Annual Review of Neuroscience - Current Issue

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.

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.

To perform computations with the efficiency necessary for animal survival, neocortical microcircuits must be capable of reconfiguring in response to experience, while carefully regulating excitatory and inhibitory connectivity to maintain stable function. This dynamic fine-tuning is accomplished through a rich array of cellular homeostatic plasticity mechanisms that stabilize important cellular and network features such as firing rates, information flow, and sensory tuning properties. Further, these functional network properties can be stabilized by different forms of homeostatic plasticity, including mechanisms that target excitatory or inhibitory synapses, or that regulate intrinsic neuronal excitability. Here we discuss which aspects of neocortical circuit function are under homeostatic control, how this homeostasis is realized on the cellular and molecular levels, and the pathological consequences when circuit homeostasis is impaired. A remaining challenge is to elucidate how these diverse homeostatic mechanisms cooperate within complex circuits to enable them to be both flexible and stable.

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.

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.

The cochlear implant (CI) is considered the most successful neuroprosthesis as it enables speech comprehension in the majority of the million otherwise deaf patients. In hearing by electrical stimulation of the auditory nerve, the broad spread of current from each electrode acts as a bottleneck that limits the transfer of sound frequency information. Hence, there remains a major unmet medical need for improving the quality of hearing with CIs. Recently, optogenetic stimulation of the cochlea has been suggested as an alternative approach for hearing restoration. Cochlear optogenetics promises to transfer more sound frequency information, hence improving hearing, as light can conveniently be confined in space to activate the auditory nerve within smaller tonotopic ranges. In this review, we discuss the latest experimental and technological developments of optogenetic hearing restoration and outline remaining challenges en route to clinical translation.

Over 40% of the human genome is composed of retrotransposons, DNA species that hold the potential to replicate via an RNA intermediate and are evolutionarily related to retroviruses. Retrotransposons are most studied for their ability to jump within a genome, which can cause DNA damage and novel insertional mutations. Retrotransposon-encoded products, including viral-like proteins, double-stranded RNAs, and extrachromosomal circular DNAs, can also be potent activators of the innate immune system. A growing body of evidence suggests that retrotransposons are activated in age-related neurodegenerative disorders and that such activation causally contributes to neurotoxicity. Here we provide an overview of retrotransposon biology and outline evidence of retrotransposon activation in age-related neurodegenerative disorders, with an emphasis on those involving TAR-DNA binding protein-43 (TDP-43) and tau. Studies to date provide the basis for ongoing clinical trials and hold promise for innovative strategies to ameliorate the adverse effects of retrotransposon dysregulation in neurodegenerative disorders.

The cerebellum has a well-established role in controlling motor functions, including coordination, posture, and the learning of skilled movements. The mechanisms for how it carries out motor behavior remain under intense investigation. Interestingly though, in recent years the mechanisms of cerebellar function have faced additional scrutiny since nonmotor behaviors may also be controlled by the cerebellum. With such complexity arising, there is now a pressing need to better understand how cerebellar structure, function, and behavior intersect to influence behaviors that are dynamically called upon as an animal experiences its environment. Here, we discuss recent experimental work that frames possible neural mechanisms for how the cerebellum shapes disparate behaviors and why its dysfunction is catastrophic in hereditary and acquired conditions—both motor and nonmotor. For these reasons, the cerebellum might be the ideal therapeutic target.

Ant physiology has been fashioned by 100 million years of social evolution. Ants perform many sophisticated social and collective behaviors yet possess nervous systems similar in schematic and scale to that of the fruit fly Drosophila melanogaster, a popular solitary model organism. Ants are thus attractive complementary subjects to investigate adaptations pertaining to complex social behaviors that are absent in flies. Despite research interest in ant behavior and the neurobiological foundations of sociality more broadly, our understanding of the ant nervous system is incomplete. Recent technical advances have enabled cutting-edge investigations of the nervous system in a fashion that is less dependent on model choice, opening the door for mechanistic social insect neuroscience. In this review, we revisit important aspects of what is known about the ant nervous system and behavior, and we look forward to how functional circuit neuroscience in ants will help us understand what distinguishes solitary animals from highly social ones.

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing–dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps.

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.

