New Content From Perspectives on Psychological Science

Putting Emotional Memories in Context: The Constructionist Model of Emotional Memory
John T. West, Neil W. Mulligan, Kristen A. Lindquist

Cognitive psychologists have long been interested in the intersection of emotion and memory, given that the emotions associated with a stimulus affect its memorability. Theoretical perspectives within cognitive science have guided research on how affective dimensions, such as valence and arousal, affect aspects of memory, such as accuracy, subjective vividness, consolidation, and retrieval. Here we argue that well-established theories of emotion from affective science represent a fruitful source of ideas whose implications for episodic memory have not yet been thoroughly investigated. In the current article, we propose a model of emotional memory, inspired by psychological constructionist theories of emotion, that builds upon existing perspectives in this area while generating several novel hypotheses and avenues of investigation. Following psychological constructionism, we conceive of emotions as emergent phenomena constructed when perceivers use conceptual knowledge to make sense of affective sensations in context. The constructionist model of emotional memory (CMEM) highlights new directions for future emotional-memory research, such as investigating the mnemonic consequences of conceptual emotion knowledge and considering the effects of variability in emotion construction at the situational, individual, and cultural levels.

From Voice to Self: An Integrative Framework on Self-Voice Processing
Pavo Orepic, Ana P. Pinheiro

The self-voice plays a fundamental role in communication and identity yet remains a relatively neglected topic in psychological science. As AI-generated and digitally manipulated voices become more common, understanding how individuals perceive and process their own voice is increasingly important. Disruptions in self-voice processing are implicated in several clinical conditions, including psychosis, autism, and personality disorders, highlighting the need for integrative models to explain the self-voice across contexts. However, research faces two major challenges: a methodological one (i.e., replicating the bone-conducted acoustics that shape natural self-voice perception) and a conceptual one (i.e., a persistent bias toward treating the self-voice as purely auditory). To address these gaps, we propose a framework that decomposes the self-voice into five interacting components: auditory, motor control, memory, multisensory integration, and self-concept. We review the functional and neural basis of each component and suggest how they converge within distributed brain networks to support coherent self-voice processing. This integrative framework aims to advance theoretical and translational work by bridging psychology, neuroscience, clinical research, and voice technology in the context of emerging digital voice environments.

Bringing the Reading Sciences Into the Classroom: Insights for Phonics Instruction
Tobias Ungerer, Kathleen Rastle, Blair C. Armstrong

Teaching phonics—that is, systematic mappings between letters and sounds—plays a foundational role in how children learn to read in alphabetical writing systems. Although the reading sciences yield important insights into the factors underlying effective phonics instruction, these findings have not been sufficiently linked to key decisions that teachers must make in the classroom—for instance, which spelling-sound regularities to teach, in what order to introduce them, how to illustrate them with example words, and when to teach exception words. We first show that existing phonics programs provide varying guidance on these aspects, which may affect learning outcomes in ways that are poorly understood. We then discuss how research on reading and learning can inform key considerations regarding the use of effective phonics content. We also highlight gaps in current knowledge that remain to be addressed by further work. Finally, we outline a road map for how future research could support the design and selection of optimized phonics content, thus benefiting the professional practice of diverse stakeholders in education.

Growing Technological Opacity and the Social Brain
François Osiurak, Giovanni Federico

Thanks to our remarkable ability to transmit technical content, our technologies have become more sophisticated. Intuitively, one might assume that this evolution has imposed greater demands on the technical brain. However, recent neuroscientific research suggests that this evolution has also increasingly engaged the social brain to address the opacity it has generated in making, transactive, and use processes. Here, we build on these findings to design a neurocognitive framework that outlines the role of the social brain in (a) facilitating the transmission of making processes, (b) relying on human experts as extensions of our technical cognition, and (c) engaging with certain technologies—including machines—as if they were intentional biological agents. The framework emphasizes the dynamic interplay between the technical and social brain and explores the mechanisms that drive switching between these networks in response to technological opacity, including bottom-up perceptual cues and causal uncertainty. It also considers how expertise modulates network engagement and guides the allocation of cognitive resources. Overall, this framework provides a unified perspective on how humans navigate complex technological environments, illustrating the coevolution of technical and social cognition and the adaptive strategies that allow us to interact with technologies that we cannot fully understand.

