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.

Mood-altering compounds hold promise for the treatment of many psychiatric disorders, such as depression, but connecting their molecular, circuit, and behavioral effects has been challenging. Here we find that, analogous to effects in rodent learned helplessness models, ketamine pre-exposure persistently suppresses futility-induced passivity in larval zebrafish. While antidepressants are thought to primarily act on neurons, brain-wide imaging in behaving zebrafish showed that ketamine elevates intracellular calcium in astroglia for many minutes, followed by persistent calcium downregulation post-washout. Calcium elevation depends on astroglial α1-adrenergic receptors and is required for suppression of passivity. Chemo-/optogenetic perturbations of noradrenergic neurons and astroglia demonstrate that the aftereffects of glial calcium elevation are sufficient to suppress passivity by inhibiting neuronal-astroglial integration of behavioral futility. Imaging in mouse cortex reveals that ketamine elevates astroglial calcium through conserved pathways, suggesting that ketamine exerts its behavioral effects by persistently modulating evolutionarily ancient neuromodulatory systems spanning neurons and astroglia.

Much of systems neuroscience posits the functional importance of brain activity patterns that lack natural scales of sizes, durations, or frequencies. The field has developed prominent, and sometimes competing, explanations for the nature of this scale-free activity. Here, we reconcile these explanations across species and modalities. First, we link estimates of excitation-inhibition (E-I) balance with time-resolved correlation of distributed brain activity. Second, we develop an unbiased method for sampling time series constrained by this time-resolved correlation. Third, we use this method to show that estimates of E-I balance account for diverse scale-free phenomena without need to attribute additional function or importance to these phenomena. Collectively, our results simplify existing explanations of scale-free brain activity and provide stringent tests on future theories that seek to transcend these explanations.

Calcium imaging with protein-based indicators is widely used to follow neural activity in intact nervous systems, but current protein sensors report neural activity at timescales much slower than electrical signalling and are limited by trade-offs between sensitivity and kinetics. Here we used large-scale screening and structure-guided mutagenesis to develop and optimize several fast and sensitive GCaMP-type indicators. The resulting 'jGCaMP8' sensors, based on the calcium-binding protein calmodulin and a fragment of endothelial nitric oxide synthase, have ultra-fast kinetics (half-rise times of 2 ms) and the highest sensitivity for neural activity reported for a protein-based calcium sensor. jGCaMP8 sensors will allow tracking of large populations of neurons on timescales relevant to neural computation.