Annual review of neuroscience最新文献

Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key challenge in context-dependent learning that had been largely ignored previously: Under naturalistic conditions, context is typically uncertain, necessitating contextual inference. We review a theoretical approach to formalizing context-dependent learning in the face of contextual uncertainty and the core computations it requires. We show how this approach begins to organize a large body of disparate experimental observations, from multiple levels of brain organization (including circuits, systems, and behavior) and multiple brain regions (most prominently the prefrontal cortex, the hippocampus, and motor cortices), into a coherent framework. We argue that contextual inference may also be key to understanding continual learning in the brain. This theory-driven perspective places contextual inference as a core component of learning.

Despite increasing evidence of its involvement in several key functions of the cerebral cortex, the vestibular sense rarely enters our consciousness. Indeed, the extent to which these internal signals are incorporated within cortical sensory representation and how they might be relied upon for sensory-driven decision-making, during, for example, spatial navigation, is yet to be understood. Recent novel experimental approaches in rodents have probed both the physiological and behavioral significance of vestibular signals and indicate that their widespread integration with vision improves both the cortical representation and perceptual accuracy of self-motion and orientation. Here, we summarize these recent findings with a focus on cortical circuits involved in visual perception and spatial navigation and highlight the major remaining knowledge gaps. We suggest that vestibulo-visual integration reflects a process of constant updating regarding the status of self-motion, and access to such information by the cortex is used for sensory perception and predictions that may be implemented for rapid, navigation-related decision-making.

Striosomes form neurochemically specialized compartments of the striatum embedded in a large matrix made up of modules called matrisomes. Striosome-matrix architecture is multiplexed with the canonical direct-indirect organization of the striatum. Striosomal functions remain to be fully clarified, but key information is emerging. First, striosomes powerfully innervate nigral dopamine-containing neurons and can completely shut down their activity, with a following rebound excitation. Second, striosomes receive limbic and cognition-related corticostriatal afferents and are dynamically modulated in relation to value-based actions. Third, striosomes are spatially interspersed among matrisomes and interneurons and are influenced by local and global neuromodulatory and oscillatory activities. Fourth, striosomes tune engagement and the motivation to perform reinforcement learning, to manifest stereotypical behaviors, and to navigate valence conflicts and valence discriminations. We suggest that, at an algorithmic level, striosomes could serve as distributed scaffolds to provide formats of the striatal computations generated through development and refined through learning. We propose that striosomes affect subjective states. By transforming corticothalamic and other inputs to the functional formats of the striatum, they could implement state transitions in nigro-striato-nigral circuits to affect bodily and cognitive actions according to internal motives whose functions are compromised in neuropsychiatric conditions.

Cell replacement therapy represents a promising approach for treating neurodegenerative diseases. Contrary to the common addition strategy to generate new neurons from glia by overexpressing a lineage-specific transcription factor(s), a recent study introduced a subtraction strategy by depleting a single RNA-binding protein, Ptbp1, to convert astroglia to neurons not only in vitro but also in the brain. Given its simplicity, multiple groups have attempted to validate and extend this attractive approach but have met with difficulty in lineage tracing newly induced neurons from mature astrocytes, raising the possibility of neuronal leakage as an alternative explanation for apparent astrocyte-to-neuron conversion. This review focuses on the debate over this critical issue. Importantly, multiple lines of evidence suggest that Ptbp1 depletion can convert a selective subpopulation of glial cells into neurons and, via this and other mechanisms, reverse deficits in a Parkinson's disease model, emphasizing the importance of future efforts in exploring this therapeutic strategy.

In mammals, the activity of neurons in the entorhinal-hippocampal network is modulated by the animal's position and its movement through space. At multiple stages of this distributed circuit, distinct populations of neurons can represent a rich repertoire of navigation-related variables like the animal's location, the speed and direction of its movements, or the presence of borders and objects. Working together, spatially tuned neurons give rise to an internal representation of space, a cognitive map that supports an animal's ability to navigate the world and to encode and consolidate memories from experience. The mechanisms by which, during development, the brain acquires the ability to create an internal representation of space are just beginning to be elucidated. In this review, we examine recent work that has begun to investigate the ontogeny of circuitry, firing patterns, and computations underpinning the representation of space in the mammalian brain.

