Animals need to rapidly learn to recognize and avoid predators. This ability may be especially important for young animals due to their increased vulnerability. It is unknown whether, and how, nascent vertebrates are capable of such rapid learning. Here, we used a robotic predator-prey interaction assay to show that 1 week after fertilization-a developmental stage where they have approximately 1% the number of neurons of adults-zebrafish larvae rapidly and robustly learn to recognize a stationary object as a threat after the object pursues the fish for ∼1 min. Larvae continue to avoid the threatening object after it stops moving and can learn to distinguish threatening from non-threatening objects of a different color. Whole-brain functional imaging revealed the multi-timescale activity of noradrenergic neurons and forebrain circuits that encoded the threat. Chemogenetic ablation of those populations prevented the learning. Thus, a noradrenergic and forebrain multiregional network underlies the ability of young vertebrates to rapidly learn to recognize potential predators within their first week of life.

Animals need to rapidly learn to recognize and avoid predators. This ability may be especially important for young animals due to their increased vulnerability. It is unknown whether, and how, nascent vertebrates are capable of such rapid learning. Here, we used a robotic predator-prey interaction assay to show that 1 week after fertilization-a developmental stage where they have approximately 1% the number of neurons of adults-zebrafish larvae rapidly and robustly learn to recognize a stationary object as a threat after the object pursues the fish for ∼1 min. Larvae continue to avoid the threatening object after it stops moving and can learn to distinguish threatening from non-threatening objects of a different color. Whole-brain functional imaging revealed the multi-timescale activity of noradrenergic neurons and forebrain circuits that encoded the threat. Chemogenetic ablation of those populations prevented the learning. Thus, a noradrenergic and forebrain multiregional network underlies the ability of young vertebrates to rapidly learn to recognize potential predators within their first week of life.

Transient exposure to ketamine can trigger lasting changes in behavior and mood. We found that brief ketamine exposure causes long-term suppression of futility-induced passivity in larval zebrafish, reversing the "giving-up" response that normally occurs when swimming fails to cause forward movement. Whole-brain imaging revealed that ketamine hyperactivates the norepinephrine-astroglia circuit responsible for passivity. After ketamine washout, this circuit exhibits hyposensitivity to futility, leading to long-term increased perseverance. Pharmacological, chemogenetic, and optogenetic manipulations show that norepinephrine and astrocytes are necessary and sufficient for ketamine's long-term perseverance-enhancing aftereffects. In vivo calcium imaging revealed that astrocytes in adult mouse cortex are similarly activated during futility in the tail suspension test and that acute ketamine exposure also induces astrocyte hyperactivation. The cross-species conservation of ketamine's modulation of noradrenergic-astroglial circuits and evidence that plasticity in this pathway can alter the behavioral response to futility hold promise for identifying new strategies to treat affective disorders.

As animals adapt to new situations, neuromodulation is a potent way to alter behavior, yet mechanisms by which neuromodulatory nuclei compute during behavior are underexplored. The serotonergic raphe supports motor learning in larval zebrafish by visually detecting distance traveled during swims, encoding action effectiveness, and modulating motor vigor. We found that swimming opens a gate for visual input to cause spiking in serotonergic neurons, enabling encoding of action outcomes and filtering out learning-irrelevant visual signals. Using light-sheet microscopy, voltage sensors, and neurotransmitter/modulator sensors, we tracked millisecond-timescale neuronal input-output computations during behavior. Swim commands initially inhibited serotonergic neurons via GABA, closing the gate to spiking. Immediately after, the gate briefly opened: voltage increased consistent with post-inhibitory rebound, allowing swim-induced visual motion to evoke firing through glutamate, triggering serotonin secretion and modulating motor vigor. Ablating GABAergic neurons impaired raphe coding and motor learning. Thus, serotonergic neuromodulation arises from action-outcome coincidence detection within the raphe, suggesting the existence of similarly fast and precise circuit computations across neuromodulatory nuclei.

Both neurons and glia communicate via diffusible neuromodulatory substances, but the substrates of computation in such neuromodulatory networks are unclear. During behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine drives fast excitation and delayed inhibition of behavior and circuit activity. We find that the inhibitory arm of this feedforward motif is implemented by astroglial purinergic signaling. Neuromodulator imaging, behavioral pharmacology, and perturbations of neurons and astroglia reveal that norepinephrine triggers astroglial release of adenosine triphosphate, extracellular conversion into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. This work, along with a companion piece by Lefton and colleagues demonstrating an analogous pathway mediating the effect of norepinephrine on synaptic connectivity in mice, identifies a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in norepinephrine-mediated behavioral and brain state transitions.

Astrocytes are predominant glial cells that tile the central nervous system and participate in well-established functional and morphological interactions with neurons, blood vessels, and other glia. These ubiquitous cells display rich intracellular Ca signaling, which has now been studied for over 30 years. In this review, we provide a summary and perspective of recent progress concerning the study of astrocyte intracellular Ca signaling as well as discussion of its potential functions. Progress has occurred in the areas of imaging, silencing, activating, and analyzing astrocyte Ca signals. These insights have collectively permitted exploration of the relationships of astrocyte Ca signals to neural circuit function and behavior in a variety of species. We summarize these aspects along with a framework for mechanistically interpreting behavioral studies to identify directly causal effects. We finish by providing a perspective on new avenues of research concerning astrocyte Ca signaling.

All multicellular systems produce and dynamically regulate extracellular matrices (ECM) that play important roles in both biochemical and mechanical signaling. Though the spatial arrangement of these extracellular assemblies is critical to their biological functions, visualization of ECM structure is challenging, in part because the biomolecules that compose the ECM are difficult to fluorescently label individually and collectively. Here, we present a cell-impermeable small molecule fluorophore, termed Rhobo6, that turns on and red shifts upon reversible binding to glycans. Given that most ECM components are densely glycosylated, the dye enables wash-free visualization of ECM, in systems ranging from in vitro substrates to in vivo mouse mammary tumors. Relative to existing techniques, Rhobo6 provides a broad substrate profile, superior tissue penetration, nonperturbative labeling, and negligible photobleaching. This work establishes a straightforward method for imaging the distribution of ECM in live tissues and organisms, lowering barriers for investigation of extracellular biology.

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful patterns embedded within complex and rich data sources. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a range of biosensors (calcium, norepinephrine, ATP, acetylcholine, dopamine), cell types (astrocytes, oligodendrocytes, microglia, neurons), organs (brains and spinal cords), animal models (zebrafish and mouse), and imaging modalities (confocal, two-photon, light sheet). As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.

Motor neurons are the final common pathway through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically suppress a single class of proprioceptive neuron that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.