Current techniques for monitoring GABA (γ-aminobutyric acid), the primary inhibitory neurotransmitter in vertebrates, cannot follow transients in intact neural circuits. To develop a GABA sensor, we applied the design principles used to create the fluorescent glutamate receptor iGluSnFR. We used a protein derived from a previously unsequenced Pseudomonas fluorescens strain and performed structure-guided mutagenesis and library screening to obtain intensity-based GABA sensing fluorescence reporter (iGABASnFR) variants. iGABASnFR is genetically encoded, detects GABA release evoked by electric stimulation of afferent fibers in acute brain slices and produces readily detectable fluorescence increases in vivo in mice and zebrafish. We applied iGABASnFR to track mitochondrial GABA content and its modulation by an anticonvulsant, swimming-evoked, GABA-mediated transmission in zebrafish cerebellum, GABA release events during interictal spikes and seizures in awake mice, and found that GABA-mediated tone decreases during isoflurane anesthesia.

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.

Whole-brain imaging allows for comprehensive functional mapping of distributed neural pathways, but neuronal perturbation experiments are usually limited to targeting predefined regions or genetically identifiable cell types. To complement whole-brain measures of activity with brain-wide manipulations for testing causal interactions, we introduce a system that uses measuredactivity patterns to guide optical perturbations of any subset of neurons in the same fictively behaving larval zebrafish. First, a light-sheet microscope collects whole-brain data that are rapidly analyzed by a distributed computing system to generate functional brain maps. On the basis of these maps, the experimenter can then optically ablate neurons and image activity changes across the brain. We applied this method to characterize contributions of behaviorally tuned populations to the optomotor response. We extended the system to optogenetically stimulate arbitrary subsets of neurons during whole-brain imaging. These open-source methods enable delineating the contributions of neurons to brain-wide circuit dynamics and behavior in individual animals.

Simultaneous recordings of large populations of neurons in behaving animals allow detailed observation of high-dimensional, complex brain activity. However, experimental approaches often focus on singular behavioral paradigms or brain areas. Here, we recorded whole-brain neuronal activity of larval zebrafish presented with a battery of visual stimuli while recording fictive motor output. We identified neurons tuned to each stimulus type and motor output and discovered groups of neurons in the anterior hindbrain that respond to different stimuli eliciting similar behavioral responses. These convergent sensorimotor representations were only weakly correlated to instantaneous motor activity, suggesting that they critically inform, but do not directly generate, behavioral choices. To catalog brain-wide activity beyond explicit sensorimotor processing, we developed an unsupervised clustering technique that organizes neurons into functional groups. These analyses enabled a broad overview of the functional organization of the brain and revealed numerous brain nuclei whose neurons exhibit concerted activity patterns.

We developed a new way to engineer complex proteins toward multidimensional specifications using a simple, yet scalable, directed evolution strategy. By robotically picking mammalian cells that were identified, under a microscope, as expressing proteins that simultaneously exhibit several specific properties, we can screen hundreds of thousands of proteins in a library in just a few hours, evaluating each along multiple performance axes. To demonstrate the power of this approach, we created a genetically encoded fluorescent voltage indicator, simultaneously optimizing its brightness and membrane localization using our microscopy-guided cell-picking strategy. We produced the high-performance opsin-based fluorescent voltage reporter Archon1 and demonstrated its utility by imaging spiking and millivolt-scale subthreshold and synaptic activity in acute mouse brain slices and in larval zebrafish in vivo. We also measured postsynaptic responses downstream of optogenetically controlled neurons in C. elegans.

Due to their small size and transparency, zebrafish larvae are amenable to a range of fluorescence microscopy techniques. With the development of sensitive genetically encoded calcium indicators, this has extended to the whole-brain imaging of neural activity with cellular resolution. This technique has been used to study brain-wide population dynamics accompanying sensory processing and sensorimotor transformations, and has spurred the development of innovative closed-loop behavioral paradigms in which stimulus-response relationships can be studied. More recently, microscopes have been developed that allow whole-brain calcium imaging in freely swimming and behaving larvae. In this review, we highlight the technologies underlying whole-brain functional imaging in zebrafish, provide examples of the sensory and motor processes that have been studied with this technique, and discuss the need to merge data from whole-brain functional imaging studies with neurochemical and anatomical information to develop holistic models of functional neural circuits.

Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to "zoom out" by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution.

The serotonergic system in the vertebrate brain is implicated in various behaviors and diseases. Its involvement in motor control has been studied for over half a century, but efforts to build a unified model of its functions have been hampered due to the complexity of serotonergic neuromodulation. This review summarizes the anatomical structure of the serotonergic system, its afferent and efferent connections to other brain regions, and recent insights into the sensorimotor computations in the serotonergic system, and considers future research directions into the roles of serotonergic system in motor control.

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.

Light sheet fluorescence microscopy is an efficient method for imaging large volumes of biological tissue, including brains of larval zebrafish, at high spatial and fairly high temporal resolution with minimal phototoxicity.Here, we provide a practical guide for those who intend to build a light sheet microscope for fluorescence imaging in live larval zebrafish brains or other tissues.