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Adjusting behavioral methods when applying nonlinear dynamical measures to stimulus rate.

Barbara Bruhns Frey1

  • 1State of Tennessee, Governor's Office of Children's Care Coordination, William R. Snodgrass Tennessee Tower, Eighth Ave. North, 27th Floor, Nashville, TN 37243, USA. Barbara.A.Frey@Vanderbilt.edu

Nonlinear Dynamics, Psychology, and Life Sciences
|March 8, 2006
PubMed
Summary

This study explores trial-to-trial variability in behavior using nonlinear dynamical analysis. Controlling trial timing, specifically using inter-stimulus intervals, is recommended for accurate analysis of behavioral time series data.

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Area of Science:

  • Behavioral science
  • Dynamical systems theory
  • Cognitive psychology

Background:

  • Trial-to-trial variability is often overlooked in behavioral studies.
  • Sequence effects in data suggest dependence on prior events, making them suitable for nonlinear dynamical analysis.
  • Applying nonlinear dynamical tools to behavioral data necessitates careful consideration of experimental methodology, particularly trial timing.

Purpose of the Study:

  • To investigate the assumptions of trial timing in nonlinear dynamical analysis of behavioral data.
  • To explore the impact of trial timing control on the analysis of response time series.
  • To initiate a discussion on appropriate experimental control of trial timing.

Main Methods:

  • Response times from simple two-choice tasks were analyzed as time series.

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  • Two nonlinear dynamical measures were applied to assess time series properties.
  • Stimulus rate and stimulus-response mapping were manipulated to examine trial timing control.
  • Two methods of controlling stimulus rate were compared: response-stimulus interval and inter-stimulus interval.

    • Main Results:

    • Significant differences in estimated dimensionalities (m) were found between observed and comparison time series.
    • Varying experimental factors (stimulus rate, stimulus-response mapping) led to differences in dimensionality estimates.
    • The inter-stimulus interval method for controlling stimulus rate yielded more reliable results for nonlinear dynamical measures.

    Conclusions:

    • Appropriate control of trial timing is crucial for accurate nonlinear dynamical analysis of behavioral data.
    • The inter-stimulus interval is the recommended method for controlling stimulus rate when applying nonlinear dynamical measures.
    • Further research and discussion are needed regarding experimental methodologies for trial timing control in behavioral research.