The present study aimed to investigate whether or not the so-called "bouba-kiki" effect is mediated by speech-specific representations. Sine-wave versions of naturally produced pseudowords were used as auditory stimuli in an implicit association task (IAT) and an explicit cross-modal matching (CMM) task to examine cross-modal shape-sound correspondences. A group of participants trained to hear the sine-wave stimuli as speech was compared to a group that heard them as non-speech sounds. Sound-shape correspondence effects were observed in both groups and tasks, indicating that speech-specific processing is not fundamental to the "bouba-kiki" phenomenon. Effects were similar across groups in the IAT, while in the CMM task the speechmode group showed a stronger effect compared with the non-speech group. This indicates that, while both tasks reflect auditoryvisual associations, only the CMM task is additionally sensitive to associations involving speech-specific representations.

No abstract

Dual Process Theory is currently a popular theory for explaining why we show bounded rationality in reasoning and decision-making tasks. This theory proposes there must be a sharp distinction in thinking to explain two clusters of correlational features. One cluster describes a fast and intuitive process (Type 1), while the other describes a slow and reflective one (Type 2). A problem for this theory is identifying a common principle that binds these features together, explaining why they form a unity, the unity problem. To solve it, a hypothesis is developed combining embodied predictive processing with symbolic classical approaches. The hypothesis, simplified, states that Type 1 processes are bound together because they rely on embodied predictive processing whereas Type 2 processes form a unity because they are accomplished by symbolic classical cognition. To show that this is likely the case, the features of Dual Process Theory are discussed in relation to these frameworks.

No abstract

Dual Process Theory has increasingly gained fame as a framework for explaining evidence in reasoning and decision making tasks. This theory proposes there must be a sharp distinction in thinking to explain two clusters of correlational features. One cluster describes a fast and intuitive process (Type 1), while the other describes a slow andreflective one (Type 2), (see Evans, 2008; Evans & Stanovich, 2013; Kahneman, 2011). However, as Samuels (2009) has noted, there is a problem of determining why these group of features form clusters, more than what the labels Type (or system) 1 and 2 can capture, the unity problem. We understand there might be differences in the processingarchitecture that grounds each type of process, thus requiring distinct cognitive frameworks for each. We argue that the predictive processing approach (as held by Hohwy, 2013 and Clark, 2016) is a more suitable framework for Type 1 processing. Such an approach proposes cognition is in the job of attempting to predict what will perturb sensory inputs next. These are not personal predictions but rather multiple sub-personalpredictions that even the visual system makes at various layers at each millisecond that passes. Rather than being based on a symbolic representation of each aspect of the world, these predictions are made on the basis of statistical information updated moment by moment. This statistical content tracks previous sensory states and the causes of theseprevious sensory states. Kahneman (2011) has been arguing that there is a link between perception and Type 1 processing. What we hold is that such link obtains because Type 1 judgments actually are predictions stemming from higher layers of perceptual systems which work by means of predictive processing. On the other hand, we propose sucharchitecture does not handle Type 2 processes. Rather, these seem to be based on classical symbol systems executing heuristic search as explained by Newell (1980). In conclusion, we propose a dual framework is necessary for explaining why there are two clusters of features. Such a framework would include predictive processing for explaining Type 1processing and computations on symbolic representations for Type 2 processing.