Evidence map›Paper›PMID 42327148›Full record

ArticlebioRxiv : the preprint server for biology2026

Why do we seek information about the future? On the origins of subjective value without instrumental value.

Ethan S Bromberg-Martin, Josh Merel, Ilya E Monosov

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ethan S Bromberg-MartinSolomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0002-7953-5205
Josh MerelFauna Robotics, New York City, USA.
Ilya E MonosovSolomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA.ORCID 0000-0003-0057-7929

Funding

MECHANISMS OF INFORMATION SEEKING IN THE PRIMATE BRAINR01MH116937 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2019 to 2026
$4.0M
Neural Circuits that Regulate Risk SeekingR01MH110594 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2017 to 2026
$3.9M
Neuronal mechanisms of novelty seekingR01MH128344 · NIMH · WASHINGTON UNIVERSITY · PI Ilya E. Monosov · 2022 to 2026
$1.9M
INTERFERONS IN AUTOIMMUNE ASSOCIATED-AVOIDANCE LEARNINGF32MH010643 · NIMH · UNIVERSITY OF COLORADO DENVER · PI SCHROTT, LISA M · 1993 to 1995
–
NIMH NIH HHS F32 MH010643NIMH NIH HHS R01 MH110594NIMH NIH HHS R01 MH116937NIMH NIH HHS R01 MH128344
6 · The paper itself

Abstract

Why do we want to know the future? Humans and many animals pay for information to predict uncertain rewards, even when they cannot control them. The reason for this conserved yet seemingly paradoxical preference - "subjective value without instrumental value" - remains unknown. Here we develop a normative framework to explain the origins of such preferences, their persistence across species, and their contributions to survival. We formalize and evaluate theories that explain subjective value as originating from an adaptive estimate of advantage for solving core computational problems in naturalistic environments. We show that human and animal subjective values are remarkably well suited to solve these problems, accomplishing the goals of multiple theories simultaneously. We derive novel forms of information to enable existing theories to be dissociated, and show that pooling their subjective values improves performance across diverse environments. Thus, organisms may value information because it pays diverse dividends in nature.

Identifiers

PMID42327148
PMCPMC13277909

What OpenQuestion holds

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LicenceCC BY-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.