Brain and behavior undergo measurable changes in their underlying state and neuromodulators are thought to contribute to these fluctuations. Why do we undergo such changes, and what function could the underlying neuromodulatory systems perform? Here we examine theoretical answers to these questions with respect to the locus coeruleus/norepinephrine system focusing on peripheral markers for arousal, such as pupil diameter, that are thought to provide a window into brain wide noradrenergic signaling. We explore a computational role for arousal systems in facilitating internal state transitions that facilitate credit assignment and promote accurate perceptions in non-stationary environments. We summarize recent work that supports this idea and highlight open questions as well as alternative views of how arousal affects cognition.

The tail of the striatum (TS) is increasingly recognized as a unique subdivision of the striatum, characterized by its dense sensory inputs and projections received from a distinct group of dopamine neurons. Separate lines of research have characterized the functional role of TS, and TS-projecting dopamine neurons, in three realms: saccadic eye movement towards valuable visual stimuli; tone-guided choice between two options; and defensive responses to threatening stimuli. We propose a framework for reconciling these diverse roles as varied implementations of a conserved response to salient stimuli, with dopamine in TS providing a teaching signal to promote quick attentional shifts that facilitate stimulus-driven orientation and/or avoidance.

Methodological advances have facilitated extensive revision of traditional views of thalamic and cholinergic contributions to cognition and behavior. Increasing attention to the integrative capabilities of the thalamus highlights its role beyond a simple sensory relay, recognizing its complex connectivity and role in orchestrating different phases of attention. Correspondingly, modern conceptualizations position the cholinergic system as key in integrating sensory information with attention and goals. These theoretical developments have occurred largely in parallel, but have large conceptual overlap. We review this overlap, including evidence from animal, patient, neuroimaging, and computational studies, and suggest thalamo-cholinergic cognition plays a key role in coordinating stable and flexible attention.

Cognitive flexibility exhibits dynamic changes throughout development, with different forms of flexibility showing dissociable developmental trajectories. In this review, we propose that an adolescent-specific mode of flexibility in the face of changing environmental contingencies supports the emergence of adolescent-to-adult gains in cognitive shifting efficiency. We first describe how cognitive shifting abilities monotonically improve from childhood to adulthood, accompanied by increases in brain state flexibility, neural variability, and excitatory/inhibitory balance. We next summarize evidence supporting the existence of a dopamine-driven, adolescent peak in flexible behavior that results in reward seeking, undirected exploration, and environmental sampling. We propose a neurodevelopmental framework that relates these adolescent behaviors to the refinement of neural phenotypes relevant to mature cognitive flexibility, and thus highlight the importance of the adolescent period in fostering healthy neurocognitive trajectories.

This article reviews the prevalence of stress and explores resilience factors in children and adolescents with specific learning disabilities (SLDs). We show that the increased stress and emotional challenges faced by this group are likely due to societal pressures and stigma. Recent findings on neuroendocrine changes in this population are discussed, suggesting a predisposition to psychiatric disorders. This review advocates for a societal shift towards the neurodiversity paradigm, which recognizes SLDs as natural variations in brain function, emphasizing individual strengths and promoting a more inclusive approach that values cognitive diversity. Such advocacy is likely important to combat stress and stigma in those with SLDs. This article also reviews recent work identifying resilience-promoting factors, such as perception of self and peer/teacher relationships, for enhancing emotional well-being and mental health for children and adolescents with SLD.

Animal brains are probably the most complex computational machines on our planet, and like everything in biology, they are the product of evolution. Advances in developmental and palaeobiology have been expanding our general understanding of how nervous systems can change at a molecular and structural level. However, how these changes translate into altered function - that is, into 'computation' - remains comparatively sparsely explored. What, concretely, does it mean for neuronal computation when neurons change their morphology and connectivity, when new neurons appear or old ones disappear, or when transmitter systems are slowly modified over many generations? And how does evolution use these many possible knobs and dials to constantly tune computation to give rise to the amazing diversity in animal behaviours we see today? Addressing these major gaps of understanding benefits from choosing a suitable model system. Here, I present the vertebrate retina as one perhaps unusually promising candidate. The retina is ancient and displays highly conserved core organisational principles across the entire vertebrate lineage, alongside a myriad of adjustments across extant species that were shaped by the history of their visual ecology. Moreover, the computational logic of the retina is readily interrogated experimentally, and our existing understanding of retinal circuits in a handful of species can serve as an anchor when exploring the visual circuit adaptations across the entire vertebrate tree of life, from fish deep in the aphotic zone of the oceans to eagles soaring high up in the sky.

