The 4-day working week is gaining interest, with international trials reporting enhanced staff wellbeing and performance, despite spending less time on the job. Here, we argue that improved performance on a 4-day working week arises through two psychological mechanisms of recovery and motivation: because better rested, better motivated brains, create better work.

Structured internal representations ('cognitive maps') shape cognition, from imagining the future and counterfactual past, to transferring knowledge to new settings. Our understanding of how such representations are formed and maintained in biological and artificial neural networks has grown enormously. The cognitive mapping hypothesis of schizophrenia extends this enquiry to psychiatry, proposing that diverse symptoms - from delusions to conceptual disorganization - stem from abnormalities in how the brain forms structured representations. These abnormalities may arise from a confluence of neurophysiological perturbations (excitation-inhibition imbalance, resulting in attractor instability and impaired representational capacity) and/or environmental factors such as early life psychosocial stressors (which impinge on representation learning). This proposal thus links knowledge of neural circuit abnormalities, environmental risk factors, and symptoms.

Lateralization is a defining characteristic of the human brain, often studied through localized approaches that focus on interhemispheric differences between homologous pairs of regions. It is also important to emphasize an integrative perspective of global brain asymmetry, in which hemispheric differences are understood through global patterns across the entire brain.

In complex tasks requiring cognitive control, humans show trial-by-trial alterations in response time (RT), which are evident even when sensory-motor or other contextual aspects of the task remain stable. Exaggerated intra-individual RT variability is associated with brain injuries and frequently seen in aging and neuropsychological disorders. In this opinion, we discuss recent electrophysiology and imaging studies in humans and neurobiological studies in monkeys that indicate RT variability is linked with executive control fluctuation and that prefrontal cortical regions play essential, but dissociable, roles in such fluctuation of control and the resulting behavioral variability. We conclude by discussing emerging models proposing that both extremes of behavioral variability (significantly higher or lower) might reflect aberrant alterations in various aspects of decision-making processes.

Classroom learning occurs within a multidimensional context of inter-related neurocognitive, motivational, and socioemotional processes. Multisubject approaches in neuroscience are poised to capture these dynamics using multimodal, time-resolved, and nonlinear methodologies and may help us identify the factors that facilitate or impede learning in such highly complex and social environments.

Cognition arises from neural operations at multiple spatial scales, from individual neurons to large-scale networks. Despite extensive research on coding principles and emergent cognitive processes across brain areas, investigation across scales has been limited. Here, we propose ways to test the idea that different cognitive processes emerge from distinct information coding principles at various scales, which collectively give rise to complex behavior. This approach involves comparing brain-behavior associations and the underlying neural geometry across scales, alongside an investigation of global and local scale interactions. Bridging findings across species and techniques through open science and collaborations is essential to comprehensively understand the multiscale brain and its functions.

Habits are the behavioral output of two brain systems. A stimulus-response (S-R) system that encourages us to efficiently repeat well-practiced actions in familiar settings, and a goal-directed system concerned with flexibility, prospection, and planning. Getting the balance between these systems right is crucial: an imbalance may leave people vulnerable to action slips, impulsive behaviors, and even compulsive behaviors. In this review we examine how recent advances in our understanding of these competing brain mechanisms can be harnessed to increase the control over both making and breaking habits. We discuss applications in everyday life, as well as validated and emergent interventions for clinical populations affected by the balance between these systems. As research in this area accelerates, we anticipate a rapid influx of new insights into intentional behavioral change and clinical interventions, including new opportunities for personalization of these interventions based on the neurobiology, environmental context, and personal preferences of an individual.

Earlier research has established strong evidence for structural brain changes across pregnancy. Pritschet et al. now enhanced our understanding of pregnancy-induced brain plasticity by following one woman throughout her pregnancy and the postpartum period, revealing insights into the dynamics of grey and white matter alterations across the transition to motherhood.

Despite decades of research, we lack objective diagnostic or prognostic biomarkers of mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has a single cause that can be uncovered by comparing average phenotypic values of patient and control samples. Here, we discuss the problematic assumptions on which this paradigm is based and highlight recent efforts that seek to characterize, rather than minimize, the inherent clinical and biological variability that underpins psychiatric populations. Embracing such variability is necessary to understand pathophysiological mechanisms and develop more targeted and effective treatments.

