Age differences in the default network at rest and the relation to self-referential processing
Bibliographic record
Abstract
Older adults show a 'positivity bias' in tasks involving emotion and self-referential processing. A critical network that is involved in self-referencing and shows age-related decline is the default network (DN). The purpose of the current study was to investigate age differences in pre- and post-task DN functional connectivity (FC) and signal variability, and to examine whether they are predictive of the positivity bias in self-referencing. We measured FC and within-subject variability of the DN in resting-state scans preceding and following tasks involving personality judgements on the self and a close other. Older adults endorsed more positive traits than younger adults on both tasks. FC was weaker post-task in older vs younger adults, and younger adults had greater variability than older adults in DN nodes. Younger adults with higher post-task DN variability had more negative self-ratings. For both age groups, greater FC in the DN was associated with more negative self-ratings. Neither FC nor variability was related to other ratings, despite the potential for self-processing when making other judgements. Our findings suggest that ageing leads to reduced FC and variability in the DN, which is most apparent after task, and may be one mechanism underlying the positive bias with age.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".