Prenatal Protein Malnutrition Produces Resistance to Distraction Similar to Noradrenergic Deafferentation of the Prelimbic Cortex in a Sustained Attention Task
Bibliographic record
Abstract
Exposure to malnutrition early in development increases likelihood of neuropsychiatric disorders, affective processing disorders, and attentional problems later in life. Many of these impairments are hypothesized to arise from impaired development of the prefrontal cortex. The current experiments examine the impact of prenatal malnutrition on the noradrenergic and cholinergic axons in the prefrontal cortex to determine if these changes contribute to the attentional deficits seen in prenatal protein malnourished rats (6% casein vs. 25% casein). Because prenatally malnourished animals had significant decreases in noradrenergic fibers in the prelimbic cortex with spared innervation in the anterior cingulate cortex and showed no changes in acetylcholine innervation of the prefrontal cortex, we compared deficits produced by malnutrition to those produced in adult rats by noradrenergic lesions of the prelimbic cortex. All animals were able to perform the baseline sustained attention task accurately. However, with the addition of visual distractors to the sustained attention task, animals that were prenatally malnourished and those that were noradrenergically lesioned showed cognitive rigidity, i.e., were less distractible than control animals. All groups showed similar changes in behavior when exposed to withholding reinforcement, suggesting specific attentional impairments rather than global difficulties in understanding response rules, bottom-up perceptual problems, or cognitive impairments secondary to dysfunction in sensitivity to reinforcement contingencies. These data suggest that prenatal protein malnutrition leads to deficits in noradrenergic innervation of the prelimbic cortex associated with cognitive rigidity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".