Blood flow in the human cerebral cortex: Large-scale pial vascularization and 1D simulation
Bibliographic record
Abstract
Understanding cerebral circulation is crucial for early diagnosis and patient-oriented therapies for brain conditions. However, blood flow simulations at the organ scale have been limited. This work introduces a framework for modeling extensive vascular networks in the human cerebral cortex and conducting pulsatile blood flow simulations. Using a patient-specific cerebral geometry, we applied a parallelized adaptive constrained constructive optimization algorithm to create a comprehensive pial vascular network in the left hemisphere, starting from the main cerebral arteries. The resulting network included over 75 000, 103 000, and 55 000 vessels for the anterior, middle, and posterior territories, respectively. Pial vessel diameters featured a median [interquartile range, IQR] value of [Formula: see text]. We integrated the pial vascular network model with the Anatomically-Detailed Arterial Network (ADAN) model to conduct one-dimensional (1D) blood flow simulations under normotensive and hypertensive conditions. Viscoelastic dissipation proved to be a key ingredient in the characterization of the hemodynamic environments in the pial circulation. In the normotensive scenario, mean blood pressure in the pial vessels resulted in a median [IQR] value of [Formula: see text]. The flow pulsatility index and its corresponding damping factor were effective descriptors of the hypertensive state. The median [IQR] pulsatility index in the normotensive state was [Formula: see text], and in hypertension it increased up to [Formula: see text], while its corresponding damping factor in the normotensive state was [Formula: see text], and in the hypertensive state it was reduced to [Formula: see text]. We observed large regional pressure gradients in terminal vessels, with pressure levels ranging from [Formula: see text] in normotension to [Formula: see text] in hypertension. Additionally, the pulsatility index at terminal vessels increased with distance from the Circle of Willis in the hypertensive case, contrasting with the decreasing pattern seen in normotension. This approach provides a unique characterization of hemodynamics in the pial vascular network of the human cerebral cortex, paving the way for research into microcirculatory environments, the link between hemodynamics and neural function, and their roles in conditions like stroke and dementia.
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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 | 0.000 | 0.000 |
| 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".