Perturbations in risk/reward decision making and frontal cortical catecholamine regulation induced by mild traumatic brain injury
Bibliographic record
Abstract
Mild traumatic brain injury (mTBI) disrupts cognitive processes that influence risk taking behavior. Little is known regarding the effects of repetitive mild injury (rmTBI) or whether these outcomes are sex specific. Risk/reward decision making is mediated by the prefrontal cortex (PFC), which is densely innervated by catecholaminergic fibers. Aberrant PFC catecholamine activity has been documented following TBI and may underlie TBI-induced risky behavior. The present study characterized the effects of rmTBI on risk/reward decision making behavior and catecholamine transmitter regulatory proteins within the PFC. Rats were exposed to sham, single (smTBI), or three closed-head controlled cortical impact (CH-CCI) injuries and assessed for injury-induced effects on risk/reward decision making using a probabilistic discounting task (PDT). In the first week post-final surgery, mTBI increased risky choice preference. By the fourth week, males exhibited increased latencies to make risky choices following rmTBI, demonstrating a delayed effect on processing speed. When levels of tyrosine hydroxylase (TH) and the norepinephrine reuptake transporter (NET) were measured within subregions of the PFC, females exhibited dramatic increases of TH levels within the orbitofrontal cortex (OFC) following smTBI. However, both males and females demonstrated reduced levels of OFC NET following rmTBI. These results indicate the OFC is susceptible to catecholamine instability after rmTBI and suggests that not all areas of the PFC contribute equally to TBI-induced imbalances. Overall, the CH-CCI model of rmTBI has revealed time-dependent and sex-specific changes in risk/reward decision making and catecholamine regulation following repetitive mild head injuries.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".