The Müller-Lyer line-length task interpreted as a conflict paradigm: A chronometric study and a diffusion account

Predictions and rewards affect decision-making but not subjective experience

To survive, organisms constantly make decisions to avoid danger and maximize rewards in information-rich environments. As a result, decisions about sensory input are not only driven by sensory information but also by other factors, such as the expected rewards of a decision (known as the payoff matrix) or by information about temporal regularities in the environment (known as cognitive priors or predictions). However, it is unknown to what extent these different types of information affect subjective experience or whether they merely result in nonperceptual response criterion shifts. To investigate this question, we used three carefully matched manipulations that typically result in behavioral shifts in decision criteria: a visual illusion (Müller-Lyer condition), a punishment scheme (payoff condition), and a change in the ratio of relevant stimuli (base rate condition). To gauge shifts in subjective experience, we introduce a task in which participants not only make decisions about what they have just seen but are also asked to reproduce their experience of a target stimulus. Using Bayesian ordinal modeling, we show that each of these three manipulations affects the decision criterion as intended but that the visual illusion uniquely affects sensory experience as measured by reproduction. In a series of follow-up experiments, we use computational modeling to show that although the visual illusion results in a distinct drift-diffusion (DDM) parameter profile relative to nonsensory manipulations, reliance on DDM parameter estimates alone is not sufficient to ascertain whether a given manipulation is perceptual or nonperceptual.

The Müller-Lyer illusion through mental imagery

Previous studies have pointed to a link between visual perception and mental imagery. The present experiment focuses on one of the best-known illusions, the Müller-Lyer illusion, now reproduced under conditions of real perception and by means of imagery. To that purpose, a tailored ad-hoc set of combined figures was presented to a total of 161 fine art students (M age = 20,34, SD = 1,75) who individually worked with two different variations of the Müller-Lyer figures which consisted of a 10 mm long shaft and two fins set at an angle of 30º, being 15 mm long in one instance and 45 mm long in the other. In small groups, participants also completed an image control questionnaire. Results yielded that the longer the oblique lines, the larger the magnitude of the illusion both in the situation of real perception and in the imaginary situation. Also, the magnitude of the illusion augmented in the situation of perception in contrast to the imaginary situation, both with 15 mm long fins and with those of 45 mm. However, no significant differences were found in the magnitude of the illusion between high and low individuals in image control, although interactions between image control and other variables were indeed significant. The consistency of the outcome is a step forward in the study of illusions through mental images and opens the door to new lines of research that could involve innovative methods of analysis, different versions of the illusion and wider groups of participants.

Delta plots for conflict tasks: An activation-suppression race model

We describe a mathematically simple yet precise model of activation suppression that can explain the negative-going delta plots often observed in standard Simon tasks. The model postulates a race between the identification of the relevant stimulus attribute and the suppression of irrelevant location-based activation, with the irrelevant activation only having an effect if the irrelevant activation is still present at the moment when central processing of the relevant attribute starts. The model can be fitted by maximum likelihood to observed distributions of RTs in congruent and incongruent trials, and it provides good fits to two previously-reported data sets with plausible parameter values. R and MATLAB software for use with the model is provided.