We discuss recent findings suggesting that non-human animals lack memory for stimulus sequences, and therefore do not represent the order of stimuli faithfully. These observations have far-reaching consequences for animal cognition, neuroscience, and studies of the evolution of language and culture. This is because, if non-human animals do not remember or process information about order faithfully, then it is unlikely that non-human animals perform mental simulations, construct mental world models, have episodic memory, or transmit culture faithfully. If this suggested sequence bottleneck proves to be a prevalent characteristic of animal memory systems, as suggested by recent work, it would require a re-examination of some influential concepts and ideas.

Dreams have long captivated human curiosity, but empirical research in this area has faced significant methodological challenges. Recent interdisciplinary advances have now opened up new opportunities for studying dreams. This review synthesizes these advances into three methodological frameworks and describes how they overcome historical barriers in dream research. First, with observable dreaming, neural decoding and real-time reporting offer more direct measures of dream content. Second, with dream engineering, targeted stimulation and lucidity provide routes to experimentally manipulate dream content. Third, with computational dream analysis, the generation and exploration of large dream-report databases offer powerful avenues to identify patterns in dream content. By enabling researchers to systematically observe, engineer, and analyze dreams, these innovations herald a new era in dream science.

Many magic tricks rely solely on vision, but there are few, if any, that rely on auditory perception alone. Here, we question why this is so and argue that research focusing on this issue could provide deeper theoretical insights into the similarities and differences between our senses.

Clinicians have suggested but not shown how anxiety involves altered planning. Here, I synthesize and extend computational models of planning in a framework that can be used to explain planning biases in anxiety. To spur its development, I spotlight two of its promising areas: task construal and meta-control.

A recent study by Peysakhovich and colleagues reveals how the superior colliculus (SC), a deep brain structure commonly associated with spatial orienting and motor control, causally contributes to the abstraction of visual categories. This highlights how subcortical areas with motor-control labels may have central roles in high-level visual cognition and opens avenues for investigation.

Explaining brain plasticity in blindness is challenging because the early visual cortex (EVC) responds to many different tasks, each type supporting a different explanation. Can individual differences help unify the experimental findings into a coherent theory and clarify the nature of brain plasticity?

Pain, an indicator of potential tissue damage, ideally falls under individual control. Although previous work shows a trend towards reduced pain in contexts where pain is controllable, there is a large variability across studies that is probably related to different aspects of control. We therefore outline a taxonomy of different aspects of control relevant to pain, sketch how control over pain can be integrated into a Bayesian pain model, and suggest changes in expectations and their precision as potential mechanisms. We also highlight confounding cognitive factors, particularly predictability, that emphasize the necessity for careful experimental designs. Finally, we describe the neurobiological underpinnings of how control affects pain processing in studies using different types of control, and highlight the roles of the anterior insula, middle frontal gyrus (MFG), and anterior cingulate cortex (ACC).

Spatial cognition is fundamental to our species. One might therefore expect that spatial communication systems would have evolved to make common distinctions. However, many have argued that spatial communication systems exhibit considerable cross-linguistic diversity, challenging the view that space structures language. We review recent work on spatial communication that merits revisiting the relationship between language and space. We provide a framework that places action as the driver of spatial communication systems across languages, in which spatial demonstratives - the earliest spatial terms - play a fundamental role in honing attention and theory of mind capacities that are crucial for language and cognition more broadly. We discuss how demonstratives emerged early in language evolution to serve a combination of spatial, social, and functional needs.

Children approach language by learning parts and constructing wholes. But they can also first learn wholes and then discover parts. We demonstrate this understudied yet impactful process in children creating language without input. Whole-to-part learning thus need not be driven by hard-to-segment input and is a bias that children bring to language.

