Sleep deprivation attenuates neural responses to outcomes from risky decision‐making
Bibliographic record
Abstract
Sleep loss impacts a broad range of brain and cognitive functions. However, how sleep deprivation affects risky decision-making remains inconclusive. This study used functional MRI to examine the impact of one night of total sleep deprivation (TSD) on risky decision-making behavior and the underlying brain responses in healthy adults. In this study, we analyzed data from N = 56 participants in a strictly controlled 5-day and 4-night in-laboratory study using a modified Balloon Analogue Risk Task. Participants completed two scan sessions in counter-balanced order, including one scan during rested wakefulness (RW) and another scan after one night of TSD. Results showed no differences in participants' risk-taking propensity and risk-induced activation between RW and TSD. However, participants showed significantly reduced neural activity in the anterior cingulate cortex and bilateral insula for loss outcomes, and in bilateral putamen for win outcomes during TSD compared with RW. Moreover, risk-induced activation in the insula negatively correlated with participants' risk-taking propensity during RW, while no such correlations were observed after TSD. These findings suggest that sleep loss may impact risky decision-making by attenuating neural responses to decision outcomes and impairing brain-behavior associations.
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 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) | 0.000 | 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".