Individuals vary in their innate behaviours, even when they have the same genome and have been reared in the same environment. The extent of individuality in plastic behaviours, like learning, is less well characterized. Also unknown is the extent to which intragenotypic differences in learning generalize: if an individual performs well in one assay, will it perform well in other assays? We investigated this using the fruit fly , an organism long-used to study the mechanistic basis of learning and memory. We found that isogenic flies, reared in identical laboratory conditions, and subject to classical conditioning that associated odorants with electric shock, exhibit clear individuality in their learning responses. Flies that performed well when an odour was paired with shock tended to perform well when the odour was paired with bitter taste or when other odours were paired with shock. Thus, individuality in learning performance appears to be prominent in isogenic animals reared identically, and individual differences in learning performance generalize across some aversive sensory modalities. Establishing these results in flies opens up the possibility of studying the genetic and neural circuit basis of individual differences in learning in a highly suitable model organism.

Quality assessment of tree-like structures obtained from a neuron reconstruction algorithm is necessary for evaluating the performance of the algorithm. The lack of user-friendly software for calculating common metrics motivated us to develop a Python toolbox called PyNeval, which is the first open-source toolbox designed to evaluate reconstruction results conveniently as far as we know. The toolbox supports popular metrics in two major categories, geometrical metrics and topological metrics, with an easy way to configure custom parameters for each metric. We tested the toolbox on both synthetic data and real data to show its reliability and robustness. As a demonstration of the toolbox in real applications, we used the toolbox to improve the performance of a tracing algorithm successfully by integrating it into an optimization procedure.

Motor systems must continuously adapt their output to maintain a desired trajectory. While the spinal circuits underlying rhythmic locomotion are well described, little is known about how the network modulates its output strength. A major challenge has been the difficulty of recording from spinal neurons during behavior. Here, we use voltage imaging to map the membrane potential of large populations of glutamatergic neurons throughout the spinal cord of the larval zebrafish during fictive swimming in a virtual environment. We characterized a previously undescribed subpopulation of tonic-spiking ventral V3 neurons whose spike rate correlated with swimming strength and bout length. Optogenetic activation of V3 neurons led to stronger swimming and longer bouts but did not affect tail beat frequency. Genetic ablation of V3 neurons led to reduced locomotor adaptation. The power of voltage imaging allowed us to identify V3 neurons as a critical driver of locomotor adaptation in zebrafish.

Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional nanofilm that facilitates subcellular visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of ≈3.2 µm (full width at half maximum) and are observed with a mean spatial frequency of 1 hotspot per ≈7.5 µm of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots colocalized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.

Laboratory behavioural tasks are an essential research tool. As questions asked of behaviour and brain activity become more sophisticated, the ability to specify and run richly structured tasks becomes more important. An increasing focus on reproducibility also necessitates accurate communication of task logic to other researchers. To these ends, we developed pyControl, a system of open-source hardware and software for controlling behavioural experiments comprising a simple yet flexible Python-based syntax for specifying tasks as extended state machines, hardware modules for building behavioural setups, and a graphical user interface designed for efficiently running high-throughput experiments on many setups in parallel, all with extensive online documentation. These tools make it quicker, easier, and cheaper to implement rich behavioural tasks at scale. As important, pyControl facilitates communication and reproducibility of behavioural experiments through a highly readable task definition syntax and self-documenting features. Here, we outline the system's design and rationale, present validation experiments characterising system performance, and demonstrate example applications in freely moving and head-fixed mouse behaviour.

Recurrent outbreaks of novel zoonotic coronavirus (CoV) diseases in recent years have highlighted the importance of developing therapeutics with broad-spectrum activity against CoVs. Because all CoVs use -1 programmed ribosomal frameshifting (-1 PRF) to control expression of key viral proteins, the frameshift signal in viral mRNA that stimulates -1 PRF provides a promising potential target for such therapeutics. To test the viability of this strategy, we explored whether small-molecule inhibitors of -1 PRF in SARS-CoV-2 also inhibited -1 PRF in a range of bat CoVs-the most likely source of future zoonoses. Six inhibitors identified in new and previous screens against SARS-CoV-2 were evaluated against the frameshift signals from a panel of representative bat CoVs as well as MERS-CoV. Some drugs had strong activity against subsets of these CoV-derived frameshift signals, while having limited to no effect on -1 PRF caused by frameshift signals from other viruses used as negative controls. Notably, the serine protease inhibitor nafamostat suppressed -1 PRF significantly for multiple CoV-derived frameshift signals. These results suggest it is possible to find small-molecule ligands that inhibit -1 PRF specifically in a broad spectrum of CoVs, establishing frameshift signals as a viable target for developing pan-coronaviral therapeutics.

