Adaptive memory: Is the animacy effect on memory due to emotional arousal?

Animate entities are often better remembered than inanimate ones. The proximal mechanisms underlying this animacy effect on recall are unclear. In two experiments, we tested whether the animacy effect is due to emotional arousal. Experiment 1 revealed that translations of the animate words used in the pioneering study of Nairne et al. (Psychological science, 24, 2099–2105, 2013) were perceived as being more arousing than translations of the inanimate words, suggesting that animacy might have been confounded with arousal in previous studies. In Experiment 2, new word lists were created in which the animate and inanimate words were matched on arousal (amongst several other dimensions), and participants were required to reproduce the animate and inanimate words in a free recall task. There was a tendency towards better memory for arousing items, but robust animacy effects were obtained even though animate and inanimate words were matched on arousal. Thus, while arousal may contribute to the animacy effect when it is not carefully controlled for, it cannot explain the memory advantage of animate items.     

Delay knowledge and trial set count modulate use of proactive versus reactive control: A meta-analytic review

The AX-continuous performance task (AX-CPT) and dot pattern expectancy (DPX) are the predominant cognitive paradigms used to assess the relative utilization of proactive versus reactive cognitive control. Experimental parameters vary widely between studies and systematically between different modalities (i.e., fMRI vs. EEG) with unknown consequences for the implementation of control. This meta-analytic review systematically surveyed these bodies of literature (k = 43, 73 data points) to resolve how cue–probe delay knowledge, delay length, and trial set count modulate the preferential use of proactive versus reactive control. In healthy young adults, delay knowledge and increasing trial set count each bias participants toward greater proactive control. Further, the interaction of delay knowledge and trial set count accounts for ~40% of variability in proactive/reactive control performance. As trial count varies reliably between experimental modalities, it is critical to understand how these parameters activate distinct cognitive processes and tap into different neural mechanisms for control. Subgroup analyses revealed important distinctions from our results in healthy young adults. Healthy, slightly older adults (ages 30–45 years) performed more reactively compared to healthy young adults. In addition, participants with schizophrenia showed evidence of more proactive control as trial set count increased. In light of this meta-analytic review, we conclude that delay knowledge and trial set length are important parameters to account for in the assessment of proactive versus reactive control. More broadly, this metaregression provides strong evidence that cognitive control becomes more reactive when timing demands are not known, and that both healthy persons and persons with schizophrenia shift toward proactive control with increasing repetitions of a task set.     

When attention is intact in adults with ADHD

Is covert visuospatial attention—selective processing of information in the absence of eye movements—preserved in adults with attention-deficit/hyperactivity disorder (ADHD)? Previous findings are inconclusive due to inconsistent terminology and suboptimal methodology. To settle this question, we used well-established spatial cueing protocols to investigate the perceptual effects of voluntary and involuntary attention on an orientation discrimination task for a group of adults with ADHD and their neurotypical age-matched and gender-matched controls. In both groups, voluntary attention significantly improved accuracy and decreased reaction times at the relevant location, but impaired accuracy and slowed reaction times at irrelevant locations, relative to a distributed attention condition. Likewise, involuntary attention improved accuracy and speeded responses. Critically, the magnitudes of all these orienting and reorienting attention effects were indistinguishable between groups. Thus, these counterintuitive findings indicate that spatial covert attention remains functionally intact in adults with ADHD.     

The Role of Optimism,Social Constraints,Coping, and Cognitive Processing in Psychosocial Adjustment Among Breast Cancer Survivors

The social-cognitive processing model suggests that a socially constrained environment may impede adjustment to a chronic illness. The present study primarily investigated the mediating psychological pathways through which social constraints on cancer-related disclosure, low optimism, disengagement-oriented coping, and brooding could be associated with low levels of psychosocial adjustment. One hundred twenty-five female breast cancer survivors participated in a cross-sectional study. Path analysis was used to examine the proposed model. Low optimism, increased social constraints, and higher levels of brooding appeared to be risk factors for poor psychosocial adjustment to breast cancer. Disengagement-oriented coping and brooding partially mediated the relationship between social constraints and adjustment. Brooding totally mediated the relationship between disengagement-oriented coping and adjustment. The current findings provide support for the value of the social-cognitive processing model among breast cancer survivors. The mapping of psychological pathways of adjustment to breast cancer may have useful clinical implications for better adjustment outcomes.     

Systems Factorial Technology provides new insights on the other-race effect

The other-race effect refers to the difficulty of discriminating between faces from ethnic and racial groups other than one’s own. This effect may be caused by a slow, feature-by-feature, analytic process, whereas the discrimination of own-race faces occurs faster and more holistically. However, this distinction has received inconsistent support. To provide a critical test, we employed Systems Factorial Technology (Townsend & Nozawa in Journal of Mathematical Psychology, 39, 321–359, 1995), which is a powerful tool for analyzing the organization of mental networks underlying perceptual processes. We compared Taiwanese participants’ face discriminations of both own-race (Taiwanese woman) and other-race (Caucasian woman) faces according to the faces’ nose-to-mouth separation and eye-to-eye separation. We found evidence for weak holistic processing (parallel processing) coupled with the strong analytic property of a self-terminating stopping rule for own-race faces, in contrast to strong analytic processing (serial self-terminating processing) for other-race faces, supporting the holistic/analytic hypothesis.     

