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The glucocorticoid hormones cortisol and corticosterone coordinate circadian events and are master regulators of the stress response. These actions of the glucocorticoids are mediated by mineralocorticoid receptors (NR3C2, or MRs) and glucocorticoid receptors (NR3C1, or GRs). MRs bind the natural glucocorticoids cortisol and corticosterone with a 10-fold higher affinity than GRs. The glucocorticoids are inactivated only in the nucleus tractus solitarii (NTS), rendering the NTS-localized MRs aldosterone-selective and involved in regulation of salt appetite. Everywhere else in the brain MRs are glucocorticoid-preferring. MR and GR are transcription factors involved in gene regulation but recently were also found to mediate rapid non-genomic actions. Genomic MRs, with a predominant localization in limbic circuits, are important for the threshold and sensitivity of the stress response system. Non-genomic MRs promote appraisal processes, memory retrieval, and selection of coping style. Activation of GRs makes energy substrates available and dampens initial defense reactions. In the brain, GR activation enhances appetitive- and fear-motivated behavior and promotes memory storage of the selected coping style in preparation of the future. Thus, MRs and GRs complement each other in glucocorticoid control of the initiation and termination of the stress response, suggesting that the balance in MR- and GR-mediated actions is crucial for homeostasis and health.

Article

The majority of anxiety disorders emerge during childhood and adolescence, a developmental period characterized by dynamic changes in frontolimbic circuitry. Frontolimbic circuitry plays a key role in fear learning and has been a focus of recent efforts to understand the neurobiological correlates of anxiety disorders across development. Although less is known about the neurobiological underpinnings of anxiety disorders in youth than in adults, studies of pediatric anxiety have revealed alterations in both the structure and function of frontolimbic circuitry. The amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), and hippocampus contribute to fear conditioning and extinction, and interactions between these regions have been implicated in anxiety during development. Specifically, children and adolescents with anxiety disorders show altered amygdala volumes and exhibit heightened amygdala activation in response to neutral and fearful stimuli, with the magnitude of signal change in amygdala reactivity corresponding to the severity of symptomatology. Abnormalities in the PFC and ACC and their connections with the amygdala may reflect weakened top-down control or compensatory efforts to regulate heightened amygdala reactivity associated with anxiety. Taken together, alterations in frontolimbic connectivity are likely to play a central role in the etiology and maintenance of anxiety disorders. Future studies should aim to translate the emerging understanding of the neurobiological bases of pediatric anxiety disorders to optimize clinical interventions for youth.

Article

Pedro Martínez, Volker Hartenstein, and Simon G. Sprecher

The emergence and diversification of bilateral animals are among the most important transitions in the history of life on our planet. A proper understanding of the evolutionary process will derive from answering such key questions as, how did complex body plans arise in evolutionary time, and how are complex body plans “encoded” in the genome? the first step is focusing on the earliest stages in bilaterian evolution, probing the most elusive organization of the genomes and microscopic anatomy in basally branching taxa, which are currently assembled in a clade named Xenacoelomorpha. This enigmatic phylum is composed of three major taxa: acoel flatworms, nemertodermatids, and xenoturbellids. Interestingly, the constituent species of this clade have an enormously varied set of morphologies; not just the obvious external features but also their tissues present a high degree of constructional variation. This interesting diversity of morphologies (a clear example being the nervous system, with animals showing different degrees of compaction) provides a unique system in which to address outstanding questions regarding the parallel evolution of genomes and the many morphological characters encoded by them. A systematic exploration of the anatomy of members of these three taxa, employing immunohistochemistry, in situ hybridization, and high-throughput transmission electron microscopy, will provide the reference framework necessary to understand the changing roles of genes and gene networks during the evolution of xenacoelomorph morphologies and, in particular, of their nervous systems.

Article

Navigation is the ability of animals to move through their environment in a planned manner. Different from directed but reflex-driven movements, it involves the comparison of the animal’s current heading with its intended heading (i.e., the goal direction). When the two angles don’t match, a compensatory steering movement must be initiated. This basic scenario can be described as an elementary navigational decision. Many elementary decisions chained together in specific ways form a coherent navigational strategy. With respect to navigational goals, there are four main forms of navigation: explorative navigation (exploring the environment for food, mates, shelter, etc.); homing (returning to a nest); straight-line orientation (getting away from a central place in a straight line); and long-distance migration (seasonal long-range movements to a location such as an overwintering place). The homing behavior of ants and bees has been examined in the most detail. These insects use several strategies to return to their nest after foraging, including path integration, route following, and, potentially, even exploit internal maps. Independent of the strategy used, insects can use global sensory information (e.g., skylight cues), local cues (e.g., visual panorama), and idiothetic (i.e., internal, self-generated) cues to obtain information about their current and intended headings. How are these processes controlled by the insect brain? While many unanswered questions remain, much progress has been made in recent years in understanding the neural basis of insect navigation. Neural pathways encoding polarized light information (a global navigational cue) target a brain region called the central complex, which is also involved in movement control and steering. Being thus placed at the interface of sensory information processing and motor control, this region has received much attention recently and emerged as the navigational “heart” of the insect brain. It houses an ordered array of head-direction cells that use a wide range of sensory information to encode the current heading of the animal. At the same time, it receives information about the movement speed of the animal and thus is suited to compute the home vector for path integration. With the help of neurons following highly stereotypical projection patterns, the central complex theoretically can perform the comparison of current and intended heading that underlies most navigation processes. Examining the detailed neural circuits responsible for head-direction coding, intended heading representation, and steering initiation in this brain area will likely lead to a solid understanding of the neural basis of insect navigation in the years to come.