Repetitive negative thinking (RNT) is a transdiagnostic construct that encompasses rumination and worry, yet what precisely is shared between rumination and worry is unclear. To clarify this, we develop a meta-control account of RNT. Meta-control refers to the reinforcement and control of mental behavior via similar computations as reinforce and control motor behavior. We propose rumination and worry are coarse terms for failure in meta-control, just as tripping and falling are coarse terms for failure in motor control. We delineate four meta-control stages and risk factors increasing the chance of failure at each, including open-ended thoughts (stage 1), individual differences influencing subgoal execution (stage 2) and switching (stage 3), and challenges inherent to learning adaptive mental behavior (stage 4). Distinguishing these stages therefore elucidates diverse processes that lead to the same behavior of excessive RNT. Our account also subsumes prominent clinical accounts of RNT into a computational cognitive neuroscience framework.

Ultrasound neuromodulation is a promising technology that could revolutionize study and treatment of brain conditions ranging from mood disorders to Alzheimer's disease and stroke. An understanding of how ultrasound directly modulates specific ion channels could provide a roadmap for targeting specific neurological circuits and achieving desired neurophysiological outcomes. Although experimental challenges make it difficult to unambiguously identify which ion channels are sensitive to ultrasound , recent progress indicates that there are likely several different ion channels involved, including members of the K2P, Piezo, and TRP channel families. A recent result linking TRPM2 channels in the hypothalamus to induction of torpor by ultrasound in rodents demonstrates the feasibility of targeting a specific ion channel in a specific population of neurons.

Animals face behavioral problems that can be conceptualized in terms of a gradient of spatial and temporal proximity. I propose that solving close-proximity behavioral problems involves integrating disparate types of information in complex and flexible ways. In this framework, the midbrain periaqueductal gray (PAG) is understood as a key region involved in close-proximity motivated cognition. Anatomically, the PAG has access to signals across the neuroaxis via extensive connectivity with cortex, subcortex, and brainstem. However, the flow of signals is not unidirectional, as the PAG projects to the cortex directly, and further ascending signal flow is attained via the midline thalamus. Overall, the anatomical organization of the PAG allows is to be a critical hub engaged in cognition "here and now".

Medical innovation and technologic advances enrich daily living and occur within our normative worlds, that are socially constructed. These advances confront society with critical questions about the nature of human life, laying bare the inadequacies of extant norms and boundaries. Yet, society has been unable to develop consensus about when life ends. Scientific studies highlight that life is best characterized by continua without natural boundaries. Thus, scientific information alone cannot be employed to justify the socially constructed health categories required for setting norms and boundaries. An iterative process that integrates a broad range of non-scientific data with advancing scientific information is needed to facilitate consensus for updating social norms and boundaries. This can lead to a new taxonomy of living across the measurable continuum of life and align our normative worlds with the dizzying pace of medical innovation and advances in technologies transforming the world in which we live.

Cognitive flexibility denotes the ability to disengage from a current task and shift one's focus to a different activity. An individual's level of flexibility is not fixed; rather, people adapt their readiness to switch tasks to changing circumstances. We here review recent studies in the task-switching literature that have produced new insights into the contextual factors that drive this adaptation of flexibility, as well as proposals regarding the underlying cognitive mechanisms and learning processes. A fast-growing literature suggests that there are several different means of learning the need for, and implementing, changes in one's level of flexibility. These, in turn, have distinct consequences for the degree to which adjustments in cognitive flexibility are transferrable to new stimuli and tasks.

