Evidence map›Paper›PMID 30530856›Full record

ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2019

Hard Decisions Shape the Neural Coding of Preferences.

Katharina Voigt, Carsten Murawski, Sebastian Speer, Stefan Bode

Abstract read
In one paragraph

Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
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  12. Believing and Beliefs-Neurophysiological Underpinnings.Frontiers in behavioral neuroscience · 2022
    Article
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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

4 authors.

Katharina VoigtMelbourne School of Psychological Sciences.
Carsten MurawskiDepartment of Finance, The University of Melbourne, Victoria 3010, Australia.ORCID 0000-0002-1237-9535
Sebastian SpeerMelbourne School of Psychological Sciences.
Stefan BodeMelbourne School of Psychological Sciences, sbode@unimelb.edu.au.ORCID 0000-0002-0258-7795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the mismatch between initial preferences and decision outcomes. In contrast, this functional magnetic resonance imaging and eye-tracking study with male and female human participants found that preferences are already updated online during the process of decision-making. Preference changes were predicted from activity in left dorsolateral prefrontal cortex and precuneus while making hard decisions. Fixation durations during this phase predicted both choice outcomes and subsequent preference changes. These preference adjustments became behaviorally relevant only for choices that were remembered and were in turn associated with hippocampus activity. Our results suggest that preferences evolve dynamically as decisions arise, potentially as a mechanism to prevent stalemate situations in underdetermined decision scenarios.

Indexed as

AdolescentAdultBrain MappingChoice BehaviorCognitive DissonanceDecision MakingEye MovementsFemaleFixation, OcularHippocampusHumansLinear ModelsMagnetic Resonance ImagingMaleMemoryParietal Lobechoice-induced preference changedecision-makingfMRIprecuneuspreference formationprefrontal cortex

Identifiers

PMID30530856
PMCPMC6343649

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.