Article

Divine C. Nwafor, Allison L. Brichacek, Sreeparna Chakraborty, Catheryne A. Gambill, Stanley A. Benkovic, and Candice M. Brown

The blood-brain barrier (BBB) is a dynamic structural interface between the brain and periphery that plays a critical function in maintaining cerebral homeostasis. Over the past two decades, technological advances have improved our understanding of the neuroimmune and neuroendocrine mechanisms that regulate a healthy BBB. The combination of biological sex, sex steroids, age, coupled with innate and adaptive immune components orchestrates the crosstalk between the BBB and the periphery. Likewise, the BBB also serves as a nexus within the hypothalamic-pituitary-adrenal (HPA) and gut-brain-microbiota axes. Compromised BBB integrity permits the entry of bioactive molecules, immune cells, microbes, and other components that migrate into the brain parenchyma and compromise neuronal function. A paramount understanding of the mechanisms that determine the bidirectional crosstalk between the BBB and immune and endocrine pathways has become increasingly important for implementation of therapeutic strategies to treat a number of neurological disorders that are significantly impacted by the BBB. Examples of these disorders include multiple sclerosis, Alzheimer’s disease, stroke, epilepsy, and traumatic brain injury.

Article

The traditional view of central nervous system function presumed that learning is the province of the brain. From this perspective, the spinal cord functions primarily as a conduit for incoming/outgoing neural impulses, capable of organizing simple reflexes but incapable of learning. Research has challenged this view, demonstrating that neurons within the spinal cord, isolated from the brain by means of a spinal cut (transection), can encode environmental relations and that this experience can have a lasting effect on function. The exploration of this issue has been informed by work in the learning literature that establishes the behavioral criteria and work within the pain literature that has shed light on the underlying neurobiological mechanisms. Studies have shown that spinal systems can exhibit single stimulus learning (habituation and sensitization) and are sensitive to both stimulus–stimulus (Pavlovian) and response–outcome (instrumental) relations. Regular environmental relations can both bring about an alteration in the performance of a spinally mediated response and impact the capacity to learn in future situations. The latter represents a form of behavioral metaplasticity. At the neurobiological level, neurons within the central gray matter of the spinal cord induce lasting alterations by engaging the NMDA receptor and signal pathways implicated in brain-dependent learning and memory. Of particular clinical importance, uncontrollable/unpredictable pain (nociceptive) input can induce a form of neural over-excitation within the dorsal horn (central sensitization) that impairs adaptive learning. Pain input after a contusion injury can increase tissue loss and undermines long-term recovery.

Article

Tim C. Kietzmann, Patrick McClure, and Nikolaus Kriegeskorte

The goal of computational neuroscience is to find mechanistic explanations of how the nervous system processes information to give rise to cognitive function and behavior. At the heart of the field are its models, that is, mathematical and computational descriptions of the system being studied, which map sensory stimuli to neural responses and/or neural to behavioral responses. These models range from simple to complex. Recently, deep neural networks (DNNs) have come to dominate several domains of artificial intelligence (AI). As the term “neural network” suggests, these models are inspired by biological brains. However, current DNNs neglect many details of biological neural networks. These simplifications contribute to their computational efficiency, enabling them to perform complex feats of intelligence, ranging from perceptual (e.g., visual object and auditory speech recognition) to cognitive tasks (e.g., machine translation), and on to motor control (e.g., playing computer games or controlling a robot arm). In addition to their ability to model complex intelligent behaviors, DNNs excel at predicting neural responses to novel sensory stimuli with accuracies well beyond any other currently available model type. DNNs can have millions of parameters, which are required to capture the domain knowledge needed for successful task performance. Contrary to the intuition that this renders them into impenetrable black boxes, the computational properties of the network units are the result of four directly manipulable elements: input statistics, network structure, functional objective, and learning algorithm. With full access to the activity and connectivity of all units, advanced visualization techniques, and analytic tools to map network representations to neural data, DNNs represent a powerful framework for building task-performing models and will drive substantial insights in computational neuroscience.