Epilepsy is highly prevalent and notoriously pharmacoresistant. New therapeutic interventions are urgently needed, both for preventing the seizures themselves as well as negative outcomes and comorbidities associated with chronic epilepsy. While the cerebellum is not traditionally associated with epilepsy or seizures, research over the past decade has outlined the cerebellum as a brain region that is uniquely suited for both therapeutic needs. This review discusses our current understanding of the cerebellum as a key node within seizure networks, capable of both attenuating seizures in several animal models, and conversely, prone to altered structure and function in chronic epilepsy. Critical next steps are to advance therapeutic modulation of the cerebellum more towards translation, and to provide a more comprehensive characterization of how the cerebellum is impacted by chronic epilepsy, in order to subvert negative outcomes.

Understanding behavior in aging has benefited greatly from cognitive neuroscience. Our foundational understanding of the brain in advanced age is based on what now amounts to several decades of work demonstrating differences in brain structure, network organization, and function. Earlier work in this field was focused primarily on the prefrontal cortex and hippocampus. More recent evidence has expanded our understanding of the aging brain to also implicate the cerebellum. Recent frameworks have suggested that the cerebellum may act as scaffolding for cortical function, and there is an emerging literature implicating the structure in Alzheimer's disease. At this juncture, there is evidence highlighting the potential importance of the cerebellum in advanced age, though the field of study is relatively nascent. Here, we provide an overview of key findings in the literature as it stands now and highlight several key future directions for study with respect to the cerebellum in aging.

Dehumanization has been characterized as common in medical settings, despite limited work directly examining this. In this context, everyday dehumanization is believed to be largely unconscious and unintentional, resulting from a variety of factors often related to structural and organizational aspects of healthcare. This article adopts the patients' and the healthcare providers' perspective to explore how dehumanization can have helpful and hurtful effects on patient outcomes and provider well-being. Future directions include more direct assessment of dehumanization in healthcare settings, centering the needs and experiences of people with mental illness and comorbid conditions, and improving our understanding of dehumanization relative to emotion regulation processes.

People from low- and middle-income countries (LMICs) represent large portions of the world population, often occupy less favorable living conditions, and typically suffer greater health risks, yet frequently receive little research and global health attention. The present study reviews emerging evidence on problematic use of the Internet (PUI) in LMICs prior/during the COVID-19 pandemic. Analyzed studies mainly focused on general properties of PUI in university students, problematic gaming in youth, or problematic use of social media in adults, registering higher prevalence estimates, as compared with earlier reports. Research mainly focused on initially affected regions and COVID-exposed populations. Overall, unfavorable circumstances, including poor social support, family relationships, and lifestyle tendencies/habits, may present potential risk for PUI in LMICs, likely exacerbated during the pandemic.

Cyberchondria (CYB) is characterized by excessive online searching for medical information and is associated with increasing levels of distress, anxiety, and interference with daily activities. As the use of digital devices and the Internet as a source of everyday information has increased, particularly during the current coronavirus disease (COVID-19) pandemic, so has CYB, becoming an object of interest to clinicians and researchers. The present review will provide an overview of the latest updates in CYB research. Emerging evidence draws attention to various vulnerability factors for developing CYB, including personal characteristics such as female gender, younger age, or a history of mental disorder, as well as engagement in particular forms of online behavior, such as increased use of social media, increased acceptance of online information, and information overload. Additionally, recent studies suggest that CYB may itself act as a mediating factor for increased COVID-19-related psychological burden. However, the data are still very sparse. Knowledge gaps include a universally accepted definition of CYB, severity thresholds to help differentiate nonpathological online health searches from CYB, as well as robustly evidence-based interventions.

The present paper reviews recent studies on problematic Internet use (PIU) prevalence before and during the coronavirus disease 2019 (COVID-19) pandemic. Several pre-pandemic meta-analyses reported PIU prevalence estimates ranging from 6% to 9.7%. Experts in the field of online addictions speculated that PIU would increase during the pandemic because of increased time spent on the Internet. However, it is still unclear if increased time on the Internet resulted in higher PIU prevalence estimates during the pandemic. Prevalence estimates differed greatly across studies during the COVID-19 pandemic. Possible inconsistencies are outlined together with future directions for PIU prevalence studies.

