The marmoset default-mode network identified by deactivations in task-based fMRI studies
Bibliographic record
Abstract
SUMMARY Understanding the default-mode network (DMN) in the common marmoset (Callithrix jacchus) has been challenging due to inconsistencies with human and marmoset DMNs. By analyzing task-negative activation in fMRI studies, we identified medial prefrontal cortical areas, rostral auditory areas, entorhinal cortex, posterior cingulate cortex area 31, hippocampus, hypothalamus, and basomedial amygdala as marmoset DMN components. Notable, medial and posterior parietal areas that were previously hypothesized to be part of the DMN were activated during visual task blocks. Seed analysis using resting-state fMRI showed strong connectivity between task-negative areas, and tracer data supported a structural network aligning with this functional DMN. These findings challenge previous definition of the marmoset DMN and reconcile many inconsistencies with the DMNs observed in humans, macaque monkeys, and even rodents. Overall, these results highlight the marmoset as a powerful model for DMN research, with potential implications for studying neuropsychiatric disorders where DMN activity and connectivity are altered.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".