Formal Modeling as Theoretical Glue Between Laboratory and Naturalistic Studies of Memory
Qiong Zhang

Memory research has evolved along two distinct traditions: well-controlled laboratory experiments emphasizing precision and tractability and naturalistic-memory experiments emphasizing generalization to real-world contexts. Although both have yielded important insights, we do not yet have a generalized theory of memory consistently interpreted across laboratory and naturalistic paradigms. By analyzing the strengths and limitations of the two traditions, I propose that formal modeling is the key to creating this theoretical link. A formal theory, instantiated in precise computational models that are developed over decades of laboratory-based experiments, needs naturalistic experiments to test its generalizability and reveal its limitations. Naturalistic experiments, in turn, better connect with existing laboratory paradigms when their results are explained by the same theoretical model. To achieve this, I propose a step-by-step procedure in which naturalistic settings are considered as all possible scenarios that could be realized in the real world, with laboratory settings forming a smaller subset that we have understood well. Our goal as memory researchers is to incrementally expand the scope of existing laboratory studies, theories, and models to account for increasingly naturalistic scenarios, ultimately achieving a generalized theory of memory. Together, the proposed framework no longer views laboratory versus naturalistic approaches as a trade-off to navigate, given their different priorities and methodologies, but considers them both essential in working toward the same goal.

Chaos Theory and Child Development: Quantifying Nonlinear Pathways of Growth
Ori Ossmy

Traditional developmental science has often described child growth as a sequence of stages or linear progressions, yet many phenomena—abrupt spurts and regressions, idiosyncratic pathways, and widening individual differences—resist linear accounts. This article proposes chaos theory as a framework for quantifying developmental trajectories. Chaos theory, which addresses how complex patterns emerge from simple rules in deterministic yet unpredictable ways, aligns with observations of sensitive developmental periods, emergent behaviors, and divergent outcomes. I situate chaos theory alongside dynamic systems theory, neuroconstructivism, and developmental-cascade models and clarify how chaos might add mathematical precision to established insights: Bifurcation analysis identifies tipping points at which behaviors reorganize; Lyapunov exponents quantify stability and sensitivity to small perturbations; state-space methods reconstruct attractor landscapes from dense time series; and complexity metrics discriminate structured variability from noise. These tools convert powerful metaphors—soft assembly, attractors, cascades—into testable hypotheses about when and why qualitative change occurs. Such a framework also motivates micro genetic and high-density longitudinal designs, computational modeling of phase transitions, and interventions conceived as targeted perturbations delivered near sensitive windows. Finally, I will discuss why adopting a chaos framework can be advantageous compared with (or in concert with) traditional linear models.

Children’s Third-Party Punishment Reveals a Genuine Concern for Fairness and Justice
Young-eun Lee, Felix Warneken

Why do people punish wrongdoers when they are not personally affected? Researchers on costly third-party punishment have long debated whether such behavior reflects strategic self-interest or a moral commitment to fairness and justice. Recent developmental evidence offers important insights into this question. We argue that the origins of costly third-party punishment in early childhood are best explained by nonstrategic moral concerns. Young children selectively punish norm violators, incur personal costs to do so, and intervene even when they stand to gain nothing—often without reputational incentives or expectations of future benefit. Empirical studies indicate that children’s punishment is driven by egalitarian norms, retributive motives, and efforts to alleviate victims’ distress. In contrast, strategic motivations, such as reputation management and self-protection, appear only later in development. These findings challenge the view that third-party punishment is grounded in self-interest and instead support the idea that a concern for justice underlies the earliest forms of human norm enforcement. We conclude that whereas strategic considerations may shape punishment in adolescence and adulthood, they build upon an early-emerging moral foundation centered on fairness and justice.

