Generating complex three-dimensional stimuli (Greebles) for haptic expertise training

An apparatus is described that accurately measures response times and video records hand movements during haptic object recognition using complex three-dimensional (3-D) forms. The apparatus was used for training participants to become expert at perceptual judgments of 3-D objects (Greebles) using only their sense of touch. Inspiration came from previous visual experiments, and therefore training and testing protocols that were similar to the earlier visual procedures were used. Two sets of Greebles were created. One set (clay Greebles) was hand crafted from clay, and the other (plastic Greebles) was machine created using rapid prototyping technology. Differences between these object creation techniques and their impact on perceptual expertise training are discussed. The full set of these stimuli may be downloaded from www.psychonomic.org/archive/.     

Generating possibilities

Our knowledge of the most basic alternative possibilities can be thought of as generated recursively from what we know about the actual world. But what are the generating principles? According to one view, they are recombinational: roughly, alternative possibilities are generated by “patching together” parts of distinct worlds or “blotting out” parts of worlds to yield new worlds. I argue that this view is inadequate. It is difficult to state in a way that is true and non-trivial, and anyway fails to account for our knowledge that there might have been other things, properties, relations, and combinations of these than there actually are. I sketch and defend an alternative view based on the distinction between determinable and determinate properties: roughly, alternative possibilities are generated by “intra-determinable” variation, variation from one determinate to another of the same determinable.     

Generating probable consequences

A study was conducted to examine some of the factors that influence peoples' generation of likely consequences associated with a major hypothetical life event, involving the loss of the function of one of one's own limbs. The design included four limbs involving two inclusion relations, thumb-hand and foot-leg, and two viewpoints involving consequences for one-self or for others. The results indicated that subjects generate more numerous consequences for primary than for secondary consequences, more for short-term consequences than for medium- or long-term ones, more for an inclusive limb than for an included limb (e.g., hand vs thumb), and more pertaining to one-self than to others. Individual differences in the generation of consequences were not associated with prior experience involving functional loss of the limbs tested or with general differences in academic performance. The results permit inference about some of the mental processes that accompany consequence generation.     

Generating and remembering passwords

A survey evaluating the generation and use of passwords revealed that students have 8.18 password uses. With 4.45 different passwords to cover these functions, the average password has 1.84 applications. Two thirds of passwords are designed around one's personal characteristics, with most of the remainder relating to relatives, friends or lovers. Proper names and birthdays are the primary information used in constructing passwords, accounting for about half of all password constructions. Almost all respondents reuse passwords, and about two thirds of password uses are duplications. Passwords have been forgotten by a third of respondents, and over half keep a written record of them. We found empirical confirmation of some ‘bad password practices’ discussed in the literature, and provide suggestions for password construction and use. Copyright © 2004 John Wiley & Sons, Ltd.     

Generating nonsymbolic number stimuli

Studies investigating nonsymbolic numbers (e.g., dot arrays) are confronted with the problem that changes in numerosity are always accompanied by changes in the visual properties of the stimulus. It is therefore debated whether the visual properties of the stimulus rather than number can explain the results obtained in studies investigating nonsymbolic number processing. In this report, we present a program (available at ; note that the program is designed to work with the Psychophysics Toolbox in MATLAB) that exports information about the visual properties of stimuli that co-vary with number (area extended, item size, total surface, density, and circumference). Consequently, insight into the relation between the visual properties of the stimulus and numerical distance can be achieved, and post hoc analyses can be conducted to directly reveal whether numerical distance or (some combinations of) the visual properties of a stimulus could be the most likely candidate underlying the results. Here, we report data that demonstrate the program’s usefulness for research on nonsymbolic number stimuli.     

