Prefrontal Compensatory Engagement in TBI is due to Altered Functional Engagement Of Existing Networks and not Functional Reorganization
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Bibliographic record
Abstract
Functional neuroimaging studies of traumatic brain injury (TBI) have demonstrated altered neural recruitment, specifically within prefrontal cortex (PFC). This is manifest typically as increased recruitment of homologous regions of PFC (e.g., right ventrolateral PFC during performance of a verbal working memory task, possibly in response to damage involving the left PFC). The behavioral correlates of these functional changes are poorly understood. We used fMRI and multivariate analytic methods to investigate changes in spatially distributed activity patterns and their behavioral correlates in a sample of TBI patients with diffuse axonal injury (DAI, but without focal injury) and matched healthy controls. Participants performed working memory tasks with varying memory load and executive demand. We identified networks within left and right PFC that uniquely and positively correlated with performance in our control and TBI samples respectively, providing evidence of compensatory functional recruitment. Next we combined brain-behavior and functional connectivity analyses to investigate whether compensatory brain changes were facilitated by functional reorganization (i.e., recruitment of brain regions not engaged by our control sample) or altered functional engagement (i.e., differential recruitment of similar brain regions between the two groups based on task demands). In other words, does altered recruitment represent the instantiation of novel neural networks to support working memory performance after injury or the unmasking of extant, but behaviorally latent, functional connectivity? Our results support an altered functional engagement hypothesis. Areas within PFC that are normally coactivated during working memory are behaviorally relevant at an earlier stage of difficulty for TBI patients as compared to controls. This altered functional engagement, also evident in the aging literature, is attributable to distributed changes owing to significant DAI.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it