On the Goals and Limitations of Psychological Science: Some Thoughts in Memory of Daniel Kahneman
Gideon Keren

Daniel Kahneman was a prominent multifaceted psychologist whose work had a persuasive impact on the fields of attention (his initial research) and the field of judgment and decision-making (and the closely related domain of behavioral economics), for which he received the Nobel Prize. The current article was initiated by a correspondence with Kahneman regarding the scientific value of the two-system premise. This correspondence went much beyond the initial two-system issue, ending with a query regarding the methods and goals of psychological research and its inherent limitations. The major issue concerned the extent to which precision in psychological research can be achieved and, specifically, the value of formal models in psychological science. This article summarizes some fundamental controversial issues raised in this correspondence regarding the nature of knowledge attained in psychological science and the role of theories and models in the process of obtaining this knowledge.

Principles of Sociopolitical Competency in Psychological Practice, Research, and Teaching
Richard E. Redding, Nina C. Silander

Research shows that sociopolitical attitudes and values (SPAVs) often play an important role in people’s personal and social identity, life choices, psychological and behavioral functioning, and interpersonal relationships (including those between psychologists and their clients). Thus, SPAVs are frequently relevant to the work that psychologists do, whether as clinicians, researchers, or educators. After reviewing the research on the impact of SPAVs on people’s lives and relationships, we provide a set of evidence-based principles for effectively addressing SPAVs in clinical practice, psychological research, education and professional training, and professional ethics.

Manufacturing Pessimism: Structural Incentives and Social Psychology’s Narrative of Human Nature
Jan-Erik Lönnqvist

Social psychology presents itself as liberal, yet its dominant narratives—obedience, cruelty, conformity, and bias—reflect a persistently pessimistic portrayal of human nature. Here I argue that this pattern is structurally produced. A two-level framework distinguishes the content level, in which pessimistic narratives circulate, from the structural level, in which incentive regimes in academic publishing, media, and pedagogy systematically select and stabilize that content. Two mechanisms are identified. A market-selection mechanism explains why attention economies favor dramatic, morally arousing findings. An institutional-stabilization mechanism explains why pessimistic narratives prove especially durable: They participate in the constitutive logic of the “psy-complex,” in which psychological expertise gains authority by rendering human conduct legible as a problem requiring expert correction. Findings that portray ordinary people as biased, obedient, or morally fragile are apt to generate the remediation apparatus on which the field’s social legitimacy depends. Archival evidence shows that classic studies were staged and selectively framed to produce pessimistic morals. The replication crisis retroactively identified much of this content as incentive-compatible rather than epistemically robust. Reform efforts (e.g., registered reports, open data, equity-oriented partnerships) can address the market-selection side; changing the institutional-stabilization dynamic requires reflexive attention to whose interests a deficit-focused discipline serves.

Effects May Both Increase or Decrease in the Long Term: A Statistical Illustration
Mathias Berggren, Jessica Kay Flake

It has been argued that small effect sizes observed at a single instance should not be dismissed because they can often accumulate in the long term. This follows a classic argument by Abelson (1985). However, it has also been argued that such long-term accumulation is entirely speculative and need not happen. Using a simple statistical illustration, we show how restrictive Abelson’s assumptions are and argue that they are unlikely to be met in psychological research. This demonstrates that the Abelson example is unrealistically biased toward the accumulation of effect sizes; even small deviations can have large consequences for the long-term effect sizes. This is true even if no long-term counteracting mechanisms, such as habituation, are at play. Further, it is shown how long-term effect sizes may be smaller than those observed at a single time point. If the theoretical value of an effect lies in the long term, it should be examined in that long term, and not merely be the subject of speculation in the short term.

Feedback on this article? Email [email protected] or login to comment.