Theoretical neuroscientists often try to understand how the structure of a neural network relates to its function by focusing on structural features that would either follow from optimization or occur consistently across possible implementations. Both optimization theories and ensemble modeling approaches have repeatedly proven their worth, and it would simplify theory building considerably if predictions from both theory types could be derived and tested simultaneously. Here we show how tensor formalism from theoretical physics can be used to unify and solve many optimization and ensemble modeling approaches to predicting synaptic connectivity from neuronal responses. We specifically focus on analyzing the solution space of synaptic weights that allow a thresholdlinear neural network to respond in a prescribed way to a limited number of input conditions. For optimization purposes, we compute the synaptic weight vector that minimizes an arbitrary quadratic loss function. For ensemble modeling, we identify synaptic weight features that occur consistently across all solutions bounded by an arbitrary quadratic function. We derive a common solution to this suite of nonlinear problems by showing how each of them reduces to an equivalent linear problem that can be solved analytically. Although identifying the equivalent linear problem is nontrivial, our tensor formalism provides an elegant geometrical perspective that allows us to solve the problem numerically. The final algorithm is applicable to a wide range of interesting neuroscience problems, and the associated geometric insights may carry over to other scientific problems that require constrained optimization.

L-Lactate is increasingly appreciated as a key metabolite and signaling molecule in mammals. However, investigations of the inter- and intra-cellular dynamics of L-lactate are currently hampered by the limited selection and performance of L-lactate-specific genetically encoded biosensors. Here we now report a spectrally and functionally orthogonal pair of high-performance genetically encoded biosensors: a green fluorescent extracellular L-lactate biosensor, designated eLACCO2.1, and a red fluorescent intracellular L-lactate biosensor, designated R-iLACCO1. eLACCO2.1 exhibits excellent membrane localization and robust fluorescence response. To the best of our knowledge, R-iLACCO1 and its affinity variants exhibit larger fluorescence responses than any previously reported intracellular L-lactate biosensor. We demonstrate spectrally and spatially multiplexed imaging of L-lactate dynamics by coexpression of eLACCO2.1 and R-iLACCO1 in cultured cells, and in vivo imaging of extracellular and intracellular L-lactate dynamics in mice.

The endoplasmic reticulum (ER) and the Golgi apparatus are the first sorting stations along the secretory pathway of mammalian cells and have a crucial role in protein quality control and cellular homeostasis. While machinery components mediating ER-to-Golgi transport have been mapped, it is unclear how exchange between the two closely juxtaposed organelles is coordinated in living cells. Here, using gene editing to tag machinery components, live-cell confocal and stimulated emission depletion (STED) super-resolution microscopy, we show that ER-to-Golgi transport occurs via a dynamic network of tubules positive for the small GTPase ARF4. swCOPI machinery is tightly associated to this network and moves with tubular-vesicular structures. Strikingly, the ARF4 network appears to be continuous with the ER and ARF4 tubules remodel around static ER exit sites (ERES) defined by COPII machinery. We were further able to dissect the steps of ER-to-Golgi transport with functional trafficking assays. A wave of cargo released from the ER percolates through peripheral and Golgi-tethered ARF4 structures before filling the cis-Golgi. Perturbation via acute degradation of ARF4 shows an active regulatory role for the GTPase and COPI in anterograde transport. Our data supports a model in which anterograde ER-to-Golgi transport occurs via an ARF4 tubular-vesicular network directly connecting the ER and Golgi-associated pre-cisternae.

As observed in human language learning and song learning in birds, the fruit fly Drosophila melanogaster changes its' auditory behaviors according to prior sound experiences. Female flies that have heard male courtship songs of the same species are less responsive to courtship songs of different species. This phenomenon, known as song preference learning in flies, requires GABAergic input to pC1 neurons in the central brain, with these neurons playing a key role in mating behavior by integrating multimodal sensory and internal information. The neural circuit basis of this GABAergic input, however, has not yet been identified. Here, we find that pCd-2 neurons, totaling four cells per hemibrain and expressing the sex-determination gene doublesex, provide the GABAergic input to pC1 neurons for song preference learning. First, RNAi-mediated knockdown of GABA production in pCd-2 neurons abolished song preference learning. Second, pCd-2 neurons directly, and in many cases mutually, connect with pC1 neurons, suggesting the existence of reciprocal circuits between pC1 and pCd-2 neurons. Finally, GABAergic and dopaminergic inputs to pCd-2 neurons are necessary for song preference learning. Together, this study suggests that reciprocal circuits between pC1 and pCd-2 neurons serve as a sensory and internal state-integrated hub, allowing flexible control over female copulation. Consequently, this provides a neural circuit model that underlies experience-dependent auditory plasticity.

