Jove
Visualize
Contact Us

Related Experiment Videos

Models for the perception of orientation in random dot patterns.

J Mates1, P Lánský, N Yakimoff

  • 1Institute of Physiology, Czechoslovak Academy of Sciences, Praha.

Biological Cybernetics
|January 1, 1990
PubMed
Summary

This study compares mathematical models for orientation perception in random dot patterns. Image-based models offer greater flexibility in explaining experimental data, especially for ambiguous orientations.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties.

Chaos (Woodbury, N.Y.)·2020
Same author

Entropy factor for randomness quantification in neuronal data.

Neural networks : the official journal of the International Neural Network Society·2017
Same author

HOLMES: The electron capture decay of [Formula: see text]Ho to measure the electron neutrino mass with sub-eV sensitivity.

The European physical journal. C, Particles and fields·2015
Same author

Temporal integration in sensorimotor synchronization.

Journal of cognitive neuroscience·2013
Same author

Parametric inference of neuronal response latency in presence of a background signal.

Bio Systems·2013
Same author

Randomness of spontaneous activity and information transfer in neurons.

Physiological research·2008
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Area of Science:

  • Visual perception
  • Computational neuroscience
  • Mathematical modeling

Background:

  • Orientation perception in random dot patterns is crucial for understanding visual processing.
  • Existing mathematical models vary in their ability to capture experimental findings.
  • The complexity of visual stimuli, like random dot patterns, necessitates robust modeling approaches.

Purpose of the Study:

  • To summarize and compare existing mathematical models of orientation perception.
  • To propose novel solutions for modeling orientation perception.
  • To evaluate model adequacy against experimental results.

Main Methods:

  • Analysis of models based on dot coordinates.
  • Investigation of models derived from the image function.

Related Experiment Videos

  • Introduction of stochastic variants for deterministic models.
  • Comparison of model predictions with experimental data.

    • Main Results:

    • Models utilizing the image function demonstrate superior flexibility.
    • Image-based models effectively render experimental data features, including orientation ambiguity.
    • Stochastic model variants are introduced to enhance deterministic approaches.

    Conclusions:

    • Image function-based mathematical models are more adept at explaining orientation perception in random dot patterns.
    • The proposed models and their stochastic variants offer improved explanations for experimental observations.
    • Further research can refine these models for enhanced predictive power in visual neuroscience.