Psychological review最新文献

Ostensive communication (Sperber & Wilson, 1986/1995) involves both an informative and a communicative intention: The communicator draws attention not only to the information she intends to convey but also to her intention to convey it. This elicits an expectation of relevance in addressees that guides them in identifying the information communicated. This notion of ostensive communication has been influential in pragmatics, developmental psychology, and comparative psychology but also raises many questions. In the light of much relevant research, elaboration, and criticism over the years, we put forward a revised, broadened, more explicit, and more explanatory account of ostensive communication and of the role played in it by cognitive expectations of relevance and social expectations of cooperativeness. We distinguish two forms of ostension: In basic ostension, communicators give evidence of the information they intend to communicate, and in mentalistic communication, they give evidence of their intention to communicate that information. We interpret relevant comparative psychology findings (such as Gómez, 1996) as suggesting that a basic, nonmentalistic form of ostension may have evolved in great apes as a solution to the problems and opportunities presented by intentional communication. We discuss Csibra and Gergely's (2009) "natural pedagogy theory" claim that ostension is specifically adapted for the transmission of general knowledge to children. Correcting earlier pragmatic theories inspired by Grice (1989) including our own, we argue that typical verbal communication makes use of both basic and mentalistic ostension. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

A recent line of research has shown that humans and rodents can monitor errors in their timing behavior in individual trials. This ability is called temporal error monitoring (TEM). Electrophysiological studies showed that TEM-related neural signals of error are present before the timing behavior is manifested. These results have crucial implications for the function and modeling of TEM as they show that timing errors are read out rather than detected retrospectively. Such real-time error monitoring allows emergent timing error signals to improve the impending timing behavior in a prospective fashion (e.g., increasing the timing threshold when "earlier-than-target" errors are detected), enabling within-trial error corrections. In this article, we present a drift-diffusion model of real-time TEM with prospective (within-trial) behavioral modulation/refinement elements that are sensitive to task representations. Our model predicts the read-out of timing signals before the manifestation of the timing behavior and the translation of these signals into the improvement of timing accuracy within individual trials (thus improving overall precision) without violating the psychophysical and statistical features of the timing behavior. Finally, the task representation dependency of the decision element accounts for the widely reported reward-rate maximizing timing behavior. Our model introduces a new theoretical foundation for TEM with many testable behavioral and electrophysiological predictions. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Psychological network theories provide an important alternative to traditional common cause theories, such as the g-theory of general intelligence and brain-based explanations of depression. Network theories, which are often formalized using the Ising model from statistical physics, have gained significant empirical support. However, the binary nature of nodes in Ising-type models presents a limitation, as many psychological data sets include responses with uncertain or neutral categories (e.g., "don't know" or "not relevant"). Ternary spin models, such as the Blume-Capel model, overcome this constraint by incorporating a third node state, zero, that can represent such responses, enabling more nuanced scale representations. The resulting models exhibit more complex dynamics and provide new insights into research across a range of psychological constructs. We illustrate our approach with examples from three key subdisciplines of psychology. First, we introduce a ternary spin model for attitudes, extending the Ising attitude model. Next, we propose a unified framework encompassing both bipolar disorder and major depressive disorder. Finally, we present a novel ternary network model for understanding knowledge acquisition. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Interdependent subsistence styles, such as rice farming, are thought to underlie the evolution of collectivistic cultures, which emphasize collective welfare over individual gains. Rice farming can produce mutual dependence within communities but also create conflicting interests, as people cooperate to provide valuable public goods. However, current theories of the origins of collectivism fail to address the interplay between mutual dependence and conflict. As a consequence of these limitations, the evolutionary dynamics of collectivism and its association with cooperation are still unclear. We advance a theoretical model to study the evolution of cultural traits that enhance people's valuations of collective welfare, one of the key features of collectivistic cultures. Our model investigates the evolutionary dynamics of cooperation and cultural evolution in ecologies with distinct interdependence structures. We find evidence that higher degrees of mutual dependence facilitate the evolution and persistence of collectivism. However, the degree of conflicting interests also plays a crucial role in driving the diffusion and maintenance of collectivistic norms. In particular, the selective advantage of collectivism is strongest when people experience some degree of conflict of interests, an effect that is magnified by heightened mutual dependence. These results clarify how variation in interdependence could underlie the ecological origins of collectivism, lending support to and expanding the scope of current theories of the cultural evolution of cooperation. More broadly, the framework presented here elucidates how fitness interdependence can be influenced by different ecological factors, and, in turn, influence the evolution of social behaviors. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Morbid curiosity, or the seemingly paradoxical drive to engage with aversive or grotesque stimuli, has long puzzled psychologists, who have traditionally framed it as either a form of sensation-seeking or a mechanism for unambiguous threat learning. The current article proposes a novel adaptationist model positioning morbid curiosity as an evolved cognitive mechanism specifically tuned to resolve ambiguity surrounding survival-relevant stimuli. Drawing on evolutionary theory, cognitive psychology, and neurobiological evidence, I argue that morbid curiosity functions primarily as an uncertainty-reduction strategy, motivating individuals to approach ambiguous stimuli to clarify their threat or benefit. Unlike basic emotions such as fear or disgust that typically trigger immediate avoidance, morbid curiosity fosters cautious approach behaviors aimed at gathering survival-critical information. The proposed model thereby reconceptualizes morbid curiosity as an adaptive, ambiguity-oriented cognitive system, offering novel insights into broader questions about human motivation, information-seeking, and adaptive cognition. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

As people engage in tasks over extended periods, their psychological states change systematically due to factors such as practice, learning, and/or boredom. However, the dominant frameworks for modeling cognitive processes, such as evidence accumulation models, only consider a single estimate of a process across the duration of an experiment. Our study describes, develops, and assesses the ParAcT-DDM framework: the Parameters Across Time Diffusion Decision Model, which unifies previous modeling efforts from practice and decision-making research. Specifically, our framework models time-varying changes to diffusion decision model parameters by assuming that rather than being constant across time, their estimates follow theoretically informed time-varying (e.g., trial-varying or block-varying) functions. Focusing on two diffusion model parameters: drift rate (task efficiency) and threshold (caution), our empirical results show that ParAcT-DDM variants vastly outperform the standard diffusion model in four existing data sets, including one where participants completed a practice block before data recording began, suggesting that time-varying cognitive processes often occur in typical cognitive experiments, even when the experimental design explicitly tries to remove practice effects. Finally, we find that the existence of time-varying processes causes systematic biases in the parameter estimates of the standard diffusion model, suggesting that our ParAcT-DDM framework can be crucial to ensuring the robustness of inferences against time-varying changes, regardless of whether these changes are of direct interest. (PsycInfo Database Record (c) 2026 APA, all rights reserved).