An investigation of resting state functional connectivity of the anterior and posterior Hippocampal subregions in posttraumatic stress disorder and its relationship with symptoms
Bibliographic record
Abstract
Posttraumatic stress disorder (PTSD) is associated with abnormal hippocampal activity; however, the functional connectivity (FC) of the hippocampus with other brain regions and its relations with symptoms warrants further attention. I investigated FC of the hippocampus at a subregional level in PTSD during a resting state compared to trauma exposed controls (TECs). Based on imaging literature in PTSD, I targeted the FCs of the hippocampal head and tail subregions with the amygdala, medial prefrontal cortex (mPFC), and the posterior cingulate (PCC). The PTSD group had significantly greater FC compared to the TEC group between the left hippocampal head and the right amygdala, and for the left hippocampal tail with bilateral PCC. Resting state FC predicted symptom severity at time of scan and 4-months post-scan. These results highlight abnormal illness-related FC with both the hippocampal head and tail and provide support for future investigations of imaging biomarkers predictive of disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".