Neurotransmitter classification from electron microscopy images at synaptic sites in Drosophila melanogaster.

High-resolution electron microscopy of nervous systems has enabled the reconstruction of synaptic connectomes. However, we do not know the synaptic sign for each connection (i.e., whether a connection is excitatory or inhibitory), which is implied by the released transmitter. We demonstrate that artificial neural networks can predict transmitter types for presynapses from electron micrographs: a network trained to predict six transmitters (acetylcholine, glutamate, GABA, serotonin, dopamine, octopamine) achieves an accuracy of 87% for individual synapses, 94% for neurons, and 91% for known cell types across a D. melanogaster whole brain. We visualize the ultrastructural features used for prediction, discovering subtle but significant differences between transmitter phenotypes. We also analyze transmitter distributions across the brain and find that neurons that develop together largely express only one fast-acting transmitter (acetylcholine, glutamate, or GABA). We hope that our publicly available predictions act as an accelerant for neuroscientific hypothesis generation for the fly.

Atlas of the aging mouse brain reveals white matter as vulnerable foci.

Aging is the key risk factor for cognitive decline, yet the molecular changes underlying brain aging remain poorly understood. Here, we conducted spatiotemporal RNA sequencing of the mouse brain, profiling 1,076 samples from 15 regions across 7 ages and 2 rejuvenation interventions. Our analysis identified a brain-wide gene signature of aging in glial cells, which exhibited spatially defined changes in magnitude. By integrating spatial and single-nucleus transcriptomics, we found that glial aging was particularly accelerated in white matter compared with cortical regions, whereas specialized neuronal populations showed region-specific expression changes. Rejuvenation interventions, including young plasma injection and dietary restriction, exhibited distinct effects on gene expression in specific brain regions. Furthermore, we discovered differential gene expression patterns associated with three human neurodegenerative diseases, highlighting the importance of regional aging as a potential modulator of disease. Our findings identify molecular foci of brain aging, providing a foundation to target age-related cognitive decline.

Hindbrain modules differentially transform activity of single collicular neurons to coordinate movements.

Seemingly simple behaviors such as swatting a mosquito or glancing at a signpost involve the precise coordination of multiple body parts. Neural control of coordinated movements is widely thought to entail transforming a desired overall displacement into displacements for each body part. Here we reveal a different logic implemented in the mouse gaze system. Stimulating superior colliculus (SC) elicits head movements with stereotyped displacements but eye movements with stereotyped endpoints. This is achieved by individual SC neurons whose branched axons innervate modules in medulla and pons that drive head movements with stereotyped displacements and eye movements with stereotyped endpoints, respectively. Thus, single neurons specify a mixture of endpoints and displacements for different body parts, not overall displacement, with displacements for different body parts computed at distinct anatomical stages. Our study establishes an approach for unraveling motor hierarchies and identifies a logic for coordinating movements and the resulting pose.

Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

A brainstem integrator for self-location memory and positional homeostasis in zebrafish.

To track and control self-location, animals integrate their movements through space. Representations of self-location are observed in the mammalian hippocampal formation, but it is unknown if positional representations exist in more ancient brain regions, how they arise from integrated self-motion, and by what pathways they control locomotion. Here, in a head-fixed, fictive-swimming, virtual-reality preparation, we exposed larval zebrafish to a variety of involuntary displacements. They tracked these displacements and, many seconds later, moved toward their earlier location through corrective swimming ("positional homeostasis"). Whole-brain functional imaging revealed a network in the medulla that stores a memory of location and induces an error signal in the inferior olive to drive future corrective swimming. Optogenetically manipulating medullary integrator cells evoked displacement-memory behavior. Ablating them, or downstream olivary neurons, abolished displacement corrections. These results reveal a multiregional hindbrain circuit in vertebrates that integrates self-motion and stores self-location to control locomotor behavior.

Glioblastoma hijacks neuronal mechanisms for brain invasion.

Glioblastomas are incurable tumors infiltrating the brain. A subpopulation of glioblastoma cells forms a functional and therapy-resistant tumor cell network interconnected by tumor microtubes (TMs). Other subpopulations appear unconnected, and their biological role remains unclear. Here, we demonstrate that whole-brain colonization is fueled by glioblastoma cells that lack connections with other tumor cells and astrocytes yet receive synaptic input from neurons. This subpopulation corresponds to neuronal and neural-progenitor-like tumor cell states, as defined by single-cell transcriptomics, both in mouse models and in the human disease. Tumor cell invasion resembled neuronal migration mechanisms and adopted a Lévy-like movement pattern of probing the environment. Neuronal activity induced complex calcium signals in glioblastoma cells followed by the de novo formation of TMs and increased invasion speed. Collectively, superimposing molecular and functional single-cell data revealed that neuronal mechanisms govern glioblastoma cell invasion on multiple levels. This explains how glioblastoma's dissemination and cellular heterogeneity are closely interlinked.

Natural sensory context drives diverse brain-wide activity during C. elegans mating.

