Springer Science and Business Media LLC

A method of transforming a vertical rack and pinion-type electrode slide into a miniature drill press is described. Advantages of the instrument are noted and several applications suggested. Specifications are included for the aluminum electrode mold for cat cortical electrode casts.

Over the last 40 years, object recognition studies have moved from using simple line drawings, to more detailed illustrations, to more ecologically valid photographic representations. Researchers now have access to various stimuli sets, however, existing sets lack the ability to independently manipulate item format, as the concepts depicted are unique to the set they derive from. To enable such comparisons, Rossion and Pourtois (2004) revisited Snodgrass and Vanderwart’s (1980) line drawings and digitally re-drew the objects, adding texture and shading. In the current study, we took this further and created a set of stimuli that showcase the same objects in photographic form. We selected six photographs of each object (three color/three grayscale) and collected normative data and RTs. Naming accuracy and agreement was high for all photographs and appeared to steadily increase with format distinctiveness. In contrast to previous data patterns for drawings, naming agreement (H values) did not differ between grey and color photographs, nor did familiarity ratings. However, grey photographs received significantly lower mental imagery agreement and visual complexity scores than color photographs. This suggests that, in comparison to drawings, the ecological nature of photographs may facilitate deeper critical evaluation of whether they offer a good match to a mental representation. Color may therefore play a more vital role in photographs than in drawings, aiding participants in judging the match with their mental representation. This new photographic stimulus set and corresponding normative data provide valuable materials for a wide range of experimental studies of object recognition.

The present article introduces the multivariate Elo-type algorithm (META), which is inspired by the Elo rating system, a tool for the measurement of the performance of chess players. The META is intended for adaptive experiments with correlated traits. The relationship of the META to other existing procedures is explained, and useful variants and modifications are discussed. The META was investigated within three simulation studies. The gain in efficiency of the univariate Elo-type algorithm was compared to standard univariate procedures; the impact of using correlational information in the META was quantified; and the adaptability to learning and fatigue was investigated. Our results show that the META is a powerful tool to efficiently control task performance in a short time period and to assess correlated traits. The R code of the simulations, the implementation of the META in MATLAB, and an example of how to use the META in the context of neuroscience are provided in supplemental materials.

One of the recent major advances in cognitive psychology research has been the option of web-based in addition to lab-based experimental research. This option fosters experimental research by increasing the pace and size of collecting data sets. Importantly, web-based research profits heavily from integrating tasks that are frequently applied in cognitive psychology into open access software. For instance, an open access random-dot kinematogram (RDK) plugin has recently been integrated into the jsPsych software for web-based research. This plugin allows researchers to implement experimental tasks with varying coherence levels (with that varying task difficulty) of moving dots or varying signal to noise ratios of colored dots. Here, we introduce the random-object kinematogram (ROK) plugin for the jsPsych software which, among other new features, enables researchers to include oriented objects (e.g., triangles or arrows) instead of dots as stimuli. This permits experiments with feature congruency (e.g., upwards-moving triangles pointing upwards) or incongruency (e.g., upwards-moving triangles pointing downwards), allowing to induce gradual degrees of stimulus interference, in addition to gradual degrees of task difficulty. We elaborate on possible set-ups with this plugin in two experiments examining participants’ RTs and error rates on different combinations of coherence and congruency levels. Results showed increased RTs and error rates on trials with lower coherence percentages, and on trials with lower congruency levels. We discuss other new features of the ROK plugin and conclude that the possibility of gradually varying the coherence level and congruency level independently from each other offers novel possibilities when conducting web-based experiments.

Eye-trackers are a popular tool for studying cognitive, emotional, and attentional processes in different populations (e.g., clinical and typically developing) and participants of all ages, ranging from infants to the elderly. This broad range of processes and populations implies that there are many inter- and intra-individual differences that need to be taken into account when analyzing eye-tracking data. Standard parsing algorithms supplied by the eye-tracker manufacturers are typically optimized for adults and do not account for these individual differences. This paper presents gazepath, an easy-to-use R-package that comes with a graphical user interface (GUI) implemented in Shiny (RStudio Inc 2015). The gazepath R-package combines solutions from the adult and infant literature to provide an eye-tracking parsing method that accounts for individual differences and differences in data quality. We illustrate the usefulness of gazepath with three examples of different data sets. The first example shows how gazepath performs on free-viewing data of infants and adults, compared to standard EyeLink parsing. We show that gazepath controls for spurious correlations between fixation durations and data quality in infant data. The second example shows that gazepath performs well in high-quality reading data of adults. The third and last example shows that gazepath can also be used on noisy infant data collected with a Tobii eye-tracker and low (60 Hz) sampling rate.

Expert review sessions are often conducted to determine the content validity of scale items. The accurate quantification of content validity is usually limited by a relatively small number of experts as well as by a small number of rating categories. These factors, combined with the bounded and discrete nature of rating scale categories, hinder use of traditional methods for computing standard errors and confidence intervals. Using an application of the score method, researchers can construct an asymmetric interval that is better suited for these situations. SAS code is provided to automate the computations, and a discussion of two methods for using the obtained results for content validation decisionmaking follows.

In social sciences, the study of group differences concerning latent constructs is ubiquitous. These constructs are generally measured by means of scales composed of ordinal items. In order to compare these constructs across groups, one crucial requirement is that they are measured equivalently or, in technical jargon, that measurement invariance (MI) holds across the groups. This study compared the performance of scale- and item-level approaches based on multiple group categorical confirmatory factor analysis (MG-CCFA) and multiple group item response theory (MG-IRT) in testing MI with ordinal data. In general, the results of the simulation studies showed that MG-CCFA-based approaches outperformed MG-IRT-based approaches when testing MI at the scale level, whereas, at the item level, the best performing approach depends on the tested parameter (i.e., loadings or thresholds). That is, when testing loadings equivalence, the likelihood ratio test provided the best trade-off between true-positive rate and false-positive rate, whereas, when testing thresholds equivalence, the χ2 test outperformed the other testing strategies. In addition, the performance of MG-CCFA’s fit measures, such as RMSEA and CFI, seemed to depend largely on the length of the scale, especially when MI was tested at the item level. General caution is recommended when using these measures, especially when MI is tested for each item individually.