Current Opinion in Neurobiology最新文献

One of the most exciting new developments in systems neuroscience is the progress being made toward neurophysiological experiments that move beyond simplified laboratory settings and address the richness of natural behavior. This is enabled by technological advances such as wireless recording in freely moving animals, automated quantification of behavior, and new methods for analyzing large data sets. Beyond new empirical methods and data, however, there is also a need for new theories and concepts to interpret that data. Such theories need to address the particular challenges of natural behavior, which often differ significantly from the scenarios studied in traditional laboratory settings. Here, we discuss some strategies for developing such novel theories and concepts and some example hypotheses being proposed.

The metabolic signals that regulate sleep and the metabolic functions that occur during sleep are active areas of research. Prior studies have focused on sugars and nucleotides but new genetic evidence suggests novel functions of lipid and amino acid metabolites in sleep. Additional genetic studies of energetic signaling pathways and the circadian clock transcription factor network have increased our understanding of how sleep responds to changes in the metabolic state. This review focuses on key recent insights from genetic experiments in humans and model organisms to improve our understanding of the interrelationship between metabolism and sleep.

Understanding how subjects perceive sensory stimuli in their environment and use this information to guide appropriate actions is a major challenge in neuroscience. To study perceptual decision-making in animals, researchers use tasks that either probe spontaneous responses to stimuli (often described as “naturalistic”) or train animals to associate stimuli with experimenter-defined responses. Spontaneous decisions rely on animals’ pre-existing knowledge, while trained tasks offer greater versatility, albeit often at the cost of extensive training. Here, we review emerging approaches to investigate perceptual decision-making using both spontaneous and trained behaviors, highlighting their strengths and limitations. Additionally, we propose how trained decision-making tasks could be improved to achieve faster learning and a more generalizable understanding of task rules.

The selection and execution of context-appropriate behaviors is controlled by the integrated action of neural circuits throughout the brain. However, how activity is coordinated across brain regions, and how nervous system structure enables these functional interactions, remain open questions. Recent technical advances have made it feasible to build brain-wide maps of nervous system structure and function, such as brain activity maps, connectomes, and cell atlases. Here, we review recent progress in this area, focusing on C. elegans and D. melanogaster, as recent work has produced global maps of these nervous systems. We also describe neural circuit motifs elucidated in studies of specific networks, which highlight the complexities that must be captured to build accurate models of whole-brain function.

The precision of primate visually guided reaching likely evolved to meet the many challenges faced by living in arboreal environments, yet much of what we know about the underlying primate brain organization derives from a set of highly constrained experimental paradigms. Here we review the role of vision to guide natural reach-to-grasp movements in marmoset monkey prey capture to illustrate the breadth and diversity of these behaviors in ethological contexts, the fast predictive nature of these movements [1,2], and the advantages of this particular primate model to investigate the underlying neural mechanisms in more naturalistic contexts [3]. In addition to their amenability to freely-moving neural recording methods for investigating the neural basis of dynamic ethological behaviors [4,5], marmosets have a smooth neocortical surface that facilitates imaging and array recordings [6,7] in all areas in the primate fronto-parietal network [8,9]. Together, this model organism offers novel opportunities to study the real-world interplay between primate vision and reach-to-grasp dynamics using ethologically motivated neuroscientific experimental designs.

The cnidarian Hydra vulgaris is a small polyp with a nervous system of few hundred neurons belonging to a dozen cell types, organized in two nerve nets without cephalization or ganglia. Using this simple neural “chassis”, Hydra can maintain a stable repertoire of behaviors, even performing complex fixed-action patterns, such as somersaulting and feeding. The ability to image the activity of Hydra's entire neural and muscle tissue has revealed that Hydra's nerve nets are divided into coactive ensembles of neurons, associated with specific movements. These ensembles can be activated by neuropeptides and interact using cross-inhibition circuits and implement integrate-to-threshold algorithms. In addition, Hydra's nervous system can self-assemble from dissociated cells in a stepwise modular architecture. Studies of Hydra and other cnidarians could enable the systematic deciphering of the neural basis of its behavior and help provide perspective on basic principles of neuroscience.

The homing pigeon is the foundational model species used to investigate the neural control of avian navigation. The olfactory system is critically involved in implementing the so-called olfactory map, used to locate position relative to home from unfamiliar locations. The hippocampal formation supports a complementary navigational system based on familiar visual landmarks. Insight into the neural control of pigeon navigation has been revolutionised by GPS-tracking technology, which has been crucial for both detailing the critical role of environmental odours for navigation over unfamiliar areas as well as offering unprecedented insight into the role of the hippocampal formation in visual landscape/landmark-based navigation, including a possible, unexpected role in visual–spatial perception.

Advances in autism spectrum disorder (ASD) genetics have identified many genetic causes, reflecting remarkable progress while at the same time identifying challenges such as heterogeneity and pleiotropy, which complicate attempts to connect genetic risk to mechanisms. High-throughput functional genomic approaches have yielded progress by defining a molecular pathology in the brain of individuals with ASD and in identifying convergent biological pathways through which risk genes are predicted to act. These studies indicate that ASD genetic risk converges in early brain development, primarily during the period of cortical neurogenesis. Over development, genetic perturbations in turn lead to broad neuronal signaling dysregulation, most prominent in glutamatergic cortical-cortical projecting neurons and somatostatin positive interneurons, which is accompanied by glial dyshomeostasis throughout the cerebral cortex. Connecting these developmental perturbations to disrupted neuronal and glial function in the postnatal brain is an important direction in current research. Coupling functional genomic approaches with advances in induced pluripotent stem cell-derived neural organoid development provides a promising avenue for connecting brain pathology to developmental mechanisms.