The mechanisms linking sensation and action during learning are poorly understood. Layer 2/3 neurons in the motor cortex might participate in sensorimotor integration and learning; they receive input from sensory cortex and excite deep layer neurons, which control movement. Here we imaged activity in the same set of layer 2/3 neurons in the motor cortex over weeks, while mice learned to detect objects with their whiskers and report detection with licking. Spatially intermingled neurons represented sensory (touch) and motor behaviours (whisker movements and licking). With learning, the population-level representation of task-related licking strengthened. In trained mice, population-level representations were redundant and stable, despite dynamism of single-neuron representations. The activity of a subpopulation of neurons was consistent with touch driving licking behaviour. Our results suggest that ensembles of motor cortex neurons couple sensory input to multiple, related motor programs during learning.

In many machine learning applications, labeling every instance of data is burdensome. Multiple Instance Learning (MIL), in which training data is provided in the form of labeled bags rather than labeled instances, is one approach for a more relaxed form of supervised learning. Though much progress has been made in analyzing MIL problems, existing work considers bags that have a finite number of instances. In this paper we argue that in many applications of MIL (e.g. image, audio, etc.) the bags are better modeled as low dimensional manifolds in high dimensional feature space. We show that the geometric structure of such manifold bags affects PAC-learnability. We discuss how a learning algorithm that is designed for finite sized bags can be adapted to learn from manifold bags. Furthermore, we propose a simple heuristic that reduces the memory requirements of such algorithms. Our experiments on real-world data validate our analysis and show that our approach works well.

How neurons form synapses within specific layers remains poorly understood. In the Drosophila medulla, neurons target to discrete layers in a precise fashion. Here we demonstrate that the targeting of L3 neurons to a specific layer occurs in two steps. Initially, L3 growth cones project to a common domain in the outer medulla, overlapping with the growth cones of other neurons destined for a different layer through the redundant functions of N-Cadherin (CadN) and Semaphorin-1a (Sema-1a). CadN mediates adhesion within the domain and Sema-1a mediates repulsion through Plexin A (PlexA) expressed in an adjacent region. Subsequently, L3 growth cones segregate from the domain into their target layer in part through Sema-1a/PlexA-dependent remodeling. Together, our results and recent studies argue that the early medulla is organized into common domains, comprising processes bound for different layers, and that discrete layers later emerge through successive interactions between processes within domains and developing layers.

Physical traces underlying simple memories can be confined to a single group of cells in the brain. In the fly Drosophila melanogaster, the Kenyon cells of the mushroom bodies house traces for both appetitive and aversive odor memories. The adenylate cyclase protein, Rutabaga, has been shown to mediate both traces. Here, we show that, for appetitive learning, another group of cells can additionally accommodate a Rutabaga-dependent memory trace. Localized expression of rutabaga in either projection neurons, the first-order olfactory interneurons, or in Kenyon cells, the second-order interneurons, is sufficient for rescuing the mutant defect in appetitive short-term memory. Thus, appetitive learning may induce multiple memory traces in the first- and second-order olfactory interneurons using the same plasticity mechanism. In contrast, aversive odor memory of rutabaga is rescued selectively in the Kenyon cells, but not in the projection neurons. This difference in the organization of memory traces is consistent with the internal representation of reward and punishment.

Connections between neuronal populations may be genetically hardwired or random. In the insect olfactory system, projection neurons of the antennal lobe connect randomly to Kenyon cells of the mushroom body. Consequently, while the odor responses of the projection neurons are stereotyped across individuals, the responses of the Kenyon cells are variable. Surprisingly, downstream of Kenyon cells, mushroom body output neurons show stereotypy in their responses. We found that the stereotypy is enabled by the convergence of inputs from many Kenyon cells onto an output neuron, and does not require learning. The stereotypy emerges in the total response of the Kenyon cell population using multiple odor-specific features of the projection neuron responses, benefits from the nonlinearity in the transfer function, depends on the convergence:randomness ratio, and is constrained by sparseness. Together, our results reveal the fundamental mechanisms and constraints with which convergence enables stereotypy in sensory responses despite random connectivity.