Emotions are fundamental to our experience and behavior, affecting and motivating all aspects of our lives. Scientists of various disciplines have been fascinated by emotions for centuries, yet even today vigorous debates abound about how to define emotions and how to best study their neural underpinnings. Defining emotions from an evolutionary perspective and acknowledging their important functional roles in supporting survival allows the study of emotion states in diverse species. This approach enables taking advantage of modern tools in behavioral, systems, and circuit neurosciences, allowing the precise dissection of neural mechanisms and behavior underlying emotion processes in model organisms. Here we review findings about the neural circuit mechanisms underlying emotion processing across species and try to identify points of convergence as well as important next steps in the pursuit of understanding how emotions emerge from neural activity.

Examination of cognition has historically been approached from language and introspection. However, human language-dependent definitions ignore the evolutionary roots of brain mechanisms and constrain their study in experimental animals. We promote an alternative view, namely that cognition, including memory, can be explained by exaptation and expansion of the circuits and algorithms serving bodily functions. Regulation and protection of metabolic and energetic processes require time-evolving brain computations enabling the organism to prepare for altered future states. Exaptation of such circuits was likely exploited for exploration of the organism's niche. We illustrate that exploration gives rise to a cognitive map, and in turn, environment-disengaged computation allows for mental travel into the past (memory) and the future (planning). Such brain-body interactions not only occur during waking but also persist during sleep. These exaptation steps are illustrated by the dual, endocrine-homeostatic and memory, contributions of the hippocampal system, particularly during hippocampal sharp-wave ripples.

Migraine is a complex neurovascular pain disorder linked to the meninges, a border tissue innervated by neuropeptide-containing primary afferent fibers chiefly from the trigeminal nerve. Electrical or mechanical stimulation of this nerve surrounding large blood vessels evokes headache patterns as in migraine, and the brain, blood, and meninges are likely sources of headache triggers. Cerebrospinal fluid may play a significant role in migraine by transferring signals released from the brain to overlying pain-sensitive meningeal tissues, including dura mater. Interactions between trigeminal afferents, neuropeptides, and adjacent meningeal cells and tissues cause neurogenic inflammation, a critical target for current prophylactic and abortive migraine therapies. Here we review the importance of the cranial meninges to migraine headaches, explore the properties of trigeminal meningeal afferents, and briefly review emerging concepts, such as meningeal neuroimmune interactions, that may one day prove therapeutically relevant.

This review explores the interface between circadian timekeeping and the regulation of brain function by astrocytes. Although astrocytes regulate neuronal activity across many time domains, their cell-autonomous circadian clocks exert a particular role in controlling longer-term oscillations of brain function: the maintenance of sleep states and the circadian ordering of sleep and wakefulness. This is most evident in the central circadian pacemaker, the suprachiasmatic nucleus, where the molecular clock of astrocytes suffices to drive daily cycles of neuronal activity and behavior. In Alzheimer's disease, sleep impairments accompany cognitive decline. In mouse models of the disease, circadian disturbances accelerate astroglial activation and other brain pathologies, suggesting that daily functions in astrocytes protect neuronal homeostasis. In brain cancer, treatment in the morning has been associated with prolonged survival, and gliomas have daily rhythms in gene expression and drug sensitivity. Thus, circadian time is fast becoming critical to elucidating reciprocal astrocytic-neuronal interactions in health and disease.

Primates have evolved diverse cognitive capabilities to navigate their complex social world. To understand how the brain implements critical social cognitive abilities, we describe functional specialization in the domains of face processing, social interaction understanding, and mental state attribution. Systems for face processing are specialized from the level of single cells to populations of neurons within brain regions to hierarchically organized networks that extract and represent abstract social information. Such functional specialization is not confined to the sensorimotor periphery but appears to be a pervasive theme of primate brain organization all the way to the apex regions of cortical hierarchies. Circuits processing social information are juxtaposed with parallel systems involved in processing nonsocial information, suggesting common computations applied to different domains. The emerging picture of the neural basis of social cognition is a set of distinct but interacting subnetworks involved in component processes such as face perception and social reasoning, traversing large parts of the primate brain.