Wavelet analysis of neuroelectric waveforms: a conceptual tutorial

This paper presents a nontechnical, conceptually oriented introduction to wavelet analysis and its application to neuroelectric waveforms such as the EEG and event related potentials (ERP). Wavelet analysis refers to a growing class of signal processing techniques and transforms that use wavelets and wavelet packets to decompose and manipulate time-varying, nonstationary signals. Neuroelectric waveforms fall into this category of signals because they typically have frequency content that varies as a function of time and recording site. Wavelet techniques can optimize the analysis of such signals by providing excellent joint time-frequency resolution. The ability of wavelet analysis to accurately resolve neuroelectric waveforms into specific time and frequency components leads to several analysis applications. Some of these applications are time-varying filtering for denoising single trial ERPs, EEG spike and spindle detection, ERP component separation and measurement, hearing-threshold estimation via auditory brainstem evoked response measurements, isolation of specific EEG and ERP rhythms, scale-specific topographic analysis, and dense-sensor array data compression. The present tutorial describes the basic concepts of wavelet analysis that underlie these and other applications. In addition, the application of a recently developed method of custom designing Meyer wavelets to match the waveshapes of particular neuroelectric waveforms is illustrated. Matched wavelets are physiologically sensible pattern analyzers for EEG and ERP waveforms and their superior performance is illustrated with real data examples.     

Finger-pressure waveforms measured on Clynes' Sentograph distinguish among emotions

We examined the transient finger-pressure when subjects were exposed to the schematic faces which depict "anger," "joy," "sadness," and "no emotion," and to two nonfacial stimuli. In Exp. 1, nine undergraduate women were asked to discriminate between those target stimuli and the nontarget stimuli by pressing on the finger rest of Clynes' Sentograph, without informing subjects that this experiment was to measure emotions. In Exp. 2, the same subjects were asked to express their feelings evoked by the schematic faces by pressing on the finger rest. Results indicate that, even on the discrimination task, the differentiation in the finger-pressure waveforms among emotions was observed. Such differentiation suggests the possibility of measuring the expression of emotions with finger pressure even when the subjects are not aware their emotions are being measured. The identifiable characteristics of the waveforms are the long duration for "sadness" and the strong intensity of pressure for "anger."     

Generating initial models for reasoning

Much of the knowledge that children and adults have about the world resides in intuitive models. Previous work shows that intuitive models allow for computation of specific outcomes given information about the system, but little is known about how such models are acquired. The current study tested three hypotheses about how children and adults construct intuitive models when they encounter a new property: (1) intuitive models are constructed by transferring principles from familiar properties; (2) with development, children shift from applying a default model to constructing specialized models; and (3) younger children's model construction is constrained by the domain, but becomes increasingly domain independent with development. Participants from three age groups (10, 13, and 19 years) made a series of judgments about two familiar properties and one novel property. Causal models showed that all age groups transferred principles from the familiar properties to the novel property. None of the age groups used a default model. There was developmental change in the effect of domain; younger, but not older, children's models were affected by domain. These findings suggest that the transfer process is developmentally invariant but that constraints on the process (i.e., domain dependence and understanding of base models) change with development.     

Generating explanations via analogical comparison

Generating explanations can be highly effective in promoting learning in both adults and children. Our interest is in the mechanisms that underlie this effect and in whether and how they operate in early learning. In adult reasoning, explanation may call on many subprocesses—including comparison, counterfactual reasoning, and reasoning by exclusion; but it is unlikely that all these processes are available to young children. We propose that one process that may serve both children and adults is comparison. In this study, we asked whether children would use the results of a comparison experience when asked to explain why a model skyscraper was stable. We focused on a challenging principle—that diagonal cross-bracing lends stability to physical structures (Gentner et al., Cognitive Science, 40, 224–240, 2016). Six-year-olds either received no training or interacted with model skyscrapers in one of three different conditions, designed to vary in their potential to invite and support comparison. In the Single Model condition, children interacted with a single braced model. In the comparison conditions (Low Alignability and High Alignability), children compared braced and unbraced models. Following experience with the models, children were asked to explain why the braced model was stable. They then received two transfer tasks. We found that children who received highly alignable pairs were most likely to (a) produce brace-based explanations and (b) transfer the brace principle to a dissimilar context. This provides evidence that children can benefit from analogical comparison in generating explanations and also suggests limitations on this ability.     

