Changes of Structural and Functional Attention Control Networks in Subclinical Hypothyroidism
Bibliographic record
Abstract
Objective: This study aimed to explore the structural changes in patients with subclinical hypothyroidism (SCH) using voxel-based morphometry (VBM) and to investigate the altered attentional control networks using functional MRI (fMRI) during the performance of a modified Stroop task with Chinese characters. Methods: High-resolution three-dimensional (3D) T1-weighted images and an fMRI scan were taken from 18 patients with SCH and 18 matched control subjects. The Montreal Cognitive Assessment Chinese-revised (MoCA-CR) and the Stroop task were used to evaluate the cognitive and attention control of the participants. Results: Compared to controls, the VBM results showed decreased gray matter volumes (GMVs) in bilateral prefrontal cortices (PFCs, including middle, medial, and inferior frontal gyri), cingulate gyrus, precuneus, left middle temporal gyrus, and insula in patients with SCH. The fMRI results showed a distributed network of brain regions in both groups, consisting of PFCs (including superior and middle and inferior frontal cortices), anterior cingulate cortex (ACC), posterior cingulate cortex, and precuneus, as well as the insula and caudate nucleus. Compared to controls, the SCH group had lower activation of the above brain areas, especially during the color-naming task. In addition, the normalized GMV (nGMV) was negatively correlated with thyroid-stimulating hormone (TSH) level (r = −0.722, p < 0.001). Conclusion: Results indicate that patients with SCH exhibit reduced GMVs, altered BOLD signals, and activation in regions associated with attention control, which further suggest that patients with SCH may have attentional control deficiency, and the weakened PFC–ACC–precuneus brain network might be one of the neural mechanisms. Negative correlations between nGMV and TSH suggest that TSH elevation may induce abnormalities in the cortex.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".