Neurobiology of Chronic Pain, Posttraumatic Stress Disorder, and Mild Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVES: This article describes the neurobiology of psychological injuries-chronic pain, concussion/mild traumatic brain injury (MTBI), and fear/posttraumatic stress disorder (PTSD)-toward elucidating common mechanisms in central and peripheral sensitization that contribute to their onset, exacerbation, and maintenance. Central sensitization refers to central nervous system (CNS) and related processes, while peripheral sensitization is typically referred to as receptor field expansion. The three psychological injury diagnoses/conditions are accompanied by impairments in function after negligent events (such as motor vehicle accidents (MVAs)) that lead to tort court action. METHODS: The conducted literature review involved an extensive scoping review of recent neurobiological literature on chronic pain, PTSD, and MTBI. The literature review sought biological markers that distinguish them. RESULTS: For chronic pain, concussion/MTBI, and fear/PTSD, this article reviewed definitions and critical neurobiological research. The literature review did not find evidence of biological markers, but the role of sensitization emerged as important. CONCLUSIONS: Common therapeutic processes, such as focusing on sensitization, might be helpful for these conditions. As for causal mechanisms related to sensitization in the causality of psychological injuries, the major ones hypothesized relate to the biopsychosocial model, psychological control, and activation-inhibition coordination.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".