Specialized mechanosensory end organs within mammalian skin—hair follicle-associated lanceolate complexes, Meissner corpuscles, and Pacinian corpuscles—enable our perception of light, dynamic touch1. In each of these end organs, fast-conducting mechanically sensitive neurons, called Aβ low-threshold mechanoreceptors (Aβ LTMRs), associate with resident glial cells, known as terminal Schwann cells (TSCs) or lamellar cells, to form complex axon ending structures. Lanceolate-forming and corpuscle-innervating Aβ LTMRs share a low threshold for mechanical activation, a rapidly adapting (RA) response to force indentation, and high sensitivity to dynamic stimuli1–6. How mechanical stimuli lead to activation of the requisite mechanotransduction channel Piezo27–15 and Aβ RA-LTMR excitation across the morphologically dissimilar mechanosensory end organ structures is not understood. Here, we report the precise subcellular distribution of Piezo2 and high-resolution, isotropic 3D reconstructions of all three end organs formed by Aβ RA-LTMRs determined by large volume enhanced Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) imaging. We found that within each end organ, Piezo2 is enriched along the sensory axon membrane and is minimally or not expressed in TSCs and lamellar cells. We also observed a large number of small cytoplasmic protrusions enriched along the Aβ RA-LTMR axon terminals associated with hair follicles, Meissner corpuscles, and Pacinian corpuscles. These axon protrusions reside within close proximity to axonal Piezo2, occasionally contain the channel, and often form adherens junctions with nearby non-neuronal cells. Our findings support a unified model for Aβ RA-LTMR activation in which axon protrusions anchor Aβ RA-LTMR axon terminals to specialized end organ cells, enabling mechanical stimuli to stretch the axon in hundreds to thousands of sites across an individual end organ and leading to activation of proximal Piezo2 channels and excitation of the neuron.

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

Our nervous system contains billions of neurons that form precise connections with each other through interactions between cell surface proteins (CSPs). In Drosophila, the Dpr and DIP immunoglobulin protein subfamilies form homophilic or heterophilic interactions to instruct synaptic connectivity, synaptic growth and cell survival. However, the upstream regulation and downstream signaling mechanisms of Dprs and DIPs are not clear. In the Drosophila larval neuromuscular system, DIP-α is expressed in the dorsal and ventral type-Is motor neurons (MNs). We conducted an F1 dominant modifier genetic screen to identify regulators of Dprs and DIPs. We found that the transcription factor, huckebein (hkb), genetically interacts with DIP-α and is important for target recognition specifically in the dorsal Is MN, but not the ventral Is MN. Loss of hkb led to complete removal of DIP-α expression. We then confirmed that this specificity is through the dorsal Is MN specific transcription factor, even-skipped (eve), which acts downstream of hkb. Genetic interaction between hkb and eve revealed that they act in the same pathway to regulate dorsal Is MN connectivity. Our study provides insight into the transcriptional regulation of DIP-α and suggests that distinct regulatory mechanisms exist for the same CSP in different neurons.

Many neurons in the central nervous system produce a single primary cilium that serves as a specialized signaling organelle. Several neuromodulatory G-protein-coupled receptors (GPCRs) localize to primary cilia in neurons, although it is not understood how GPCR signaling from the cilium impacts circuit function and behavior. We find that the vertebrate ancient long opsin A (VALopA), a G-coupled GPCR extraretinal opsin, targets to cilia of zebrafish spinal neurons. In the developing 1-d-old zebrafish, brief light activation of VALopA in neurons of the central pattern generator circuit for locomotion leads to sustained inhibition of coiling, the earliest form of locomotion. We find that a related extraretinal opsin, VALopB, is also G-coupled, but is not targeted to cilia. Light-induced activation of VALopB also suppresses coiling, but with faster kinetics. We identify the ciliary targeting domains of VALopA. Retargeting of both opsins shows that the locomotory response is prolonged and amplified when signaling occurs in the cilium. We propose that ciliary localization provides a mechanism for enhancing GPCR signaling in central neurons.

Rhodamine dyes are excellent scaffolds for developing a broad range of fluorescent probes. A key property of rhodamines is their equilibrium between a colorless lactone and fluorescent zwitterion. Tuning the lactone–zwitterion equilibrium constant (KL–Z) can optimize dye properties for specific biological applications. Here, we use known and novel organic chemistry to prepare a comprehensive collection of rhodamine dyes to elucidate the structure–activity relationships that govern KL–Z. We discovered that the auxochrome substituent strongly affects the lactone–zwitterion equilibrium, providing a roadmap for the rational design of improved rhodamine dyes. Electron-donating auxochromes, such as julolidine, work in tandem with fluorinated pendant phenyl rings to yield bright, red-shifted fluorophores for live-cell single-particle tracking (SPT) and multicolor imaging. The N-aryl auxochrome combined with fluorination yields red-shifted Förster resonance energy transfer (FRET) quencher dyes useful for creating a new semisynthetic indicator to sense cAMP using fluorescence lifetime imaging microscopy (FLIM). Together, this work expands the synthetic methods available for rhodamine synthesis, generates new reagents for advanced fluorescence imaging experiments, and describes structure–activity relationships that will guide the design of future probes.