CoChat
Sign Up
Cited by 233Visual perception and processing mechanismsNeural dynamics and brain functionNeural and Behavioral Psychology Studies

Stochastic models of decisions about motion direction: Behavior and physiology

Ditterich, Jochen·2006·Neural Networks
DOI 10.1016/j.neunet.2006.05.042
Open this paper in CoChat — free account

Abstract

Roitman and Shadlen [Roitman J. D., & Shadlen M. N. (2002). Response of neurons in the lateral intraparietal area during a combined visual discrimination reaction time task. Journal of Neuroscience, 22, 9475-9489] have published a non-human primate study on visual decision making. They collected both behavioral and neurophysiological data and provided evidence that the data are qualitatively consistent with a mechanism based on accumulating sensory evidence up to a decision threshold. I have previously demonstrated that a time-variant diffusion model can account quite well quantitatively for both the behavioral and the neural data. In this manuscript I discuss how well the data constrains different components and parameters of the computational process. I also discuss the biological plausibility of the model parameters. I will demonstrate that a relatively large class of models, both with and without temporal integration and both stationary and time-variant could account for the behavioral data. Both the single cell recordings from the parietal cortex and previously published data from the extrastriate visual cortex provide additional constraints. Overall, the data favor a diffusion model with time-variant gain and leaky integrators. The integration time constant, however, turns out not to be well-constrained by the data.

Integrity signals

Registry

Crossref · 10.1016/j.neunet.2006.05.042

Cites

44 of 44 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The model with urgency explains the longer RTs on error trials.

    “The model with urgency explains the longer RTs on error trials 36 (Supplementary Fig. 7).”

    From Decision-making with multiple alternatives (2008) · cites this paper as [36]

  • Because chance represents 50% correct, there is less impetus to complete the trial at weak motion strengths, which probably explains the weaker urgency signal u(t) seen previously in 2-choice experiments.

    “Because chance represents 50% correct, there is less impetus to complete the trial at weak motion strengths, which probably explains the weaker urgency signal, u(t), seen previously in 2-choice experiments2,36.”

    From Decision-making with multiple alternatives (2008) · cites this paper as [36]

  • According to the bounded accumulation model, the longer RT on errors arises as a consequence of the urgency signal u(t), which imposes a more lax criterion for terminating the decision, thereby rendering errors more frequent.

    “According to the model, the longer RT on errors arises as a consequence of the urgency signal, u(t), which effectively imposes a more lax criterion for terminating the decision (as if the bound were dropping as a function of time), thereby rendering errors more frequent36.”

    From Decision-making with multiple alternatives (2008) · cites this paper as [36]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Ditterich, J.
Affiliations
University of California, Davis (US)
Corresponding author
Ditterich, Jochen
ORCID
Ditterich, Jochen
Venue
Neural Networks
Publisher
Elsevier BV
Published
2006-10
Volume
19
Issue
8
Pages
981-1012
ISSN
0893-6080 (ISSN-L)
DOI
10.1016/j.neunet.2006.05.042
OpenAlex
W2002824768
Cited by
233
References
44
Citations by year
2026: 4 · 2025: 7 · 2024: 13 · 2023: 16 · 2022: 13 · 2021: 11 · 2020: 16 · 2019: 9 · 2018: 18 · 2017: 15 · 2016: 13 · 2015: 15 · 2014: 15 · 2013: 11 · 2012: 12
FWCI
3.22
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Neural Networks (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
motion direction discrimination, visual decision making, diffusion models, decision threshold, sensory evidence accumulation, lateral intraparietal area, parietal cortex, extrastriate cortex, leaky integrator, computational neuroscience, single-unit recording
MeSH terms
Action Potentials, Animals, Behavior, Behavior, Animal, Decision Making, Discrimination, Psychological, Humans, Models, Biological, Models, Neurological, Motion, Motion Perception, Neurons, Reaction Time, Stochastic Processes, Time Factors, Visual Cortex

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review