Distributional reaction time properties in the Eriksen task: marked differences or hidden similarities with the Simon task?

Abstract

In conflict tasks, the irrelevant stimulus attribute needs to be suppressed for the correct response to be produced. In the Simon task, earlier researchers have proposed that this suppression is the reason that, after an initial increase, the interference effect decreases for longer RTs, as reflected by late, negative-going delta plots. This view has been challenged by observations of positive-going delta plots, even for long RTs, in other conflict tasks, despite a similar necessity for suppression. For late negative-going delta plots to be interpreted as reflecting suppression, a necessary, although maybe not sufficient, condition is that similar patterns should be observed for other conflict tasks. We reasoned that a similar suppression could be present, but hidden, in the Eriksen flanker task. By recording and analyzing electromyograms of the muscles involved in response execution, we could compute delta plots separately for trials that elicited a subthreshold incorrect response activation (partial error). Late negative-going delta plots were observable on partial-error trials, although they were weaker than for the Simon task, reducing the impact of this inversion on the overall distribution. We further showed that this pattern is modulated by time pressure. Those results indicate that mechanisms leading to negative-going delta plots, similar to those observed in the Simon task, are also at play in the Eriksen task. The link between negative-going delta plots and executive online control is discussed.

Using Covert Response Activation to Test Latent Assumptions of Formal Decision-Making Models in Humans

“…Like the standard DDM, the only way for the LCA to produce faster errors than correct responses is to add across-trial variability in the starting points of the accumulators (Usher and McClelland, 2001;Ratcliff and Smith, 2004). In the context of a flanker task, this additional assumption would lead to equivalent increases in fast errors across congruency conditions, contrary to what is usually observed (Gratton et al, 1988;Hübner et al, 2010;White et al, 2011;Servant et al, 2014). Therefore, the standard LCA cannot account for behavioral performance in the flanker task for the same reason as for the standard DDM (White et al, 2011).…”

“…However, the model has recently been enriched by attentional control mechanisms that weight sensory evidence in a flexible and goal-directed way (Hübner et al, 2010;White et al, 2011), allowing capture of behavioral performance in more ecological choice situations requiring filtering of irrelevant information. Such situations have traditionally been studied with the flanker paradigm (Eriksen and Eriksen, 1974). Subjects are instructed to press a right or a left button according to a central symbolic target (e.g., a left response to the letter H and a right response to the letter S).…”

“…Assuming a standard 5-item display with the target being centered at 0, the quantity of attention allocated to the target, right inner flanker and right outer flanker over time (the left flankers are symmetrical) is given as follows: The DSTP and SSP capture RT distributions and accuracy data from flanker tasks under a wide variety of experimental manipulations (Hüb-ner et al, 2010;White et al, 2011). This new generation of diffusion models also explains particular interactions between flanker congruency and well known psychological laws (Servant et al, 2014). However, the DSTP and SSP so largely mimic each other on behavioral grounds that it has proven difficult to determine the superiority of one model over another.…”

“…In between-hand choice reaction time (RT) tasks, previous work has shown covert incorrect EMG activation in a portion of trials in which the correct response was finally given (Fig. 1;Coles et al, 1985;Burle et al, 2014). This phenomenon, termed "partial error," challenges sequential sampling models of perceptual decision making that assume that motor activity is engaged only once a decision threshold is reached (Ratcliff and Smith, 2004;Bogacz et al, 2006).…”

“…Although fMRI and EEG allow researchers to study decision making in humans at a systems level, both techniques present important limitations. The low temporal resolution of fMRI prevents any characterization of decision signal dynamics and most EEG studies rely on averaging procedures known to generate temporal distortions (Meyer et al, 1988;Burle et al, 2008). Although single-trial analysis techniques are currently being developed (Sadja et al, 2011), this approach is limited by the very small signal-to-noise ratio of the EEG coupled with the high variety of noise sources.…”