Site-specific recombinases have been used for two decades to manipulate the structure of animal genomes in highly predictable ways and have become major research tools. However, the small number of recombinases demonstrated to have distinct specificities, low toxicity, and sufficient activity to drive reactions to completion in animals has been a limitation. In this report we show that four recombinases derived from yeast-KD, B2, B3, and R-are highly active and nontoxic in Drosophila and that KD, B2, B3, and the widely used FLP recombinase have distinct target specificities. We also show that the KD and B3 recombinases are active in mice.

Glomeruli are functional units in the olfactory system. The mouse olfactory bulb contains roughly 2,000 glomeruli, each receiving inputs from olfactory sensory neurons (OSNs) that express a specific odorant receptor gene. Odors typically activate many glomeruli in complex combinatorial patterns and it is unknown which features of neuronal activity in individual glomeruli contribute to odor perception. To address this, we used optogenetics to selectively activate single, genetically identified glomeruli in behaving mice. We found that mice could perceive the stimulation of a single glomerulus. Single-glomerulus stimulation was also detected on an intense odor background. In addition, different input intensities and the timing of input relative to sniffing were discriminated through one glomerulus. Our data suggest that each glomerulus can transmit odor information using identity, intensity and temporal coding cues. These multiple modes of information transmission may enable the olfactory system to efficiently identify and localize odor sources.

Understanding gene expression is essential for deciphering cellular functions. However, methods for analyzing the expression of numerous genes in situ within a given tissue remain limited. The EASI-FISH protocol described here has been adapted to detect the expression of dozens of genes in the intact adult Drosophila central nervous system (CNS) using commercially available reagents. This protocol includes a new gel formulation that enhances gel robustness, enabling multiple rounds of hybridization and allowing the embedding of multiple brains per gel. This improvement increases throughput, facilitates optimal comparison of experimental conditions, and reduces reagent costs. Additionally, by employing the GAL4-UAS system for co-detection of green fluorescent protein (GFP), gene expression can be visualized in specific neuronal or glial cell types. Notably, the high resolution achieved through expansion microscopy, combined with the sensitivity of the method, allows for the detection of single RNA transcripts. This approach effectively integrates high image quality with high throughput, making it a powerful tool for studying gene expression throughout the intact fly brain.

The lack of efficient tools to label multiple endogenous targets in cell lines without staining or fixation has limited our ability to track physiological and pathological changes in cells over time via live-cell studies. Here, we outline the FAST-HDR vector system to be used in combination with CRISPR-Cas9 to allow visual live-cell studies of up to three endogenous proteins within the same cell line. Our approach utilizes a novel set of advanced donor plasmids for homology-directed repair and a streamlined workflow optimized for microscopy-based cell screening to create genetically modified cell lines that do not require staining or fixation to accommodate microscopy-based studies. We validated this new methodology by developing two advanced cell lines with three fluorescent-labeled endogenous proteins that support high-content imaging without using antibodies or exogenous staining. We applied this technology to study seven severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/COVID-19) viral proteins to understand better their effects on autophagy, mitochondrial dynamics, and cell growth. Using these two cell lines, we were able to identify the protein ORF3a successfully as a potent inhibitor of autophagy, inducer of mitochondrial relocalization, and a growth inhibitor, which highlights the effectiveness of live-cell studies using this technology.

Information processing by brain circuits depends on Ca-dependent, stochastic release of the excitatory neurotransmitter glutamate. Whilst optical glutamate sensors have enabled detection of synaptic discharges, understanding presynaptic machinery requires simultaneous readout of glutamate release and nanomolar presynaptic Ca in situ. Here, we find that the fluorescence lifetime of the red-shifted Ca indicator Cal-590 is Ca-sensitive in the nanomolar range, and employ it in combination with green glutamate sensors to relate quantal neurotransmission to presynaptic Ca kinetics. Multiplexed imaging of individual and multiple synapses in identified axonal circuits reveals that glutamate release efficacy, but not its short-term plasticity, varies with time-dependent fluctuations in presynaptic resting Ca or spike-evoked Ca entry. Within individual presynaptic boutons, we find no nanoscopic co-localisation of evoked presynaptic Ca entry with the prevalent glutamate release site, suggesting loose coupling between the two. The approach enables a better understanding of release machinery at central synapses.