How the body remembers: Examining the default mode and sensorimotor networks during moral injury autobiographical memory retrieval in PTSD
Bibliographic record
Abstract
Neural representations of sensory percepts and motor responses constitute key elements of autobiographical memory. However, these representations may remain as unintegrated sensory and motor fragments in traumatic memory, thus contributing toward re-experiencing and reliving symptoms in trauma-related conditions such as post-traumatic stress disorder (PTSD). Here, we investigated the sensorimotor network (SMN) and posterior default mode network (pDMN) using a group independent component analysis (ICA) by examining their functional connectivity during a script-driven memory retrieval paradigm of (potentially) morally injurious events in individuals with PTSD and healthy controls. Moral injury (MI), where an individual acts or fails to act in a morally aligned manner, is examined given its inherent ties to disrupted motor planning and thus sensorimotor mechanisms. Our findings revealed significant differences in functional network connectivity across the SMN and pDMN during MI retrieval in participants with PTSD (n = 65) as compared to healthy controls (n = 25). No such significant group-wise differences emerged during retrieval of a neutral memory. PTSD-related alterations included hyperconnectivity between the SMN and pDMN, enhanced within-network connectivity of the SMN with premotor areas, and increased recruitment of the supramarginal gyrus into both the SMN and the pDMN during MI retrieval. In parallel with these neuroimaging findings, a positive correlation was found between PTSD severity and subjective re-experiencing intensity ratings after MI retrieval. These results suggest a neural basis for traumatic re-experiencing, where reliving and/or re-enacting a past morally injurious event in the form of sensory and motor fragments occurs in place of retrieving a complete, past-contextualized narrative as put forth by Brewin and colleagues (1996) and Conway and Pleydell-Pearce (2000). These findings have implications for bottom-up treatments targeting directly the sensory and motoric elements of traumatic experiences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".