Psychological review最新文献

Questions on early sapiens cognition, the cognitive abilities of our ancestors, are intriguing but notoriously hard to tackle. Leaving no hard traces in the archeological record, these abilities need to be inferred from indirect evidence, informed by our understanding of present-day cognition. Most of such attempts acknowledge the role that culture, as a faculty, has played for human evolution, but they underrate or even disregard the role of distinct cultural traditions and the ensuing diversity, both in present-day humans and as a dimension of past cognition. We argue that culture has exerted a profound impact on human cognition from the start in a dual manner: It scaffolds cognition through both development and evolution, and it thereby continually diversifies the form and content of human thinking. To unveil early sapiens cognition and retrace its evolutionary trajectories, this cognitive diversity must be considered. We present two strategies to achieve this: large-scale extrapolation and phylogenetic comparison. The former aims at filtering out diversity to determine what is basic and universal versus culturally shaped (illustrated for theory of mind abilities). The latter capitalizes on the diversity to reconstruct evolutionary trajectories (illustrated for religious beliefs). The two methods, in combination, advance our understanding of the cognitive abilities of our early sapiens ancestors and of how these abilities emerged and evolved. To conclude, we discuss the implications of this approach for our insights into early cognition itself and its scientific investigation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Perception and action rely on integrating or binding different features of stimuli and responses. Such bindings are short-lived, but they can be retrieved for a limited amount of time if any of their features is reactivated. This is particularly true for stimulus-response bindings, allowing for flexible recycling of previous action plans. A relation to learning of stimulus-response associations suggests itself, and previous accounts have proposed binding as an initial step of forging associations in long-term memory. The evidence for this claim is surprisingly mixed, however. Here we propose a framework that explains previous failures to detect meaningful relations of binding and learning by highlighting the joint contribution of three variables: (a) decay, (b) the number of repetitions, and (c) the time elapsing between repetitions. Accounting for the interplay of these variables provides a promising blueprint for innovative experimental designs that bridge the gap between immediate bindings on the one hand and lasting associations in memory on the other hand. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

How can choice, confidence, and response times be modeled simultaneously? Here, we propose the new dynamical weighted evidence and visibility (dynWEV) model, an extension of the drift-diffusion model of decision-making, to account for choices, reaction times, and confidence simultaneously. The decision process in a binary perceptual task is described as a Wiener process accumulating sensory evidence about the choice options bounded by two constant thresholds. To account for confidence judgments, we assume a period of postdecisional accumulation of sensory evidence and parallel accumulation of information about the reliability of the present stimulus. We examined model fits in two experiments, a motion discrimination task with random dot kinematograms and a postmasked orientation discrimination task. A comparison between the dynWEV model, two-stage dynamical signal detection theory, and several versions of race models of decision-making showed that only dynWEV produced acceptable fits of choices, confidence, and reaction time. This finding suggests that confidence judgments depend not only on choice evidence but also on a parallel estimate of stimulus discriminability and postdecisional accumulation of evidence. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Identifying early causal factors leading to the development of poor mental health and behavioral outcomes is essential to design efficient preventive interventions. The substantial associations observed between parental risk factors (e.g., maternal stress in pregnancy, parental education, parental psychopathology, parent-child relationship) and child outcomes point toward the importance of parents in shaping child outcomes. However, such associations may also reflect confounding, including genetic transmission-that is, the child inherits genetic risk common to the parental risk factor and the child outcome. This can generate associations in the absence of a causal effect. As randomized trials and experiments are often not feasible or ethical, observational studies can help to infer causality under specific assumptions. This review aims to provide a comprehensive summary of current causal inference methods using observational data in intergenerational settings. We present the rich causal inference toolbox currently available to researchers, including genetically informed and analytical methods, and discuss their application to child mental health and related outcomes. We outline promising research areas and discuss how existing approaches can be combined or extended to probe the causal nature of intergenerational effects. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Affective experiences are commonly represented by either transient emotional reactions to discrete events or longer term, sustained mood states that are characterized by a more diffuse and global nature. While both have considerable influence in shaping memory, their interaction can produce mood-congruent memory (MCM), a psychological phenomenon where emotional memory is biased toward content affectively congruent with a past or current mood. The study of MCM has direct implications for understanding how memory biases form in daily life, as well as debilitating negative memory schemas that contribute to mood disorders such as depression. To elucidate the factors that influence the presence and strength of MCM, here we systematically review the literature for studies that assessed MCM by inducing mood in healthy participants. We observe that MCM is often reported as enhanced accuracy for previously encoded mood-congruent content or preferential recall for mood-congruent autobiographical events, but may also manifest as false memory for mood-congruent lures. We discuss the relevant conditions that shape these effects, as well as instances of mood-incongruent recall that facilitate mood repair. Further, we provide guiding methodological and theoretical considerations, emphasizing the limited neuroimaging research in this area and the need for a renewed focus on memory consolidation. Accordingly, we propose a theoretical framework for studying the neural basis of MCM based on the neurobiological underpinnings of mood and emotion. In doing so, we review evidence for associative network models of spreading activation, while also considering alternative models informed by the cognitive neuroscience literature of emotional memory bias. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