Natural goal-directed behaviors often involve complex sequences of many stimulus-triggered components. Understanding how brain circuits organize such behaviors requires mapping the interactions between an animal, its environment, and its nervous system. Here, we use brain-wide neuronal imaging to study the full performance of mating by the C. elegans male. We show that as mating unfolds in a sequence of component behaviors, the brain operates similarly between instances of each component but distinctly between different components. When the full sensory and behavioral context is taken into account, unique roles emerge for each neuron. Functional correlations between neurons are not fixed but change with behavioral dynamics. From individual neurons to circuits, our study shows how diverse brain-wide dynamics emerge from the integration of sensory perception and motor actions in their natural context.

A genetically tractable jellyfish model for systems and evolutionary neuroscience.

Jellyfish are radially symmetric organisms without a brain that arose more than 500 million years ago. They achieve organismal behaviors through coordinated interactions between autonomously functioning body parts. Jellyfish neurons have been studied electrophysiologically, but not at the systems level. We introduce Clytia hemisphaerica as a transparent, genetically tractable jellyfish model for systems and evolutionary neuroscience. We generate stable F1 transgenic lines for cell-type-specific conditional ablation and whole-organism GCaMP imaging. Using these tools and computational analyses, we find that an apparently diffuse network of RFamide-expressing umbrellar neurons is functionally subdivided into a series of spatially localized subassemblies whose synchronous activation controls directional food transfer from the tentacles to the mouth. These data reveal an unanticipated degree of structured neural organization in this species. Clytia affords a platform for systems-level studies of neural function, behavior, and evolution within a clade of marine organisms with growing ecological and economic importance.

Differential encoding in prefrontal cortex projection neuron classes across cognitive tasks.

Single-cell transcriptomics has been widely applied to classify neurons in the mammalian brain, while systems neuroscience has historically analyzed the encoding properties of cortical neurons without considering cell types. Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) projection neurons relate to axonal projections and encoding properties across multiple cognitive tasks. We found that most types projected to multiple targets, and most targets received projections from multiple types, except PFC→PAG (periaqueductal gray). By comparing Ca2+ activity of the molecularly homogeneous PFC→PAG type against two heterogeneous classes in several two-alternative choice tasks in freely moving mice, we found that all task-related signals assayed were qualitatively present in all examined classes. However, PAG-projecting neurons most potently encoded choice in cued tasks, whereas contralateral PFC-projecting neurons most potently encoded reward context in an uncued task. Thus, task signals are organized redundantly, but with clear quantitative biases across cells of specific molecular-anatomical characteristics.

Molecular Basis of Chemotactile Sensation in Octopus.

Animals display wide-ranging evolutionary adaptations based on their ecological niche. Octopuses explore the seafloor with their flexible arms using a specialized "taste by touch" system to locally sense and respond to prey-derived chemicals and movement. How the peripherally distributed octopus nervous system mediates relatively autonomous arm behavior is unknown. Here, we report that octopus arms use a family of cephalopod-specific chemotactile receptors (CRs) to detect poorly soluble natural products, thereby defining a form of contact-dependent, aquatic chemosensation. CRs form discrete ion channel complexes that mediate the detection of diverse stimuli and transduction of specific ionic signals. Furthermore, distinct chemo- and mechanosensory cells exhibit specific receptor expression and electrical activities to support peripheral information coding and complex chemotactile behaviors. These findings demonstrate that the peripherally distributed octopus nervous system is a key site for signal processing and highlight how molecular and anatomical features synergistically evolve to suit an animal's environmental context.

Behavior- and Modality-General Representation of Confidence in Orbitofrontal Cortex.

Every decision we make is accompanied by a sense of confidence about its likely outcome. This sense informs subsequent behavior, such as investing more-whether time, effort, or money-when reward is more certain. A neural representation of confidence should originate from a statistical computation and predict confidence-guided behavior. An additional requirement for confidence representations to support metacognition is abstraction: they should emerge irrespective of the source of information and inform multiple confidence-guided behaviors. It is unknown whether neural confidence signals meet these criteria. Here, we show that single orbitofrontal cortex neurons in rats encode statistical decision confidence irrespective of the sensory modality, olfactory or auditory, used to make a choice. The activity of these neurons also predicts two confidence-guided behaviors: trial-by-trial time investment and cross-trial choice strategy updating. Orbitofrontal cortex thus represents decision confidence consistent with a metacognitive process that is useful for mediating confidence-guided economic decisions.

Volumetric Ca2+ Imaging in the Mouse Brain Using Hybrid Multiplexed Sculpted Light Microscopy.

Calcium imaging using two-photon scanning microscopy has become an essential tool in neuroscience. However, in its typical implementation, the tradeoffs between fields of view, acquisition speeds, and depth restrictions in scattering brain tissue pose severe limitations. Here, using an integrated systems-wide optimization approach combined with multiple technical innovations, we introduce a new design paradigm for optical microscopy based on maximizing biological information while maintaining the fidelity of obtained neuron signals. Our modular design utilizes hybrid multi-photon acquisition and allows volumetric recording of neuroactivity at single-cell resolution within up to 1 × 1 × 1.22 mm volumes at up to 17 Hz in awake behaving mice. We establish the capabilities and potential of the different configurations of our imaging system at depth and across brain regions by applying it to in vivo recording of up to 12,000 neurons in mouse auditory cortex, posterior parietal cortex, and hippocampus.