Problematic Usage of the Internet (PUI) represents a spectrum of excessive online behaviors and is linked to reduced quality of life and high rates of psychiatric comorbidity, with growing demand for effective treatments. This paper provides a narrative review of pharmacological studies for PUI conducted to date. Most pharmacological treatment trials have focused on bupropion and escitalopram or involved samples with common comorbidities and used current treatments for the relevant comorbid disorders. Overall, there remains a dearth of high-quality evidence, with the current literature lacking control groups, large sample sizes, validated outcome measures, longer term treatment and follow-up periods. The literature cannot at this stage determine evidence-based pharmacological treatments for PUI.

This Current Opinion in Behavioral Sciences article reviews trials that evaluated an obesity treatment that combines response-inhibition training with high-calorie foods and training designed to reduce attention for high-calorie foods. Two randomized controlled trials suggest that food-response inhibition and attention training produced significant body-fat loss, along with a reduction in valuation of, and reward-region response to, high-calorie foods. However, these effects did not emerge in a third trial, potentially because this trial used more heterogeneous food images, which reduced inhibition learning and attentional learning. Collectively, results suggest that food-response inhibition and attention training can devalue high-calorie foods and result in weight loss, but only if a homogeneous set of high-calorie and low-calorie food images is used.

Behavioral inhibition (BI), an infant temperament characterized by distress to novelty, is amongst the strongest early risk markers for future anxiety. In this review, we highlight three ways that recent research elucidates key details about the pathophysiology of anxiety in individuals with BI. First, atypical amygdala connectivity during infancy may be related to BI. Second, developmental shifts in cognitive control may portend risk for anxiety for children with BI. Lastly, distinct cognitive control processes moderate the BI-anxiety relation in different ways. Studying the intersection of these three streams of work may inform prevention or intervention work.

Interest in studying cognitive ecology has moved the field of animal cognition into the wild. Animals face many challenges such as finding food and other resources, avoiding and deterring predators and choosing the best mate to increase their reproductive success. To solve these dilemmas, animals need to rely on a range of cognitive abilities. Studying cognition in natural settings is a powerful approach revealing the link between adaptive form and biological function. Recent technological and analytical advances opened up completely new opportunities and research directions for studying animal cognition. Such innovative studies were able to disclose the variety in cognitive processes that animals use to survive and reproduce. Cognition indeed plays a major role in the daily lives of wild animals, in which the integration of many different types of information using a diverse range of cognitive processes enhances fitness.

The amygdala plays a central role in emotion and social behavior, yet its role in processing social and affective touch is not well established. Longitudinal studies reveal that touch-deprived infants show later in life exaggerated emotional reactivity related to structural and functional changes in the amygdala and other brain structures. The internal organization and connectivity of the amygdala is well-suited to process the sensory features of tactile stimuli and also the socio-cognitive dimensions of the received touch. The convergent processing of bottom-up and top-down pathways that carry information about touch results in the elaboration of context appropriate autonomic responses. Indeed, the positive value of affective touch in humans and social grooming in non-human primates is correlated with vagal tone and the release of oxytocin and endogenous opioids. Grooming, the non-human primate equivalent of affective touch in humans, reduces vigilance, that depends on the amygdala. During touch-induced vagal tone and low vigilance, neural activity in the amygdala is substantially different from activity corresponding to the attentive processing of tactile stimuli. Under these circumstances neurons no longer respond phasically to each touch stimulus, rather they signal a sustained functional state in which the amygdala appears decoupled from monitoring the external environment.

Modern lifestyle and adversities such as the COVID-19 pandemic pose challenges for our physical and mental health. Hence, it is of the utmost importance to identify mechanisms by which we can improve resilience to stress and quickly adapt to adversity. While there are several factors that improve stress resilience, social behavior-primarily in the form of social touch-is especially vital. This article provides an overview of how the somatosensory system plays a key role in translating the socio-emotional information of social touch into active coping with stress. Important future directions include evaluating in humans whether stress resilience can be modulated through the stimulation of low-threshold C-fiber mechanoreceptors and using this technology in the prevention of stress-related neuropsychiatric disorders such as major depressive disorder.

