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Methodological improvements to a Procedure for Rapidly Establishing Steady-State Behavior.

Bryan Klapes1, Christine L Ginalis1, J J McDowell1

  • 1Department of Psychology, Emory University.

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|March 12, 2021
PubMed
Summary

Researchers optimized the Procedure for Rapidly Establishing Steady-State Behavior (PRESS-B) using shorter changeover delays (COD) and wider reinforcement ranges. These changes improved data quality and retention in behavioral studies.

Keywords:
matching lawoperant behaviorrandom-interval schedules

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Area of Science:

  • Behavioral Psychology
  • Experimental Psychology
  • Reinforcement Learning

Background:

  • The Procedure for Rapidly Establishing Steady-State Behavior (PRESS-B) is a method for collecting behavioral data.
  • Previous implementations of PRESS-B may have limitations in data quality and retention.
  • Optimizing experimental parameters is crucial for reliable behavioral research.

Purpose of the Study:

  • To enhance the data quality and retention of the PRESS-B method.
  • To investigate the effects of changeover delay (COD) length on data acquisition.
  • To explore the impact of reinforcement rate ratio ranges and inter-schedule blackouts.

Main Methods:

  • Three experiments were conducted involving participants and concurrent random-interval random-interval (conc RI RI) schedules.
  • Experiment 1 manipulated changeover delay (COD) lengths.
  • Experiments 2 and 3 varied reinforcement rate ratio ranges and introduced blackout periods between schedules.

Main Results:

  • A shorter COD (0.5-s) reduced instances of exclusive reinforcer acquisition but did not affect generalized matching law (GML) fit quality.
  • Wider reinforcement rate ratio ranges significantly decreased exclusive reinforcer acquisition.
  • Implementing brief blackouts between schedules improved GML fit consistency.

Conclusions:

  • Future PRESS-B studies should utilize shorter COD, wider reinforcement ranges, and inter-schedule blackouts.
  • These parameter adjustments are recommended for optimizing data quality and retention in behavioral experiments.
  • The findings contribute to refining methodologies in the study of behavior and reinforcement.