Morphometric Measurement of Mean Cortical Curvature: Analysis of Alterations in Cognitive Impairment
Bibliographic record
Abstract
Background and Objectives: Cognitive impairment, including mild cognitive impairment (MCI) and Alzheimer’s disease (AD), is a growing public health concern. Early detection and an understanding of structural changes are crucial for accurate diagnosis and timely intervention. Cortical curvature, a morphometric measure derived from structural magnetic resonance imaging (MRI), has emerged as a potential biomarker for neurodegenerative processes. This study investigates the relationship between mean cortical curvature and cognitive impairment. Materials and Methods: A cross-sectional study was conducted with 58 participants, categorized into, first, cognitively impaired (CI) and non-cognitively impaired (NC) groups and, second, a normal cognitive group (NC), a mild cognitive performance group (MPG), and a low cognitive performance group (LPG) based on the Montreal Cognitive Assessment (MoCA) score. MRI data were acquired using a 3.0 Tesla scanner, and cortical reconstruction was performed using FreeSurfer 7.2.0. Mean cortical curvature values were extracted for 34 brain regions per hemisphere. Results: Significant differences in mean cortical curvature were found between the CI and NC groups. In the right hemisphere, statistically significant changes in mean curvature were observed in the isthmus cingulate (U = 188.5, p = 0.006), lingual (U = 202.5, p = 0.013), pars orbitalis (U = 221.5, p = 0.031), and posterior cingulate regions (U = 224.5, p = 0.035). In the left hemisphere, significant differences were detected in the cuneus (U = 226.5, p = 0.038) and posterior cingulate (U = 231.5, p = 0.046) regions. Analysis across three cognitive performance groups (NC, MPG, and LPG) showed significant curvature differences in the right isthmus cingulate (H(2) = 7.492, p = 0.024) and lingual regions (H(2) = 6.250, p = 0.044). Conclusions: Decreased mean cortical curvature in brain regions associated with cognitive function could be indicative of cognitive impairment and may reflect early neurodegenerative changes. These results highlight cortical curvature as a potential structural sign for cognitive impairment, showing the need for further investigation in longitudinal studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| 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) | 0.001 | 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".