A bottleneck in face identification: repetition priming from flanker images

There is evidence that face processing is capacity-limited in distractor interference tasks and in tasks requiring overt recognition memory. We examined whether capacity limits for faces can be observed with a more sensitive measure of visual processing, by measuring repetition priming of flanker faces that were presented alongside a face or a nonface target. In Experiment 1, we found identity priming for face flankers, by measuring repetition priming across a change in image, during task-relevant nonface processing, but not during the processing of a concurrently-presented face target. Experiment 2 showed perceptual priming of the flanker faces, across identical images at prime and test, when they were presented alongside a face target. In a third Experiment, all of these effects were replicated by measuring identity priming and perceptual priming within the same task. Overall, these results imply that face processing is capacity limited, such that only a single face can be identified at one time. Merely attending to a target face appears sufficient to trigger these capacity limits, thereby extinguishing identification of a second face in the display, although our results demonstrate that the additional face remains at least subject to superficial image processing.     

Automated analysis of the WISC-R: A validation study

This study evaluated and automated analysis system for the WISC-R Reports generated by psychological examiners and by a comoputer program were rated by a random sample of National Association of School Psychologists menbers using a rating scale developed for this study. The results indicated significantly higher ratings for the automated analysis on an overall item and on items addressing Verbal-Performance discrepancies, relative weaknesses, and relative lack of irresponsible interpretation. These results support cautious use of the automated reports and validation in current practice.     

Biased lineup instructions and face identification from video images

Previous eyewitness memory research has shown that biased lineup instructions reduce identification accuracy, primarily by increasing false-positive identifications in target-absent lineups. Because some attempts at identification do not rely on a witness's memory of the perpetrator but instead involve matching photos to images on surveillance video, the authors investigated the effects of biased instructions on identification accuracy in a matching task. In Experiment 1, biased instructions did not affect the overall accuracy of participants who used video images as an identification aid, but nearly all correct decisions occurred with target-present photo spreads. Both biased and unbiased instructions resulted in high false-positive rates. In Experiment 2, which focused on video-photo matching accuracy with target-absent photo spreads, unbiased instructions led to more correct responses (i.e., fewer false positives). These findings suggest that investigators should not relax precautions against biased instructions when people attempt to match photos to an unfamiliar person recorded on video.     

Haptic perception: A tutorial

This tutorial focuses on the sense of touch within the context of a fully active human observer. It is intended for graduate students and researchers outside the discipline who seek an introduction to the rapidly evolving field of human haptics. The tutorial begins with a review of peripheral sensory receptors in skin, muscles, tendons, and joints. We then describe an extensive body of research on “what” and “where” channels, the former dealing with haptic perception of objects, surfaces, and their properties, and the latter with perception of spatial layout on the skin and in external space relative to the perceiver. We conclude with a brief discussion of other significant issues in the field, including vision-touch interactions, affective touch, neural plasticity, and applications.     

An X Windows tool for synthesizing face images from eigenvectors

An X Windows software tool for the construction of faces with a weighted combination of eigenvectors is described. The eigenvectors were extracted from an autoassociative matrix that comprised 100 face images. The program input consists of eigenvectors and sets of weights that describe individual faces and combines these to create face images. The tool creates a panel of buttons that permits the display of individual eigenvectors and the display of an average face as well. Facilities for on-line changes to the intensity of individual eigenvectors can be used to change the appearance of a face. Previously, O’Toole, Abdi, Deffenbacher, and Bartlett (1991) have shown that the intensity of certain individual eigenvectors contains reliable information for determining the sex and race of the face.     

