Evidence map›Paper›PMID 30007746›Full record

ReviewTrends in neurosciences2018

Bridging Neural and Computational Viewpoints on Perceptual Decision-Making.

Redmond G O'Connell, Michael N Shadlen, KongFatt Wong-Lin, Simon P Kelly

Abstract readReview
In one paragraph

Review in Trends in neurosciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.

0numbers the graph read from it
0cells of the map it votes in
82citing 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

82 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Model-based analysis of stop-signal data reveals robust neural and clinical correlates of evidence accumulation but not inhibition.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  5. Article
  6. A Movement-Independent Signature of Urgency during Human Perceptual Decision-Making.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2026
    Article
  7. Article
  8. Article
  9. Neural mechanisms of flexible perceptual inference.PLoS computational biology · 2025
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Neurophysiology of Perceptual Decision-Making and Its Alterations in Attention-Deficit Hyperactivity Disorder.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  18. Article
  19. Article
  20. Article

22 more citing papers are in PubMed but not listed here.

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.

Redmond G O'ConnellTrinity College Institute of Neuroscience and School of Psychology, Trinity College Dublin, Ireland. Electronic address: reoconne@tcd.ie.
Michael N ShadlenHoward Hughes Medical Institute and Department of Neuroscience, Columbia University, New York, NY 10032, USA; Zuckerman Mind Brain Behaviour Institute and Kavli Institute for Brain Science, Columbia University, New York, NY 10032, USA.
KongFatt Wong-LinIntelligent Systems Research Centre, University of Ulster, Magee Campus, Northland Road, Derry, BT48 7JL, UK.
Simon P KellySchool of Electrical and Electronic Engineering, University College Dublin, Dublin, Ireland. Electronic address: simon.kelly@ucd.ie.

Funding

Instrumentation, Fabrication, and Design CoreP30EY019007 · NEI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Xin Zhang · 2010 to 2026
$12.9M
NEURAL MECHANISMS OF VISUAL PERCEPTIONR01EY011378 · NEI · UNIVERSITY OF WASHINGTON · PI SHADLEN, MICHAEL NEIL · 1996 to 2017
$3.8M
Howard Hughes Medical InstituteNEI NIH HHS P30 EY019007NEI NIH HHS R01 EY011378
6 · The paper itself

Abstract

Sequential sampling models have provided a dominant theoretical framework guiding computational and neurophysiological investigations of perceptual decision-making. While these models share the basic principle that decisions are formed by accumulating sensory evidence to a bound, they come in many forms that can make similar predictions of choice behaviour despite invoking fundamentally different mechanisms. The identification of neural signals that reflect some of the core computations underpinning decision formation offers new avenues for empirically testing and refining key model assumptions. Here, we highlight recent efforts to explore these avenues and, in so doing, consider the conceptual and methodological challenges that arise when seeking to infer decision computations from complex neural data.

Indexed as

Action PotentialsAnimalsChoice BehaviorDecision MakingHumansMotion PerceptionNeuronsPsychomotor Performancecomputational modellinglateral intraparietal area (LIP)perceptual decision-makingsequential sampling

Identifiers

PMID30007746
PMCPMC6215147

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.