Intrusive memories of trauma: A target for research bridging cognitive science and its clinical application
Bibliographic record
Abstract
Intrusive memories of a traumatic event can be distressing and disruptive, and comprise a core clinical feature of post-traumatic stress disorder (PTSD). Intrusive memories involve mental imagery-based impressions that intrude into mind involuntarily, and are emotional. Here we consider how recent advances in cognitive science have fueled our understanding of the development and possible treatment of intrusive memories of trauma. We conducted a systematic literature search in PubMed, selecting articles published from 2008 to 2018 that used the terms "trauma" AND ("intrusive memories" OR "involuntary memories") in their abstract or title. First, we discuss studies that investigated internal (neural, hormonal, psychophysiological, and cognitive) processes that contribute to intrusive memory development. Second, we discuss studies that targeted these processes using behavioural/pharmacological interventions to reduce intrusive memories. Third, we consider possible clinical implications of this work and highlight some emerging research avenues for treatment and prevention, supplemented by new data to examine some unanswered questions. In conclusion, we raise the possibility that intrusive memories comprise an alternative, possibly more focused, target in translational research endeavours, rather than only targeting overall symptoms of disorders such as PTSD. If so, relatively simple approaches could help to address the need for easy-to-deliver, widely-scalable trauma interventions.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".