Crossmodal correspondences: A tutorial review

In many everyday situations, our senses are bombarded by many different unisensory signals at any given time. To gain the most veridical, and least variable, estimate of environmental stimuli/properties, we need to combine the individual noisy unisensory perceptual estimates that refer to the same object, while keeping those estimates belonging to different objects or events separate. How, though, does the brain “know” which stimuli to combine? Traditionally, researchers interested in the crossmodal binding problem have focused on the roles that spatial and temporal factors play in modulating multisensory integration. However, crossmodal correspondences between various unisensory features (such as between auditory pitch and visual size) may provide yet another important means of constraining the crossmodal binding problem. A large body of research now shows that people exhibit consistent crossmodal correspondences between many stimulus features in different sensory modalities. For example, people consistently match high-pitched sounds with small, bright objects that are located high up in space. The literature reviewed here supports the view that crossmodal correspondences need to be considered alongside semantic and spatiotemporal congruency, among the key constraints that help our brains solve the crossmodal binding problem.     

Connectionist models of conditioning: A tutorial

Models containing networks of neuron-like units have become increasingly prominent in the study of both cognitive psychology and artificial intelligence. This article describes the basic features of connectionist models and provides an illustrative application to compound-stimulus effects in respondent conditioning. Connectionist models designed specifically for operant conditioning are not yet widely available, but some current learning algorithms for machine learning indicate that such models are feasible. Conversely, designers for machine learning appear to have recognized the value of behavioral principles in producing adaptive behavior in their creations.     

Resilience characterized and quantified from physical activity data: A tutorial in R

Consistent physical activity is key for health and well-being, but it is vulnerable to stressors. The process of recovering from such stressors and bouncing back to the previous state of physical activity can be referred to as resilience. Quantifying resilience is fundamental to assess and manage the impact of stressors on consistent physical activity. In this tutorial, we present a method to quantify the resilience process from physical activity data. We leverage the prior operationalization of resilience, as used in various psychological domains, as area under the curve and expand it to suit the characteristics of physical activity time series. As use case to illustrate the methodology, we quantified resilience in step count time series (length = 366 observations) for eight participants following the first COVID-19 lockdown as a stressor. Steps were assessed daily using wrist-worn devices. The methodology is implemented in R and all coding details are included. For each person’s time series, we fitted multiple growth models and identified the best one using the Root Mean Squared Error (RMSE). Then, we used the predicted values from the selected model to identify the point in time when the participant recovered from the stressor and quantified the resulting area under the curve as a measure of resilience for step count. Further resilience features were extracted to capture the different aspects of the process. By developing a methodological guide with a step-by-step implementation, we aimed at fostering increased awareness about the concept of resilience for physical activity and facilitate the implementation of related research.     

Perception of intersensory synchrony: A tutorial review

For most multisensory events, observers perceive synchrony among the various senses (vision, audition, touch), despite the naturally occurring lags in arrival and processing times of the different information streams. A substantial amount of research has examined how the brain accomplishes this. In the present article, we review several key issues about intersensory timing, and we identify four mechanisms of how intersensory lags might be dealt with: by ignoring lags up to some point (a wide window of temporal integration), by compensating for predictable variability, by adjusting the point of perceived synchrony on the longer term, and by shifting one stream directly toward the other.     

Fast face detection using a unified architecture for unconstrained and infrared face images

Human face detection along with its localization is a difficult task when the face is presented in the cluttered scene in an unconstrained scenario that might be with arbitrary pose variations, occlusions, random backgrounds and infrared (IR) environment. This paper proposes a novel face detection method which can address some of these issues and challenges quite successfully during face detection in unconstrained as well as infrared environments. It makes use of Fast Successive Mean Quantization Transform (FastSMQT) features for image enhancement and feature representation to deal with illumination and sensor insensitiveness. A split up Sparse Network of Winnows (SNoW) with Winnow updating rule is then exploited to speed up the original SNoW classifier. Finally, the features and classifiers are combined together with skin detection algorithm for face detection in crowd image and head orientation correction of near infrared faces. The proposed face detector is robust in handling pose, occlusion, illumination, blur and low image resolution. The experiment is performed on six challenging and publicly available databases, viz. BIOID, LFW, FDDB, UFI, WIDER FACE and IIT Delhi near infrared. The experimental results depict that the proposed method outperforms traditional as well as some advanced methods in detecting unconstrained and infrared faces under challenging situations.     

A tutorial explaining a machine vision model that emulates human performance when it recovers natural 3D scenes from 2D images

This tutorial has two purposes: (i) it provides an example of a computational model that emulates what human beings see in natural environments, and (ii) it explains why, as well as how, each computation can be done.     

