Quantifying the Effect of Repeated Impacts and Lateral Tip Movements on Brain Responses during Controlled Cortical Impact
Bibliographic record
Abstract
Controlled cortical impact (CCI) is a widely used laboratory neurotrauma model to study traumatic brain injury. During CCI, the brain is damaged by an impactor tip, which travels along its axial direction to a pre-defined depth at a pre-set speed. A recent study, however, using high-speed imaging analysis demonstrated that the impactor tip of an electromagnetically driven CCI device experienced repeated impacts and lateral movements, rather than a single axial impact. How these repeated impacts and lateral movements affect internal brain stresses/strains-which are the direct cause of neuronal damage and affect the accuracy and reproducibility of CCI-remains unknown. We use a previously validated, highly detailed three-dimensional finite element (FE) mouse brain model to investigate the effect of repeated impacts and lateral movements on brain responses during CCI. We also measured tip movements of an in-house pneumatically driven CCI and conducted FE simulations. We found that the repeated impacts had minimal effect on peak strains. The lateral movements of the tip, however, greatly increased brain strains and affected large brain regions. Hence, it is necessary to monitor and control lateral movements to ensure the accuracy and reproducibility of CCI.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".