MRI investigation of orientation-dependent changes in microstructure and function in a mouse model of mild traumatic brain injury
Bibliographic record
Abstract
While neuroimaging studies have revealed notable white matter damage following mild traumatic brain injury (mTBI), the specific tracts and brain regions affected vary widely across studies. Here, we explored whether the spatial orientation of white matter tracts influences susceptibility to repeated mTBI, predicting that tracts oriented orthogonal to the axis of rotation of the head during impact (within the plane of rotation) would exhibit the most damage. Using a model of repeated rotational mTBI in mice, we acquired advanced diffusion MRI (diffusional kurtosis imaging using oscillating gradient encoding) and resting-state functional MRI (fMRI) data at baseline and 1-week post-injury. Consistent with our prediction, while both diffusivity and diffusional kurtosis decreased in the white matter of injured mice, only diffusional kurtosis revealed microstructural changes confined to tracts oriented orthogonal to the right-left axis of rotation. In addition, both region and subregion analyses showed functional connectivity (FC) deficits between regions connected via tracts running orthogonal to the rotation axis. The orientation-dependent changes in imaging metrics were validated by histopathological analyses. Females showed greater microstructural changes than males using diffusion MRI following injury, while no sex differences were detected by fMRI. Interestingly, the region-specific and subregion-specific FC analyses showed overlapping but non-identical changes in FC suggesting the utility of using both coarse and fine levels of brain parcellation for FC analyses in mTBI. These findings suggest that mTBI imaging studies may benefit from the consideration that damage after mTBI will predominate in tracts that are oriented orthogonal to the axis of rotation produced by the impact and that diffusivity and diffusional kurtosis as well as region and subregion-specific fMRI analyses can detect these changes.
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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".