Intertemporal choice across short and long time horizons: an fMRI study
Bibliographic record
Abstract
Abstract This preregistered fMRI study investigates the neural mechanisms underlying intertemporal choices involving waiting and postponing. On a behavioral level, choices made regarding rewards available in seconds that require waiting compared to choices about rewards postponed to a number days are surprisingly similar. The explanation to this short/long time scales gap is lacking even after considering time perception and external factors, such as stress. To address that this study is the first to examine the overlapping and distinct neural circuitry involved in the intertemporal choices over seconds and days, and the waiting period within subject. Our results revealed considerable overlap in brain activation during choices that consider seconds and days delays to reward in the executive control (dACC, dlPFC) and prospection (PCC/precuneus, dmPFC) networks, but not in the valuation network. Consistent with existent literature we found the valuation network activation (both vmPFC and ventral striatum) being parametrically modulated by individual subjective values of delayed rewards. Overall, the key network determined through representational similarity and decoding analyses was prospection accounting for similarity in activation during decision making across time scales of delays and discriminating between waiting and postponing the reward. These findings enhance our understanding of the neural underpinnings of intertemporal choices and their implications for real-life decisions occurring across varying time horizons, such as paying to skip advertisements while watching videos or deciding on the next-day delivery service.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".