Evidence map›Paper›PMID 40791467›Full record

ArticlebioRxiv : the preprint server for biology2025

A Rational Information Gathering Account of Infant Habituation.

Gili Karni, Lauren Emberson, Marcelo G Mattar, Nathaniel D Daw

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

5 · Who and what money

Authors and funding

4 authors.

Gili KarniPrinceton Neuroscience Institute, Princeton University.ORCID 0000-0003-1854-1158
Lauren EmbersonDepartment of Psychology, University of British Columbia.ORCID 0000-0002-2374-6580
Marcelo G MattarDepartment of Psychology, New York University.ORCID 0000-0003-3303-2490
Nathaniel D DawPrinceton Neuroscience Institute and Department of Psychology, Princeton University.ORCID 0000-0001-5029-1430

Funding

CRCNS: Computational Foundations for Externalizing/Internalizing PsychopathologyR01MH135587 · NIMH · PRINCETON UNIVERSITY · PI DAW, NATHANIEL DOUGLASS · 2023 to 2025
$613k
NIMH NIH HHS R01 MH135587
6 · The paper itself

Abstract

Gaze is one of the primary experimental measures for studying cognitive development, especially in preverbal infants. However, the field is only beginning to develop a principled explanatory framework for making sense of the various factors affecting gaze. We approach this issue by addressing infant gaze from first principles, using rational information gathering. In particular, we revisit the influential descriptive account of Hunter and Ames (1988) (H&A), which posits a set of regularities argued to govern how gaze preference for a stimulus changes with experience and other factors. When the H&A's model is reconsidered from the perspective of rational information gathering (as recently also proposed by other authors), one feature of the model emerges as surprising: that preference for a stimulus is not monotonic with exposure. This claim, which has at least some empirical support, is in contrast to most statistical measures of informativeness, which strictly decline with experience. We present a normative, computational theory of visual exploration that rationalizes this and other features of the classic account. Our account suggests that H&A's signature nonmonotonic pattern is a direct manifestation of a ubiquitous principle of the value of information in sequential tasks, other consequences of which have recently been observed in a range of settings including deliberation, exploration, curiosity, and boredom. This is that the value of information gathering, putatively driving gaze, depends on the interplay of a stimulus' informativeness (called

Identifiers

PMID40791467
PMCPMC12338556

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.