Task switching following 24 h of total sleep deprivation
Bibliographic record
Abstract
Task switching is a ubiquitous feature of many human activities that involve multitasking. In addition, owing to occupational demands, many individuals are required to engage in task switching under various levels of sleep deprivation, such as those who work in military and medical contexts. Nevertheless, little is known about the effects that sleep loss has on the neural bases of task switching. To address this shortcoming, we administered a cued switching task to participants following a night of normal sleep and also following a night of total sleep deprivation - in counterbalanced order. The behavioral results demonstrated a cost (i.e. longer reaction time) both as a function of sleep deprivation and task switching. Sleep deprivation resulted in greater activation in the frontoparietal network, whereas task switching was correlated with greater activation in the thalamus and superior temporal gyrus. However, despite increases in fatigue and sleepiness and a reduction in cognitive effectiveness (computed from actigraphic data), the reaction time cost associated with switching (i.e. switch cost) was not exacerbated by sleep deprivation. The results are discussed in terms of the involvement of executive functions in mitigating the effects of sleep deprivation on task switching.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".