Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord.

Approximately four in five neurons are excitatory. This is true across functional regions and species. Why do we have so many excitatory neurons? Little is known. Here we provide a normative answer to this question. We designed a task-agnostic, learning-independent and experiment-testable measurement of functional complexity, which quantifies the network’s ability to solve complex problems. Using the larval Drosophila whole-brain electron microscopy connectome, we discovered the optimal Excitatory-Inhibitory (E-I) ratio that maximizes the functional complexity: 75-81% percentage of neurons are excitatory. This number is consistent with the true distribution observed via scRNA-seq. We found that the abundance of excitatory neurons confers an advantage in functional complexity, but only when inhibitory neurons are highly connected. In contrast, when the E-I identities are sampled uniformly (not dependent on connectivity), the optimal E-I ratio falls around equal population size, and its overall achieved functional complexity is sub-optimal. Our functional complexity measurement offers a normative explanation for the over-abundance of excitatory neurons in the brain. We anticipate that this approach will further uncover the functional significance of various neural network structures.

An important strategy for efficient neural coding is to match the range of cellular responses to the distribution of relevant input signals. However, the structure and relevance of sensory signals depend on behavioral state. Here, we show that behavior modifies neural activity at the earliest stages of fly vision. We describe a class of wide-field neurons that provide feedback to the most peripheral layer of the Drosophila visual system, the lamina. Using in vivo patch-clamp electrophysiology, we found that lamina wide-field neurons respond to low-frequency luminance fluctuations. Recordings in flying flies revealed that the gain and frequency tuning of wide-field neurons change during flight, and that these effects are mimicked by the neuromodulator octopamine. Genetically silencing wide-field neurons increased behavioral responses to slow-motion stimuli. Together, these findings identify a cell type that is gated by behavior to enhance neural coding by subtracting low-frequency signals from the inputs to motion detection circuits.

We have developed miniature telemetry systems that capture neural, EMG, and acceleration signals from a freely moving insect or other small animal and transmit the data wirelessly to a remote digital receiver. The systems are based on custom low-power integrated circuits (ICs) that amplify, filter, and digitize four biopotential signals using low-noise circuits. One of the chips also digitizes three acceleration signals from an off-chip microelectromechanical-system accelerometer. All information is transmitted over a wireless ~ 900-MHz telemetry link. The first unit, using a custom chip fabricated in a 0.6- μm BiCMOS process, weighs 0.79 g and runs for two hours on two small batteries. We have used this system to monitor neural and EMG signals in jumping and flying locusts as well as transdermal potentials in weakly swimming electric fish. The second unit, using a custom chip fabricated in a 0.35-μ m complementary metal-oxide semiconductor CMOS process, weighs 0.17 g and runs for five hours on a single 1.5-V battery. This system has been used to monitor neural potentials in untethered perching dragonflies.

Target interception is a complex sensorimotor behavior which requires fine tuning of the sensory system and its strategic coordination with the motor system. Despite various theories about how interception is achieved, its neural implementation remains unknown. We have previously shown that hunting dragonflies employ a balance of reactive and predictive control to intercept prey, using sophisticated model driven predictions to account for expected prey and self-motion. Here we explore the neural substrate of this interception system by investigating a well-known class of target-selective descending neurons (TSDNs). These cells have long been speculated to underlie interception steering but have never been studied in a behaving dragonfly. We combined detailed neuroanatomy, high-precision kinematics data and state-of-the-art neural telemetry to measure TSDN activity during flight. We found that TSDNs are exquisitely tuned to prey angular size and speed at ethological distances, and that they synapse directly onto neck and wing motoneurons in an unusual manner. However, we found that TSDNs were only weakly active during flight and are thus unlikely to provide the primary steering signal. Instead, they appear to drive the foveating head movements that stabilize prey on the eye before and likely throughout the interception flight. We suggest the TSDN population implements the reactive portion of the interception steering control system, coordinating head and wing movements to compensate for unexpected prey motion.

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement.

The placement of neuronal cell bodies relative to the neuropile differs among species and brain areas. Cell bodies can be either embedded as in mammalian cortex or segregated as in invertebrates and some other vertebrate brain areas. Why are there such different arrangements? Here we suggest that the observed arrangements may simply be a reflection of wiring economy, a general principle that tends to reduce the total volume of the neuropile and hence the volume of the inclusions in it. Specifically, we suggest that the choice of embedded versus segregated arrangement is determined by which neuronal component - the cell body or the neurite connecting the cell body to the arbor - has a smaller volume. Our quantitative predictions are in agreement with existing and new measurements.

Many animals rely on acoustic cues to decide what action to take next. Unraveling the wiring patterns of the auditory neural pathways is prerequisite for understanding such information processing. Here we reconstructed the first step of the auditory neural pathway in the fruit fly brain, from primary to secondary auditory neurons, at the resolution of transmission electron microscopy. By tracing axons of two major subgroups of auditory sensory neurons in fruit flies, low-frequency tuned Johnston's organ (JO)-B neurons and high-frequency tuned JO-A neurons, we observed extensive connections from JO-B neurons to the main second-order neurons in both the song-relay and escape pathways. In contrast, JO-A neurons connected strongly to a neuron in the escape pathway. Our findings suggest that heterogeneous JO neuronal populations could be recruited to modify escape behavior whereas only specific JO neurons contribute to courtship behavior. We also found that all JO neurons have postsynaptic sites at their axons. Presynaptic modulation at the output sites of JO neurons could affect information processing of the auditory neural pathway in flies. This article is protected by copyright. All rights reserved.

A complex brain consists of multiple intricate neural networks assembled from distinct sets of input and output neurons as well as region-specific local interneurons. Within a given anatomical set, there exist diverse neuronal types that can vary in morphology, neural physiology, and modes of neurotransmission. The genetic programs that guide specification of neuronal types during neurogenesis preconfigure the brain. This is best demonstrated in the Drosophila central brain, which is composed of ∼100 pairs of individually tailored neuronal lineages. Each neuronal lineage (the neurons/glia produced from a single stem cell) can contain multiple morphological classes of neurons that can consist of many analogous neuronal types. The detailed patterns of neuronal diversification are lineage-specific and can differ drastically even among neighboring neuronal lineages. Furthermore, the interrelationships between neuronal lineages and neural networks are complex. These phenomena underscore the importance of tracking all neuronal lineages in understanding brain development and evolution.

Wnt signaling through Frizzled proteins guides posterior cells and axons in C. elegans into different spatial domains. Here we demonstrate an essential role for Wnt signaling through Ror tyrosine kinase homologs in the most prominent anterior neuropil, the nerve ring. A genetic screen uncovered cwn-2, the C. elegans homolog of Wnt5, as a regulator of nerve ring placement. In cwn-2 mutants, all neuronal structures in and around the nerve ring are shifted to an abnormal anterior position. cwn-2 is required at the time of nerve ring formation; it is expressed by cells posterior of the nerve ring, but its precise site of expression is not critical for its function. In nerve ring development, cwn-2 acts primarily through the Wnt receptor CAM-1 (Ror), together with the Frizzled protein MIG-1, with parallel roles for the Frizzled protein CFZ-2. The identification of CAM-1 as a CWN-2 receptor contrasts with CAM-1 action as a non-receptor in other C. elegans Wnt pathways. Cell-specific rescue of cam-1 and cell ablation experiments reveal a crucial role for the SIA and SIB neurons in positioning the nerve ring, linking Wnt signaling to specific cells that organize the anterior nervous system.