People's decisions often deviate from classical notions of rationality, incurring costs to themselves and society. One way to reduce the costs of poor decisions is to redesign the decision problems people face to encourage better choices. While often subtle, these nudges can have dramatic effects on behavior and are increasingly popular in public policy, health care, and marketing. Although nudges are often designed with psychological theories in mind, they are typically not formalized in computational terms and their effects can be hard to predict. As a result, designing nudges can be difficult and time-consuming. To address this challenge, we propose a computational framework for understanding and predicting the effects of nudges. Our approach builds on recent work modeling human decision making as adaptive use of limited cognitive resources, an approach called resource-rational analysis. In our framework, nudges change the metalevel problem the agent faces-that is, the problem of how to make a decision. This changes the optimal sequence of cognitive operations an agent should execute, which in turn influences their behavior. We show that models based on this framework can account for known effects of nudges based on default options, suggested alternatives, and information highlighting. In each case, we validate the model's predictions in an experimental process-tracing paradigm. We then show how the framework can be used to automatically construct optimal nudges, and demonstrate that these nudges improve people's decisions more than intuitive heuristic approaches. Overall, our results show that resource-rational analysis is a promising framework for formally characterizing and constructing nudges. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Many aspects of visual perception, including the classification of shapes into known categories and the induction of new shape categories from examples, are driven by shape similarity. But there is as yet no generally agreed, principled measure of the degree to which two shapes are "similar." Here, we derive a measure of shape similarity based on the Bayesian skeleton estimation framework of Feldman and Singh (2006). The new measure, called generative similarity, is based on the idea that shapes should be considered similar in proportion to the posterior probability that they were generated from a common skeletal model rather than from distinct skeletal models. We report a series of experiments in which subjects were shown a small number (1, 2, or 3) of 2D or 3D "nonsense" shapes (generated randomly in a manner designed to avoid known shape categories) and asked to select other members of the "same" shape class from a larger set of (random) alternatives. We then modeled subjects' choices using a variety of shape similarity measures drawn from the literature, including our new measure, skeletal cross-likelihood, a skeleton-based measure recently proposed by Ayzenberg and Lourenco (2019), a nonskeletal part-based similarity model proposed by Erdogan and Jacobs (2017), and a convolutional neural network model (Vedaldi & Lenc, 2015). We found that our new similarity measure generally predicted subjects' selections better than these competing proposals. These results help explain how the human visual system evaluates shape similarity and open the door to a broader view of the induction of shape categories. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

We address four issues in response to Osth and Hurlstone's (2022) commentary on the context retrieval and updating (CRU) theory of serial order (Logan, 2021). First, we clarify the relations between CRU, chains, and associations. We show that CRU is not equivalent to a chaining theory and uses similarity rather than association to retrieve contexts. Second, we fix an error Logan (2021) made in accounting for the tendency to recall ACB instead of ACD in recalling ABCDEF (fill-in vs. in-fill errors, respectively). When implemented correctly, the idea that subjects mix the current context with an initial list cue after the first order error correctly predicts that fill-in errors are more frequent than in-fill errors. Third, we address position-specific prior-list intrusions, suggesting modifications to CRU and introducing a position-coding model based on CRU representations to account for them. We suggest that position-specific prior-list intrusions are evidence for position coding on some proportion of the trials but are not evidence against item coding on other trials. Finally, we address position-specific between-group intrusions in structured lists, agreeing with Osth and Hurlstone that reasonable modifications to CRU cannot account for them. We suggest that such intrusions support position coding on some proportion of the trials but do not rule out CRU-like item-based codes. We conclude by suggesting that item-independent and item-dependent coding are alternative strategies for serial recall and we stress the importance of accounting for immediate performance. (PsycInfo Database Record (c) 2024 APA, all rights reserved).