fMRI Study on the Functional Connectivity of Nucleus Accumbens in Patients with Knee Osteoarthritis
Bibliographic record
Abstract
Objective:To explore the underlying mechanism of pain syndrome in patients with knee osteoarthritis(KOA)via comparing the resting state functional connectivity(rs-FC)group difference of nucleus accumbens(NAc)between patients with KOA and healthy controls.Methods:A total of 16 KOA patients were enrolled as the KOA group,and 16 healthy controls were enrolled as the healthy control group.All of those subjects were enrolled from various communities in Fuzhou city,Fujian province.Firstly,all subjects'general and behavioral data,including gender,age,and the brief pain inventory(BPI)score,were collected.The KOA group also used the knee injury and osteoarthritis outcome score(KOOS)to assess pain intensity,and functional magnetic resonance imaging(fMRI)data were preprocessed using the CONN18b software package,resting-state fMRI(rs-fMRI)and structural MRI were performed within one week after completed the general and behaviourl data assessment for the two groups.Pre-processing of fMRI data was performed via using a pipeline in CONN18b toolbox.Our study used the AAL template NAc of the Montreal Neuroscience Institute(MNI)as the region of interest to analyze the differences in the functional connectivity between the NAc and the whole brain voxels in the two groups of subjects and its correlation with the KOOS.Results:The general data(age,gender)of the KOA group were matched with the healthy control group,and the BPI score of the healthy control group was 0.Functional connectivity between bilateral nucleus accumbens and whole brain volume were analyzed in the two groups.Compared to the healthy control group,increased rsFC was found between bilateral NAc and bilateral anterior cingulate cortex,the left caudate and the right temporal pole.Our study also found significantly decreased rsFC between bilateral NAc and the right dorsolateral prefrontal cortex(DLPFC),the left secondary sensory area(S2)and bilateral angular gyrus.About the correlation between brain regions with differences in functional connectivity of bilateral NAc and the pain subtest of KOOS in the two groups,the rsFCs of bilateral NAc-right DLPFC/bilateral NAc-left S2 were positively correlated with pain subtest of the KOOS in the KOA group.Conclusion:It suggests that the abnormal functional connectivity between default mode network,where the brain regions related to cognitive control,emotional regulation,sensory processing and NAc,which is related to the central dopamine system,may be one of the underlying mechanisms of pain syndrome of KOA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".