Evidence map›Paper›PMID 40623837›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2025

Incorporation of a Cost of Deliberation Time in Perceptual Decision Making.

Shinichiro Kira, Ariel Zylberberg, Michael N Shadlen

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Shinichiro KiraDepartment of Neurobiology, Harvard Medical School, Boston, Massachusetts 02115.ORCID 0000-0003-0056-5928
Ariel ZylberbergZuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027 ariel.zylberberg@gmail.com.ORCID 0000-0002-2572-4748
Michael N ShadlenZuckerman Mind Brain Behavior Institute, Columbia University, New York, New York 10027.ORCID 0000-0002-2002-2210

Funding

YILMA SIV VACCINIA VACCINE TRIALP51RR000166 · NCRR · UNIVERSITY OF WASHINGTON · PI BAILLIE, THOMAS ALLAN · 1985 to 2011
$161.1M
Vision Research CoreP30EY001730 · NEI · UNIVERSITY OF WASHINGTON · PI JAMES Bryant HURLEY · 1985 to 2026
$23.5M
NEURAL MECHANISMS OF VISUAL PERCEPTIONR01EY011378 · NEI · UNIVERSITY OF WASHINGTON · PI SHADLEN, MICHAEL NEIL · 1996 to 2017
$3.8M
Computational and circuit mechanisms of decision makingR01NS113113 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SHADLEN, MICHAEL NEIL · 2019 to 2023
$2.2M
NCRR NIH HHS P51 RR000166NEI NIH HHS P30 EY001730NEI NIH HHS R01 EY011378NINDS NIH HHS R01 NS113113
6 · The paper itself

Abstract

Many decisions benefit from the accumulation of evidence obtained sequentially over time. In such circumstances, the decision-maker must balance speed against accuracy, while considering the cost associated with the passage of time. A neural mechanism to achieve this balance is to accumulate evidence and to terminate the deliberation when enough evidence has accrued. To accommodate time costs, it has been hypothesized that the criterion to terminate a decision may become lax as a function of time. Here we tested this hypothesis by manipulating the cost of time in a perceptual choice-reaction time (RT) task. Human participants (both sexes) discriminated the direction of motion in a dynamic random-dot display, which varied in difficulty across trials. Unbeknownst to the participants, halfway through the experiment, we increased the time pressure by canceling a small fraction of trials, mimicking a broken fixation, if they had not made a decision by a provisional deadline. This subtle manipulation led participants to make faster but less accurate decisions. Choice and RT were well explained by a bounded evidence-accumulation process. We developed a novel computational method to estimate the time-dependent changes in the stopping bounds directly from the participants' RT and choice data. Our analysis revealed that the bounds decline as a function of time, and that this decline is steeper following the time-cost manipulation. The time-varying decision bounds approximate an optimal stopping policy, although the specific bound shape is idiosyncratic across individuals.

Indexed as

Decision MakingMotion PerceptionReaction TimeAdultChoice BehaviorFemaleHumansMalePhotic StimulationPsychomotor PerformanceTime FactorsYoung Adultcollapsing decision boundsdecision makingdrift-diffusion modelrandom-dot motion taskspeed-accuracy tradeofftime costs

Identifiers

PMID40623837
PMCPMC12311769

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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.