A Systematic Review of Structural and Functional Imaging Correlates of Headache or Pain after Mild Traumatic Brain Injury
Bibliographic record
Abstract
Headaches and pain-related symptoms are the most disabling somatic complaints following mild traumatic brain injury (mTBI). In this study, we reviewed the existing literature examining structural differences in brain morphology and axonal connections, as well as functional differences in brain activity and connectivity associated with pain or post-traumatic headache (PTH) following mTBI. We searched MEDLINE®, Embase, PubMed, Cumulative Index of Nursing and Allied Health Literature (CINAHL), Cochrane Central Register of Controlled Trials, and Web of Science databases for: (1) TBI OR concussion OR post-concussion syndrome; (2) pain OR headache; and (3) magnetic resonance imaging OR functional MRI OR diffusion tensor imaging. Inclusion criteria were that articles be original studies written in English about participants with mTBI or concussion diagnosis with results reported about pain and/or headache. Excluded were review articles, case studies, documentaries, and studies related to moderate to severe TBI. Quality was assessed using the Newcastle–Ottawa Scale (NOS) quality assessment tool. Nineteen out of 3439 studies satisfied the inclusion and exclusion criteria. Participants with pain-related symptoms had lower cortical thickness in frontal and parietal cortical areas and spinothalamic tract volume. Differences in axonal connectivity were displayed in the corpus callosum, spinothalamic tract, fornix-septohippocampal circuit, and periaqueductal gray. Less activation in pain-related regions during a heat-pain task-based fMRI was reported in participants with PTH. In conclusion, individuals with pain following mTBI display differences in brain structure and brain function, suggesting irregularities in the descending pain modulatory system. These findings primarily provide information on neuroimaging differences in adults; there is limited research in pediatric populations.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.006 |
| Bibliometrics | 0.014 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".