Default mode network mediates low‐frequency fluctuations in brain activity and behavior during sustained attention
Bibliographic record
Abstract
The low-frequency (<0.1 Hz) fluctuation in sustained attention attracts enormous interest in cognitive neuroscience and clinical research since it always leads to cognitive and behavioral lapses. What is the source of the spontaneous fluctuation in sustained attention in neural activity, and how does the neural fluctuation relate to behavioral fluctuation? Here, we address these questions by collecting and analyzing two independent fMRI and behavior datasets. We show that the neural (fMRI) fluctuation in a key brain network, the default-mode network (DMN), mediate behavioral (reaction time) fluctuation during sustained attention. DMN shows the increased amplitude of fluctuation, which correlates with the behavioral fluctuation in a similar frequency range (0.01-0.1 Hz) but not in the lower (<0.01 Hz) or higher (>0.1 Hz) frequency range. This was observed during both auditory and visual sustained attention and was replicable across independent datasets. These results provide a novel insight into the neural source of attention-fluctuation and extend the former concept that DMN was deactivated in cognitive tasks. More generally, our findings highlight the temporal dynamic of the brain-behavior relationship.
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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 | 0.003 |
| 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 | 0.001 |
| 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".