Mechanosensory corpuscles detect transient touch and vibratory signals in the skin of vertebrates, enabling navigation, foraging, and precise manipulation of objects1. The corpuscle core comprises a terminal neurite of a mechanoreceptor afferent, the only known touch-sensing element within corpuscles, surrounded by terminal Schwann cells called lamellar cells (LCs)2–4. However, the precise corpuscular ultrastructure, and the role of LCs in touch detection are unknown. Here we used enhanced focused ion beam scanning electron microscopy and electron tomography to reveal the three-dimensional architecture of avian Meissner (Grandry) corpuscle5. We show that corpuscles contain a stack of LCs innervated by two afferents, which form large-area contacts with LCs. LCs form tether-like connections with the afferent membrane and contain dense core vesicles which release their content onto the afferent. Furthermore, by performing simultaneous electrophysiological recordings from both cell types, we show that mechanosensitive LCs use calcium influx to trigger action potential firing in the afferent and thus serve as physiological touch sensors in the skin. Our findings suggest a bi-cellular mechanism of touch detection, which comprises the afferent and LCs, likely enables corpuscles to encode the nuances of tactile stimuli.

Navigating animals continuously integrate velocity signals to update internal representations of their directional heading and spatial location in the environment. How neural circuits combine sensory and motor information to construct these velocity estimates and how these self-motion signals, in turn, update internal representations that support navigational computations are not well understood. Recent work in Drosophila has identified a neural circuit that performs angular path integration to compute the fly's head direction, but the nature of the velocity signal is unknown. Here we identify a pair of neurons necessary for angular path integration that encode the fly's rotational velocity with high accuracy using both visual optic flow and motor information. This estimate of rotational velocity does not rely on a moment-to-moment integration of sensory and motor information. Rather, when visual and motor signals are congruent, these neurons prioritize motor information over visual information, and when the two signals are in conflict, reciprocal inhibition selects either the motor or visual signal. Together, our results suggest that flies update their head direction representation by constructing an estimate of rotational velocity that relies primarily on motor information and only incorporates optic flow signals in specific sensorimotor contexts, such as when the motor signal is absent.

Ionic driving forces provide the net electromotive force for ion movement across membranes and are therefore a fundamental property of all cells. In the nervous system, chloride driving force (DFCl) determines inhibitory signaling, as fast synaptic inhibition is mediated by chloride-permeable GABAA and glycine receptors. Here we present a new tool for all-Optical Reporting of CHloride Ion Driving force (ORCHID). We demonstrate ORCHID’s ability to provide accurate, high-throughput measurements of resting and dynamic DFCl from genetically targeted cell types over a range of timescales. ORCHID confirms theoretical predictions about the biophysical mechanisms that establish DFCl, reveals novel differences in DFCl between neurons and astrocytes under different network conditions, and affords the first in vivo measurements of intact DFCl in mouse cortical neurons. This work extends our understanding of chloride homeostasis and inhibitory synaptic transmission and establishes a precedent for utilizing all-optical methods to assess ionic driving force.

Motor systems flexibly implement diverse motor programs to pattern behavioral sequences, yet their neural underpinnings remain unclear. Here, we investigated the neural circuit mechanisms of flexible courtship behavior in Drosophila. Courting males alternately produce two types of courtship song. By recording calcium signals in the ventral nerve cord (VNC) in behaving flies, we found that different songs are produced by activating overlapping neural populations with distinct motor functions in a combinatorial manner. Recordings from the brain suggest that song is driven by two descending pathways – one defines when to sing and the other specifies what song to sing. Connectomic analysis reveals that these “when” and “what” descending pathways provide structured input to VNC neurons with different motor functions. These results suggest that dynamic changes in the activation patterns of descending pathways drive different combinations of motor modules, thereby flexibly switching between different motor actions.

The mushroom body (MB) is the center for associative learning in insects. In Drosophila, intersectional split-GAL4 drivers and electron microscopy (EM) connectomes have laid the foundation for precise interrogation of the MB neural circuits. However, many cell types upstream and downstream of the MB remained to be investigated due to lack of driver lines. Here we describe a new collection of over 800 split-GAL4 and split-LexA drivers that cover approximately 300 cell types, including sugar sensory neurons, putative nociceptive ascending neurons, olfactory and thermo-/hygro-sensory projection neurons, interneurons connected with the MB-extrinsic neurons, and various other cell types. We characterized activation phenotypes for a subset of these lines and identified the sugar sensory neuron line most suitable for reward substitution. Leveraging the thousands of confocal microscopy images associated with the collection, we analyzed neuronal morphological stereotypy and discovered that one set of mushroom body output neurons, MBON08/MBON09, exhibits striking individuality and asymmetry across animals. In conjunction with the EM connectome maps, the driver lines reported here offer a powerful resource for functional dissection of neural circuits for associative learning in adult Drosophila.

