Memory retrieval brain–behavior disconnection in mild traumatic brain injury: A magnetoencephalography and diffusion tensor imaging study
Bibliographic record
Abstract
Mild traumatic brain (mTBI) injury is often associated with long-term cognitive and behavioral complications, including an increased risk of memory impairment. Current research challenges include a lack of cross-modal convergence regarding the underlying neural-behavioral mechanisms of mTBI, which hinders therapeutics and outcome management for this frequently under-treated and vulnerable population. We used multi-modality imaging methods including magnetoencephalography (MEG) and diffusion tensor imaging (DTI) to investigate brain-behavior impairment in mTBI related to working memory. A total of 41 participants were recruited, including 23 patients with a first-time mTBI imaged within 3 months of injury (all male, age = 29.9, SD = 6.9), and 18 control participants (all male, age = 27.3, SD = 5.3). Whole-brain statistics revealed spatially concomitant functional-structural disruptions in brain-behavior interactions in working memory in the mTBI group compared with the control group. These disruptions are located in the hippocampal-prefrontal region and, additionally, in the amygdala (measured by MEG neural activation and DTI measures of fractional anisotropy in relation to working memory performance; p < .05, two-way ANCOVA, nonparametric permutations, corrected). Impaired brain-behavior connections found in the hippocampal-prefrontal and amygdala circuits indicate brain dysregulation of memory, which may leave mTBI patients vulnerable to increased environmental demands exerting memory resources, leading to related cognitive and emotional psychopathologies. The findings yield clinical implications and highlight a need for early rehabilitation after mTBI, including attention- and sensory-based behavioral exercises.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".