The intricate network of the brain's neurons and synapses poses unparalleled challenges for research, distinct from other biological studies. This is particularly true when dissecting how neurons and their functional units work at a cell biological level. While traditional microscopy has been foundational, it was unable to reveal the deeper complexities of neural interactions. However, an imaging renaissance has transformed our capabilities. Advancements in light and electron microscopy, combined with correlative imaging, now achieve unprecedented resolutions, uncovering the most nuanced neural structures. Maximizing these tools requires more than just technical proficiency. It is crucial to align research aims, allocate resources wisely, and analyze data effectively. At the heart of this evolution is interdisciplinary collaboration, where various experts come together to translate detailed imagery into significant biological insights. This review navigates the latest developments in microscopy, underscoring both the promise of and prerequisites for bending this powerful tool set to understanding neuronal cell biology.

The zebrafish visual system has become a paradigmatic preparation for behavioral and systems neuroscience. Around 40 types of retinal ganglion cells (RGCs) serve as matched filters for stimulus features, including light, optic flow, prey, and objects on a collision course. RGCs distribute their signals via axon collaterals to 12 retinorecipient areas in forebrain and midbrain. The major visuomotor hub, the optic tectum, harbors nine RGC input layers that combine information on multiple features. The retinotopic map in the tectum is locally adapted to visual scene statistics and visual subfield–specific behavioral demands. Tectal projections to premotor centers are topographically organized according to behavioral commands. The known connectivity in more than 20 processing streams allows us to dissect the cellular basis of elementary perceptual and cognitive functions. Visually evoked responses, such as prey capture or loom avoidance, are controlled by dedicated multistation pathways that—at least in the larva—resemble labeled lines. This architecture serves the neuronal code's purpose of driving adaptive behavior.

It has long been argued that only humans could produce and understand language. But now, for the first time, artificial language models (LMs) achieve this feat. Here we survey the new purchase LMs are providing on the question of how language is implemented in the brain. We discuss why, a priori, LMs might be expected to share similarities with the human language system. We then summarize evidence that LMs represent linguistic information similarly enough to humans to enable relatively accurate brain encoding and decoding during language processing. Finally, we examine which LM properties—their architecture, task performance, or training—are critical for capturing human neural responses to language and review studies using LMs as in silico model organisms for testing hypotheses about language. These ongoing investigations bring us closer to understanding the representations and processes that underlie our ability to comprehend sentences and express thoughts in language.

Seeing in three dimensions is a major property of the visual system in mammals. The circuit underlying this property begins in the retina, from which retinal ganglion cells (RGCs) extend to the same or opposite side of the brain. RGC axons decussate to form the optic chiasm, then grow to targets in the thalamus and midbrain, where they synapse with neurons that project to the visual cortex. Here we review the cellular and molecular mechanisms of RGC axonal growth cone guidance across or away from the midline via receptors to cues in the midline environment. We present new views on the specification of ipsi- and contralateral RGC subpopulations and factors implementing their organization in the optic tract and termination in subregions of their targets. Lastly, we describe the functional and behavioral aspects of binocular vision, focusing on the mouse, and discuss recent discoveries in the evolution of the binocular circuit.

Since its recent discovery, the meningeal lymphatic system has reshaped our understanding of central nervous system (CNS) fluid exchange, waste clearance, immune cell trafficking, and immune privilege. Meningeal lymphatics have also been demonstrated to functionally modify the outcome of neurological disorders and their responses to treatment, including brain tumors, inflammatory diseases such as multiple sclerosis, CNS injuries, and neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. In this review, we discuss recent evidence of the contribution of meningeal lymphatics to neurological diseases, as well as the available experimental methods for manipulating meningeal lymphatics in these conditions. Finally, we also provide a discussion of the pressing questions and challenges in utilizing meningeal lymphatics as a prime target for CNS therapeutic intervention and possibly drug delivery for brain disorders.

The activity patterns of grid cells form distinctively regular triangular lattices over the explored spatial environment and are largely invariant to visual stimuli, animal movement, and environment geometry. These neurons present numerous fascinating challenges to the curious (neuro)scientist: What are the circuit mechanisms responsible for creating spatially periodic activity patterns from the monotonic input-output responses of single neurons? How and why does the brain encode a local, nonperiodic variable—the allocentric position of the animal—with a periodic, nonlocal code? And, are grid cells truly specialized for spatial computations? Otherwise, what is their role in general cognition more broadly? We review efforts in uncovering the mechanisms and functional properties of grid cells, highlighting recent progress in the experimental validation of mechanistic grid cell models, and discuss the coding properties and functional advantages of the grid code as suggested by continuous attractor network models of grid cells.

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.