Evidence map›Paper›PMID 32500144›Full record

ArticleCerebral cortex (New York, N.Y. : 1991)2020

Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions.

Y Yau, M Dadar, M Taylor, Y Zeighami, L K Fellows, P Cisek, A Dagher

Abstract read
In one paragraph

Article in Cerebral cortex (New York, N.Y. : 1991), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  3. Article
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  7. Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021
    Article
  14. Article
  15. Article
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

7 authors.

Y YauMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.
M DadarMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.
M TaylorMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.
Y ZeighamiMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.
L K FellowsMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.
P CisekDépartement of Neuroscience, Université of Montréal, Montréal, Quebec H3C 3J7, Canada.
A DagherMcConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montréal, Quebec H3A 2B4, Canada.

Funding

CIHR FDN-143242
6 · The paper itself

Abstract

Current models of decision-making assume that the brain gradually accumulates evidence and drifts toward a threshold that, once crossed, results in a choice selection. These models have been especially successful in primate research; however, transposing them to human fMRI paradigms has proved it to be challenging. Here, we exploit the face-selective visual system and test whether decoded emotional facial features from multivariate fMRI signals during a dynamic perceptual decision-making task are related to the parameters of computational models of decision-making. We show that trial-by-trial variations in the pattern of neural activity in the fusiform gyrus reflect facial emotional information and modulate drift rates during deliberation. We also observed an inverse-urgency signal based in the caudate nucleus that was independent of sensory information but appeared to slow decisions, particularly when information in the task was ambiguous. Taken together, our results characterize how decision parameters from a computational model (i.e., drift rate and urgency signal) are involved in perceptual decision-making and reflected in the activity of the human brain.

Indexed as

AdultBrain MappingCaudate NucleusDecision MakingFacial RecognitionFemaleHumansMagnetic Resonance ImagingMaleModels, NeurologicalMultivariate AnalysisTemporal LobeYoung Adultdecision-makingdrift diffusion modelfMRImultivariate pattern analysisurgency gating

Identifiers

PMID32500144
PMCPMC7566688

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.