Self-referential encoding in the developing brain
Bibliographic record
Abstract
Episodic memory is closely linked to the self and information related to the self tends to be better remembered. In adults, the brain's default mode network (DMN) supports self-referential thought and memory, with the medial prefrontal cortex (mPFC) being important for both functions. How the DMN supports self-referential encoding in children, and where in the mPFC the processes of self-referencing and episodic memory interact, is unknown. We investigated the neural development of self-referential encoding in 83 participants ages 7-25. While undergoing MRI, participants viewed objects and answered self-referential or semantic questions. Self-referential compared to semantic encoding resulted in better recollection across all ages. Self-referential encoding was associated with greater activation across the DMN and inferior frontal gyrus (IFG), with age-related increases in the dorsal mPFC and left IFG. Region-of-interest analyses revealed the interaction of self-referential episodic memory in the anterior mPFC and left hippocampus. The dorsal and anterior mPFC showed a counteraction effect of self-related thinking with the previously demonstrated age-related increase in DMN deactivation for subsequent memory encoding. These results suggest that self-referential facilitation matures and interacts with the episodic memory system in the brain to support the development of episodic memory from childhood to adulthood.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".