Effect of age at time of injury on long-term changes in intrinsic functional connectivity in traumatic brain injury
Bibliographic record
Abstract
BACKGROUND: Alterations in resting-state functional connectivity (rsFC) occur in the acute and chronic phases following traumatic brain injury (TBI); however, few studies have assessed long-term (>1 year) changes in rsFC. METHODS: sfMRI scans at the sub-acute (~10 days) and long-term (~18 months) phases. We examined changes in voxel-based rsFC from anterior medial prefrontal cortex (aMPFC) and posterior cingulate cortex (PCC) seeds in the default mode network (DMN) between both phases. The effect of age at the time of injury on long-term rsFC was also examined. RESULTS: Increased rsFC from the aMPFC and the PCC to frontal and temporal regions was shown at ~18-months post-injury. Widespread increases in rsFC from the aMPFC and between the PCC and frontal regions were shown for younger patients at time of injury, but limited increases of rsFC were noted at ~18 months in older patients. CONCLUSION: Long-term increases in rsFC were found following TBI, but age at the time of injury was associated with distinct rsFC profiles suggesting that younger patients show greater increases in rsFC over time.
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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 | 0.002 |
| 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) | 0.001 | 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".