Effect of Insulin Sensitivity on Corticolimbic Responses to Food Picture in Women with Polycystic Ovary Syndrome
Bibliographic record
Abstract
OBJECTIVE: Insulin is one of several molecules that transmit information about energy balance to the brain. It has been hypothesized that insulin resistance fosters non-homeostatic eating. The objective of the current study was to characterize corticolimbic brain responses to appetitive stimuli in subjects with insulin sensitivities ranging from resistant to normal. DESIGN AND METHODS: Sixteen women diagnosed with polycystic ovary syndrome (PCOS) underwent functional magnetic resonance imaging (fMRI) while viewing pictures of high calorie (HC) foods, low calorie (LC) foods, and control (C) pictures. RESULTS: A region of interest analysis of the blood oxygen level dependent (BOLD) signal revealed widespread activation within corticolimbic regions in response to food pictures. Activated regions included the dorsolateral prefrontal cortex (DLPFC), medial prefrontal cortex (mPFC) , insula, nucleus accumbens (NAc), pallidum, ventral tegmental area (VTA), putamen, amygdala, caudate, substantia nigra, hippocampus, pulvinar, and midbrain. Activation of the anterior cingulate, dorsolateral prefrontal cortex (DLPFC), and midbrain by HC food pictures (HC - C) and activation of the lateral orbitofrontal cortex (OFC), pallidum, substantia nigra, ventral tegmental area (VTA), pulvinar, and midbrain by LC food pictures (LC - C) was negatively correlated with insulin sensitivity. In contrast, activation of the OFC, DLPFC, insula, hypothalamus, pallidum, substantia nigra, VTA, pulvinar, and midbrain by the HC - LC contrast was positively correlated with insulin sensitivity, whereas activation of the caudate was negatively correlated. CONCLUSIONS: The association between insulin sensitivity and corticolimbic responses to food pictures may reflect abnormal brain responses to insulin feedback that contribute to the development and or perpetuation of obesity in PCOS.
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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 | 0.000 | 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) | 0.002 | 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".