OpenAlexaboutno aff
Liling Chen, Li‐Yu Hu, Jianjun Wang, Jinhuan Zhang, Hanqing Lyu, Jinping Xu, Jianxiang Chen, Haibo Yu

Bibliographic record

VenueBrain Research Bulletin · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCerebellumMagnetic resonance imagingDepression (economics)Cognitive impairmentFunctional magnetic resonance imagingMedicineCognitionPsychologyNeuroimagingNeuroscienceRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Subcortical vascular mild cognitive impairment (svMCI) frequently occurs alongside depression symptoms, significantly affecting patients' quality of life. While cognitive decline and depression symptoms are linked to cerebellar changes, the specific relationship between these changes and cognitive status in svMCI patients with depression symptoms remains unclear. OBJECTIVE: This study aimed to investigates the gray matter volume and functional alterations in the cerebellum of svMCI patients, with and without depression symptoms, and their correlation with cognitive and depressive symptoms. METHODS: We enrolled 16 svMCI patients with depression symptoms (svMCI+D), 15 without (svMCI-D), and 12 normal controls (NC). Multimodal MRI scans were conducted, assessing gray matter volume and resting-state functional connectivity (RSFC) in the cerebellum. Correlations between RSFC and clinical scores from the Montreal Cognitive Assessment (MoCA) and Hamilton Depression Scale (HAMD) were analyzed. RESULTS: Structural analysis indicated gray matter atrophy in left cerebellar lobules I_IV and VI (Cere6.L) in svMCI patients. svMCI+D patients showed reduced RSFC between Cere6.L and left cerebellar region IX and the left superior frontal gyrus (SFGdor.L). Both svMCI+D and svMCI-D groups showed increased RSFC between Cere6.L and the right caudate nucleus. RSFC between Cere6.L and SFGdor.L correlated negatively with HAMD scores in svMCI+D and positively with MoCA scores in svMCI-D. RSFC between Cere6.L and the right caudate nucleus also correlated positively with MoCA in the svMCI-D. CONCLUSION: Cerebellar abnormalities, including the gray matter atrophy and RSFC changes, are associated with svMCI, particularly when depression symptoms are present. These results suggest potential diagnostic and therapeutic implications for svMCI and emphasize the need for further research on the cerebellum's role in cognitive and emotional disorders.

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 score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.024
GPT teacher head0.310
Teacher spread0.286 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueBrain Research BulletinSame topicFunctional Brain Connectivity StudiesFrench-language works237,207