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Cited by 691Visual perception and processing mechanismsNeural and Behavioral Psychology StudiesDecision-Making and Behavioral Economics

The effect of stimulus strength on the speed and accuracy of a perceptual decision

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Palmer, John, Huk, Alexander C., Shadlen, Michael N.·2005·Journal of Vision
DOI 10.1167/5.5.1
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Abstract

Both the speed and the accuracy of a perceptual judgment depend on the strength of the sensory stimulation. When stimulus strength is high, accuracy is high and response time is fast; when stimulus strength is low, accuracy is low and response time is slow. Although the psychometric function is well established as a tool for analyzing the relationship between accuracy and stimulus strength, the corresponding chronometric function for the relationship between response time and stimulus strength has not received as much consideration. In this article, we describe a theory of perceptual decision making based on a diffusion model. In it, a decision is based on the additive accumulation of sensory evidence over time to a bound. Combined with simple scaling assumptions, the proportional-rate and power-rate diffusion models predict simple analytic expressions for both the chronometric and psychometric functions. In a series of psychophysical experiments, we show that this theory accounts for response time and accuracy as a function of both stimulus strength and speed-accuracy instructions. In particular, the results demonstrate a close coupling between response time and accuracy. The theory is also shown to subsume the predictions of Piéron's Law, a power function dependence of response time on stimulus strength. The theory's analytic chronometric function allows one to extend theories of accuracy to response time.

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  • Such an accumulation process explains both the choice and accuracy of decisions over a range of difficulty levels as well as the time required to make the decision.

    “Such an accumulation process explains both the choice and accuracy of decisions over a range of difficulty levels as well as the time required to make the decision9.”

    From Changes of mind in decision-making (2009) · cites this paper as [9]

  • The choice at initiation and reaction times as a function of task difficulty (coherence of dot motion) were explained by a bounded drift-diffusion model consistent with previous studies in humans and monkeys.

    “The choice at initiation (initial hand trajectory) and reaction times as a function of task difficulty (coherence of dot motion) were explained by a bounded drift-diffusion model (Fig. 2, black curves) consistent with previous studies in humans and monkeys1,9,14.”

    From Changes of mind in decision-making (2009) · cites this paper as [9]

  • The pattern of slower performance was explained by the same model with higher initiation bounds.

    “The pattern was explained by the same model with higher initiation bounds9.”

    From Changes of mind in decision-making (2009) · cites this paper as [9]

  • The model explains both the diminishing returns associated with prolonged viewing and the tradeoff between speed and accuracy in reaction time experiments.

    “It explains both the diminishing returns associated with prolonged viewing in our experiment (Fig. S3) (20) and the tradeoff between speed and accuracy in reaction time experiments (13, 39, 40).”

    From Representation of Confidence Associated with a Decision by Neurons in the Parietal Cortex (2009) · cites this paper as [39]

  • A formal model of bounded accumulation accounts quantitatively for subjects' speed and accuracy in 2-choice tasks.

    “First, a formal model of bounded accumulation accounts quantitatively for subjects’ speed and accuracy3,6.”

    From Decision-making with multiple alternatives (2008) · cites this paper as [3]

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Authors
Palmer, J., Huk, A. C., & Shadlen, M. N.
Affiliations
  • University of Washington (US)
  • The University of Texas at Austin (US)
  • Howard Hughes Medical Institute (US)
ORCID
Venue
Journal of Vision
Publisher
Association for Research in Vision and Ophthalmology (ARVO)
Published
2005-05-02
Volume
5
Issue
5
Pages
1
ISSN
1534-7362 (ISSN-L)
DOI
10.1167/5.5.1
OpenAlex
W2135075084
Semantic Scholar
abf73168fa849aa554fea630060ed3f593512493
Cited by
691
References
89
Citations by year
2026: 17 · 2025: 36 · 2024: 29 · 2023: 38 · 2022: 47 · 2021: 43 · 2020: 36 · 2019: 25 · 2018: 39 · 2017: 27 · 2016: 39 · 2015: 47 · 2014: 51 · 2013: 39 · 2012: 35
FWCI
11.07
Type
journal article
Language
en
Open access
Locations
  • Journal of Vision (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Eye Institute (EY11378, R01EY011378)
  • National Center for Research Resources (RR00166, P51RR000166)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Keywords
perceptual decision making, stimulus strength, reaction time (psychology), decision accuracy, diffusion models, psychometric functions, speed-accuracy trade-off, sensory evidence accumulation
MeSH terms
Decision Making, Humans, Psychometrics, Psychomotor Performance, Reaction Time, Visual Perception, Reproducibility of Results

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