The Nature of Traumatic Memories: A 4-T fMRI Functional Connectivity Analysis
Bibliographic record
Abstract
OBJECTIVE: This study used functional connectivity analyses to assess interregional brain activity correlations during the recall of traumatic memories in traumatized subjects with and without posttraumatic stress disorder (PTSD). METHOD: Both 4-T functional magnetic resonance imaging (fMRI) and functional connectivity analyses were used to assess interregional brain activity correlations during script-driven symptom provocation in traumatized subjects with (N=11) and without (N=13) PTSD. Functional connectivity analyses were carried out by using data for brain regions activated in both the PTSD group and the comparison group. The use of functional connectivity analyses in addition to subtraction analyses allowed assessment of specific brain regions involved in the recall of traumatic events and of the neuronal networks underlying the recall of such events. RESULTS: Significant between-group differences in functional connectivity were found. Comparison of connectivity maps at coordinates x=2, y=20, z=36 (right anterior cingulate gyrus) for the two groups showed that the subjects without PTSD had greater correlation than the PTSD subjects in the left superior frontal gyrus (Brodmann's area 9), left anterior cingulate gyrus (Brodmann's area 32), left striatum (caudate), left parietal lobe (Brodmann's areas 40 and 43), and left insula (Brodmann's area 13). In contrast, the PTSD subjects showed greater correlation than the subjects without PTSD in the right posterior cingulate gyrus (Brodmann's area 29), right caudate, right parietal lobe (Brodmann's areas 7 and 40), and right occipital lobe (Brodmann's area 19). CONCLUSIONS: The differences in brain connectivity between PTSD and comparison subjects may account for the nonverbal nature of traumatic memory recall in PTSD subjects, compared to a more verbal pattern of traumatic memory recall in comparison subjects.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".