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Related Experiment Videos

Linear phase correction models for synchronization: parameter identification and estimation of parameters.

Hans-Henning Schulze1, Dirk Vorberg

  • 1Philipps-Universitat Marburg, Fachbereich Psychologie, Gutenbergstrasse 18, Marburg, 35037, Germany. schulze@mailer.uni.marburg.de

Brain and Cognition
|January 29, 2002
PubMed
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This study presents linear phase correction models for synchronized tapping, detailing their components and stochastic properties. Parameter estimation from data proved challenging due to significant interdependencies identified via simulations.

Area of Science:

  • Neuroscience
  • Motor Control
  • Computational Modeling

Background:

  • Synchronized tapping involves complex motor control and timing mechanisms.
  • Understanding the stochastic properties of these systems is crucial for accurate modeling.
  • Existing models may not fully capture the intricacies of phase correction.

Purpose of the Study:

  • To present linear phase correction models for synchronized tapping.
  • To analyze the stochastic properties of these models.
  • To investigate methods for parameter identification and estimation from empirical data.

Main Methods:

  • Development of generalized linear phase correction models.
  • Inclusion of a central timer, motor execution, and phase correction mechanisms.

Related Experiment Videos

  • Application of Monte Carlo simulations for parameter estimation and analysis.

    • Main Results:

    • Models incorporate central timing, motor execution, and phase correction components.
    • Parameter interdependency presents significant challenges for model estimation.
    • Stochastic properties of the models were analyzed.

    Conclusions:

    • Linear phase correction models offer a framework for synchronized tapping.
    • Parameter estimation requires careful consideration of interdependencies.
    • Further research is needed to refine estimation techniques for these models.