Estimating psychological networks and their accuracy: A tutorial paper

The usage of psychological networks that conceptualize behavior as a complex interplay of psychological and other components has gained increasing popularity in various research fields. While prior publications have tackled the topics of estimating and interpreting such networks, little work has been conducted to check how accurate (i.e., prone to sampling variation) networks are estimated, and how stable (i.e., interpretation remains similar with less observations) inferences from the network structure (such as centrality indices) are. In this tutorial paper, we aim to introduce the reader to this field and tackle the problem of accuracy under sampling variation. We first introduce the current state-of-the-art of network estimation. Second, we provide a rationale why researchers should investigate the accuracy of psychological networks. Third, we describe how bootstrap routines can be used to (A) assess the accuracy of estimated network connections, (B) investigate the stability of centrality indices, and (C) test whether network connections and centrality estimates for different variables differ from each other. We introduce two novel statistical methods: for (B) the correlation stability coefficient, and for (C) the bootstrapped difference test for edge-weights and centrality indices. We conducted and present simulation studies to assess the performance of both methods. Finally, we developed the free R-package bootnet that allows for estimating psychological networks in a generalized framework in addition to the proposed bootstrap methods. We showcase bootnet in a tutorial, accompanied by R syntax, in which we analyze a dataset of 359 women with posttraumatic stress disorder available online.     

Intersensory binding across space and time: A tutorial review

Spatial ventriloquism refers to the phenomenon that a visual stimulus such as a flash can attract the perceived location of a spatially discordant but temporally synchronous sound. An analogous example of mutual attraction between audition and vision has been found in the temporal domain, where temporal aspects of a visual event, such as its onset, frequency, or duration, can be biased by a slightly asynchronous sound. In this review, we examine various manifestations of spatial and temporal attraction between the senses (both direct effects and aftereffects), and we discuss important constraints on the occurrence of these effects. Factors that potentially modulate ventriloquism—such as attention, synesthetic correspondence, and other cognitive factors—are described. We trace theories and models of spatial and temporal ventriloquism, from the traditional unity assumption and modality appropriateness hypothesis to more recent Bayesian and neural network approaches. Finally, we summarize recent evidence probing the underlying neural mechanisms of spatial and temporal ventriloquism.     

Visual stimuli on the Commodore Amiga: A tutorial

The Commodore Amiga home microcomputer, together withDeLuxePaint, a commercial software package, can generate many useful visual stimuli, including random-dot stereograms, apparent motion, texture edges, aftereffects from dimming and brightening, motion aftereffects, dynamic random noise, and drifting and counterphase gratings. Videotapes can readily be made of these displays. No programming experience is necessary.     

Drawing conclusions from choice response time models: A tutorial using the linear ballistic accumulator

Cognitive models of choice and response times can lead to deeper insights into the processes underlying decisions than standard analyses of accuracy and response time data. The application of these models, however, has historically been reserved for the authors of the models, and their associates. Recently, choice response time models have become more accessible through the release of user-friendly software for estimating their parameters. The aim of this tutorial is to provide guidance about the process of using these parameter estimates and associated model fits to make conclusions about experimental data. We use an application of one response time model, the linear ballistic accumulator, as an example to demonstrate the steps required to select an appropriate parametric characterization of a data set. We also discuss how to evaluate the quality of the agreement between model and data, including guidelines for presenting model predictions for group-level data.     

Consciousness of Social Face: the development and validation of a scale measuring desire to gain face versus fear of losing face

This article describes the development and validation of a scale that measures two distinct needs for individuals to manage their social "face". Scale development process resulted in an 11-item Consciousness of Social Face (CSF) scale made up of the following two correlated dimensions: desire to gain face and fear of losing face. The two-factor correlated structure of CSF scale was stable across multiple samples of both students and non-students subjects. The construct validity of CSF scale, including convergent validity, discriminant validity, and criterion-related validity was also demonstrated by examining relationships with other personality or demographical variables.