NavWell: A simplified virtual-reality platform for spatial navigation and memory experiments Abstract Being able to navigate, recall important locations, and find the way home are critical skills, essential for survival for both humans and animals. These skills can be examined in the laboratory using the Morris water maze, often considered the gold standard test of animal navigation. In this task, animals are required to locate and recall the location of an escape platform hidden in a pool filled with water. Because animals can not see the platform directly, they must use various landmarks in the environment to escape. With recent advances in technology and virtual reality (VR), many tasks originally used in the animal literature can now be translated for human studies. The virtual water maze task is no exception. However, a number of issues are associated with these mazes, including cost, lack of flexibility, and lack of standardization in terms of experimental designs and procedures. Here we present a virtual water maze system (NavWell) that is readily downloadable and free to use. The system allows for the easy design of experiments and the testing of participants on a desktop computer or fully immersive VR environment. The data from four independent experiments are presented in order to validate the software. From these experiments, a set of procedures for use with a number of well-known memory tests is suggested. This potentially can help with the standardization of navigational research and with navigational testing in the clinic or in an educational environment. Finally, we discuss the limitations of the software and plans for its development and future use.

The Jena Speaker Set (JESS)—A database of voice stimuli from unfamiliar young and old adult speakers Abstract Here we describe the Jena Speaker Set (JESS), a free database for unfamiliar adult voice stimuli, comprising voices from 61 young (18–25 years) and 59 old (60–81 years) female and male speakers uttering various sentences, syllables, read text, semi-spontaneous speech, and vowels. Listeners rated two voice samples (short sentences) per speaker for attractiveness, likeability, two measures of distinctiveness (“deviation”-based [DEV] and “voice in the crowd”-based [VITC]), regional accent, and age. Interrater reliability was high, with Cronbach’s α between .82 and .99. Young voices were generally rated as more attractive than old voices, but particularly so when male listeners judged female voices. Moreover, young female voices were rated as more likeable than both young male and old female voices. Young voices were judged to be less distinctive than old voices according to the DEV measure, with no differences in the VITC measure. In age ratings, listeners almost perfectly discriminated young from old voices; additionally, young female voices were perceived as being younger than young male voices. Correlations between the rating dimensions above demonstrated (among other things) that DEV-based distinctiveness was strongly negatively correlated with rated attractiveness and likeability. By contrast, VITC-based distinctiveness was uncorrelated with rated attractiveness and likeability in young voices, although a moderate negative correlation was observed for old voices. Overall, the present results demonstrate systematic effects of vocal age and gender on impressions based on the voice and inform as to the selection of suitable voice stimuli for further research into voice perception, learning, and memory.

Validation of a matrix reasoning task for mobile devices Abstract Many cognitive tasks have been adapted for tablet-based testing, but tests to assess nonverbal reasoning ability, as measured by matrix-type problems that are suited to repeated testing, have yet to be adapted for and validated on mobile platforms. Drawing on previous research, we developed the University of California Matrix Reasoning Task (UCMRT)—a short, user-friendly measure of abstract problem solving with three alternate forms that works on tablets and other mobile devices and that is targeted at a high-ability population frequently used in the literature (i.e., college students). To test the psychometric properties of UCMRT, a large sample of healthy young adults completed parallel forms of the test, and a subsample also completed Raven’s Advanced Progressive Matrices and a math test; furthermore, we collected college records of academic ability and achievement. These data show that UCMRT is reliable and has adequate convergent and external validity. UCMRT is self-administrable, freely available for researchers, facilitates repeated testing of fluid intelligence, and resolves numerous limitations of existing matrix tests.

The validity of RFID badges measuring face-to-face interactions Abstract Face-to-face interactions are important for a variety of individual behaviors and outcomes. In recent years, a number of human sensor technologies have been proposed to incorporate direct observations in behavioral studies of face-to-face interactions. One of the most promising emerging technologies is the application of active Radio Frequency Identification (RFID) badges. They are increasingly applied in behavioral studies because of their low costs, straightforward applicability, and moderate ethical concerns. However, despite the attention that RFID badges have recently received, there is a lack of systematic tests on how valid RFID badges are in measuring face-to-face interactions. With two studies, we aim to fill this gap. Study 1 (N = 11) compares how data assessed with RFID badges correspond with video data of the same interactions (construct validity) and how this fit can be improved using straightforward data processing strategies. The analyses show that the RFID badges have a sensitivity of 50%, which can be enhanced to 65% when flickering signals with gaps of less than 75 s are interpolated. The specificity is relatively less affected by this interpolation process (before interpolation 97%, after interpolation 94.7%)—resulting in an improved accuracy of the measurement. In Study 2 (N = 73) we show that self-report data of social interactions correspond highly with data gathered with the RFID badges (criterion validity).

Habit2: A stand-alone software solution for presenting stimuli and recording infant looking times in order to study infant development Abstract Many aspects of infant development are assessed using infant looking times to visual and audiovisual stimuli. In this article, we describe a stand-alone software package that allows simultaneous stimulus presentation to infants and recording of their looking times via a keypress by a human observer. The software was developed to run both on 64-bit Intel-based Macs running Mac OS/X 10.10 (Yosemite) or later and on 64-bit Windows 7 and 10. It can present a variety of visual and/or auditory stimuli; is customizable with respect to how trials are initiated, how trial lengths are defined, and the phases of the experiment; and can be used to record looking times online or after the fact, as well as to assess the reliability of coding. The software is freely available at http://habit.ucdavis.edu.

