Performance of typical and superior face recognizers on a novel interactive face matching procedure

Unfamiliar simultaneous face matching is error prone. Reducing incorrect identification decisions will positively benefit forensic and security contexts. The absence of view-independent information in static images likely contributes to the difficulty of unfamiliar face matching. We tested whether a novel interactive viewing procedure that provides the user with 3D structural information as they rotate a facial image to different orientations would improve face matching accuracy. We tested the performance of ‘typical’ (Experiment 1) and ‘superior’ (Experiment 2) face recognizers, comparing their performance using high-quality (Experiment 3) and pixelated (Experiment 4) Facebook profile images. In each trial, participants responded whether two images featured the same person with one of these images being either a static face, a video providing orientation information, or an interactive image. Taken together, the results show that fluid orientation information and interactivity prompt shifts in criterion and support matching performance. Because typical and superior face recognizers both benefited from the structural information provided by the novel viewing procedures, our results point to qualitatively similar reliance on pictorial encoding in these groups. This also suggests that interactive viewing tools can be valuable in assisting face matching in high-performing practitioner groups.     

Ensemble coding of facial identity is not refined by experience: Evidence from other-race and inverted faces

The ability to recognize identity despite within-person variability in appearance is likely a face-specific skill and shaped by experience. Ensemble coding – the automatic extraction of the average of a stimulus array – has been proposed as a mechanism underlying face learning (allowing one to recognize novel instances of a newly learned face). We investigated whether ensemble encoding, like face learning and recognition, is refined by experience by testing participants with upright own-race faces and two categories of faces with which they lacked experience: other-race faces (Experiment 1) and inverted faces (Experiment 2). Participants viewed four images of an unfamiliar identity and then were asked whether a test image of that same identity had been in the study array. Each test image was a matching exemplar (from the array), matching average (the average of the images in the array), non-matching exemplar (a novel image of the same identity), or non-matching average (an average of four different images of the same identity). Adults showed comparable ensemble coding for all three categories (i.e., reported that matching averages had been present more than non-matching averages), providing evidence that this early stage of face learning is not shaped by face-specific experience.     

Decisional forgiveness across spanish and american samples: Translation,validation, and measurement invariance of the decision to forgive scale

Current Psychology - More than twenty different models of how forgiveness occurs have been proposed within forgiveness literature. One idea highlighted in many of these models was that forgiveness...     

Understanding fish cognition: a review and appraisal of current practices

Animal Cognition - With over 30,000 recognized species, fishes exhibit an extraordinary variety of morphological, behavioural, and life-history traits. The field of fish cognition has grown...     

“What shall we do with the inebriate?” asylum treatment and the disease concept of alcoholism in the late nineteenth century

During the late nineteenth century a number of physicians, sometimes called inebriety specialists, combined a narrowly physicalistic disease concept of alcoholism with a high regard for the curative power of asylum treatment to advocate the development of specialized asylums for the treatment of alcoholism. Central to the idea of such an inebriate asylum was the belief that the power to detain the alcoholic was necessary to cure his disease. This article considers why inebriety specialists held this belief as well as why others opposed it. It also describes alternative approaches to alcoholism and the fate of efforts, during this period, to treat the alcoholic by confining him.     

The Role of Children's Neurophysiological Functioning in the Links Between Emotion-Parenting Behaviors and Child Anxiety Symptoms: A Biological Sensitivity to Context Framework

A plethora of data supports links between parenting behaviors and child anxiety, but few studies have examined factors that can contribute to variability in these relations. Adopting a biological sensitivity to context framework, this study explored the role of children's physiological stress reactivity in the links between emotion-parenting and child anxiety symptoms in a group of Chinese families. Sixty-one parent–child dyads (child M_age = 8.21 years, SD = 1.40, range = 6–12 years) participated in an acute stress protocol, from which children's physiological (cortisol and respiratory sinus arrhythmia) responses to a social speech task were recorded. Participants then completed questionnaires assessing parents’ emotion-parenting behaviors and children's anxiety symptoms. Results showed that the relation between supportive emotion-parenting and child anxiety was stronger in the context of greater child RSA suppression to acute stress, such that children higher in RSA suppression exhibited lower anxiety symptoms when supportive emotion-parenting was higher than when it was lower. Thus, these findings supported the biological sensitivity to context model. No significant moderation effect was detected for cortisol reactivity or recovery. Instead, exploratory mediation analyses showed that supportive emotion-parenting was negatively related to child anxiety via greater cortisol recovery. There was also a significant indirect path where unsupportive emotion-parenting was related to blunted cortisol recovery, which in turn was associated with higher child anxiety. The results highlight the importance of coaching parents to respond in supportive ways to children's emotional expressions, particularly in the context of greater child reactivity, to help buffer against childhood anxiety symptoms.     

Timing the “magical number seven”: Presentation rate and regularity affect verbal working memory performance

The informative value of time and temporal structure often remains neglected in cognitive assessments. However, next to information about stimulus identity we can exploit temporal ordering principles, such as regularity, periodicity, or grouping to generate predictions about the timing of future events. Such predictions may improve cognitive performance by optimising adaptation to dynamic stimuli. Here, we investigated the influence of temporal structure on verbal working memory by assessing immediate recall performance for aurally presented digit sequences (forward digit span) as a function of standard (1000 ms stimulus-onset-asynchronies, SOAs), short (700 ms), long (1300 ms) and mixed (700–1300 ms) stimulus timing during the presentation phase. Participant's digit spans were lower for short and mixed SOA presentation relative to standard SOAs. This confirms an impact of temporal structure on the classic “magical number seven,” suggesting that working memory performance can in part be regulated through the systematic application of temporal ordering principles.     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

A Process Model of Causal Reasoning

How do we make causal judgments? Many studies have demonstrated that people are capable causal reasoners, achieving success on tasks from reasoning to categorization to interventions. However, less is known about the mental processes used to achieve such sophisticated judgments. We propose a new process model—the mutation sampler—that models causal judgments as based on a sample of possible states of the causal system generated using the Metropolis–Hastings sampling algorithm. Across a diverse array of tasks and conditions encompassing over 1,700 participants, we found that our model provided a consistently closer fit to participant judgments than standard causal graphical models. In particular, we found that the biases introduced by mutation sampling accounted for people's consistent, predictable errors that the normative model by definition could not. Moreover, using a novel experimental methodology, we found that those biases appeared in the samples that participants explicitly judged to be representative of a causal system. We conclude by advocating sampling methods as plausible process-level accounts of the computations specified by the causal graphical model framework and highlight opportunities for future research to identify not just what reasoners compute when drawing causal inferences, but also how they compute it.