Annual review of neuroscience最新文献

Social interactions involve processes ranging from face recognition to understanding others' intentions. To guide appropriate behavior in a given context, social interactions rely on accurately predicting the outcomes of one's actions and the thoughts of others. Because social interactions are inherently dynamic, these predictions must be continuously adapted. The neural correlates of social processing have largely focused on emotion, mentalizing, and reward networks, without integration of systems involved in prediction. The cerebellum forms predictive models to calibrate movements and adapt them to changing situations, and cerebellar predictive modeling is thought to extend to nonmotor behaviors. Primary cerebellar dysfunction can produce social deficits, and atypical cerebellar structure and function are reported in autism, which is characterized by social communication challenges and atypical predictive processing. We examine the evidence that cerebellar-mediated predictions and adaptation play important roles in social processes and argue that disruptions in these processes contribute to autism.

What changes in neural architecture account for the emergence and expansion of dexterity in primates? Dexterity, or skill in performing motor tasks, depends on the ability to generate highly fractionated patterns of muscle activity. It also involves the spatiotemporal coordination of activity in proximal and distal muscles across multiple joints. Many motor skills require the generation of complex movement sequences that are only acquired and refined through extensive practice. Improvements in dexterity have enabled primates to manufacture and use tools and humans to engage in skilled motor behaviors such as typing, dance, musical performance, and sports. Our analysis leads to the following synthesis: The neural substrate that endows primates with their enhanced motor capabilities is due, in part, to (a) major organizational changes in the primary motor cortex and (b) the proliferation of output pathways from other areas of the cerebral cortex, especially from the motor areas on the medial wall of the hemisphere.

Nearly all structures in our body experience mechanical forces. At a molecular scale, these forces are detected by ion channels that function as mechanotransducers converting physical forces into electrochemical responses. Here we focus on PIEZOs, a family of mechanically activated ion channels comprising PIEZO1 and PIEZO2. The significance of these channels is highlighted by their roles in touch and pain sensation as well as in cardiovascular and respiratory physiology, among others. Moreover, mutations in PIEZOs cause somatosensory, proprioceptive, and blood disorders. The goal here is to present the diverse physiology and pathophysiology of these unique channels, discuss ongoing research and critical gaps in the field, and explore the pharmaceutical interest in targeting PIEZOs for therapeutic development.

Comparative neuroscience is entering the era of big data. New high-throughput methods and data-sharing initiatives have resulted in the availability of large, digital data sets containing many types of data from ever more species. Here, we present a framework for exploiting the new possibilities offered. The multimodality of the data allows vertical translations, which are comparisons of different aspects of brain organization within a single species and across scales. Horizontal translations compare particular aspects of brain organization across species, often by building abstract feature spaces. Combining vertical and horizontal translations allows for more sophisticated comparisons, including relating principles of brain organization across species by contrasting horizontal translations, and for making formal predictions of unobtainable data based on observed results in a model species.

As a frontal node in the primate social brain, the medial prefrontal cortex (MPFC) plays a critical role in coordinating one's own behavior with respect to that of others. Current literature demonstrates that single neurons in the MPFC encode behavior-related variables such as intentions, actions, and rewards, specifically for self and other, and that the MPFC comes into play when reflecting upon oneself and others. The social moderator account of MPFC function can explain maladaptive social cognition in people with autism spectrum disorder, which tips the balance in favor of self-centered perspectives rather than taking into consideration the perspective of others. Several strands of evidence suggest a hypothesis that the MPFC represents different other mental models, depending on the context at hand, to better predict others' emotions and behaviors. This hypothesis also accounts for aberrant MPFC activity in autistic individuals while they are mentalizing others.

The central theme of this review is the dynamic interaction between information selection and learning. We pose a fundamental question about this interaction: How do we learn what features of our experiences are worth learning about? In humans, this process depends on attention and memory, two cognitive functions that together constrain representations of the world to features that are relevant for goal attainment. Recent evidence suggests that the representations shaped by attention and memory are themselves inferred from experience with each task. We review this evidence and place it in the context of work that has explicitly characterized representation learning as statistical inference. We discuss how inference can be scaled to real-world decisions by approximating beliefs based on a small number of experiences. Finally, we highlight some implications of this inference process for human decision-making in social environments.

Addiction is a disease characterized by compulsive drug seeking and consumption observed in 20-30% of users. An addicted individual will favor drug reward over natural rewards, despite major negative consequences. Mechanistic research on rodents modeling core components of the disease has identified altered synaptic transmission as the functional substrate of pathological behavior. While the initial version of a circuit model for addiction focused on early drug adaptive behaviors observed in all individuals, it fell short of accounting for the stochastic nature of the transition to compulsion. The model builds on the initial pharmacological effect common to all addictive drugs-an increase in dopamine levels in the mesolimbic system. Here, we consolidate this early model by integrating circuits underlying compulsion and negative reinforcement. We discuss the genetic and epigenetic correlates of individual vulnerability. Many recent data converge on a gain-of-function explanation for circuit remodeling, revealing blueprints for novel addiction therapies.

Neurons in the brain represent information in their collective activity. The fidelity of this neural population code depends on whether and how variability in the response of one neuron is shared with other neurons. Two decades of studies have investigated the influence of these noise correlations on the properties of neural coding. We provide an overview of the theoretical developments on the topic. Using simple, qualitative, and general arguments, we discuss, categorize, and relate the various published results. We emphasize the relevance of the fine structure of noise correlation, and we present a new approach to the issue. Throughout this review, we emphasize a geometrical picture of how noise correlations impact the neural code.

Maps of the nervous system inspire experiments and theories in neuroscience. Advances in molecular biology over the past decades have revolutionized the definition of cell and tissue identity. Spatial transcriptomics has opened up a new era in neuroanatomy, where the unsupervised and unbiased exploration of the molecular signatures of tissue organization will give rise to a new generation of brain maps. We propose that the molecular classification of brain regions on the basis of their gene expression profile can circumvent subjective neuroanatomical definitions and produce common reference frameworks that can incorporate cell types, connectivity, activity, and other modalities. Here we review the technological and conceptual advances made possible by spatial transcriptomics in the context of advancing neuroanatomy and discuss how molecular neuroanatomy can redefine mapping of the nervous system.

The common marmoset (Callithrix jacchus), a small New World primate, is receiving substantial attention in the neuroscience and biomedical science fields because its anatomical features, functional and behavioral characteristics, and reproductive features and its amenability to available genetic modification technologies make it an attractive experimental subject. In this review, I outline the progress of marmoset neuroscience research and summarize both the current status (opportunities and limitations) of and the future perspectives on the application of marmosets in neuroscience and disease modeling.