Functional Correlates of Midline Brain Volume Loss in Chronic Traumatic Brain Injury
Bibliographic record
Abstract
Traumatic brain injury (TBI) is associated with long-term changes in daily life functioning, yet the neuroanatomical correlates of these changes are poorly understood. This study related outcome assessed across several domains to brain structure derived from quantitative magnetic resonance imaging (MRI). Sixty individuals spanning a wide range of TBI severity participated 1-year post-injury as part of the Toronto TBI study. Volumetric data over 38 brain regions were derived from high resolution T1-weighted MRI scans. Functioning was assessed with a battery of self- and significant-other rated measures. Multivariate analysis (partial least squares) was used to identify shared variance between the neuroimaging and outcome measures. TBI was associated with item endorsement on outcome questionnaires without strong evidence for severity or focal lesion effects. Prefrontal midline, cingulate, medial temporal, right inferior parietal and basal ganglia/thalamic volumes were associated with measures of initiative, energization, and physical complaints. In the chronic stage of TBI, self-initiation, energization, and physical complaints related to a specific pattern of volume loss in midline and lateral regions known to be involved in motivation, apathy, and attention. These results suggest that crucial functional changes in chronic TBI may be associated with volume loss in established midline-frontal and attentional circuits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".