Development of relational reasoning during adolescence
Bibliographic record
Abstract
Non-linear changes in behaviour and in brain activity during adolescent development have been reported in a variety of cognitive tasks. These developmental changes are often interpreted as being a consequence of changes in brain structure, including non-linear changes in grey matter volumes, which occur during adolescence. However, very few studies have attempted to combine behavioural, functional and structural data. This multi-method approach is the one we took in the current study, which was designed to investigate developmental changes in behaviour and brain activity during relational reasoning, the simultaneous integration of multiple relations. We used a relational reasoning task known to recruit rostrolateral prefrontal cortex (RLPFC), a region that undergoes substantial structural changes during adolescence. The task was administered to female participants in a behavioural (N = 178, 7-27 years) and an fMRI study (N = 37, 11-30 years). Non-linear changes in accuracy were observed, with poorer performance during mid-adolescence. fMRI and VBM results revealed a complex picture of linear and possibly non-linear changes with age. Performance and structural changes partly accounted for changes with age in RLPFC and medial superior frontal gyrus activity but not for a decrease in activation in the anterior insula/frontal operculum between mid-adolescence and adulthood. These functional changes might instead reflect the maturation of neurocognitive strategies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".