Deficits in executive function and suppression of default mode network in obesity
Bibliographic record
Abstract
BACKGROUND: Although nutritional and metabolic factors are well established in obesity, neurocognitive determinants are less understood. Using data from the Human Connectome Project, this study concurrently investigated neurocognitive performance, neural activation during a working memory task, and cortical brain morphometry in relation to obesity in a group of young adults, 22-35 years old. METHODS: ). Performance tests comprised a battery of behavioral neurocognitive assessments. Neural activity was measured as blood-oxygenation-level-dependent (BOLD) activity during an N-Back task using functional magnetic resonance imaging (fMRI). Cortical morphometry included indices of volume, thickness, and surface area. RESULTS: Relative to the control group, the obese group exhibited significantly worse performance in terms of the National Institutes of Health Toolkit (NIH) 9-Hole Peg Board, Penn Working Memory Test, Delay Discounting, Penn Progressive Matrices, NIH Picture Vocabulary Test, Dimensional Change Card Sort Test and the in-scanner N-Back working memory test (FDR-corrected ps<0.05; ds = 0.231-0.405). The obese group also exhibited significantly greater BOLD activation in N-Back task-negative regions, including the ventromedial prefrontal cortex, posterior cingulate, and right precentral gyrus (FDR-corrected ps<0.05). Supplemental functional connectivity analyses provided evidence that the implicated regions were part of the default mode network. Significant differences in morphometry were present in the medial orbitofrontal cortex, rostral anterior cingulate cortex, inferior and superior parietal gyri, and temporal pole (FDR-corrected p<0.001). A data-driven integrative model classified 73.8% of participants correctly. CONCLUSIONS AND RELEVANCE: This multimodal investigation suggests diverse aspects of neurocognition are associated with obesity, particularly implicating deficits in executive function and ineffective suppression of the default mode network.
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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 | 0.001 | 0.010 |
| 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".