RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans

J Vis Exp. 2021 Jul 17:(173). doi: 10.3791/62285.

Abstract

The most extensively employed paradigm for the analysis of relational behavior is the transposition task. Nevertheless, it has two important limitations for its use in humans. The first one is the "ceiling effect" reported in linguistic participants. The second limitation is that the standard transposition task, being a simple choice task between two stimuli, does not include active behavioral patterns and their recording, as relevant factors in emergence of relational behavior. In the present work, a challenging multi-object task based on transposition, integrated with recording software, is presented. This paradigm requires behavioral active patterns to form stimuli compounds with a given relational criteria. The paradigm is composed of three arrangements: a) a bank of stimuli, b) sample relational compounds, and c) comparison relational compounds. The task consists of the participant constructing two comparison relational compounds by dragging figures of a bank of stimuli with the same relation shown by the sample relational compounds. These factors conform an integrated system that can be manipulated in an individual or integrative manner. The software records discrete responses (e.g., stimuli selections, placements) and continuous responses (e.g., tracking of cursor movements, figure dragging). The obtained data, data analysis and graphical representations proposed are compatible with frameworks that assume an active nature of the attentional and perceptual processes and an integrated and continuous system between the perceiver and the environment. The proposed paradigm deepens the systematic study of relational behavior in humans in the framework of the transposition paradigm and expands it to a continuous analysis of interaction between active patterns and the dynamics of relational behavior.

Publication types

  • Video-Audio Media

MeSH terms

  • Attention*
  • Humans