Annual review of neuroscience最新文献

Cognition unfolds dynamically over flexible timescales. A major goal of the field is to understand the computational and neurobiological principles that enable this flexibility. Here, we argue that the neurobiology of timing provides a platform for tackling these questions. We begin with an overview of proposed coding schemes for the representation of elapsed time, highlighting their computational properties. We then leverage the one-dimensional and unidirectional nature of time to highlight common principles across these coding schemes. These principles facilitate a precise formulation of questions related to the flexible control, variability, and calibration of neural dynamics. We review recent work that demonstrates how dynamical systems analysis of thalamocortical population activity in timing tasks has provided fundamental insights into how the brain calibrates and flexibly controls neural dynamics. We conclude with speculations about the architectural biases and neural substrates that support the control and calibration of neural dynamics more generally.

Locomotion, like all behaviors, possesses an inherent flexibility that allows for the scaling of movement kinematic features, such as speed and vigor, in response to an ever-changing external world and internal drives. This flexibility is embedded in the organization of the spinal locomotor circuits, which encode and decode commands from the brainstem and proprioceptive feedback. This review highlights our current understanding of the modular organization of these locomotor circuits and how this modularity endows them with intrinsic mechanisms to adjust speed and vigor, thereby contributing to the flexibility of locomotor movements.

The twenty-first century has brought forth a deluge of theories and data shedding light on the neural mechanisms of motivated behavior. Much of this progress has focused on dopaminergic dynamics, including their signaling properties (how do they vary with expectations and outcomes?) and their downstream impacts in target regions (how do they affect learning and behavior?). In parallel, the basal ganglia have been elevated from their original implication in motoric function to a canonical circuit facilitating the initiation, invigoration, and selection of actions across levels of abstraction, from motor to cognitive operations. This review considers how striatal D1 and D2 opponency allows animals to perform cost-benefit calculations across multiple scales: locally, whether to select a given action, and globally, whether to engage a particular corticostriatal circuit for guiding behavior. An emerging understanding of such functions reconciles seemingly conflicting data and has implications for neuroscience, psychology, behavioral economics, and artificial intelligence.

Deep brain stimulation (DBS), a method in which electrical stimulation is delivered to specific areas of the brain, is an effective treatment for managing symptoms of a number of neurological and neuropsychiatric disorders. Clinical access to neural circuits during DBS provides an opportunity to study the functional link between neural circuits and behavior. This review discusses how the use of DBS in Parkinson's disease and dystonia has provided insights into the brain networks and physiological mechanisms that underlie motor control. In parallel, insights from basic science about how patterns of electrical stimulation impact plasticity and communication within neural circuits are transforming DBS from a therapy for treating symptoms to a therapy for treating circuits, with the goal of training the brain out of its diseased state.

Auditory processing in mammals begins in the peripheral inner ear and extends to the auditory cortex. Sound is transduced from mechanical stimuli into electrochemical signals of hair cells, which relay auditory information via the primary auditory neurons to cochlear nuclei. Information is subsequently processed in the superior olivary complex, lateral lemniscus, and inferior colliculus and projects to the auditory cortex via the medial geniculate body in the thalamus. Recent advances have provided valuable insights into the development and functioning of auditory structures, complementing our understanding of the physiological mechanisms underlying auditory processing. This comprehensive review explores the genetic mechanisms required for auditory system development from the peripheral cochlea to the auditory cortex. We highlight transcription factors and other genes with key recurring and interacting roles in guiding auditory system development and organization. Understanding these gene regulatory networks holds promise for developing novel therapeutic strategies for hearing disorders, benefiting millions globally.

The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.

In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.

Predictive processing is a computational framework that aims to explain how the brain processes sensory information by making predictions about the environment and minimizing prediction errors. It can also be used to explain some of the key symptoms of psychotic disorders such as schizophrenia. In recent years, substantial advances have been made in our understanding of the neuronal circuitry that underlies predictive processing in cortex. In this review, we summarize these findings and how they might relate to psychosis and to observed cell type-specific effects of antipsychotic drugs. We argue that quantifying the effects of antipsychotic drugs on specific neuronal circuit elements is a promising approach to understanding not only the mechanism of action of antipsychotic drugs but also psychosis. Finally, we outline some of the key experiments that should be done. The aims of this review are to provide an overview of the current circuit-based approaches to psychosis and to encourage further research in this direction.

It is a common view that the intricate array of specialized domains in the ventral visual pathway is innately prespecified. What this review postulates is that it is not. We explore the origins of domain specificity, hypothesizing that the adult brain emerges from an interplay between a domain-general map-based architecture, shaped by intrinsic mechanisms, and experience. We argue that the most fundamental innate organization of cortex in general, and not just the visual pathway, is a map-based topography that governs how the environment maps onto the brain, how brain areas interconnect, and ultimately, how the brain processes information.