Glia Accumulate Evidence that Actions Are Futile and Suppress Unsuccessful Behavior.

When a behavior repeatedly fails to achieve its goal, animals often give up and become passive, which can be strategic for preserving energy or regrouping between attempts. It is unknown how the brain identifies behavioral failures and mediates this behavioral-state switch. In larval zebrafish swimming in virtual reality, visual feedback can be withheld so that swim attempts fail to trigger expected visual flow. After tens of seconds of such motor futility, animals became passive for similar durations. Whole-brain calcium imaging revealed noradrenergic neurons that responded specifically to failed swim attempts and radial astrocytes whose calcium levels accumulated with increasing numbers of failed attempts. Using cell ablation and optogenetic or chemogenetic activation, we found that noradrenergic neurons progressively activated brainstem radial astrocytes, which then suppressed swimming. Thus, radial astrocytes perform a computation critical for behavior: they accumulate evidence that current actions are ineffective and consequently drive changes in behavioral states. VIDEO ABSTRACT.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.

Mapping the Neural Substrates of Behavior.

Assigning behavioral functions to neural structures has long been a central goal in neuroscience and is a necessary first step toward a circuit-level understanding of how the brain generates behavior. Here, we map the neural substrates of locomotion and social behaviors for Drosophila melanogaster using automated machine-vision and machine-learning techniques. From videos of 400,000 flies, we quantified the behavioral effects of activating 2,204 genetically targeted populations of neurons. We combined a novel quantification of anatomy with our behavioral analysis to create brain-behavior correlation maps, which are shared as browsable web pages and interactive software. Based on these maps, we generated hypotheses of regions of the brain causally related to sensory processing, locomotor control, courtship, aggression, and sleep. Our maps directly specify genetic tools to target these regions, which we used to identify a small population of neurons with a role in the control of walking.

Neural Circuits for Emotion.

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.

How Instructions, Learning, and Expectations Shape Pain and Neurobiological Responses.

Treatment outcomes are strongly influenced by expectations, as evidenced by the placebo effect. Meta-analyses of clinical trials reveal that placebo effects are strongest in pain, indicating that psychosocial factors directly influence pain. In this review, I focus on the neural and psychological mechanisms by which instructions, learning, and expectations shape subjective pain. I address new experimental designs that help researchers tease apart the impact of these distinct processes and evaluate the evidence regarding the neural mechanisms by which these cognitive factors shape subjective pain. Studies reveal that expectations modulate pain through parallel circuits that include both pain-specific and domain-general circuits such as those involved in affect and learning. I then review how expectations, learning, and verbal instructions impact clinical outcomes, including placebo analgesia and responses to pharmacological treatments, and discuss implications for future work.

The Serotonergic System Tracks the Outcomes of Actions to Mediate Short-Term Motor Learning.

To execute accurate movements, animals must continuously adapt their behavior to changes in their bodies and environments. Animals can learn changes in the relationship between their locomotor commands and the resulting distance moved, then adjust command strength to achieve a desired travel distance. It is largely unknown which circuits implement this form of motor learning, or how. Using whole-brain neuronal imaging and circuit manipulations in larval zebrafish, we discovered that the serotonergic dorsal raphe nucleus (DRN) mediates short-term locomotor learning. Serotonergic DRN neurons respond phasically to swim-induced visual motion, but little to motion that is not self-generated. During prolonged exposure to a given motosensory gain, persistent DRN activity emerges that stores the learned efficacy of motor commands and adapts future locomotor drive for tens of seconds. The DRN's ability to track the effectiveness of motor intent may constitute a computational building block for the broader functions of the serotonergic system. VIDEO ABSTRACT.

Neural Signaling in Cancer.

Nervous system activity regulates development, homeostasis, and plasticity of the brain as well as other organs in the body. These mechanisms are subverted in cancer to propel malignant growth. In turn, cancers modulate neural structure and function to augment growth-promoting neural signaling in the tumor microenvironment. Approaching cancer biology from a neuroscience perspective will elucidate new therapeutic strategies for presently lethal forms of cancer. In this review, we highlight the neural signaling mechanisms recapitulated in primary brain tumors, brain metastases, and solid tumors throughout the body that regulate cancer progression.

Melding Synthetic Molecules and Genetically Encoded Proteins to Forge New Tools for Neuroscience.

Unraveling the complexity of the brain requires sophisticated methods to probe and perturb neurobiological processes with high spatiotemporal control. The field of chemical biology has produced general strategies to combine the molecular specificity of small-molecule tools with the cellular specificity of genetically encoded reagents. Here, we survey the application, refinement, and extension of these hybrid small-molecule:protein methods to problems in neuroscience, which yields powerful reagents to precisely measure and manipulate neural systems.