Sex and age differences in cognitive bias and neural activation in response to cognitive bias testing
Bibliographic record
Abstract
Cognitive symptoms of depression, including negative cognitive bias, are more severe in women than in men. Current treatments to reduce negative cognitive bias are not effective and sex differences in the neural activity underlying cognitive bias may play a role. Here we examined sex and age differences in cognitive bias and functional connectivity in a novel paradigm. Male and female rats underwent an 18-day cognitive bias procedure, in which they learned to discriminate between two contexts (shock paired context A, no-shock paired context B), during either adolescence (postnatal day (PD 40)), young adulthood (PD 100), or middle-age (PD 210). Cognitive bias was measured as freezing behaviour in response to an ambiguous context (context C), with freezing levels akin to the shock paired context coded as negative bias. All animals learned to discriminate between the two contexts, regardless of sex or age. However, adults (young adults, middle-aged) displayed a greater negative cognitive bias compared to adolescents, and middle-aged males had a greater negative cognitive bias than middle-aged females. Females had greater neural activation of the nucleus accumbens, amygdala, and hippocampal regions to the ambiguous context compared to males, and young rats (adolescent, young adults) had greater neural activation in these regions compared to middle-aged rats. Functional connectivity between regions involved in cognitive bias differed by age and sex, and only adult males had negative correlations between the frontal regions and hippocampal regions. These findings highlight the importance of examining age and sex when investigating the underpinnings of negative cognitive bias and lay the groundwork for determining what age- and sex-specific regions to target in future cognitive bias studies.
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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) | 0.000 | 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) | 0.002 | 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".