The Role of Negative Space: Lateral Ventricular Expansion Is a Better Correlate of Cognition Than Hippocampal Volume
Bibliographic record
Abstract
BACKGROUND: The hippocampus (HC) is a key biomarker in Alzheimer's disease (AD), yet the relationship between ventricular enlargement-a marker of brain atrophy-and cognition remains underexplored. We evaluate whether lateral-temporal horn ventricular measurements are a viable correlate for cognition. METHOD: From the ADNI dataset, we analyzed cognitive data from 481 cognitively healthy (CH), 548 mild cognitively-impaired (MCI), and 222 AD individuals. We obtained factors for memory, language, and executive function from validated confirmatory factor analysis. We used MRI data to segment the HC and the temporal horns of the lateral ventricles (LV) with a Convolutional Neural Network. Volumes were adjusted for intracranial volume (ICV). We calculated the HC-to-Ventricle ratio (HVR), [HC / (HC + LV)], a medial-temporal integrity measurement. Finally, with Pearson correlations, we assessed the relationships between cognition and HC, LV, and HVR. RESULT: LV showed stronger negative correlations with cognition than HC, particularly in CH and MCI. Memory: In MCI, HVR (r = .43) and LV (r = -0.40) correlated more strongly with memory than HC (r = .38). In AD, HC (r = .45) and HVR, (r = .44) outperformed LV (r = .32). Executive function: Across groups, LV (CH, r = -.24; MCI, r = -.28; AD, r = -.34) and HVR (CH, r =.22, MCI, r = .18, AD, r = .36) exceeded HC (CH, r = .15, AD, r = .3). Language: In CH and MCI, only LV and HVR, and not HC, were significantly associated with the latent score; with LV (CH, r = -.24; MCI, r = -.3) slightly outperformed HVR (CH, r = .21; MCI, r = .24). For the patients with AD, the correlation of HC (r = .28) while significant, was still weaker than HVR (r = .31). CONCLUSION: Lateral ventricular enlargement correlates more strongly with cognitive decline than hippocampal atrophy alone. The HVR, by design, integrates information from both hippocampal atrophy and ventricular expansion, making it a more comprehensive and robust measure of medial-temporal integrity. These results highlight the importance of ventricular expansion as a key biomarker in AD research and clinical assessments.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".