Independent race of colour and word can predict the Stroop effect

Mainstream theories of the Stroop effect suggest that faster colour classification on congruent trials (say, the word RED printed in red colour) relative to incongruent trials (GREEN in red) is due to channel interaction. Namely, information from the irrelevant word channel perturbs processing of the print colour, causing in turn slower processing of incongruent displays. In this note, I advance a new model in which colour and word are processed in parallel and completely independent channels. The Stroop effect is then the outcome of signal redundancy in congruent displays, where both colour and word contribute to the same response. Numerical computations show that the model can produce the Stroop effect (along with high accuracy rates) for a subset of parameter values. Thus, it provides a proof of existence for a separate channel theory, and a challenge to many existing theories.     

Distribution-free tests of stochastic dominance for small samples

One variable is said to “stochastically dominate” another if the probability of observations smaller than x is greater for one variable than the other, for all x. Inferring stochastic dominance from data samples is important for many applications of econometrics and experimental psychology, but little is known about the performance of existing inferential methods. Through simulation, we show that three of the most widely used inferential methods are inadequate for use in small samples of the size commonly encountered in many applications (up to 400 observations from each distribution). We develop two new inferential methods that perform very well in a limited, but practically important, case where the two variables are guaranteed not to be equal in distribution. We also show that extensions of these new methods, and an improved version of an existing method, perform quite well in the original, unlimited case.     

Studying visual search using systems factorial methodology with target-distractor similarity as the factor

Systems factorial technology (SFT) is a theory-driven set of methodologies oriented toward identification of basic mechanisms, such as parallel versus serial processing, of perception and cognition. Studies employing SFT in visual search with small display sizes have repeatedly shown decisive evidence for parallel processing. The first strong evidence for serial processing was recently found in short-term memory search, using target-distractor (T-D) similarity as a key experimental variable (Townsend & Fifi?, 2004). One of the major goals of the present study was to employ T-D similarity in visual search to learn whether this mode of manipulating processing speed would affect the parallel versus serial issue in that domain. The result was a surprising and regular departure from ordinary parallel or serial processing. The most plausible account at present relies on the notion of positively interacting parallel channels.     

Measuring single-item identification efficiencies for letters and 3-D objects

Identification thresholds and the corresponding efficiencies (ideal/human thresholds) are typically computed by collapsing data across an entire stimulus set within a given task in order to obtain a “multiple-item” summary measure of information use. However, some individual stimuli may be processed more efficiently than others, and such differences are not captured by conventional multiple-item threshold measurements. Here, we develop and present a technique for measuring “single-item” identification efficiencies. The resulting measure describes the ability of the human observer to make use of the information provided by a single stimulus item within the context of the larger set of stimuli. We applied this technique to the identification of 3-D rendered objects (Exp. 1) and Roman alphabet letters (Exp. 2). Our results showed that efficiency can vary markedly across stimuli within a given task, demonstrating that single-item efficiency measures can reveal important information that is lost by conventional multiple-item efficiency measures.     

Converging measures of workload capacity

Does processing more than one stimulus concurrently impede or facilitate performance relative to processing just one stimulus? This fundamental question about workload capacity was surprisingly difficult to address empirically until Townsend and Nozawa (1995) developed a set of nonparametric analyses called systems factorial technology. We develop an alternative parametric approach based on the linear ballistic accumulator decision model (Brown &; Heathcote, 2008), which uses the model’s parameter estimates to measure processing capacity. We show that these two methods have complementary strengths, and that, in a data set where participants varied greatly in capacity, the two approaches provide converging evidence.     

Nice Guys Finish Fast and Bad Guys Finish Last: Facilitatory vs. Inhibitory Interaction in Parallel Systems

Systems Factorial Technology is a powerful framework for investigating the fundamental properties of human information processing such as architecture (i.e., serial or parallel processing) and capacity (how processing efficiency is affected by increased workload). The Survivor Interaction Contrast (SIC) and the Capacity Coefficient are effective measures in determining these underlying properties, based on response-time data. Each of the different architectures, under the assumption of independent processing, predicts a specific form of the SIC along with some range of capacity. In this study, we explored SIC predictions of discrete-state (Markov process) and continuous-state (Linear Dynamic) models that allow for certain types of cross-channel interaction. The interaction can be facilitatory or inhibitory: one channel can either facilitate, or slow down processing in its counterpart. Despite the relative generality of these models, the combination of the architecture oriented plus the capacity oriented analyses provide for precise identification of the underlying system.     

A reach-to-touch investigation on the nature of reading in the Stroop task

In a Stroop task, participants can be presented with a color name printed in color and need to classify the print color while ignoring the word. The Stroop effect is typically calculated as the difference in mean response time (RT) between congruent (e.g., the word RED printed in red) and incongruent (GREEN in red) trials. Delta plots compare not just mean performance, but the entire RT distributions of congruent and incongruent conditions. However, both mean RT and delta plots have some limitations. Arm-reaching trajectories allow a more continuous measure for assessing the time course of the Stroop effect. We compared arm movements to congruent and incongruent stimuli in a standard Stroop task and a control task that encourages processing of each and every word. The Stroop effect emerged over time in the control task, but not in the standard Stroop, suggesting words may be processed differently in the two tasks.     

The resurrection of Tweedledum and Tweedledee: Bimodality cannot distinguish serial and parallel processes

Simultaneously presented signals may be processed in serial or in parallel. One potentially valuable indicator of a system’s characteristics may be the appearance of multimodality in the response time (RT) distributions. It is known that standard serial models can predict multimodal RT distributions, but it is unknown whether multimodality is diagnostic of serial systems, or whether alternative architectures, such as parallel ones, can also make such predictions. We demonstrate via simulations that a multimodal RT distribution is not sufficient by itself to rule out parallel self-terminating processing, even with limited trial numbers. These predictions are discussed within the context of recent data indicating the existence of multimodal distributions in visual search.     

Comparing perception of Stroop stimuli in focused versus divided attention paradigms: Evidence for dramatic processing differences

A huge set of focused attention experiments show that when presented with color words printed in color, observers report the ink color faster if the carrier word is the name of the color rather than the name of an alternative color, the Stroop effect. There is also a large number (although not so numerous as the Stroop task) of so-called “redundant targets studies” that are based on divided attention instructions. These almost always indicate that observers report the presence of a visual target (‘redness’ in the stimulus) faster if there are two replications of the target (the word RED in red ink color) than if only one is present (RED in green or GREEN in red). The present set of four experiments employs the same stimuli and same participants in both designs. Evidence supports the traditional interference account of the Stroop effect, but also supports a non-interference parallel processing account of the word and the color in the divided attention task. Theorists are challenged to find a unifying model that parsimoniously explains both seemingly contradictory results.     

Workload capacity spaces: A unified methodology for response time measures of efficiency as workload is varied

Increasing the number of available sources of information may impair or facilitate performance, depending on the capacity of the processing system. Tests performed on response time distributions are proving to be useful tools in determining the workload capacity (as well as other properties) of cognitive systems. In this article, we develop a framework and relevant mathematical formulae that represent different capacity assays (Miller’s race model bound, Grice’s bound, and Townsend’s capacity coefficient) in the same space. The new space allows a direct comparison between the distinct bounds and the capacity coefficient values and helps explicate the relationships among the different measures. An analogous common space is proposed for the AND paradigm, relating the capacity index to the Colonius–Vorberg bounds. We illustrate the effectiveness of the unified spaces by presenting data from two simulated models (standard parallel, coactive) and a prototypical visual detection experiment. A conversion table for the unified spaces is provided.