An open-source remote heart rate imaging method with practical apparatus and algorithms Abstract Recent developments in computer science and digital image processing have enabled the extraction of an individual’s heart pulsations from pixel changes in recorded video images of human skin surfaces. This method is termed remote photoplethysmography (rPPG) and can be achieved with consumer-level cameras (e.g., a webcam or mobile camera). The goal of the present publication is two-fold. First, we aim to organize future rPPG software developments in a tractable and nontechnical manner, such that the public gains access to a basic open-source rPPG code, comes to understand its utility, and can follow its most recent progressions. The second goal is to investigate rPPG’s accuracy in detecting heart rates from the skin surfaces of several body parts after physical exercise and under ambient lighting conditions with a consumer-level camera. We report that rPPG is highly accurate when the camera is aimed at facial skin tissue, but that the heart rate recordings from wrist regions are less reliable, and recordings from the calves are unreliable. Facial rPPG remained accurate despite the high heart rates after exercise. The proposed research procedures and the experimental findings provide guidelines for future studies on rPPG.

LADEC: The Large Database of English Compounds Abstract The Large Database of English Compounds (LADEC) consists of over 8,000 English words that can be parsed into two constituents that are free morphemes, making it the largest existing database specifically for use in research on compound words. Both monomorphemic (e.g., wheel) and multimorphemic (e.g., teacher) constituents were used. The items were selected from a range of sources, including CELEX, the English Lexicon Project, the British Lexicon Project, the British National Corpus, and Wordnet, and were hand-coded as compounds (e.g., snowball). Participants rated each compound in terms of how predictable its meaning is from its parts, as well as the extent to which each constituent retains its meaning in the compound. In addition, we obtained linguistic characteristics that might influence compound processing (e.g., frequency, family size, and bigram frequency). To show the usefulness of the database in investigating compound processing, we conducted a number of analyses that showed that compound processing is consistently affected by semantic transparency, as well as by many of the other variables included in LADEC. We also showed that the effects of the variables associated with the two constituents are not symmetric. In short, LADEC provides the opportunity for researchers to investigate a number of questions about compounds that have not been possible to investigate in the past, due to the lack of sufficiently large and robust datasets. In addition to directly allowing researchers to test hypotheses using the information included in LADEC, the database will contribute to future compound research by allowing better stimulus selection and matching.

Evaluating methods for handling missing ordinal data in structural equation modeling Abstract Missing ordinal data are common in studies using structural equation modeling (SEM). Although several methods for dealing with missing ordinal data have been available, these methods often have not been systematically evaluated in SEM. In this study, we used Monte Carlo simulation to evaluate and compare five existing methods, including one direct robust estimation method and four multiple imputation methods, to deal with missing ordinal data. On the basis of the simulation results, we provide practical guidance to researchers in terms of the best way to deal with missing ordinal data in SEM.

Visual and auditory perceptual strength norms for 3,596 French nouns and their relationship with other psycholinguistic variables Abstract Perceptual experience plays a critical role in the conceptual representation of words. Higher levels of semantic variables such as imageability, concreteness, and sensory experience are generally associated with faster and more accurate word processing. Nevertheless, these variables tend to be assessed mostly on the basis of visual experience. This underestimates the potential contributions of other perceptual modalities. Accordingly, recent evidence has stressed the importance of providing modality-specific perceptual strength norms. In the present study, we developed French Canadian norms of visual and auditory perceptual strength (i.e., the modalities that have major impact on word processing) for 3,596 nouns. We then explored the relationship between these newly developed variables and other lexical, orthographic, and semantic variables. Finally, we demonstrated the contributions of visual and auditory perceptual strength ratings to visual word processing beyond those of other semantic variables related to perceptual experience (e.g., concreteness, imageability, and sensory experience ratings). The ratings developed in this study are a meaningful contribution toward the implementation of new studies that will shed further light on the interaction between linguistic, semantic, and perceptual systems.

A short version of the MacArthur–Bates Communicative Development Inventories with high validity Abstract The MacArthur–Bates Communicative Development Inventories (CDIs) are among the most widely used evaluation tools for early language development. CDIs are filled in by the parents or caregivers of young children by indicating which of a prespecified list of words and/or sentences their child understands and/or produces. Despite the success of these instruments, their administration is time-consuming and can be of limited use in clinical settings, multilingual environments, or when parents possess low literacy skills. We present a new method through which an estimation of the full-CDI score can be obtained, by combining parental responses on a limited set of words sampled randomly from the full CDI with vocabulary information extracted from the WordBank database, sampled from age-, gender-, and language-matched participants. Real-data simulations using versions of the CDI-WS for American English, German, and Norwegian as examples revealed the high validity and reliability of the instrument, even for tests having just 25 words, effectively cutting administration time to a couple of minutes. Empirical validations with new German-speaking participants confirmed the robustness of the test.