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Record W4412182431 · doi:10.1101/2025.07.07.663570

Intertemporal choice across short and long time horizons: an fMRI study

2025· preprint· en· W4412182431 on OpenAlexfundno aff
Shengjie Xu, Jeffrey C. Erlich, Evgeniya Lukinova

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldDecision Sciences
TopicInnovation Diffusion and Forecasting
Canadian institutionsnot available
FundersNYU-ECNU Institute of Brain and Cognitive Science, New York University ShanghaiHigher Education Discipline Innovation ProjectEast China Normal UniversityShanghai Municipal Education CommissionNational Natural Science Foundation of ChinaYork UniversityWellcome TrustNew York University ShanghaiHunter CollegeCity University of New YorkNational Science Foundation
KeywordsNew horizonsIntertemporal choiceEconomicsTime preferenceEconometricsDeep timePsychologyCognitive psychologyNeoclassical economicsGeologyPhysicsPaleontology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.065
GPT teacher head0.350
Teacher spread0.285 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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