ELF: A new measure of response capture

Response capture is a widespread and extensively studied phenomenon, in particular in decision tasks involving response conflict. Its intensity is routinely quantified by conditional accuracy function (CAF). We argue that this method might be misleading, and propose an alternative approach, the error location function (ELF). While CAF provides the error rate by bins of reaction time (RT), ELF represents the share of total errors below each quantile of RT. We derive from ELF an index of response capture, the error location index (ELI), which represents the area below the ELF. Using simulations of computational models, we show that ELF and ELI specifically quantify variations in response capture. Finally, we illustrate the usefulness of ELF and ELI through experimental data and show that ELF and CAF can yield to contradictory conclusions.     

Recognition-induced forgetting does not occur for temporally grouped objects unless they are semantically related

Recent evidence has shown that practice recognizing certain objects hurts memories of objects from the same category, a phenomenon called recognition-induced forgetting. In all previous studies of this effect, the objects have been related by semantic category (e.g., instances of vases). However, the relationship between objects in many real-world visual situations stresses temporal grouping rather than semantic relations (e.g., a weapon and getaway car at a crime scene), and temporal grouping is thought to cluster items in models of long-term memory. The goal of the present study was to determine whether temporally grouped objects suffer recognition-induced forgetting. To this end, we implemented a modified recognition-induced forgetting paradigm in which the objects were temporally clustered at study. Across four experiments, we found that recognition-induced forgetting occurred only when the temporally clustered objects were also semantically related. We conclude by discussing how these findings relate to real-world vision and inform models of memory.     

The anchoring bias reflects rational use of cognitive resources

Cognitive biases, such as the anchoring bias, pose a serious challenge to rational accounts of human cognition. We investigate whether rational theories can meet this challenge by taking into account the mind’s bounded cognitive resources. We asked what reasoning under uncertainty would look like if people made rational use of their finite time and limited cognitive resources. To answer this question, we applied a mathematical theory of bounded rationality to the problem of numerical estimation. Our analysis led to a rational process model that can be interpreted in terms of anchoring-and-adjustment. This model provided a unifying explanation for ten anchoring phenomena including the differential effect of accuracy motivation on the bias towards provided versus self-generated anchors. Our results illustrate the potential of resource-rational analysis to provide formal theories that can unify a wide range of empirical results and reconcile the impressive capacities of the human mind with its apparently irrational cognitive biases.     

Determining informative priors for cognitive models

The development of cognitive models involves the creative scientific formalization of assumptions, based on theory, observation, and other relevant information. In the Bayesian approach to implementing, testing, and using cognitive models, assumptions can influence both the likelihood function of the model, usually corresponding to assumptions about psychological processes, and the prior distribution over model parameters, usually corresponding to assumptions about the psychological variables that influence those processes. The specification of the prior is unique to the Bayesian context, but often raises concerns that lead to the use of vague or non-informative priors in cognitive modeling. Sometimes the concerns stem from philosophical objections, but more often practical difficulties with how priors should be determined are the stumbling block. We survey several sources of information that can help to specify priors for cognitive models, discuss some of the methods by which this information can be formalized in a prior distribution, and identify a number of benefits of including informative priors in cognitive modeling. Our discussion is based on three illustrative cognitive models, involving memory retention, categorization, and decision making.     

Time-varying decision boundaries: insights from optimality analysis

The most widely used account of decision-making proposes that people choose between alternatives by accumulating evidence in favor of each alternative until this evidence reaches a decision boundary. It is frequently assumed that this decision boundary stays constant during a decision, depending on the evidence collected but not on time. Recent experimental and theoretical work has challenged this assumption, showing that constant decision boundaries are, in some circumstances, sub-optimal. We introduce a theoretical model that facilitates identification of the optimal decision boundaries under a wide range of conditions. Time-varying optimal decision boundaries for our model are a result only of uncertainty over the difficulty of each trial and do not require decision deadlines or costs associated with collecting evidence, as assumed by previous authors. Furthermore, the shape of optimal decision boundaries depends on the difficulties of different decisions. When some trials are very difficult, optimal boundaries decrease with time, but for tasks that only include a mixture of easy and medium difficulty trials, the optimal boundaries increase or stay constant. We also show how this simple model can be extended to more complex decision-making tasks such as when people have unequal priors or when they can choose to opt out of decisions. The theoretical model presented here provides an important framework to understand how, why, and whether decision boundaries should change over time in experiments on decision-making.