Gender is important to the social and cognitive sciences, as evidenced by hundreds of meta-analyses, thousands of studies, and millions of datapoints that examine how gender (as an independent variable) shapes cognition and behavior. In this expansive literature, gender is often understood as a noun - a social category that separates 'men' from 'women'. However, gender can also be studied and understood as a verb - a cognitive process used to conceptually divide both human and non-human entities by masculinity and femininity. In this review, we outline the cognitive process of gendering and propose a framework to understand gender as a verb that enables a better understanding of how gender operates, why it is important, and how it can change.

Predicting individual behavioral traits from brain idiosyncrasies has broad practical implications, yet predictions vary widely. This constraint may be driven by a combination of signal and noise in both brain and behavioral variables. Here, we expand on this idea, highlighting the potential of extended sampling 'precision' studies. First, we discuss their relevance to improving the reliability of individualized estimates by minimizing measurement noise. Second, we review how targeted within-subject experiments, when combined with individualized analysis or modeling frameworks, can maximize signal. These improvements in signal-to-noise facilitated by precision designs can help boost prediction studies. We close by discussing the integration of precision approaches with large-sample consortia studies to leverage the advantages of both.

Generic language, that is, language that refers to a category as an abstract whole (e.g., 'Girls like pink') rather than specific individuals (e.g., 'This girl likes pink'), is a common means by which children learn about social kinds. Here, we propose that children interpret generics as signaling that their referenced categories are natural, objective, and have distinctive features, and, thus, in the social domain, that such language affects children's beliefs about the social world in ways that extend far beyond the content they explicitly communicate. On this account, even generics expressing uncontentious content (e.g., 'Girls are great at math') can lead children to think of categories as defining fundamentally distinct kinds of people and contribute to the development of stereotypes and other problematic social phenomena.

The ability to read others' intentions is crucial when pooling knowledge to form a collective decision. Decision-making improves when communication is allowed through words or touch. Coucke et al. show that visual information communicated through actions can convey not only a decision but also decision confidence, improving collective decision-making.

How do the two main types of neural dynamics, aperiodic transients and oscillations, contribute to the interactions between feedforward (FF) and feedback (FB) pathways in sensory inference and predictive processing? We discuss three theoretical perspectives. First, we critically evaluate the theory that gamma and alpha/beta rhythms play a role in classic hierarchical predictive coding (HPC) by mediating FF and FB communication, respectively. Second, we outline an alternative functional model in which rapid sensory inference is mediated by aperiodic transients, whereas oscillations contribute to the stabilization of neural representations over time and plasticity processes. Third, we propose that the strong dependence of oscillations on predictability can be explained based on a biologically plausible alternative to classic HPC, namely dendritic HPC.

Large language models (LLMs), such as ChatGPT, flood the Internet with true and false information, crafted and delivered with techniques that psychological science suggests will encourage people to think that information is true. What's more, as people feed this misinformation back into the Internet, emerging LLMs will adopt it and feed it back in other models. Such a scenario means we could lose access to information that helps us tell what is real from unreal - to do 'reality monitoring.' If that happens, misinformation will be the new foundation we use to plan, to make decisions, and to vote. We will lose trust in our institutions and each other.

The study of intellectual humility (IH), which is gaining increasing interest among cognitive scientists, has been dominated by a focus on individuals. We propose that IH operates at the collective level as the tendency of a collective's members to attend to each other's intellectual limitations and the limitations of their collective cognitive efforts. Given people's propensity to better recognize others' limitations than their own, IH may be more readily achievable in collectives than individuals. We describe the socio-cognitive dynamics that can interfere with collective IH and offer the solution of building intellectually humbling environments that create a culture of IH that can outlast the given membership of a collective. We conclude with promising research directions.

Inhibitory control is a fundamental mechanism underlying flexible behavior and features in theories across many areas of cognitive and psychological science. However, whereas many theories implicitly or explicitly assume that inhibitory control is a domain-general process, the vast majority of neuroscientific work has hitherto focused on individual domains, such as motor, mnemonic, or attentional inhibition. Here, we attempt to close this gap by highlighting recent work that demonstrates shared neuroanatomical and neurophysiological signatures of inhibitory control across domains. We propose that the regulation of thalamocortical drive by a fronto-subthalamic mechanism operating in the β band might be a domain-general mechanism for inhibitory control in the human brain.