Fluorescent indicators and actuators provide a means to optically observe and perturb dynamic events in living animals. Although chemistry and protein engineering have contributed many useful tools to observe and perturb cells, an emerging strategy is to use chemigenetics: systems in which a small molecule dye interacts with a genetically encoded protein domain. Here we review chemigenetic strategies that have been successfully employed in living animals as photosensitizers for photoablation experiments, fluorescent cell cycle indicators, and fluorescent indicators for studying dynamic biological signals. Although these strategies at times suffer from challenges, e.g. delivery of the small molecule and assembly of the chemigenetic unit in living animals, the advantages of using small molecules with high brightness, low photobleaching, no chromophore maturation time and expanded color palette, combined with the ability to genetically target them to specific cell types, make chemigenetic fluorescent actuators and indicators an attractive strategy for use in living animals.

Under the situation of the rapid expansion of hospital, the dilemma of acupuncture-moxibustion department, as well as the relevant solutions are explored. The main reasons for the shrinking situation of the service in acupuncture-moxibustion department include: the disease-based department division trends to divert many diseases suitably treated in acupuncture-moxibustion department; the environment pursuing economic benefits restricts the development of acupuncture-moxibustion therapy characterized by "simple and low-cost operation". There are three important approaches for breaking through the dilemma of acupuncture and moxibustion therapy. First, modifying the traditional service mode as waiting for patients in acupuncture-moxibustion department and promoting acupuncture and moxibustion technology to be adopted in other departments rather than limited only in acupuncture-moxibustion department. Second, increasing the charges of acupuncture and moxibustion technology rationally. Third, positioning accurately the role of acupuncture and moxibustion technology in health services based on its own characteristics and advantages and promoting it in community medical institutions. All of these solutions require the guidance of supporting policies.

The medial entorhinal cortex is part of a neural system for mapping the position of an individual within a physical environment. Grid cells, a key component of this system, fire in a characteristic hexagonal pattern of locations, and are organized in modules that collectively form a population code for the animal's allocentric position. The invariance of the correlation structure of this population code across environments and behavioural states, independent of specific sensory inputs, has pointed to intrinsic, recurrently connected continuous attractor networks (CANs) as a possible substrate of the grid pattern. However, whether grid cell networks show continuous attractor dynamics, and how they interface with inputs from the environment, has remained unclear owing to the small samples of cells obtained so far. Here, using simultaneous recordings from many hundreds of grid cells and subsequent topological data analysis, we show that the joint activity of grid cells from an individual module resides on a toroidal manifold, as expected in a two-dimensional CAN. Positions on the torus correspond to positions of the moving animal in the environment. Individual cells are preferentially active at singular positions on the torus. Their positions are maintained between environments and from wakefulness to sleep, as predicted by CAN models for grid cells but not by alternative feedforward models. This demonstration of network dynamics on a toroidal manifold provides a population-level visualization of CAN dynamics in grid cells.

Animals display selective escape behaviors when faced with environmental threats. Selection of the appropriate response by the underlying neuronal network is key to maximizing chances of survival, yet the underlying network mechanisms are so far not fully understood. Using synapse-level reconstruction of the Drosophila larval network paired with physiological and behavioral readouts, we uncovered a circuit that gates selective escape behavior for noxious light through acute and input-specific neuropeptide action. Sensory neurons required for avoidance of noxious light and escape in response to harsh touch, each converge on discrete domains of neuromodulatory hub neurons. We show that acute release of hub neuron-derived insulin-like peptide 7 (Ilp7) and cognate relaxin family receptor (Lgr4) signaling in downstream neurons are required for noxious light avoidance, but not harsh touch responses. Our work highlights a role for compartmentalized circuit organization and neuropeptide release from regulatory hubs, acting as central circuit elements gating escape responses.