Optical microscopy methods such as calcium and voltage imaging enable fast activity readout of large neuronal populations using light. However, the lack of corresponding advances in online algorithms has slowed progress in retrieving information about neural activity during or shortly after an experiment. This gap not only prevents the execution of real-time closed-loop experiments, but also hampers fast experiment-analysis-theory turnover for high-throughput imaging modalities. Reliable extraction of neural activity from fluorescence imaging frames at speeds compatible with indicator dynamics and imaging modalities poses a challenge. We therefore developed FIOLA, a framework for fluorescence imaging online analysis that extracts neuronal activity from calcium and voltage imaging movies at speeds one order of magnitude faster than state-of-the-art methods. FIOLA exploits algorithms optimized for parallel processing on GPUs and CPUs. We demonstrate reliable and scalable performance of FIOLA on both simulated and real calcium and voltage imaging datasets. Finally, we present an online experimental scenario to provide guidance in setting FIOLA parameters and to highlight the trade-offs of our approach.

Real-time neural signal processing is essential for brain-machine interfaces and closed-loop neuronal perturbations. However, most existing applications sacrifice cell-specific identity and temporal spiking information for speed. We developed a hybrid hardware-software system that utilizes a Field Programmable Gate Array (FPGA) chip to acquire and process data in parallel, enabling individual spikes from many simultaneously recorded neurons to be assigned single-neuron identities with 1-millisecond latency. The FPGA assigns labels, validated with ground-truth data, by comparing multichannel spike waveforms from tetrode or silicon probe recordings to a spike-sorted model generated offline in software. This platform allowed us to rapidly inactivate a region in vivo based on spikes from an upstream neuron before these spikes could excite the downstream region. Furthermore, we could decode animal location within 3 ms using data from a population of individual hippocampal neurons. These results demonstrate our system’s suitability for a broad spectrum of research and clinical applications.

Healthy mitochondria are critical for reproduction. During aging, both reproductive fitness and mitochondrial homeostasis decline. Mitochondrial metabolism and dynamics are key factors in supporting mitochondrial homeostasis. However, how they are coupled to control reproductive health remains unclear. We report that mitochondrial GTP (mtGTP) metabolism acts through mitochondrial dynamics factors to regulate reproductive aging. We discovered that germline-only inactivation of GTP- but not ATP-specific succinyl-CoA synthetase (SCS) promotes reproductive longevity in Caenorhabditis elegans. We further identified an age-associated increase in mitochondrial clustering surrounding oocyte nuclei, which is attenuated by GTP-specific SCS inactivation. Germline-only induction of mitochondrial fission factors sufficiently promotes mitochondrial dispersion and reproductive longevity. Moreover, we discovered that bacterial inputs affect mtGTP levels and dynamics factors to modulate reproductive aging. These results demonstrate the significance of mtGTP metabolism in regulating oocyte mitochondrial homeostasis and reproductive longevity and identify mitochondrial fission induction as an effective strategy to improve reproductive health.

Methods of three-dimensional electron microscopy have been actively developed recently and open up great opportunities for morphological work. This approach is especially useful for studying microinsects, since it is possible to obtain complete series of high-resolution sections of a whole insect. Studies on the genus Megaphragma are especially important, since the unique phenomenon of lysis of most of the neuron nuclei was discovered in species of this genus. In this study we reveal the anatomical structure of the head of Megaphragma viggianii at all levels from organs to subcellular structures. Despite the miniature size of the body, most of the organ systems of M. viggianii retain the structural plan and complexity of organization at all levels. The set of muscles and the well-developed stomatogastric nervous system of this species correspond to those of larger insects, and there is also a well-developed tracheal system in the head of this species. Reconstructions of the head of M. viggianii at the cellular and subcellular levels were obtained, and of volumetric data were analyzed. A total of 689 nucleated cells of the head were reconstructed. The ultrastructure of M. viggianii is surprisingly complex, and the evolutionary benefits of such complexity are probably among the factors limiting the further miniaturization of parasitoid wasps.

How memories are used by the brain to guide future action is poorly understood. In olfactory associative learning in Drosophila, multiple compartments of the mushroom body act in parallel to assign valence to a stimulus. Here, we show that appetitive memories stored in different compartments induce different levels of upwind locomotion. Using a photoactivation screen of a new collection of split-GAL4 drivers and EM connectomics, we identified a cluster of neurons postsynaptic to the mushroom body output neurons (MBONs) that can trigger robust upwind steering. These UpWind Neurons (UpWiNs) integrate inhibitory and excitatory synaptic inputs from MBONs of appetitive and aversive memory compartments, respectively. After training, disinhibition from the appetitive-memory MBONs enhances the response of UpWiNs to reward-predicting odors. Blocking UpWiNs impaired appetitive memory and reduced upwind locomotion during retrieval. Photoactivation of UpWiNs also increased the chance of returning to a location where activation was initiated, suggesting an additional role in olfactory navigation. Thus, our results provide insight into how learned abstract valences are gradually transformed into concrete memory-driven actions through divergent and convergent networks, a neuronal architecture that is commonly found in the vertebrate and invertebrate brains.