The effect of propensity to trust and perceptions of trustworthiness on trust behaviors in dyads.

Research on trust has burgeoned in the last few decades. Despite the growing interest in trust, little is known about trusting behaviors in non-dichotomous trust games. The current study explored propensity to trust, trustworthiness, and trust behaviors in a new computer-mediated trust relevant task.

Day-to-day variability in hybrid, passive brain-computer interfaces: comparing two studies assessing cognitive workload.

As hybrid, passive brain-computer interface systems become more advanced, it is important to grow our understanding of how to produce generalizable pattern classifiers of physiological data. One of the most difficult problems in applying machine learning algorithms to these data types is nonstationarity, which can evolve over the course of hours and days, and is more susceptible to changes resulting from complex cognitive function in comparison to simple, stimulus-based processes. This nonstationarity, referenced as day-to-day variability, results in the inability of many learning algorithms to generalize to new data.

Electrode replacement does not affect classification accuracy in dual-session use of a passive brain-computer interface for assessing cognitive workload.

The passive brain-computer interface (pBCI) framework has been shown to be a very promising construct for assessing cognitive and affective state in both individuals and teams. There is a growing body of work that focuses on solving the challenges of transitioning pBCI systems from the research laboratory environment to practical, everyday use. An interesting issue is what impact methodological variability may have on the ability to reliably identify (neuro)physiological patterns that are useful for state assessment.

Lack of association between human plasma oxytocin and interpersonal trust in a Prisoner's Dilemma paradigm.

Expanding interest in oxytocin, particularly the role of endogenous oxytocin in human social behavior, has created a pressing need for replication of results and verification of assay methods. In this study, we sought to replicate and extend previous results correlating plasma oxytocin with trust and trustworthy behavior. As a necessary first step, the two most commonly used commercial assays were compared in human plasma via the addition of a known quantity of exogenous oxytocin, with and without sample extraction.

Coadaptive aiding and automation enhance operator performance.

Objective: In this work, we expand on the theory of adaptive aiding by measuring the effectiveness of coadaptive aiding, wherein we explicitly allow for both system and user to adapt to each other.

Background: Adaptive aiding driven by psychophysiological monitoring has been demonstrated to be a highly effective means of controlling task allocation and system functioning. Psychophysiological monitoring is uniquely well suited for coadaptation, as malleable brain activity may be used as a continuous input to the adaptive system.

Reallocating attention during multiple object tracking.

Wolfe, Place, and Horowitz (Psychonomic Bulletin & Review 14:344-349, 2007) found that participants were relatively unaffected by selecting and deselecting targets while performing a multiple object tracking task, such that maintaining tracking was possible for longer durations than the few seconds typically studied. Though this result was generally consistent with other findings on tracking duration (Franconeri, Jonathon, & Scimeca Psychological Science 21:920-925, 2010), it was inconsistent with research involving cuing paradigms, specifically precues (Pylyshyn & Annan Spatial Vision 19:485-504, 2006). In the present research, we broke down the addition and removal of targets into separate conditions and incorporated a simple performance model to evaluate the costs associated with the selection and deselection of moving targets.

An assessment of non-stationarity in physiological cognitive state assessment using artificial neural networks.

With increased attention toward physiological cognitive state assessment as a component in the larger field of applied neuroscience, the need to develop methods for robust, stable assessment of cognitive state has been expressed as critical to designing effective augmented human-machine systems. The technique of cognitive state assessment, as well as its benefits, has been demonstrated by many research groups. In an effort to move closer toward a realized system, efforts must now be focused on critical issues that remain unsolved, namely instability of pattern classifiers over the course of hours and days.

Physiological cognitive state assessment: applications for designing effective human-machine systems.

Significant growth in the field of neuroscience has occurred over the last decade such that new application areas for basic research techniques are opening up to practitioners in many other areas. Of particular interest to many is the principle of neuroergonomics, by which the traditional work in neuroscience and its related topics can be applied to non-traditional areas such as human-machine system design. While work in neuroergonomics certainly predates the use of the term in the literature (previously identified by others as applied neuroscience, operational neuroscience, etc.

Smile esthetics from patients' perspectives for faces of varying attractiveness.

Introduction: Delivering an attractive smile is a key element in orthodontic patient satisfaction. Smile characteristics can be affected by the facial context. The purpose of this study was to investigate smile esthetics related to facial attractiveness and sex of the model.

The effects of day-to-day variability of physiological data on operator functional state classification.

The application of pattern classification techniques to physiological data has undergone rapid expansion. Tasks as varied as the diagnosis of disease from magnetic resonance images, brain-computer interfaces for the disabled, and the decoding of brain functioning based on electrical activity have been accomplished quite successfully with pattern classification. These classifiers have been further applied in complex cognitive tasks to improve performance, in one example as an input to adaptive automation.

Smile esthetics from the layperson's perspective.

Introduction: Computer-based smile esthetic surveys based on slider technology allow more precise control of variables and the possibility of obtaining continuous data. Variations in the perception of smiles from different facial perspectives have not been resolved. The objective of this study was to quantify the ideal and the range of acceptable values for smile variables judged by laypersons from a full-face perspective for comparison with lower-face data.

Orthodontic appliance preferences of children and adolescents.

Introduction: Although attractiveness and acceptability of orthodontic appliances have been rated by adults for themselves and for adolescents, children and adolescents have not provided any substantial data. The objective of this study was to evaluate preferences and acceptability of orthodontic appliances in children and adolescents.

Methods: Images of orthodontic appliances previously captured and standardized were selected and incorporated into a computer-based survey.

Are discrimination thresholds a valid measure of variance for judgments of slant from texture?

There have been many experiments reported in the literature that have employed discrimination procedures to estimate the variance of observers' slant judgments from texture and binocular disparity, both individually and in combination. The research described in the present article identifies two serious methodological flaws in these studies. Although discrimination thresholds can be influenced by the variance of observers' slant estimates, they can also be affected by systematic biases in observers' judgments, and the presence of 2D cues that are irrelevant to the perception of slant.

Can low level image differences account for the ability of human observers to discriminate facial identity?

A fundamental difficulty for image- or appearance-based models of face recognition is to distinguish variations in image structure between two different individuals from those that can occur for a given individual due to changes in lighting, facial expression, or pose. The research described in the present article was designed to examine how human observers are able to cope with this problem. In two experiments, observers performed either a match-to-sample task (Experiment 1) or same-different identity judgments (Experiment 2) for photographs of unfamiliar individuals.