What Can Brinley Plots Tell Us About Cognitive Aging? Exploring Simulated Data and Modified Brinley Plots.

Jessica Nicosia,Michael J Strube,Emily R Cohen-Shikora

doi:10.3389/fpsyg.2022.797583

Jessica Nicosia, Michael J Strube + Show 1 more

Open Access

https://doi.org/10.3389/fpsyg.2022.797583

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Abstract

Cognitive aging researchers have been challenged with demonstrating age-related effects above and beyond global slowing ever since Cerella raised this issue in 1990. As the literature has made clear, this has indeed proved to be a difficult task and continues to plague the field. One way that researchers have attempted to test for disproportionate age differences across task conditions is by using Brinley plots, or plotting the mean response latencies of older adults against the mean latencies for younger adults. The simplicity and large proportion of variance accounted for by these models has led to the widespread use of Brinley plots over the years. However, as systematically tested here through eight cases of simulated data, it is clear that the Brinley technique is not well suited to either identify or display the underlying structure of datasets examining age-related differences in attentional control. Some of the problems with conventional Brinley plots can be resolved by using a modified Brinley plot that includes study-specific slopes linking trial types and a no-age-difference reference line. Multilevel models find all of the relevant effects, especially if applied to trial-level data, and have the advantage of incorporating study-level moderators that might account for slope heterogeneity. Ultimately, we encourage fellow cognitive aging researchers to access the code and data for this project on OSF (https://osf.io/zxus8/) and employ the use of multilevel models over Brinley plots.

Highlights

Attentional control is a critical component of everyday behavior that allows one to focus on relevant information and resist distracting stimuli in the environment
Larger Stroop effects relative to a comparison group are taken as evidence for an attentional control deficit, for example in individuals with Schizophrenia (Cohen and Servan-Schreiber, 1992; Perlstein et al, 1998; Barch et al, 1999) or attention deficit hyperactivity disorder (ADHD; Homack and Riccio, 2004; Van Mourik et al, 2005) and, most relevant to the current study, older adults (e.g., Comalli et al, 1962; Cohn et al, 1984; Panek et al, 1984; Hartley, 1992; Spieler et al, 1996)
If the χ2-test was not significant, this suggested that the restricted model without the interaction term had a better fit than the full model, i.e., that one line would be sufficient to account for the data, and indicated the absence of a disproportionate age difference in the Stroop effect

Summary

Introduction

Attentional control is a critical component of everyday behavior that allows one to focus on relevant information and resist distracting stimuli in the environment. In the context of laboratory studies, attentional control is often assessed by examining response times and comparing performance across control and interference conditions. If a single linear component explains a majority of the variance, the implication is that a general slowing parameter explains most of the age-related variance and specific age-related mechanisms could not account for additional variance above and beyond that. These plots have shown some of the strongest correlations in all of psychology. Hale et al (1991) reported a model in which the regression line successfully accounted for 95.6% of the variance, concluding that general slowing was driving most age-related differences in their tasks

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