Generating Facial Expressions for Speech

This article reports results from a program that produces high-quality animation of facial expressions and head movements as automatically as possible in conjunction with meaning-based speech synthesis, including spoken intonation. The goal of the research is as much to test and define our theories of the formal semantics for such gestures, as to produce convincing animation. Towards this end, we have produced a high-level programming language for three-dimensional (3-D) animation of facial expressions. We have been concerned primarily with expressions conveying information correlated with the intonation of the voice: This includes the differences of timing, pitch, and emphasis that are related to such semantic distinctions of discourse as “focus,”“topic,” and “comment,”“theme” and “rheme,” or “given” and “new” information. We are also interested in the relation of affect or emotion to facial expression. Until now, systems have not embodied such rule-governed translation from spoken utterance meaning to facial expressions. Our system embodies rules that describe and coordinate these relations: intonation/information, intonation/affect, and facial expressions/affect. A meaning representation includes discourse information: What is contrastive/background information in the given context, and what is the “topic” or “theme” of the discourse? The system maps the meaning representation into how accents and their placement are chosen, how they are conveyed over facial expression, and how speech and facial expressions are coordinated. This determines a sequence of functional groups: lip shapes, conversational signals, punctuators, regulators, and manipulators. Our algorithms then impose synchrony, create coarticulation effects, and determine affectual signals, eye and head movements. The lowest level representation is the Facial Action Coding System (FACS), which makes the generation system portable to other facial models.     

Generating variables with arbitrary properties

There are occasions in psychological research where it is desirable to have available sets of variables with arbitrary intercorrelations. A quite simple procedure is described for generating pairs of such variables.     

Generating Multivariate Ordinal Data via Entropy Principles

When conducting robustness research where the focus of attention is on the impact of non-normality, the marginal skewness and kurtosis are often used to set the degree of non-normality. Monte Carlo methods are commonly applied to conduct this type of research by simulating data from distributions with skewness and kurtosis constrained to pre-specified values. Although several procedures have been proposed to simulate data from distributions with these constraints, no corresponding procedures have been applied for discrete distributions. In this paper, we present two procedures based on the principles of maximum entropy and minimum cross-entropy to estimate the multivariate observed ordinal distributions with constraints on skewness and kurtosis. For these procedures, the correlation matrix of the observed variables is not specified but depends on the relationships between the latent response variables. With the estimated distributions, researchers can study robustness not only focusing on the levels of non-normality but also on the variations in the distribution shapes. A simulation study demonstrates that these procedures yield excellent agreement between specified parameters and those of estimated distributions. A robustness study concerning the effect of distribution shape in the context of confirmatory factor analysis shows that shape can affect the robust \(\chi ^2\) and robust fit indices, especially when the sample size is small, the data are severely non-normal, and the fitted model is complex.     

Generating interior search directions for multiobjective linear programming

A new multiobjective linear programming (MOLP) algorithm is presented. The algorithm uses a variant of Karmarkar's interior-point algorithm known as the affine-scaling primal algorithm. Using this single-objective algorithm, interior search directions are generated and used to provide an approximation to the gradient of the (implicitly known) utility function. The approximation is guided by assessing locally relevant preference information for the various interior directions through interaction with a decision maker (DM). The resulting algorithm is an interactive approach that makes its progress towards the solution through the interior of the constraints polytope.     

Generating Relations Elicits a Relational Mindset in Children

Relational reasoning is a hallmark of human higher cognition and creativity, yet it is notoriously difficult to encourage in abstract tasks, even in adults. Generally, young children initially focus more on objects, but with age become more focused on relations. While prerequisite knowledge and cognitive resource maturation partially explains this pattern, here we propose a new facet important for children's relational reasoning development: a general orientation to relational information, or a relational mindset. We demonstrate that a relational mindset can be elicited, even in 4‐year‐old children, yielding greater than expected spontaneous attention to relations. Children either generated or listened to an experimenter state the relationships between objects in a set of formal analogy problems, and then in a second task, selected object or relational matches according to their preference. Children tended to make object mappings, but those who generated relations on the first task selected relational matches more often on the second task, signaling that relational attention is malleable even in young children.