Behavioral Priming 2.0: Enter a Dynamical Systems Perspective.

Dario Krpan

doi:10.3389/fpsyg.2017.01204

Abstract

On a daily basis, people are exposed to numerous stimuli, ranging from colors and smells to sounds and words, that could potentially activate different cognitive constructs and influence their actions. This type of influence on human behavior is referred to as priming. Roughly two decades ago, behavioral priming was hailed as one of the core forces that shape automatic behavior. However, failures to replicate some of the representative findings in this domain soon followed, which posed the following question: “How robust are behavioral priming effects, and to what extent are they actually important in shaping people's actions?” To shed a new light on this question, I revisit behavioral priming through the prism of a dynamical systems perspective (DSP). The DSP is a scientific paradigm that has been developed through a combined effort of many different academic disciplines, ranging from mathematics and physics to biology, economics, psychology, etc., and it deals with behavior of simple and complex systems over time. In the present paper, I use conceptual and methodological tools stemming from the DSP to propose circumstances under which behavioral priming effects are likely to occur. More precisely, I outline three possible types of the influence of priming on human behavior, to which I refer as emergence, readjustment, and attractor switch, and propose experimental designs to examine them. Finally, I discuss relevant implications for behavioral priming effects and their replications.

Highlights

Behavioral priming has recently been subjected to harsh criticisms, primarily because of numerous replication failures (e.g., Doyen et al, 2012; Pashler et al, 2012; Harris et al, 2013; Shanks et al, 2013; Rohrer et al, 2015; Wagenmakers et al, 2015)
I argued that the dynamical systems perspective (DSP) offers conceptual and methodological tools that can improve the understanding of when exactly behavioral priming effects are likely to occur and allow precise measurement of these effects
Given the absence of a strong attractor, the actor is likely to be sensitive to external perturbations such as primes, which may inform the emergence of a new stable behavioral attractor, lowering cognitive entropy in the process and allowing cognition to remain functional in meeting situational demands (Stephen et al, 2009b; Dixon et al, 2010; Vallacher et al, 2010)

Summary

INTRODUCTION

Behavioral priming has recently been subjected to harsh criticisms, primarily because of numerous replication failures (e.g., Doyen et al, 2012; Pashler et al, 2012; Harris et al, 2013; Shanks et al, 2013; Rohrer et al, 2015; Wagenmakers et al, 2015). If one considers the DSP, primes may be construed as control parameters that could alter behavioral dynamics only in very specific circumstances (see Kelso, 1995), and it is unlikely that they generally shape people’s actions in a more robust manner In line with this assumption, I propose there are three different types of influence to which I refer as (a) Emergence; (b) Readjustment; and (c) Attractor switch. Specifying how to capture changes in cognitive entropy is the final prerequisite for investigating behavioral priming under emergence As previously suggested, this can be done by tracking participants’ bodily movements and translating them into a motion time-series (e.g., change in velocity; Stephen et al, 2009b). Resources that can be consulted for catastrophe modeling include Cobb (1981), Grasman et al (2009); Guastello (2011a,b); Van der Maas et al (2003), and Zeeman (1976)

DISCUSSION

Limitations

Methods and Data