Here we argue that the assignment of subjective value to potential outcomes at the time of decision-making is an active process, in which individual features of a potential outcome of varying degrees of abstraction are represented hierarchically and integrated in a weighted fashion to produce an overall value judgment. We implicate the lateral orbital and medial prefrontal cortex in this function, situating these areas more broadly within a hierarchical integration process that takes place throughout the cortex for the ultimate purpose of valuing options to guide decisions.

Reinforcement learning is a powerful framework for modelling the cognitive and neural substrates of learning and decision making. Contemporary research in cognitive neuroscience and neuroeconomics typically uses value-based reinforcement-learning models, which assume that decision-makers choose by comparing learned values for different actions. However, another possibility is suggested by a simpler family of models, called . Policy-gradient models learn by optimizing a behavioral policy directly, without the intermediate step of value-learning. Here we review recent behavioral and neural findings that are more parsimoniously explained by policy-gradient models than by value-based models. We conclude that, despite the ubiquity of 'value' in reinforcement-learning models of decision making, policy-gradient models provide a lightweight and compelling alternative model of operant behavior.

Although the orbitofrontal cortex (OFC) robustly encodes value during preference decisions, it also encodes multiple non-value features of choice options. The role of this information, and its relationship to the options' overall value remain open questions. In this opinion, we attempt to disentangle oft-studied categories of option information - identity and attributes - in the context of both classic theories of economic choice and contradicting evidence of choice biases in multi-attribute decisions. In doing so, we aim to set forth considerations for understanding the wide variety of decision-relevant information encoded by the OFC during preference decisions.

The brain is an endocrine organ whose day-to-day function is tied to the rhythmic production of neuromodulatory hormones. Yet, traditional approaches to studying brain-hormone relationships in humans are often coarse in scope. By contrast, dense-sampling neuroimaging offers the unique ability to probe dynamic interactions between the nervous and endocrine systems. This review summarizes recent evidence of sex hormones' influence on structural and functional properties of the human brain. In particular, findings from the '28andMe' project suggest that estradiol modulates the topology of large-scale functional brain networks and progesterone rapidly shapes medial temporal lobe morphology across the menstrual cycle. This nascent body of work sets the stage for additional studies in larger cohorts. We end by discussing the potential of dense-sampling designs to further elucidate endocrine modulation of the brain, with implications for personalized medicine.

Reinforcement learning (RL) models have advanced our understanding of how animals learn and make decisions, and how the brain supports some aspects of learning. However, the neural computations that are explained by RL algorithms fall short of explaining many sophisticated aspects of human decision making, including the generalization of learned information, one-shot learning, and the synthesis of task information in complex environments.. Instead, these aspects of instrumental behavior are assumed to be supported by the brain's executive functions (EF). We review recent findings that highlight the importance of EF in learning. Specifically, we advance the theory that EF sets the stage for canonical RL computations in the brain, providing inputs that broaden their flexibility and applicability. Our theory has important implications for how to interpret RL computations in the brain and behavior.

Reinforcement learning models have been productively applied to identify neural correlates of the value of social information. However, by operationalizing social information as a lean, reward-predictive cue, this literature underestimates the richness of human social learning: Humans readily go beyond action-outcome mappings and can draw flexible inferences from a single observation. We argue that computational models of social learning need , i.e, a generative model of how others' unobservable mental states cause their observable actions. Recent advances in inferential social learning suggest that even young children learn from others by using an intuitive, generative model of other minds. Bridging developmental, Bayesian, and reinforcement learning perspectives can enrich our understanding of the neural bases of distinctively human social learning.

In the real world, uncertainty is omnipresent due to incomplete or noisy information. This makes inferring the state-of-the-world difficult. Furthermore, the state-of-the-world often changes over time, though with some regularity. This makes learning and decision-making challenging. Organisms have evolved to take advantage of environmental regularities, that allow organisms to acquire a model of the world and perform model-based inference to robustly make decisions and adjust behavior efficiently under uncertainty. Recent research has shed light on many aspects of model-based inference and its neural underpinnings. Here we review recent progress on hidden-state inference, state transition inference, and hierarchical inference processes.