Task Switching: On the Relation of Cognitive Flexibility with Cognitive Capacity

Abstract

The task-switching paradigm is deemed a measure of cognitive flexibility. Previous research has demonstrated that individual differences in task-switch costs are moderately inversely related to cognitive ability. However, current theories emphasize multiple component processes of task switching, such as task-set preparation and task-set inertia. The relations of task-switching processes with cognitive ability were investigated in the current study. Participants completed a task-switching paradigm with geometric forms and a visuospatial working memory capacity (WMC) task. The task-switch effect was decomposed with the diffusion model. Effects of task-switching and response congruency were estimated as latent differences using structural equation modeling. Their magnitudes and relations with visuospatial WMC were investigated. Effects in the means of parameter estimates replicated previous findings, namely increased non-decision time in task-switch trials. Further, task switches and response incongruency had independent effects on drift rates, reflecting their differential effects on task readiness. Findings obtained with the figural tasks employed in this study revealed that WMC was inversely related to the task-switch effect in non-decision time. Relations with drift rates were inconsistent. Finally, WMC was moderately inversely related to response caution. These findings suggest that more able participants either needed less time for task-set preparation or that they invested less time for task-set preparation.

Keywords: cognitive capacity; cognitive flexibility; diffusion model; latent difference modeling; task switching; visuospatial working memory.

Figure A1

Mean squared error (MSE) for six alternative models fitted to the RT data of the switching task. The numbers in the legend correspond with the conditions the respective parameter was allowed to depend on, i.e., 1 = equal for all conditions, 2 = split by task-switch vs. repeat, and 4 = separate for all four conditions (task-switch $\times$ response–congruency).

Figure A2

Scatterplot of observed and model-predicted proportion of errors and quantiles of correct responses (in milliseconds) for participants in the respective trial types, as defined by task repeat vs. task-switch (s0; s1) trials with response–congruent vs. incongruent (i0; i1) stimulus attributes.

Figure 1

Schematic of the task-switching paradigm. The leftmost column shows the monitor display, the next columns illustrate the task-set preparation and stimulus processing requirements as well as the required response. The rightmost column presents the trial type as defined by task sequence and response–congruency of the task-relevant and irrelevant stimulus attributes (i.e., size vs. color). The trial code specifies the processing requirements, whether the trial necessitates a task switch (s1) or not (s0), and whether the response–relevant and irrelevant stimulus attributes are associated with incongruent responses (i1) or not (i0). Trial 1 would be a task-repeat trial if the preceding warm-up trial (not shown here) was a color classification trial, too. Trial types were balanced but their pseudo-random sequence was unpredictable for participants.

Figure 2

Schematic of the figural updating task. The trials shown here present the first four trials of a block. The monitor display is shown in the leftmost column. The next columns present the recall, response, and updating requirements in the respective trials. Trials 2–4 exemplify 1-back, 2-back, and 3-back recall requirements. In reality, the sequence of recall requirements was pseudo-random and unpredictable for participants.

Figure 3

Boxplots of diffusion model (DM) parameters. Upper panel: response caution split by block; middle panel: non-decision time, split by block and task repeat (RP)/switch (SW) trials; lower panel: drift rates, split by block, task repeat (RP)/switch (SW) and response congruent (C)/incongruent (I) trials.

Figure 4

Specification of the latent difference score (LDS) model, as exemplified for the task-switch effect in the diffusion model (DM) non-decision time parameter (t₀), and its relations with visuospatial working memory capacity (WMC) that was assessed using three parallel parcels of the figural Recall-N-Back (RNB) task. Analogous models were estimated for the other parameters. Indicators of the LDS models are systematically named taking into consideration their task switch (s1; s0) and response incongruency (i1; i0) requirements (see Figure 1 for details). Parameters numerically fixed at either 1 or 0 zero are displayed using dashed lines; parameters constrained to be equal are named identically in this figure. The latent correlations between factors (ρ₁–ρ₃) are provided in Table 3.